ABSTRAK-UNBK merupakan sebuah sistem ujian nasional sekolah berbasis komputer dimana siswa menger... more ABSTRAK-UNBK merupakan sebuah sistem ujian nasional sekolah berbasis komputer dimana siswa mengerjakan ujian menggunakan komputer yang diharapkan dapat membuat ujian menjadi lebih efisien dan efektif di bandingakan dengan ujian manual yang menggunakan kertas sebagai media ujiannya. Hal ini di terapkan di SMA Santa Theresia Jakarta. Untuk mengetahui tingkat penerimaan siswa terhadap sistem UNBK maka metode yang digunakan dalam penelitian ini adalah technology acceptance model (TAM) dengan 198 siswa data quesioner yang terkumpul, hipotesis dilakukan dengan menggunakan analisis Structural Equation Model (SEM) menggunakan Smartpls. Hasil penelitian menunjukkan bahwa tingkat pengaruh yang lebih tinggi dalam penerimaan siswa terhadap Sistem UNBK adalah kemudahan penggunaan menggunakan Sistem UNBK dengan nilai 16.843. Sedangkan tingkat pengaruh yang lebih rendah dalam penerimaan adalah penggunaan minat dalam perilaku pengguna dengan nilai 2,749. Dengan nilai tersebut, ABSTRACT-UNBK is a computer-based school national examination system where students work on exams using computers which are expected to make the test more efficient and effective compared to manual tests that use paper as a test medium. This is applied at Santa Theresia High School Jakarta. To determine the level of student acceptance of the UNBK system, the method used in this study is technology acceptance model (TAM) with 198 students questionnaire data collected, the hypothesis is done using the analysis of Structural Equation Model (SEM) using Smartpls. The results showed that the higher level of influence in student acceptance of the UNBK System was the ease of use using the UNBK System with a value of 16,843. While the level of influence that is lower in acceptance is the use of interest in user behavior with a value of 2.749. With this value UNBK is good for use at Santa Theresia High School.
IAIC Transactions on Sustainable Digital Innovation, 2019
World Health Organization (WHO) states that Diabetes Mellitus is the world's top deadly disease... more World Health Organization (WHO) states that Diabetes Mellitus is the world's top deadly disease. several studies in the health sector including diabetes mellitus have been carried out to detect diseases early. In this study optimization of naive bayes classifier using particle swarm optimization was applied to the data of patients with 2 classes namely positive diabetes mellitus and negative diabetes mellitus and data on patients with 3 classes, those who tested positive for diabetes mellitus type 1, diabetes mellitus type 2 and negative diabetes mellitus. After testing, the algorithm of Naive Bayes Classifier and Naive Bayes Classifier based on Particle Swarm Optimization, the results obtained are the Naive Bayes Classifier method for 2 classes and 3 classes each producing an accuracy value of 78.88% and 68.50%. but after adding Particle Swarm Optimization the value of accuracy increased respectively to 82.58% and 71, 29%. The classification results for 2 classes have an accuracy value higher than 3 classes with a difference of 11.29%
Abstrak-This paper presents a comparison of cell nucleus segmentation and area measurement of Pap... more Abstrak-This paper presents a comparison of cell nucleus segmentation and area measurement of Pap smear images by means of modification of color canals with Canny edge detection and morphological reconstruction methods. Regular Pap smear screening is the most successful attempt of medical science and practice for the early detection of cervical cancer. Manual analysis of the cervical cells is time consuming, laborious and error prone. In early detection, cell nucleus characterization plays an important role for classifying the degree of abnormality in cervical cancer. The aim of this work is to find the matched measurement method with the manual nucleus area measurement. In this work, we utilized Pap smear single cell images from Herlev data bank in RGB mode. The cell images were selected from 90 normal and 160 abnormal class subjects that include: Mild (Light) Dysplasia, Moderate Dysplasia, Severe Dysplasia and Carcinoma In Situ classes. The nucleus of each cell image was cropped manually to localize from the cytoplasm. The color canals modification was performed on each cropped nucleus image by, first, separating each R, G, B, and grayscale canals, then implementing addition operation based on color canals (R+G+B, R+G, R+B, G+B, and grayscale). The Canny edge detection was applied on those modifications resulting in binary edge images. The nucleus segmentation was implemented on the edge images by performing region filling based on morphological reconstruction. The area property was calculated based on the segmented nucleus area. The nucleus area from the proposed method was verified to the existing manual measurement (ground truth) of the Herlev data bank. Based on thorough observation upon the selected color canals and Canny edge detection. It can be concluded that Canny edge detection with canal modification is the most significant for all abnormal classes. While for Normal Superficial, Normal Intermediate, Severe Dysplasia and Moderate Dysplasia, Canny edge detection is significant for all RGB modifications with (r 0.314-0.817 range, p-value 0.01), and for Normal Columnar, Mild (Light) Dysplasia and Carsinoma In Situ, Canny edge detection is not sensitive for the three classes. Kata Kunci-Pap smear images, nucleus, color canals, Canny edge detection, morphological reconstruction. I. PENDAHULUAN Di seluruh dunia kanker serviks merupakan salah satu kanker yang paling umum di kalangan wanita. Kanker ini penyebab hilangnya nyawa produktif pada wanita baik karena kematian dini serta kecacatan berkepanjangan. Lebih dari 80% wanita di negara berkembang meninggal karena kanker serviks [1]. Alasan utama adalah kurangnya kesadaran akan penyakit dan akses ke layanan kesehatan. Pemeriksaan rutin dengan Pap smear dapat membantu mencegah sejak dini kanker serviks. Pemeriksaan terhadap squamous epithelium dilakukan ahli patologi anatomi untuk menyatakan hasil Pap smear seorang pasien wanita memiliki sel normal atau abnormal. Tahap kunci dalam deteksi otomatis dini kanker serviks adalah akurasi segmentasi sel nukleus [2]. Selama ini segmentasi nukleus pada citra sel Pap smear banyak dilakukan pada citra berskala abu-abu (grayscale) [3]-[10]. Tujuan penelitian ini untuk membandingkan segmentasi pada citra RGB dengan citra grayscale dalam menangani segmentasi nukleus sel normal dan abnormal. Selain itu juga ingin mengetahui metode deteksi Canny dengan rekonstruksi morpologi apakah mampu mendeteksi tepi nukleus sel normal dan abnormal Pap smear. Paper ini terbagi dalam beberapa bagian. Bagian 2 membahas tentang kanker serviks. Bagian 3 tentang tentang material dan metode yang digunakan dalam penelitian. Bagian 4 menjelaskan tentang hasil dan pembahasan. Selanjutnya ditutup dengan kesimpulan dan rencana penelitian lanjutan. II. KANKER SERVIKS Kanker adalah sekelompok penyakit yang memiliki ciri adanya pertumbuhan dan penyebaran sel-sel abnormal (sel kanker) yang tidak terkendali [11]. Sel merupakan penyusun dari semua makhluk hidup. Manusia memiliki trilyunan sel, yang memungkinkan manusia untuk bernafas, bergerak, berpikir, dan melakukan semua fungsi yang mencirikan bahwa
Ciptaan disebarluaskan di bawah Lisensi Creative Commons Atribusi-NonKomersial 4.0 Internasional.... more Ciptaan disebarluaskan di bawah Lisensi Creative Commons Atribusi-NonKomersial 4.0 Internasional. Abstract-The Mantoux test is a test performed to detect tuberculosis, a test performed by injecting protein into the skin tissue of the left hand, this test is mostly done because it feels more accurate the results, the way the Mantoux test works is to measure the diameter of the protein-given area, if the diameter is less than 5 mm, the patient is not diagnosed with tuberculosis, but if the diameter of the area given by the protein exceeds 5 mm then the patient is diagnosed with tuberculosis. To help simplify the calculation, the area of the Mantoux test needs to be image processing. In this study image processing uses K-Means clustering method with edge detection, then the calculation of diameter after edge detection. And the end result is the image of the Mantoux test area can easily be calculated in diameter, without having to make measurements using a manual ruler.
