The purpose of this research is to measure the speaker recognition accuracy in Content-Based Imag... more The purpose of this research is to measure the speaker recognition accuracy in Content-Based Image Retrieval. To support research in speaker recognition accuracy, we use two approaches for recognition system: identification and verification, an identification using fuzzy Mamdani, a verification using Manhattan distance. The test results in this research. The best of distance mean is size 32x32. The best of the verification for distance rate is 965, and the speaker recognition system has a standard error of 5% and the system accuracy is 95%. From these results, we find that there is an increase in accuracy of almost 2.5%. This is due to a combination of two approaches so the system can add to the accuracy of speaker recognition.
Parametric L-System is a method for modelling virtual plants. Virtual plant modelling consists of... more Parametric L-System is a method for modelling virtual plants. Virtual plant modelling consists of components of axiom and production rules for alphabets in parametric L-System. Generally, to get the alphabet in parametric L-System, one would guess the production rules and perform a modification on the axiom. The objective of this study was to build virtual plant that was affected by the environment. The use of Bayesian networks was to extract the information structure of the growth of a plant as affected by the environment. The next step was to use the information to generate axiom and production rules for the alphabets in the parametric L-System. The results of program testing showed that among the five treatments, the combination of organic and inorganic fertilizer was the environmental factor for the experiment. The highest result of 6.41 during evaluation of the virtual plant came from the treatment with combination of high level of organic fertilizer and medium level of inorganic fertilizer. Mean error between real plant and virtual plan was 9.45 %.
Research about sound processing by computer using fuzzy logic has been known since 1970. One of a... more Research about sound processing by computer using fuzzy logic has been known since 1970. One of approach logic fuzzy method is fuzzy mamdani method. Fuzzy mamdani method is the method to give conclusion from groupof rules of fuzzy. There have to be minimum of two rules, input rule and output rule. Sound processing in canaries bierd's chirp quality can be explained as measurement standar for canary's bird's chirp to the point of song variant and volume. The background of this research is to create a sound identification system that uses dynamic data, the pattern of canary's bird's chirp obtained from dynamic data.Dynamic data is difficult to approach with certain formulas. The purpose of this research is to create indentification system to measure Canaries bird's chirp quality pre-contest. The method used in this research was statistic analysis, sound analysis and fuzzy Mamdani method. Statistic analysis was used to look for important features from Canarie's chirp sample. This analysis results Max amplitude variable, Min amplitude variable, Root-mean square. Then sound analysis results Autocorrelation time, Zero cross and Energy. Then those values were used as the input in fuzzy Mamdani method process. As for the output variables were the judges score result about the quality of bird' chirp. The results from identification system of bird's chirp quality from 6 samples are (1). Accuration level 81,67%. (2) Error sytemrate 18,33%. (3). Based on system performance and error rate that have been known can be concluded that the system can indentifyCanarie's chirp quality well.
ABSTRAK Pendekatan dalam mempelajari pemodelan pertumbuhan tanaman saat ini adalah dengan menggun... more ABSTRAK Pendekatan dalam mempelajari pemodelan pertumbuhan tanaman saat ini adalah dengan menggunakan metoda L-System yaitu sistem penulisan berulang (rewriting system) yang dilakukan secara paralel dengan menggunakan aturan gramatikal. Dengan menggunakan software Mathematica telah diidentifikasi pemodelan pertumbuhan tanaman zinnia sebanyak 6 tahap pertumbuhan selama 25 hari dan dapat divisualisasikan. ABSTRACT The approaches in the study of plant modelling growth at this time is using the method of L-system, that is a system of repetitive writing repetitive performed in parallel by using grammatical rules. By using Mathematica this modeling has been identified as 6 zinnia plant growth during the growth phase of 25 days and can be visualized.
Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System... more Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System). To make the condition close to the real environment characteristic, it is required the axiom and syntax grammar for the L-System. In this paper, we propose the use of artificial neural networks together with the L-System method, to model the plant's growth based on the current environment condition. At the beginning of plant growth, let the sprout of plant initially be denoted as axiom. This characteristic rules are illustrated in the reproduction of L-System also occur in nature of plant growth conditions based on the artificial neural networks. The software used in this modeling is Mathematica. In this research, the growth parameters value is given based on the artificial neural networks, the plant growth is visualized with the L-System method, and the 3-Dimension graph is shown as the virtual plant growth.
