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All Journal Jurnal Bisnis dan Manajemen Journal of Innovation and Applied Technology Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal POINTER Jurnal Pengabdian Kepada Masyarakat (Indonesian Journal of Community Engagement) Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Seminar Nasional Teknologi Informasi Komunikasi dan Industri DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) JPKMI (Jurnal Pengabdian Kepada Masyarakat Indonesia) Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI) Bulletin of Social Informatics Theory and Application
Bayu Rahayudi
Fakultas Ilmu Komputer - Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Public Health Social Sciences

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Sistem Diagnosis Penyakit Ikan Koi Menggunakan Metode Forward Chaining dan Dempster-Shafer Mohammad Zahrul Muttaqin; Edy Santoso; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cultivator's knowledge about what kind of diseases that can infected by Koi at the time of cultivation was very less. Disease predicted indication on Koi cultivation is an important thing to the success of cultivation. Disease prediction obtained by the facts that exist on the cultivation process. Disease determination of Koi can be a source of insufficient information. So that required applications that have knowledge such as experts (specialist). Forward Chaining and Dempster-shafer is a mathematical theory for evidence based on belief functions and plausible reasoning, used to combine separate pieces of information (evidence) to calculate the probability of an event. The method used to get the diagnosis by sorting between general and special symptoms. This application is expected to perform diagnosis and provide ways of handling such as what experts gonna do. In this research, measured accuracy level of application is 95%.
Klasifikasi Risiko Hipertensi Menggunakan Metode Learning Vector Quantization (LVQ) Ivan Agustinus; Edy Santoso; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Hypertension is one of the health problems globally and perceived by the world community. From various surveys conducted, the number of cases of hypertension that occur each year will continue to grow and the number of deaths caused by hypertension also increases. This study attempts to classify hypertensive diseases. In this study using patient data of hypertension disease by divided into 4 classes. Classification method used in this research is Learning Vector Quantization. Data in the form of weight will be entered into the database system for further classification process with LVQ. Weight obtained from medical records of hypertensive patients, This study uses 12 features. This study used 6 test scenarios that resulted in recommendation of value of learning rate 0.1, multiplier learning rate 0.2, training data as much as 50%, alpha minimum 0.001, maximum iteration of 6 and train data used in the sequence of initial id. The result of accuracy obtained is 93.841%
Peramalan Siaga Banjir dengan Menganalisis Data Curah Hujan (ARR) dan Tinggi Muka Air (AWLR) Menggunakan Metode Support Vector Regression (Studi Kasus: Perum Jasa Tirta I) Laila Diana Khulyati; Muhammad Tanzil Furqon; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Flood is a natural disaster that used to be general cause and hard to predict when it will happened. So far, the cause of flood is there's process when rainfall and waterlevel is rise, so there's required some research to do a monitoring on flood alert. From that point, system is required to be able to forecast and make it easier to analyze flood alert status in a future. To forecast a future results, there is a method that based on the availability of raw data, also with statistical analysis technique called regression method. Regression method that used in this research is Support Vector Regression. This SVR method is frequently used in forecasting, but not many of them use rainfall and waterlevel data in a same time. The purpose of this research is to do flood alert forecasting in Kambing Station DAS Brantas. The results represent flood alert forecasting at December 2016, with waterlevel data resulted minimal value of 9.584849544 in error rate and rainfall data resulted minimal value of 10.52259887 in error rate. By using values of parameters = 0.09, = 0.005, = 0.2, = 0.08 and = 0.08. Both data resulted flood alert forecasting that shows Normal.
Peramalan Produksi Gula Pasir Menggunakan Fuzzy Time Series Dengan Optimasi Algoritma Genetika (Studi Kasus PG Candi Baru Sidoarjo) Afif Ridhwan; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Production planning is done by PG Candi Baru Sidoarjo every year as an effort for improving the quality as consumers demand continues to increase. To optimize the production strategy PG Candi Baru should be able to estimate the next production target based on existing historical data. With fuzzy time series method which is optimized by Genetic Algorithm method, the writer wants to help solving the problem to predict the production of sugar, hopefully the research result can help as reference to be used as consideration to determine the amount of sugar production for the next month. Based on the result of testing the accuracy of predictive results using Mean Absolute Percentage Error (MAPE) method obtained the percentage of error rate 1.9% which means the qualification is good.