Information systems are a combination of information technology and activities of people who use ... more Information systems are a combination of information technology and activities of people who use that technology to support operations and management. Currently the procurement of Prospective Civil Servants (CPNS) has implemented system technology in carrying out each activity. One form of implementation is in the form of an online CPNS system. The purpose of this study is to find out what are the effects of system quality, information quality, online CPNS service quality on community satisfaction following online CPNS.. The method used is TAM (Technology Acceptance Model) with variable system quality, information quality and service quality. Based on the results of the study of the effect of applying the online CPNS system to community satisfaction, the results showed that: There is a significant influence between the system quality variables on community satisfaction, there is no significant effect between the quality of information on community satisfaction. There is a significant influence between service quality variables on community satisfaction.
The presence of inflammatory cells complicates the process of identifying the nuclei in the early... more The presence of inflammatory cells complicates the process of identifying the nuclei in the early detection of cervical cancer. Inflammatory cells need to be eliminated to assist pathologists in reading Pap smear slides. The texture of Grey-Level Run-Length Matrix (GLRLM) for inflammatory cells and nuclei types are investigated. The inflammatory cells and nuclei have different texture, and it can be used to differentiate them. To extract all of the features, firstly manual cropping of inflammatory cells and nuclei needs to be done. All of extracted features have been analyzed and selected by Decision Tree classifier (J48). Originally there have been eleven features in the direction of 135º which are extracted to classify cropping cells into inflammatory cells and nuclei. Then the eleven features are reduced into eight, namely low gray level run emphasis, gray level non uniformity, run length non-uniformity, long run low gray-level emphasis, short run high gray-level emphasis, short run low gray-level emphasis, long run high gray-level emphasis and run percentage based on the rule of classification. This experiment is applied into 957 cells which were from 50 images. The compositions of these cells were 122 cells of nuclei and 837 cells of inflammatory. The proposed algorithm applied to all of the cells and the result of classification by using these eight texture features obtains the sensitivity rates which show that there are still nuclei of cells that were considered as inflammatory cells. It was in accordance with the conditions of the difficulties faced by the pathologist while the specificity rate suggests that inflammatory cells detected properly and few inflammatory cells are considered as nucleus.
Abstrak-This paper presents a texture analysis and comparison of clasification of cell nucleus im... more Abstrak-This paper presents a texture analysis and comparison of clasification of cell nucleus images. Texture analysis will be focused on the nuclei of Image Pap smear cell. The method of analysis texture is the statistical second order of Grey Level Co-occurrence Matrix (GLCM). There are five parameter that will be extracted, viz. contrast, correlation, energy, homogeneity and entropy. The image nuclei used in this work are cropped images from Herlev data bank. The images from 917 subjects are categorized into seven classes. Three classes of which are normal cell image class categories that include: Normal Superficial, Normal Intermediate, and Normal Columnar, and the other four classes are categories of abnormal cell image class that include: Mild (Light) Dysplasia, Moderate Dysplasia, Severe Dysplasia and Carcinoma In Situ. The process of texture analysis developed using grayscale 8 bit level. The preprocessing of images will be conducted before texture analysis in order to improve contrast in nuclei. Based on the numerical result of all parameter, class normal and abnormal of Pap smear image have slightly different properties for correlation, energy, homogeneity and entropy. Originally, there have been 18 fetures of texture which were created to classify into two classes by decision tree classifier, ie normal and abnormal cell. The experimental study shows that in two-class classification, normal and abnormal based on the texture features and using the Decision Tree learning algorithm (J48) classifiers with the Weka Correctly Classification Instances (CCI) and Kappa Coefficient classification performance measures, the Decision Tree learning algorithm (J48) classifier performs the best with the CCI of 73.8277% and the Kappa Coefficient of 0.2785.
Skin cancer is malfunctional skin cell which have an uncontrolled growth factor and in the final ... more Skin cancer is malfunctional skin cell which have an uncontrolled growth factor and in the final phase of skin cancer, can make the person who suffer die. Detect the disease as early as possible is one way to avoid the worst possible defects and, because of its location on the surface of the skin, it would be easy for anyone to identify the skin cancer (melanoma). Early detection can be performed based on the characteristics Asymmetrical Shape, Border, Color, Diameter, Evolution (ABCDE). In this research, The early detection is focused on identifying diameter at 30 nevus images. Research method that used is processing the nevus images by converting the images into HSI images and then converted into a binary image, next step is do a segmentation using median filter, morphological construction process and at the final stage, do a edge detection with sobel operator. Edge detection process will simplify the nevus diameter area calculation. Result of the research with the 30 nevus images is the image processing method which suggested in this research can detect the nevus diameter and sucess to identify 26 images as normal nevus with diameter <6mm and 4 nevus images as melanoma with diameter >6mm.
Skin cancer is malfunctional skin cell which have an uncontrolled growth factor and in the final ... more Skin cancer is malfunctional skin cell which have an uncontrolled growth factor and in the final phase of skin cancer, can make the person who suffer die. Detect the disease as early as possible is one way to avoid the worst possible defects and, because of its location on the surface of the skin, it would be easy for anyone to identify the skin cancer (melanoma). Early detection can be performed based on the characteristics Asymmetrical Shape, Border, Color, Diameter, Evolution (ABCDE). In this research, The early detection is focused on identifying diameter at 30 nevus images. Research method that used is processing the nevus images by converting the images into HSI images and then converted into a binary image, next step is do a segmentation using median filter, morphological construction process and at the final stage, do a edge detection with sobel operator. Edge detection process will simplify the nevus diameter area calculation. Result of the research with the 30 nevus images is the image processing method which suggested in this research can detect the nevus diameter and sucess to identify 26 images as normal nevus with diameter <6mm and 4 nevus images as melanoma with diameter >6mm.