Abstrack - Soybean (Glycine max (L.) Merrill var. Willis) is one of the crops and has become a st... more Abstrack - Soybean (Glycine max (L.) Merrill var. Willis) is one of the crops and has become a staple in Indonesia. With the development of technology today soybean plants begin simulated by using a 3D shape with Groimp applications based XL System and to prove the growth simulation research using organic fertilizer and urea fertilizer at different treatment This study aimed to investigate the effect of fertilizing with liquid organic fertilizer on the productivity of soybean plants, know the time of fertilization that provides the best results and to know the interaction between fertilizer type and time of fertilization. The study was conducted with a structured design. Factors that first dose of fertilizer are: P1 (3 ml of organic fertilizer / 1 liter water / Evening), P2 (3 ml of organic fertilizer / 1 liter water / Morning), P3 (2 g urea / 1 liter water / Evening), P4 (2 g urea / 1 liter water / Morning). Parameters observed that plant height, stem length, number of branches and number of leaves. The data obtained were entered and calculated using ANFIS after the training process and the smallest error obtained from the plant where the election will be simulated in 3D. The results showed that fertilization with urea fertilizer can increase the productivity of soybean plants were compared using Liquid Organic Fertilizer. When fertilizing in the afternoon also causes soybean crop productivity higher than in the morning. Between time and type of fertilizer are to increase plant height interaction, many branches and many leaves of soybean. season and the environment affect the growth of plants and to research obtained herbs having etiolasi and after the transfer of the place after day to 28 to a place that is roomy in fact still not give an influence upon a plant which is supposed to the age of soybean already flowering at the age of to 35-40 day is not blossom, it is expected that plants season should indeed be planted in the season to the result is also maximum and environmental conditions must be considered.
—The role acquired by modeling in plant sciences includes integration of knowledge, exploration o... more —The role acquired by modeling in plant sciences includes integration of knowledge, exploration of the behavior of the plant system beyond the range of conditions covered experimentally and decision support. The purpose of the model determines its structure. Initially process artificial intelligence (PAI) were developed separately from structural (or: architectural or morphological) plant models (SPM). Combining PAI and SPM into functional structural plant models (FSPM) or virtual plants has become intelligence. This adds a dimension to classical growth modeling. FSPM are particularly suited to analyze problems in which the spatial structure of the system is an essential factor contributing to the explanation of the behavior of the system of study. Examples analyses of mechanisms of physiological response to environmental signals that affect plant architectures on production of the plant architecture (stalk, branch, leaf and bloom) in the plant. To make the condition close to the real environment characteristic, it is required the axiom and syntax grammar for the L-System. In this paper, we propose the use of fuzzy system together with the L-System method, to model the plant growth based on the current environment condition. At the beginning of plant growth, let the sprout of plant initially be denoted as axiom. This characteristic rules are illustrated in the reproduction of L-System also occur in nature of plant growth conditions based on fuzzy system. The software used in this modeling is GroIMP. The plant architecture value is given based on the fuzzy system, the plant growth is visualized with the L-System method, controlled evolution of complex structures is exemplified by the development of tree structures generated by the movement of a 3D-turtle and the 3-Dimension graph is shown as the virtual plant growth. Good modeling practice involves different steps in model development. These steps are discussed and include the conceptual modeling, data collection, model implementation, model verification and evaluation, sensitivity analysis and scenario studies.
Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System... more Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System). The L-System is generally used as the backbone to develop the realistic modeling for the plant's growth. The Genetic L-System Programming (GLP) is evolutionary creation and development of parallel rewrite systems (L-Systems) which provide a commonly used formalism to describe developmental processes of natural organisms. To make the condition close to the real environment characteristic, it is required the axiom and syntax grammar for the L-System. In this paper, we propose the use of fuzzy system together with the Genetic L-System Programming method, to model the plant's growth based on the current environment condition. At the beginning of plant growth, let the sprout of plant initially be denoted as axiom. This characteristic rules are illustrated in the reproduction of Genetic L-System Programming (simulated evolution and simulated structure formation) also occur in nature of plant growth conditions based on fuzzy system. The software used in this modeling is Mathematica. The growth parameters value is given based on the fuzzy system, the plant growth is visualized with the L-System method, controlled evolution of complex structures is exemplified by the development of tree structures generated by the movement of a 3D-turtle and the 3-Dimension graph is shown as the virtual plant growth. In this research, some samples of axiom have been given based on fuzzy system. This research also demonstrates that the Genetic L-System Programming is able to show the characteristic and structural visualization on the plant growth according to the environment.
Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System... more Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System). This L-System models the plants growth by following the production rules, which are the combination of grammar and mathematic formulae. In this paper, we propose the use of fuzzy mamdani, to model the plant growth based on the current environment condition. The varied amount of fertilizer, both organic and inorganic fertilizer, is used as the input to the Fuzzy Mamdani. The output of the Fuzzy Mamdani is used as the input to the zinnia plant growth model. The novelty of this research is the using Fuzzy Mamdani to model the zinnia plant growth with L-System methode. In this research, the dynamic plant model of zinnia variant has been developed using Fuzzy Mamdani to model the zinnia plant growth. This model has been simulated on computer software. This model shows the response of the amount of fertilizer towards the zinnia height virtually and this response is then simulated. The best height is when the plant is given 100% organic and 75% inorganic fertilizers.
Earthquake early warning service for tsunami is important for the public. On one side the service... more Earthquake early warning service for tsunami is important for the public. On one side the service cannot be easily accessed by the public especially television users. On another side the development of television technology, especially digital television, should be much easier to access. The purpose of this research is to make the method of processing data in Multimedia Home Platform (MHP) Applications for Earthquake Early Warning of Potentially Tsunami Services. Earthquake and weather data are taken from the web site Application Programming Interface (API) by The Meteorology, Climatology, and Geophysics (BMKG) in Indonesia. The research method is parsing techniques eXtensible Markup Language (XML) with the Document Object Model (DOM). The time interval for data collection from the Web site of BMKG uses the method of Systematic Sampling. Therefore, MHP applications can update Earthquakes and weather data in real-time in a specified interval. The results of XML parsing form of tsunami potential earthquake data are recorded by MHP applications into file storage. The findings show that MHP applications can display earthquake early warning of potentially Tsunami information to users of television accordance with BMKG website in real time.
Background/Objectives: To improve an identification of chlorophyll content in leaf, this paper pr... more Background/Objectives: To improve an identification of chlorophyll content in leaf, this paper presents an implementation of a supervised learning method based on membership function training in the context of mamdani fuzzy models. Methods/Statistical Analysis:this paper presents a fuzzy rule based algorithm; natural color image in leaf (Red, Green and Blue) is used as the input to the fuzzy mamdani models. The output of the fuzzy mamdani models is value of chlorophyll content. Results: The proposed approach was superior to identification of chlorophyll content in leaf using image processing technique and mamdani fuzzy method has higher identification accuracy. Conclusion/Application: Finally, the basic difference of value of chlorophyll content between fuzzy mamdani models and the actual was less than 3,1 % on average.
PEDOMAN TEKNIS PENULISAN TUGAS PROYEK PESERTA DIDIK PROGRAM PENDIDIKAN 1 TAHUN INOVASI BISNIS DAN... more PEDOMAN TEKNIS PENULISAN TUGAS PROYEK PESERTA DIDIK PROGRAM PENDIDIKAN 1 TAHUN INOVASI BISNIS DAN TEKNOLOGI ( Probistek ) ULUL ALBAB UIN MAULANA MALIK IBRAHIM MALANG
Pedoman Penulisan Laporan Kegiatan On The Job Training ( Praktek Kerja Lapangan ) Bagi Peserta Di... more Pedoman Penulisan Laporan Kegiatan On The Job Training ( Praktek Kerja Lapangan ) Bagi Peserta Didik Program Pendidikan 1 Tahun Inovasi Bisnis dan Teknologi ( Probistek ) Ulul Albab
The purpose of this research is to measure the speaker recognition accuracy in Content-Based Imag... more The purpose of this research is to measure the speaker recognition accuracy in Content-Based Image Retrieval. To support research in speaker recognition accuracy, we use two approaches for recognition system: identification and verification, an identification using fuzzy Mamdani, a verification using Manhattan distance. The test results in this research. The best of distance mean is size 32x32. The best of the verification for distance rate is 965, and the speaker recognition system has a standard error of 5% and the system accuracy is 95%. From these results, we find that there is an increase in accuracy of almost 2.5%. This is due to a combination of two approaches so the system can add to the accuracy of speaker recognition.