Information systems are a combination
of information technology and activities of people
who use... more Information systems are a combination of information technology and activities of people who use that technology to support operations and management. Currently the procurement of Prospective Civil Servants (CPNS) has implemented system technology in carrying out each activity. One form of implementation is in the form of an online CPNS system. The purpose of this study is to find out what are the effects of system quality, information quality, online CPNS service quality on community satisfaction following online CPNS.. The method used is TAM (Technology Acceptance Model) with variable system quality, information quality and service quality. Based on the results of the study of the effect of applying the online CPNS system to community satisfaction, the results showed that: There is a significant influence between the system quality variables on community satisfaction, there is no significant effect between the quality of information on community satisfaction. There is a significant influence between service quality variables on community satisfaction
ABSTRAK Penelitian ini menyajikan analisis tekstur dan klasifikasi citra sel pap smear. Pada anal... more ABSTRAK Penelitian ini menyajikan analisis tekstur dan klasifikasi citra sel pap smear. Pada analisis tekstur difokuskan pada citra nukleus sel Pap smear, metode yang digunakan adalah metode Gray Level Co-occurrence Matrix (GLCM) dengan menggunakan lima parameter yaitu korelasi, energi, homogenitas dan entropi ditambah dengan menghitung nilai Brightness pada citra yang diproses. Citra yang digunakan dalam penelitian ini menggunakan data citra Harlev, yang terdiri dari 280 citra yang sudah dikategorikan ke dalam 7 kelas yaitu 3 kelas sel normal yang meliputi Normal Superficial, Normal Intermediate, and Normal Columnar dan 4 kelas lainnya adalah kategori kelas citra sel abnormal yang meliputi Mild (Light) Dyplasia, Moderate Dysplasia, Severe Dysplasia dan Carcinoma In Situ. Berdasarkan hasil pengolahan citra yang menghasilkan nilai matriks dari setiap parameter yang dihitung, citra sel Pap smear akan diklasifikasikan menurut jenisnya normal atau abnormal dan berdasarkan kelasnya dengan menggunakan decision tree yang diolah dengan algoritma clasifier J48 pada aplikasi weka. Untuk akurasi yang dihasilkan dari klasifikasi sel normal dan abnormal adalah 73% dan untuk akurasi klasifikasi tujuh kelas adalah 34,3%. ABSTRACT This research presents the texture analysis and classification of cells pap smear image. Texture analysis focused on the cell nucleus Pap smear image, the research method used the Gray Level Co-occurrence Matrix (GLCM) method, by using five parameter that include contrast, correlation, energy, homogeneity, entropy and brightness. The image used in this research using image data Harlev. The images from 280 subjects are categorized into seven classes. Three classes of which are normal cell image class categories that include Normal Superficial, Normal Intermediate, and Normal Columnar, and the other four classes are categories of abnormal cell image class that include Mild (Light) Dyplasia, Moderate Dysplasia, Severe Dysplasia and Carcinoma In Situ. Based on the results of image processing that produces a matrix of values of each parameter were calculated, Pap smear cell image will be classified according to the type of normal or abnormal and based on the class using the decision tree treated with algorithm clasifier J48 in weka applications. To the resulting accuracy of the classification normal and abnormal cells is 73% and for seven class classification accuracy is 34,3%.
ABSTRAK Penelitian ini menyajikan analisis tekstur dan klasifikasi citra sel pap smear. Pada anal... more ABSTRAK Penelitian ini menyajikan analisis tekstur dan klasifikasi citra sel pap smear. Pada analisis tekstur difokuskan pada citra nukleus sel Pap smear, metode yang digunakan adalah metode Gray Level Co-occurrence Matrix (GLCM) dengan menggunakan lima parameter yaitu korelasi, energi, homogenitas dan entropi ditambah dengan menghitung nilai Brightness pada citra yang diproses. Citra yang digunakan dalam penelitian ini menggunakan data citra Harlev, yang terdiri dari 280 citra yang sudah dikategorikan ke dalam 7 kelas yaitu 3 kelas sel normal yang meliputi Normal Superficial, Normal Intermediate, and Normal Columnar dan 4 kelas lainnya adalah kategori kelas citra sel abnormal yang meliputi Mild (Light) Dyplasia, Moderate Dysplasia, Severe Dysplasia dan Carcinoma In Situ. Berdasarkan hasil pengolahan citra yang menghasilkan nilai matriks dari setiap parameter yang dihitung, citra sel Pap smear akan diklasifikasikan menurut jenisnya normal atau abnormal dan berdasarkan kelasnya dengan menggunakan decision tree yang diolah dengan algoritma clasifier J48 pada aplikasi weka. Untuk akurasi yang dihasilkan dari klasifikasi sel normal dan abnormal adalah 73% dan untuk akurasi klasifikasi tujuh kelas adalah 34,3%. ABSTRACT This research presents the texture analysis and classification of cells pap smear image. Texture analysis focused on the cell nucleus Pap smear image, the research method used the Gray Level Co-occurrence Matrix (GLCM) method, by using five parameter that include contrast, correlation, energy, homogeneity, entropy and brightness. The image used in this research using image data Harlev. The images from 280 subjects are categorized into seven classes. Three classes of which are normal cell image class categories that include Normal Superficial, Normal Intermediate, and Normal Columnar, and the other four classes are categories of abnormal cell image class that include Mild (Light) Dyplasia, Moderate Dysplasia, Severe Dysplasia and Carcinoma In Situ. Based on the results of image processing that produces a matrix of values of each parameter were calculated, Pap smear cell image will be classified according to the type of normal or abnormal and based on the class using the decision tree treated with algorithm clasifier J48 in weka applications. To the resulting accuracy of the classification normal and abnormal cells is 73% and for seven class classification accuracy is 34,3%.
Abstraksi-Sistem pengolahan nilai dengan cara konvensional yaitu guru bidang studi menulis nilai ... more Abstraksi-Sistem pengolahan nilai dengan cara konvensional yaitu guru bidang studi menulis nilai siswa ke dalam lembaran kertas dan disetorkan kepada wali kelas untuk dibuatkan nilai rapor masih kurang efektif dan memiliki beberapa kelemahan. Bagi siswa dan orang tua tidak dapat mengecek nilainya setiap saat, sedangkan bagi guru masih kerepotan dalam mencari data nilai yang harus membuka arsip nilai. Selain itu, masalah sulitnya dalam mengetahui kepuasan pengguna dalam menggunakan sistem pengolahan nilai harus dipecahkan. Penulis mengusulkan sistem informasi pengolahan nilai berbasis web dengan mempertimbangkan factor kepuasan yang dimiliki pengguna. Metode pengembangan sistem dalam web ini menggunakan Metode Waterfall, yang meliputi: analisa kebutuhan sistem, desain, code generation, testing dan support. Untuk desain, digunakan UML (Unified Model Language) dengan membuat Use Case Diagram, Activity Diagram, ERD, perancangan basis data dan rancangan antarmuka. Sistem pengolahan nilai berbasis web menjadi solusi dalam membantu guru, kurikulum dan siswa dalam mengakses data nilai serta dapat mengetahui tingkat kepuasan pengguna terhadap aplikasi yang dibuat. Kata Kunci: sistem pengolahan nilai, faktor kepuasan Abstract-Grade processing system with conventional way when teachers write student scores into a sheet of paper and sent to the homeroom to be made grades are less effective and have some weaknesses. For students and parents can't check its value at any time, while the teachers are still hassles in finding the data value and must open the archive value. In addition, the problem of the difficulty in knowing the user satisfaction in using the processing system value must be solved. The author proposed a system of web-based information processing value based on the user's satisfaction factor. System development methods in this website using Waterfall methods, which include: analysis of system requirements, design, code generation, testing and support. For the design, use UML (Unified Model Language) to create a Use Case Diagram, Activity Diagram, ERD, database design and interface design. System processing of web based can be solutions in support of teachers, curriculum and students in accessing the values data report and can determine the level of user satisfaction on the application.
Separation of overlapping areas on overlapping Pap smear image is still a tough thing to do. In a... more Separation of overlapping areas on overlapping Pap smear image is still a tough thing to do. In addition to the process of identification of overlapping cells which is still difficult to do, sometimes there are components in the cells that complicate the process such as the presence of inflammatory cells that resemble the nucleus though the process of overlapping cell identification on Pap smear image is needed in early detection of Pap smear test to recognize a cell that is healthy or classified as cervical cancer cells. This study aims to segment the overlapping areas of Pap smear image by utilizing the color features of the cell. Stages of identification and separation of the area use K-means method combined with Otsu method. The results obtained in some cells of overlapping areas can be perfectly separated while in some other cells the results have not been encouraging and still require further research, especially to overcome the existence of inflammatory cells that complicate the separation process.
ABSTRAK-UNBK merupakan sebuah sistem ujian nasional sekolah berbasis komputer dimana siswa menger... more ABSTRAK-UNBK merupakan sebuah sistem ujian nasional sekolah berbasis komputer dimana siswa mengerjakan ujian menggunakan komputer yang diharapkan dapat membuat ujian menjadi lebih efisien dan efektif di bandingakan dengan ujian manual yang menggunakan kertas sebagai media ujiannya. Hal ini di terapkan di SMA Santa Theresia Jakarta. Untuk mengetahui tingkat penerimaan siswa terhadap sistem UNBK maka metode yang digunakan dalam penelitian ini adalah technology acceptance model (TAM) dengan 198 siswa data quesioner yang terkumpul, hipotesis dilakukan dengan menggunakan analisis Structural Equation Model (SEM) menggunakan Smartpls. Hasil penelitian menunjukkan bahwa tingkat pengaruh yang lebih tinggi dalam penerimaan siswa terhadap Sistem UNBK adalah kemudahan penggunaan menggunakan Sistem UNBK dengan nilai 16.843. Sedangkan tingkat pengaruh yang lebih rendah dalam penerimaan adalah penggunaan minat dalam perilaku pengguna dengan nilai 2,749. Dengan nilai tersebut, ABSTRACT-UNBK is a computer-based school national examination system where students work on exams using computers which are expected to make the test more efficient and effective compared to manual tests that use paper as a test medium. This is applied at Santa Theresia High School Jakarta. To determine the level of student acceptance of the UNBK system, the method used in this study is technology acceptance model (TAM) with 198 students questionnaire data collected, the hypothesis is done using the analysis of Structural Equation Model (SEM) using Smartpls. The results showed that the higher level of influence in student acceptance of the UNBK System was the ease of use using the UNBK System with a value of 16,843. While the level of influence that is lower in acceptance is the use of interest in user behavior with a value of 2.749. With this value UNBK is good for use at Santa Theresia High School.
IAIC Transactions on Sustainable Digital Innovation, 2019
World Health Organization (WHO) states that Diabetes Mellitus is the world's top deadly disease... more World Health Organization (WHO) states that Diabetes Mellitus is the world's top deadly disease. several studies in the health sector including diabetes mellitus have been carried out to detect diseases early. In this study optimization of naive bayes classifier using particle swarm optimization was applied to the data of patients with 2 classes namely positive diabetes mellitus and negative diabetes mellitus and data on patients with 3 classes, those who tested positive for diabetes mellitus type 1, diabetes mellitus type 2 and negative diabetes mellitus. After testing, the algorithm of Naive Bayes Classifier and Naive Bayes Classifier based on Particle Swarm Optimization, the results obtained are the Naive Bayes Classifier method for 2 classes and 3 classes each producing an accuracy value of 78.88% and 68.50%. but after adding Particle Swarm Optimization the value of accuracy increased respectively to 82.58% and 71, 29%. The classification results for 2 classes have an accuracy value higher than 3 classes with a difference of 11.29%
Abstrak-This paper presents a comparison of cell nucleus segmentation and area measurement of Pap... more Abstrak-This paper presents a comparison of cell nucleus segmentation and area measurement of Pap smear images by means of modification of color canals with Canny edge detection and morphological reconstruction methods. Regular Pap smear screening is the most successful attempt of medical science and practice for the early detection of cervical cancer. Manual analysis of the cervical cells is time consuming, laborious and error prone. In early detection, cell nucleus characterization plays an important role for classifying the degree of abnormality in cervical cancer. The aim of this work is to find the matched measurement method with the manual nucleus area measurement. In this work, we utilized Pap smear single cell images from Herlev data bank in RGB mode. The cell images were selected from 90 normal and 160 abnormal class subjects that include: Mild (Light) Dysplasia, Moderate Dysplasia, Severe Dysplasia and Carcinoma In Situ classes. The nucleus of each cell image was cropped manually to localize from the cytoplasm. The color canals modification was performed on each cropped nucleus image by, first, separating each R, G, B, and grayscale canals, then implementing addition operation based on color canals (R+G+B, R+G, R+B, G+B, and grayscale). The Canny edge detection was applied on those modifications resulting in binary edge images. The nucleus segmentation was implemented on the edge images by performing region filling based on morphological reconstruction. The area property was calculated based on the segmented nucleus area. The nucleus area from the proposed method was verified to the existing manual measurement (ground truth) of the Herlev data bank. Based on thorough observation upon the selected color canals and Canny edge detection. It can be concluded that Canny edge detection with canal modification is the most significant for all abnormal classes. While for Normal Superficial, Normal Intermediate, Severe Dysplasia and Moderate Dysplasia, Canny edge detection is significant for all RGB modifications with (r 0.314-0.817 range, p-value 0.01), and for Normal Columnar, Mild (Light) Dysplasia and Carsinoma In Situ, Canny edge detection is not sensitive for the three classes. Kata Kunci-Pap smear images, nucleus, color canals, Canny edge detection, morphological reconstruction. I. PENDAHULUAN Di seluruh dunia kanker serviks merupakan salah satu kanker yang paling umum di kalangan wanita. Kanker ini penyebab hilangnya nyawa produktif pada wanita baik karena kematian dini serta kecacatan berkepanjangan. Lebih dari 80% wanita di negara berkembang meninggal karena kanker serviks [1]. Alasan utama adalah kurangnya kesadaran akan penyakit dan akses ke layanan kesehatan. Pemeriksaan rutin dengan Pap smear dapat membantu mencegah sejak dini kanker serviks. Pemeriksaan terhadap squamous