Parametric L-System is a method for modelling virtual plants. Virtual plant modelling consists of... more Parametric L-System is a method for modelling virtual plants. Virtual plant modelling consists of components of axiom and production rules for alphabets in parametric L-System. Generally, to get the alphabet in parametric L-System, one would guess the production rules and perform a modification on the axiom. The objective of this study was to build virtual plant that was affected by the environment. The use of Bayesian networks was to extract the information structure of the growth of a plant as affected by the environment. The next step was to use the information to generate axiom and production rules for the alphabets in the parametric L-System. The results of program testing showed that among the five treatments, the combination of organic and inorganic fertilizer was the environmental factor for the experiment. The highest result of 6.41 during evaluation of the virtual plant came from the treatment with combination of high level of organic fertilizer and medium level of inorganic fertilizer. Mean error between real plant and virtual plan was 9.45 %.
Research about sound processing by computer using fuzzy logic has been known since 1970. One of a... more Research about sound processing by computer using fuzzy logic has been known since 1970. One of approach logic fuzzy method is fuzzy mamdani method. Fuzzy mamdani method is the method to give conclusion from groupof rules of fuzzy. There have to be minimum of two rules, input rule and output rule. Sound processing in canaries bierd's chirp quality can be explained as measurement standar for canary's bird's chirp to the point of song variant and volume. The background of this research is to create a sound identification system that uses dynamic data, the pattern of canary's bird's chirp obtained from dynamic data.Dynamic data is difficult to approach with certain formulas. The purpose of this research is to create indentification system to measure Canaries bird's chirp quality pre-contest. The method used in this research was statistic analysis, sound analysis and fuzzy Mamdani method. Statistic analysis was used to look for important features from Canarie's chirp sample. This analysis results Max amplitude variable, Min amplitude variable, Root-mean square. Then sound analysis results Autocorrelation time, Zero cross and Energy. Then those values were used as the input in fuzzy Mamdani method process. As for the output variables were the judges score result about the quality of bird' chirp. The results from identification system of bird's chirp quality from 6 samples are (1). Accuration level 81,67%. (2) Error sytemrate 18,33%. (3). Based on system performance and error rate that have been known can be concluded that the system can indentifyCanarie's chirp quality well.
ABSTRAK Pendekatan dalam mempelajari pemodelan pertumbuhan tanaman saat ini adalah dengan menggun... more ABSTRAK Pendekatan dalam mempelajari pemodelan pertumbuhan tanaman saat ini adalah dengan menggunakan metoda L-System yaitu sistem penulisan berulang (rewriting system) yang dilakukan secara paralel dengan menggunakan aturan gramatikal. Dengan menggunakan software Mathematica telah diidentifikasi pemodelan pertumbuhan tanaman zinnia sebanyak 6 tahap pertumbuhan selama 25 hari dan dapat divisualisasikan. ABSTRACT The approaches in the study of plant modelling growth at this time is using the method of L-system, that is a system of repetitive writing repetitive performed in parallel by using grammatical rules. By using Mathematica this modeling has been identified as 6 zinnia plant growth during the growth phase of 25 days and can be visualized.
Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System... more Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System). To make the condition close to the real environment characteristic, it is required the axiom and syntax grammar for the L-System. In this paper, we propose the use of artificial neural networks together with the L-System method, to model the plant's growth based on the current environment condition. At the beginning of plant growth, let the sprout of plant initially be denoted as axiom. This characteristic rules are illustrated in the reproduction of L-System also occur in nature of plant growth conditions based on the artificial neural networks. The software used in this modeling is Mathematica. In this research, the growth parameters value is given based on the artificial neural networks, the plant growth is visualized with the L-System method, and the 3-Dimension graph is shown as the virtual plant growth.