epithelium dilakukan ahli patologi anatomi untuk menyatakan hasil Pap smear seorang pasien wanita memiliki sel normal atau abnormal. Tahap kunci dalam deteksi otomatis dini kanker serviks adalah akurasi segmentasi sel nukleus [2]. Selama ini segmentasi nukleus pada citra sel Pap smear banyak dilakukan pada citra berskala abu-abu (grayscale) [3]-[10]. Tujuan penelitian ini untuk membandingkan segmentasi pada citra RGB dengan citra grayscale dalam menangani segmentasi nukleus sel normal dan abnormal. Selain itu juga ingin mengetahui metode deteksi Canny dengan rekonstruksi morpologi apakah mampu mendeteksi tepi nukleus sel normal dan abnormal Pap smear. Paper ini terbagi dalam beberapa bagian. Bagian 2 membahas tentang kanker serviks. Bagian 3 tentang tentang material dan metode yang digunakan dalam penelitian. Bagian 4 menjelaskan tentang hasil dan pembahasan. Selanjutnya ditutup dengan kesimpulan dan rencana penelitian lanjutan. II. KANKER SERVIKS Kanker adalah sekelompok penyakit yang memiliki ciri adanya pertumbuhan dan penyebaran sel-sel abnormal (sel kanker) yang tidak terkendali [11]. Sel merupakan penyusun dari semua makhluk hidup. Manusia memiliki trilyunan sel, yang memungkinkan manusia untuk bernafas, bergerak, berpikir, dan melakukan semua fungsi yang mencirikan bahwa
Ciptaan disebarluaskan di bawah Lisensi Creative Commons Atribusi-NonKomersial 4.0 Internasional.... more Ciptaan disebarluaskan di bawah Lisensi Creative Commons Atribusi-NonKomersial 4.0 Internasional. Abstract-The Mantoux test is a test performed to detect tuberculosis, a test performed by injecting protein into the skin tissue of the left hand, this test is mostly done because it feels more accurate the results, the way the Mantoux test works is to measure the diameter of the protein-given area, if the diameter is less than 5 mm, the patient is not diagnosed with tuberculosis, but if the diameter of the area given by the protein exceeds 5 mm then the patient is diagnosed with tuberculosis. To help simplify the calculation, the area of the Mantoux test needs to be image processing. In this study image processing uses K-Means clustering method with edge detection, then the calculation of diameter after edge detection. And the end result is the image of the Mantoux test area can easily be calculated in diameter, without having to make measurements using a manual ruler.
Information systems are a combination of information technology and activities of people who use ... more Information systems are a combination of information technology and activities of people who use that technology to support operations and management. Currently the procurement of Prospective Civil Servants (CPNS) has implemented system technology in carrying out each activity. One form of implementation is in the form of an online CPNS system. The purpose of this study is to find out what are the effects of system quality, information quality, online CPNS service quality on community satisfaction following online CPNS.. The method used is TAM (Technology Acceptance Model) with variable system quality, information quality and service quality. Based on the results of the study of the effect of applying the online CPNS system to community satisfaction, the results showed that: There is a significant influence between the system quality variables on community satisfaction, there is no significant effect between the quality of information on community satisfaction. There is a significant influence between service quality variables on community satisfaction.
The presence of inflammatory cells complicates the process of identifying the nuclei in the early... more The presence of inflammatory cells complicates the process of identifying the nuclei in the early detection of cervical cancer. Inflammatory cells need to be eliminated to assist pathologists in reading Pap smear slides. The texture of Grey-Level Run-Length Matrix (GLRLM) for inflammatory cells and nuclei types are investigated. The inflammatory cells and nuclei have different texture, and it can be used to differentiate them. To extract all of the features, firstly manual cropping of inflammatory cells and nuclei needs to be done. All of extracted features have been analyzed and selected by Decision Tree classifier (J48). Originally there have been eleven features in the direction of 135º which are extracted to classify cropping cells into inflammatory cells and nuclei. Then the eleven features are reduced into eight, namely low gray level run emphasis, gray level non uniformity, run length non-uniformity, long run low gray-level emphasis, short run high gray-level emphasis, short run low gray-level emphasis, long run high gray-level emphasis and run percentage based on the rule of classification. This experiment is applied into 957 cells which were from 50 images. The compositions of these cells were 122 cells of nuclei and 837 cells of inflammatory. The proposed algorithm applied to all of the cells and the result of classification by using these eight texture features obtains the sensitivity rates which show that there are still nuclei of cells that were considered as inflammatory cells. It was in accordance with the conditions of the difficulties faced by the pathologist while the specificity rate suggests that inflammatory cells detected properly and few inflammatory cells are considered as nucleus.
Abstrak-This paper presents a texture analysis and comparison of clasification of cell nucleus im... more Abstrak-This paper presents a texture analysis and comparison of clasification of cell nucleus images. Texture analysis will be focused on the nuclei of Image Pap smear cell. The method of analysis texture is the statistical second order of Grey Level Co-occurrence Matrix (GLCM). There are five parameter that will be extracted, viz. contrast, correlation, energy, homogeneity and entropy. The image nuclei used in this work are cropped images from Herlev data bank. The images from 917 subjects are categorized into seven classes. Three classes of which are normal cell image class categories that include: Normal Superficial, Normal Intermediate, and Normal Columnar, and the other four classes are categories of abnormal cell image class that include: Mild (Light) Dysplasia, Moderate Dysplasia, Severe Dysplasia and Carcinoma In Situ. The process of texture analysis developed using grayscale 8 bit level. The preprocessing of images will be conducted before texture analysis in order to improve contrast in nuclei. Based on the numerical result of all parameter, class normal and abnormal of Pap smear image have slightly different properties for correlation, energy, homogeneity and entropy. Originally, there have been 18 fetures of texture which were created to classify into two classes by decision tree classifier, ie normal and abnormal cell. The experimental study shows that in two-class classification, normal and abnormal based on the texture features and using the Decision Tree learning algorithm (J48) classifiers with the Weka Correctly Classification Instances (CCI) and Kappa Coefficient classification performance measures, the Decision Tree learning algorithm (J48) classifier performs the best with the CCI of 73.8277% and the Kappa Coefficient of 0.2785.
Skin cancer is malfunctional skin cell which have an uncontrolled growth factor and in the final ... more Skin cancer is malfunctional skin cell which have an uncontrolled growth factor and in the final phase of skin cancer, can make the person who suffer die. Detect the disease as early as possible is one way to avoid the worst possible defects and, because of its location on the surface of the skin, it would be easy for anyone to identify the skin cancer (melanoma). Early detection can be performed based on the characteristics Asymmetrical Shape, Border, Color, Diameter, Evolution (ABCDE). In this research, The early detection is focused on identifying diameter at 30 nevus images. Research method that used is processing the nevus images by converting the images into HSI images and then converted into a binary image, next step is do a segmentation using median filter, morphological construction process and at the final stage, do a edge detection with sobel operator. Edge detection process will simplify the nevus diameter area calculation. Result of the research with the 30 nevus images is the image processing method which suggested in this research can detect the nevus diameter and sucess to identify 26 images as normal nevus with diameter <6mm and 4 nevus images as melanoma with diameter >6mm.
Skin cancer is malfunctional skin cell which have an uncontrolled growth factor and in the final ... more Skin cancer is malfunctional skin cell which have an uncontrolled growth factor and in the final phase of skin cancer, can make the person who suffer die. Detect the disease as early as possible is one way to avoid the worst possible defects and, because of its location on the surface of the skin, it would be easy for anyone to identify the skin cancer (melanoma). Early detection can be performed based on the characteristics Asymmetrical Shape, Border, Color, Diameter, Evolution (ABCDE). In this research, The early detection is focused on identifying diameter at 30 nevus images. Research method that used is processing the nevus images by converting the images into HSI images and then converted into a binary image, next step is do a segmentation using median filter, morphological construction process and at the final stage, do a edge detection with sobel operator. Edge detection process will simplify the nevus diameter area calculation. Result of the research with the 30 nevus images is the image processing method which suggested in this research can detect the nevus diameter and sucess to identify 26 images as normal nevus with diameter <6mm and 4 nevus images as melanoma with diameter >6mm.
Information systems are a combination
of information technology and activities of people
who use... more Information systems are a combination of information technology and activities of people who use that technology to support operations and management. Currently the procurement of Prospective Civil Servants (CPNS) has implemented system technology in carrying out each activity. One form of implementation is in the form of an online CPNS system. The purpose of this study is to find out what are the effects of system quality, information quality, online CPNS service quality on community satisfaction following online CPNS.. The method used is TAM (Technology Acceptance Model) with variable system quality, information quality and service quality. Based on the results of the study of the effect of applying the online CPNS system to community satisfaction, the results showed that: There is a significant influence between the system quality variables on community satisfaction, there is no significant effect between the quality of information on community satisfaction. There is a significant influence between service quality variables on community satisfaction
ABSTRAK Penelitian ini menyajikan analisis tekstur dan klasifikasi citra sel pap smear. Pada anal... more ABSTRAK Penelitian ini menyajikan analisis tekstur dan klasifikasi citra sel pap smear. Pada analisis tekstur difokuskan pada citra nukleus sel Pap smear, metode yang digunakan adalah metode Gray Level Co-occurrence Matrix (GLCM) dengan menggunakan lima parameter yaitu korelasi, energi, homogenitas dan entropi ditambah dengan menghitung nilai Brightness pada citra yang diproses. Citra yang digunakan dalam penelitian ini menggunakan data citra Harlev, yang terdiri dari 280 citra yang sudah dikategorikan ke dalam 7 kelas yaitu 3 kelas sel normal yang meliputi Normal Superficial, Normal Intermediate, and Normal Columnar dan 4 kelas lainnya adalah kategori kelas citra sel abnormal yang meliputi Mild (Light) Dyplasia, Moderate Dysplasia, Severe Dysplasia dan Carcinoma In Situ. Berdasarkan hasil pengolahan citra yang menghasilkan nilai matriks dari setiap parameter yang dihitung, citra sel Pap smear akan diklasifikasikan menurut jenisnya normal atau abnormal dan berdasarkan kelasnya dengan menggunakan decision tree yang diolah dengan algoritma clasifier J48 pada aplikasi weka. Untuk akurasi yang dihasilkan dari klasifikasi sel normal dan abnormal adalah 73% dan untuk akurasi klasifikasi tujuh kelas adalah 34,3%. ABSTRACT This research presents the texture analysis and classification of cells pap smear image. Texture analysis focused on the cell nucleus Pap smear image, the research method used the Gray Level Co-occurrence Matrix (GLCM) method, by using five parameter that include contrast, correlation, energy, homogeneity, entropy and brightness. The image used in this research using image data Harlev. The images from 280 subjects are categorized into seven classes. Three classes of which are normal cell image class categories that include Normal Superficial, Normal Intermediate, and Normal Columnar, and the other four classes are categories of abnormal cell image class that include Mild (Light) Dyplasia, Moderate Dysplasia, Severe Dysplasia and Carcinoma In Situ. Based on the results of image processing that produces a matrix of values of each parameter were calculated, Pap smear cell image will be classified according to the type of normal or abnormal and based on the class using the decision tree treated with algorithm clasifier J48 in weka applications. To the resulting accuracy of the classification normal and abnormal cells is 73% and for seven class classification accuracy is 34,3%.
ABSTRAK Penelitian ini menyajikan analisis tekstur dan klasifikasi citra sel pap smear. Pada anal... more ABSTRAK Penelitian ini menyajikan analisis tekstur dan klasifikasi citra sel pap smear. Pada analisis tekstur difokuskan pada citra nukleus sel Pap smear, metode yang digunakan adalah metode Gray Level Co-occurrence Matrix (GLCM) dengan menggunakan lima parameter yaitu korelasi, energi, homogenitas dan entropi ditambah dengan menghitung nilai Brightness pada citra yang diproses. Citra yang digunakan dalam penelitian ini menggunakan data citra Harlev, yang terdiri dari 280 citra yang sudah dikategorikan ke dalam 7 kelas yaitu 3 kelas sel normal yang meliputi Normal Superficial, Normal Intermediate, and Normal Columnar dan 4 kelas lainnya adalah kategori kelas citra sel abnormal yang meliputi Mild (Light) Dyplasia, Moderate Dysplasia, Severe Dysplasia dan Carcinoma In Situ. Berdasarkan hasil pengolahan citra yang menghasilkan nilai matriks dari setiap parameter yang dihitung, citra sel Pap smear akan diklasifikasikan menurut jenisnya normal atau abnormal dan berdasarkan kelasnya dengan menggunakan decision tree yang diolah dengan algoritma clasifier J48 pada aplikasi weka. Untuk akurasi yang dihasilkan dari klasifikasi sel normal dan abnormal adalah 73% dan untuk akurasi klasifikasi tujuh kelas adalah 34,3%. ABSTRACT This research presents the texture analysis and classification of cells pap smear image. Texture analysis focused on the cell nucleus Pap smear image, the research method used the Gray Level Co-occurrence Matrix (GLCM) method, by using five parameter that include contrast, correlation, energy, homogeneity, entropy and brightness. The image used in this research using image data Harlev. The images from 280 subjects are categorized into seven classes. Three classes of which are normal cell image class categories that include Normal Superficial, Normal Intermediate, and Normal Columnar, and the other four classes are categories of abnormal cell image class that include Mild (Light) Dyplasia, Moderate Dysplasia, Severe Dysplasia and Carcinoma In Situ. Based on the results of image processing that produces a matrix of values of each parameter were calculated, Pap smear cell image will be classified according to the type of normal or abnormal and based on the class using the decision tree treated with algorithm clasifier J48 in weka applications. To the resulting accuracy of the classification normal and abnormal cells is 73% and for seven class classification accuracy is 34,3%.