Abstrack - Soybean (Glycine max (L.) Merrill var. Willis) is one of the crops and has become a st... more Abstrack - Soybean (Glycine max (L.) Merrill var. Willis) is one of the crops and has become a staple in Indonesia. With the development of technology today soybean plants begin simulated by using a 3D shape with Groimp applications based XL System and to prove the growth simulation research using organic fertilizer and urea fertilizer at different treatment This study aimed to investigate the effect of fertilizing with liquid organic fertilizer on the productivity of soybean plants, know the time of fertilization that provides the best results and to know the interaction between fertilizer type and time of fertilization. The study was conducted with a structured design. Factors that first dose of fertilizer are: P1 (3 ml of organic fertilizer / 1 liter water / Evening), P2 (3 ml of organic fertilizer / 1 liter water / Morning), P3 (2 g urea / 1 liter water / Evening), P4 (2 g urea / 1 liter water / Morning). Parameters observed that plant height, stem length, number of branches and number of leaves. The data obtained were entered and calculated using ANFIS after the training process and the smallest error obtained from the plant where the election will be simulated in 3D. The results showed that fertilization with urea fertilizer can increase the productivity of soybean plants were compared using Liquid Organic Fertilizer. When fertilizing in the afternoon also causes soybean crop productivity higher than in the morning. Between time and type of fertilizer are to increase plant height interaction, many branches and many leaves of soybean. season and the environment affect the growth of plants and to research obtained herbs having etiolasi and after the transfer of the place after day to 28 to a place that is roomy in fact still not give an influence upon a plant which is supposed to the age of soybean already flowering at the age of to 35-40 day is not blossom, it is expected that plants season should indeed be planted in the season to the result is also maximum and environmental conditions must be considered.
—The role acquired by modeling in plant sciences includes integration of knowledge, exploration o... more —The role acquired by modeling in plant sciences includes integration of knowledge, exploration of the behavior of the plant system beyond the range of conditions covered experimentally and decision support. The purpose of the model determines its structure. Initially process artificial intelligence (PAI) were developed separately from structural (or: architectural or morphological) plant models (SPM). Combining PAI and SPM into functional structural plant models (FSPM) or virtual plants has become intelligence. This adds a dimension to classical growth modeling. FSPM are particularly suited to analyze problems in which the spatial structure of the system is an essential factor contributing to the explanation of the behavior of the system of study. Examples analyses of mechanisms of physiological response to environmental signals that affect plant architectures on production of the plant architecture (stalk, branch, leaf and bloom) in the plant. To make the condition close to the real environment characteristic, it is required the axiom and syntax grammar for the L-System. In this paper, we propose the use of fuzzy system together with the L-System method, to model the plant growth based on the current environment condition. At the beginning of plant growth, let the sprout of plant initially be denoted as axiom. This characteristic rules are illustrated in the reproduction of L-System also occur in nature of plant growth conditions based on fuzzy system. The software used in this modeling is GroIMP. The plant architecture value is given based on the fuzzy system, the plant growth is visualized with the L-System method, controlled evolution of complex structures is exemplified by the development of tree structures generated by the movement of a 3D-turtle and the 3-Dimension graph is shown as the virtual plant growth. Good modeling practice involves different steps in model development. These steps are discussed and include the conceptual modeling, data collection, model implementation, model verification and evaluation, sensitivity analysis and scenario studies.
Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System... more Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System). The L-System is generally used as the backbone to develop the realistic modeling for the plant's growth. The Genetic L-System Programming (GLP) is evolutionary creation and development of parallel rewrite systems (L-Systems) which provide a commonly used formalism to describe developmental processes of natural organisms. To make the condition close to the real environment characteristic, it is required the axiom and syntax grammar for the L-System. In this paper, we propose the use of fuzzy system together with the Genetic L-System Programming method, to model the plant's growth based on the current environment condition. At the beginning of plant growth, let the sprout of plant initially be denoted as axiom. This characteristic rules are illustrated in the reproduction of Genetic L-System Programming (simulated evolution and simulated structure formation) also occur in nature of plant growth conditions based on fuzzy system. The software used in this modeling is Mathematica. The growth parameters value is given based on the fuzzy system, the plant growth is visualized with the L-System method, controlled evolution of complex structures is exemplified by the development of tree structures generated by the movement of a 3D-turtle and the 3-Dimension graph is shown as the virtual plant growth. In this research, some samples of axiom have been given based on fuzzy system. This research also demonstrates that the Genetic L-System Programming is able to show the characteristic and structural visualization on the plant growth according to the environment.
Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System... more Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System). This L-System models the plants growth by following the production rules, which are the combination of grammar and mathematic formulae. In this paper, we propose the use of fuzzy mamdani, to model the plant growth based on the current environment condition. The varied amount of fertilizer, both organic and inorganic fertilizer, is used as the input to the Fuzzy Mamdani. The output of the Fuzzy Mamdani is used as the input to the zinnia plant growth model. The novelty of this research is the using Fuzzy Mamdani to model the zinnia plant growth with L-System methode. In this research, the dynamic plant model of zinnia variant has been developed using Fuzzy Mamdani to model the zinnia plant growth. This model has been simulated on computer software. This model shows the response of the amount of fertilizer towards the zinnia height virtually and this response is then simulated. The best height is when the plant is given 100% organic and 75% inorganic fertilizers.
Earthquake early warning service for tsunami is important for the public. On one side the service... more Earthquake early warning service for tsunami is important for the public. On one side the service cannot be easily accessed by the public especially television users. On another side the development of television technology, especially digital television, should be much easier to access. The purpose of this research is to make the method of processing data in Multimedia Home Platform (MHP) Applications for Earthquake Early Warning of Potentially Tsunami Services. Earthquake and weather data are taken from the web site Application Programming Interface (API) by The Meteorology, Climatology, and Geophysics (BMKG) in Indonesia. The research method is parsing techniques eXtensible Markup Language (XML) with the Document Object Model (DOM). The time interval for data collection from the Web site of BMKG uses the method of Systematic Sampling. Therefore, MHP applications can update Earthquakes and weather data in real-time in a specified interval. The results of XML parsing form of tsunami potential earthquake data are recorded by MHP applications into file storage. The findings show that MHP applications can display earthquake early warning of potentially Tsunami information to users of television accordance with BMKG website in real time.
Background/Objectives: To improve an identification of chlorophyll content in leaf, this paper pr... more Background/Objectives: To improve an identification of chlorophyll content in leaf, this paper presents an implementation of a supervised learning method based on membership function training in the context of mamdani fuzzy models. Methods/Statistical Analysis:this paper presents a fuzzy rule based algorithm; natural color image in leaf (Red, Green and Blue) is used as the input to the fuzzy mamdani models. The output of the fuzzy mamdani models is value of chlorophyll content. Results: The proposed approach was superior to identification of chlorophyll content in leaf using image processing technique and mamdani fuzzy method has higher identification accuracy. Conclusion/Application: Finally, the basic difference of value of chlorophyll content between fuzzy mamdani models and the actual was less than 3,1 % on average.
PEDOMAN TEKNIS PENULISAN TUGAS PROYEK PESERTA DIDIK PROGRAM PENDIDIKAN 1 TAHUN INOVASI BISNIS DAN... more PEDOMAN TEKNIS PENULISAN TUGAS PROYEK PESERTA DIDIK PROGRAM PENDIDIKAN 1 TAHUN INOVASI BISNIS DAN TEKNOLOGI ( Probistek ) ULUL ALBAB UIN MAULANA MALIK IBRAHIM MALANG
Pedoman Penulisan Laporan Kegiatan On The Job Training ( Praktek Kerja Lapangan ) Bagi Peserta Di... more Pedoman Penulisan Laporan Kegiatan On The Job Training ( Praktek Kerja Lapangan ) Bagi Peserta Didik Program Pendidikan 1 Tahun Inovasi Bisnis dan Teknologi ( Probistek ) Ulul Albab
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