Abstraksi-Sistem pengolahan nilai dengan cara konvensional yaitu guru bidang studi menulis nilai ... more Abstraksi-Sistem pengolahan nilai dengan cara konvensional yaitu guru bidang studi menulis nilai siswa ke dalam lembaran kertas dan disetorkan kepada wali kelas untuk dibuatkan nilai rapor masih kurang efektif dan memiliki beberapa kelemahan. Bagi siswa dan orang tua tidak dapat mengecek nilainya setiap saat, sedangkan bagi guru masih kerepotan dalam mencari data nilai yang harus membuka arsip nilai. Selain itu, masalah sulitnya dalam mengetahui kepuasan pengguna dalam menggunakan sistem pengolahan nilai harus dipecahkan. Penulis mengusulkan sistem informasi pengolahan nilai berbasis web dengan mempertimbangkan factor kepuasan yang dimiliki pengguna. Metode pengembangan sistem dalam web ini menggunakan Metode Waterfall, yang meliputi: analisa kebutuhan sistem, desain, code generation, testing dan support. Untuk desain, digunakan UML (Unified Model Language) dengan membuat Use Case Diagram, Activity Diagram, ERD, perancangan basis data dan rancangan antarmuka. Sistem pengolahan nilai berbasis web menjadi solusi dalam membantu guru, kurikulum dan siswa dalam mengakses data nilai serta dapat mengetahui tingkat kepuasan pengguna terhadap aplikasi yang dibuat. Kata Kunci: sistem pengolahan nilai, faktor kepuasan Abstract-Grade processing system with conventional way when teachers write student scores into a sheet of paper and sent to the homeroom to be made grades are less effective and have some weaknesses. For students and parents can't check its value at any time, while the teachers are still hassles in finding the data value and must open the archive value. In addition, the problem of the difficulty in knowing the user satisfaction in using the processing system value must be solved. The author proposed a system of web-based information processing value based on the user's satisfaction factor. System development methods in this website using Waterfall methods, which include: analysis of system requirements, design, code generation, testing and support. For the design, use UML (Unified Model Language) to create a Use Case Diagram, Activity Diagram, ERD, database design and interface design. System processing of web based can be solutions in support of teachers, curriculum and students in accessing the values data report and can determine the level of user satisfaction on the application.
Separation of overlapping areas on overlapping Pap smear image is still a tough thing to do. In a... more Separation of overlapping areas on overlapping Pap smear image is still a tough thing to do. In addition to the process of identification of overlapping cells which is still difficult to do, sometimes there are components in the cells that complicate the process such as the presence of inflammatory cells that resemble the nucleus though the process of overlapping cell identification on Pap smear image is needed in early detection of Pap smear test to recognize a cell that is healthy or classified as cervical cancer cells. This study aims to segment the overlapping areas of Pap smear image by utilizing the color features of the cell. Stages of identification and separation of the area use K-means method combined with Otsu method. The results obtained in some cells of overlapping areas can be perfectly separated while in some other cells the results have not been encouraging and still require further research, especially to overcome the existence of inflammatory cells that complicate the separation process.
Abstrak-Persoalan terbesar dalam deteksi dini otomatis citra mikroskopik Pap smear adalah segment... more Abstrak-Persoalan terbesar dalam deteksi dini otomatis citra mikroskopik Pap smear adalah segmentasi citra sel. Sel mikroskopik Pap smear dideteksi oleh ahli patologi dan dokter untuk menentukan sel tersebut normal atau tidak. Dilakukan perbandingan luas antara modifikasi operasi kanal warna Red, Green, Blue (RGB) dan grayscale menggunakan empat metode deteksi tepi yaitu Roberts, Prewitt, Sobel dan Canny dalam segmentasi luas nukleus. Untuk membantu ahli patologi anatomi dalam mendiagnosa sel mikroskopik Pap smear, dilakukan segmentasi terhadap luas nukleus sel Normal Supercifial Pap smear dengan menggunakan operasi kanal warna dan deteksi tepi. Nilai luas atau area nukleus yang dihasilkan dibandingkan dengan manual segmentasi dari data Herlev. Hasil penelitian memperlihatkan bahwa operasi kanal warna dengan modifikasi penjumlahan kanal Red dan Green (R+G) dengan deteksi tepi Canny memberikan hasil segmentasi luas nukleus sel Normal Supercifial Pap smear yang terbaik dengan prosentase selisih perbedaan 0,05-0,25% dari hasil segmentasi manual oleh ahli patologi dan dokter pada data Herlev. Kata Kunci : Normal Superfisial, nukleus, Pap smear, Kanal Warna, Deteksi Tepi 1. PENDAHULUAN Sampai hari ini, kanker serviks masih berada dalam urutan teratas penyebab kematian terkait kanker pada wanita di dunia. Lebih dari 80% wanita di negara berkembang meninggal karena kanker serviks [1]. Terdapat satu metode deteksi yaitu Pap smear yang melakukan pemeriksaan dan dapat membantu mencegah sejak dini kanker serviks. Pemeriksaan terhadap Squamous epithelium dilakukan ahli patologi anatomi untuk menyatakan hasil Pap smear seorang pasien wanita memiliki sel normal atau abnormal. Tahap kunci dalam deteksi otomatis dini kanker serviks adalah akurasi segmentasi sel nukleus [2]. Selama ini segmentasi nukleus pada citra sel Pap smear banyak dilakukan pada citra berskala abu-abu (grayscale) [3]-[10]. Tujuan penelitian ini untuk membandingkan segmentasi pada citra RGB dengan citra grayscale dalam menangani segmentasi nukleus sel Normal Superfisial. Selain itu juga ingin mengetahui metode deteksi yang terbaik antara keempat metode yaitu Roberts, Prewitt, Sobel dan Canny dalam mendeteksi tepi nukleus sel Normal Superfisial Pap smear. Paper ini terbagi dalam beberapa bagian. Bagian 2 membahas tentang metode dan material yang digunakan dalam penelitian. Bagian 3 menjelaskan tentang hasil dan pembahasan tentang operasi kanal warna citra RGB dan grayscale, deteksi tepi, segmentasi dan perhitungan luas nukleus. Selanjutnya ditutup dengan kesimpulan dan rencana penelitian lanjutan. 2. METODE DAN MATERIAL 2.1. Data Data Herlev [12] terdiri dari 917 sel citra serviks. Tiap sel diklasifikasikan ke dalam tujuh kelas oleh ahli patogi dan dokter, distribusi data diberikan pada Tabel. 1. Penelitian ini mengevaluasi segmentasi sel dari data set tersebut karena data Herlev telah memiliki hasil segmentasi manual bagi seluruh citra oleh ahli patologi dan dokter [12]. Tabel.1 Data set Herlev citra sel Pap smear [12]
Abstrak-Citra digital dapat dijadikan sebagai sumber untuk memperoleh informasi yang dapat diguna... more Abstrak-Citra digital dapat dijadikan sebagai sumber untuk memperoleh informasi yang dapat digunakan untuk menentukan suatu keputusan. Sebagai informasi, pengolahan citra digital perlu dilakukan dengan beberapa metode dan operasi. Pre-processing menjadi tahapan awal dalam pengolahan citra untuk meningkatkan kualitas citra digital. Terdapat beberapa metode pre-processing yang dapat digunakan untuk melakukan pengolahan citra digital. Operasi pre-processing yang dapat digunakan diantaranya histogram equalization, operasi titik, intensity adjustment, thresholding, median averaging, median filtering, dan fast fouring transform. Setiap metode dari pre-processing memiliki algoritma yang berbeda dengan tujuan yang sama yaitu untuk meningkatkan kualitas citra. Penggunaan metode pre-processing dapat dilakukan dengan mengambil salah satu metode terbaik sebelum melakukan proses pengolahan citra. Dari hasil pre-processing kemudian diolah kembali dengan metode deteksi tepi sobel, isotropic, canny, dan gradient untuk mendeteksi kutu kebul pada daun. Dari deteksi tepi yang dilakukan, operasi canny paling tidak sesuai untuk mendeteksi kutu kebul pada daun.
Online Information System of new student registration (SISFO PPDB) is an information system that ... more Online Information System of new student registration (SISFO PPDB) is an information system that is designed by the Government of the Republic Indonesia through City Education Office to conduct automation of new student registration selection with the purpose to ease the new student registration. The processes are conducted in an online and real time manner, starting from registration process, selection until announcement of selection results. This SISFO PPDB often faces problems such as difficulty in filling out for common people because of lack of socialization so that it is necessary for evaluation on SIFO PPDB quality. Delone Mclean Model is a model to measure the success level of an information system based on user perspective. The model that is applied in this research aims to measure the SISFO PPDB quality level. There are 270 students as the research samples, namely Vocational High School (SMK) students in Sukabumi city. Results of this research based on R-Square indicate that user satisfaction variable affects by 97% and net benefit variable affects by 87% on online SISFO PPDB, then it can be concluded that online SISFO PDB quality has been quite good in Sukabumi city. However, it is still necessary to improve its quality by socialization on the community so that the goals of SISFO PPDB application can be realized in a proper manner.
Source code yang dibuat dalam bahasa pemograman C/C++ setelah di-compiler tidak bermasalah. Tetap... more Source code yang dibuat dalam bahasa pemograman C/C++ setelah di-compiler tidak bermasalah. Tetapi sebenarnya perlu diketahui apakah source code tersebut sudah tidak memiliki kelemahan pada fungsi-fungsi yang dipakai dalam source code. Hal ini berkaitan dengan keamanan dari software yang dibuat oleh pengembang software. Evaluasi keamanan software dapat dilakukan dengan menggunakan automatic auditing tools. Dua tools yang dapat digunakan untuk review source code berbahasa C/C++ adalah Flawfinder version 1.27 dan ITS4 version 1.1.1. Perlu dievaluasi apakah Flawfinder dan ITS4 dapat digunakan dalam melakukan review source code berbahasa C.
Evaluasi dilakukan dengan cara melakukan pengujian tools terhadap 10 source code berbahasa C/C++ yang tidak bermasalah dari sisi compiler dengan total jumlah baris (line) sebanyak 575 baris. Pengujian dilakukan untuk mengumpulkan, mengolah, menyajikan dan menganalisis hit@level dan jenis-jenis ancaman dari hasil review source code flawfinder dan ITS4. Selanjutnya dapat disimpulkan perbedaan dari kedua tools tersebut berdasarkan pola pencarian yang terlihat.
Analisa terhadap hasil testing dari dua tools diperoleh bahwa Flawfinder menunjukkan jumlah Software Security Warning (SSW) lebih banyak dari ITS4. Dari persepsi warning dangerous, banyak warning yang ditunjukkan Flawfinder berada pada level low risk dan moderate risk, sedangkan ITS4 lebih banyak pada level low risk. Dari semua source code jenis ancaman yang ditemukan Flawfinder maupun ITS4 adalah buffer overflows.
Uploads
Papers by Dwiza Riana
of information technology and activities of people
who use that technology to support operations and
management. Currently the procurement of
Prospective Civil Servants (CPNS) has implemented
system technology in carrying out each activity. One
form of implementation is in the form of an online
CPNS system. The purpose of this study is to find out
what are the effects of system quality, information
quality, online CPNS service quality on community
satisfaction following online CPNS.. The method
used is TAM (Technology Acceptance Model) with
variable system quality, information quality and
service quality. Based on the results of the study of
the effect of applying the online CPNS system to
community satisfaction, the results showed that:
There is a significant influence between the system
quality variables on community satisfaction, there is
no significant effect between the quality of
information on community satisfaction. There is a
significant influence between service quality
variables on community satisfaction
Conference Presentations by Dwiza Riana
of information technology and activities of people
who use that technology to support operations and
management. Currently the procurement of
Prospective Civil Servants (CPNS) has implemented
system technology in carrying out each activity. One
form of implementation is in the form of an online
CPNS system. The purpose of this study is to find out
what are the effects of system quality, information
quality, online CPNS service quality on community
satisfaction following online CPNS.. The method
used is TAM (Technology Acceptance Model) with
variable system quality, information quality and
service quality. Based on the results of the study of
the effect of applying the online CPNS system to
community satisfaction, the results showed that:
There is a significant influence between the system
quality variables on community satisfaction, there is
no significant effect between the quality of
information on community satisfaction. There is a
significant influence between service quality
variables on community satisfaction
Evaluasi dilakukan dengan cara melakukan pengujian tools terhadap 10 source code berbahasa C/C++ yang tidak bermasalah dari sisi compiler dengan total jumlah baris (line) sebanyak 575 baris. Pengujian dilakukan untuk mengumpulkan, mengolah, menyajikan dan menganalisis hit@level dan jenis-jenis ancaman dari hasil review source code flawfinder dan ITS4. Selanjutnya dapat disimpulkan perbedaan dari kedua tools tersebut berdasarkan pola pencarian yang terlihat.
Analisa terhadap hasil testing dari dua tools diperoleh bahwa Flawfinder menunjukkan jumlah Software Security Warning (SSW) lebih banyak dari ITS4. Dari persepsi warning dangerous, banyak warning yang ditunjukkan Flawfinder berada pada level low risk dan moderate risk, sedangkan ITS4 lebih banyak pada level low risk. Dari semua source code jenis ancaman yang ditemukan Flawfinder maupun ITS4 adalah buffer overflows.