Optimasi Gizi Pada Bahan Makanan Balita Menggunakan Algoritme Genetika Vivilia Putri Agustin; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In the Golden Age (children under five years old) have an important phase in child growth. Based on Basic Health Research in 2013, the development of children in East Java is still experiencing nutritional problems. The first because, lack of knowledge of parents to the nutritional needs of children. The second because, the lack of attention to the price of food in accordance with food ingredients that have balanced nutrition.One efforts of Dinkes Malang was involving Posyandu to do counseling related to improve child nutrition. However, these efforts were still experiencing obstacles in the form of the number of portions of food given to each children has not been adjusted based on weight and age, in addition the children lack variety of foodstuffs. Thus, the reseracher search a system to optimize it. Genetic algorithm was a Algorithm that was often used to overcome the problem of optimization. The results of the system in the form of lists of food and weight and price adjusted to the weight and age of children.Based on the test results obtained optimal parameters that the optimal population amount of 100, the optimal generation amount of 70 and the optimal combination of cr value and mr value was 0.5 and 0.5 resulted in a fitness value of 50.821.
Pemodelan Regresi Linear untuk Prediksi Konsumsi Energi Primer Indonesia Menggunakan Hybrid Particle Swarm Optimization dan Continuous Ant Colony Optimization Faris Febrianto; Candra Dewi; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Primary energy consumption prediction is an important to project future government energy policy in any country. However, many primary energy consumption prediction often lack of accuracy and data sources. Indonesia primary energy consumption is the biggest than other country in south east asia region and fourth in asia pacific. Indonesia primary energy consumption always increased due to rapid economic growth in last few years, it raised 16% only in three years, 149.31Mtoe in 2010 to 174.24Mtoe in 2013. Indonesia primary energy sources from fossils energy, oil, gas, and coal, otherwise hydro energy, and other renewables energy only 3.33% from total consumption. Our aim is to create primary energy consumption prediction accurately from five input parameter, gross national income, gross domestic product, population, import, and eksport. We use multiple linear regression modelling with find intercept and slope coefficient using hybrid Particle Swarm Optimization and Continuous Ant Colony Optimization. Experiment results shows that linear regression model has average Mean Absolute Percentage Error 10.1% which is good category for primary energy consumption prediction. Hybrid method also compared with regression using standalone Particle Swarm Optimization and standalone Continuous Ant Colony Optimization.
Prediksi Jumlah Kendaraan Bermotor Di Indonesia Menggunakan Metode Average-Based Fuzzy Time Series Models Fajar Pangestu; Agus Wahyu Widodo; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Motor vehicles in Indonesia are growing in number each year. The high number of motor vehicles will affect various sectors. Impacts such as traffic congestion, pollution, accidents, and traffic violations. By predicting the number of motor vehicles, predicted data can be used by the government or related parties to create a program to reduce the impact of high number of motor vehicles. Fuzzy time series is one method for prediction. One type of fuzzy time series method is the average-based fuzzy time series. This method is an average-based fuzzy time series method that is able to determine the effective interval length, so as to provide predictive results with a good degree of accuracy. The data used in the study amounted to 45 data. The result of this research test, the average value of error calculated using Mean Absolute Percentage Error (MAPE) method is 12.67% error value indicating that this research is included in good category used in motor vehicle prediction in Indonesia because it has accuracy value below 20 %.
Optimasi Komposisi Pakan Kuda Dewasa Menggunakan Algoritme Genetika Rheza Raditya Andrianto; Lailil Muflikhah; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesia is one of a country in the world that has a diversity of livestock population such as cows, goats, sheep, and horses. Over time followed by the modern era, the horse population decreased because of the role of horses in various ways and non-fulfillment of nutrition by the horses feed. In this study tries to implement genetic algorithm to get the composition of feed at a minimal cost but the required nutritional standards remain met so as to maintain the health and stability of the horse breed. The representation used in this study is a real code in which each chromosome initializes the feed ingredients used. The reprodustion method used in this study is extended intermediate crossover combined with reciprocal exchange mutation method, and for the last step elitism selection used as a method for selection. Based on the testing results of this study, the optimal parameters obtained is at 70 population, 250 generation and value combination of crossover rate and mutation rate as 0,5 and 0,5 with the highest fitness 0,18887407184772886. The result obtained in the form of feed composition with a minimum cost based on the nutritional needs of adult horses.
Implementasi Metode JST-Backpropagation untuk Klasifikasi Rumah Layak Huni (Studi Kasus: Desa Kidal Kecamatan Tumpang Kabupaten Malang) Riza Rizqiana Perdana Putri; Muhammad Tanzil Furqon; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The house has a big role for each individual and family because house is not only a place to live but house should be comfortable and safe and can maintain the privacy of each family member in accordance with the function of the house as a medium for the implementation of family guidance and education. But in reality, there are still many houses in Indonesia that still do not meet the requirements of a habitable home. The government created a program to assist repairing of uninhabitable homes to provide assistance in order to be right on target, the government must determine whether a person has a habitable home or an uninhabitable home. Therefore, to overcome these problems created an intelligent system for the classification of habitable home using backpropagation algorithm. this study uses 160 data from the Village Kidal Tumpang District Malang Regency which is divided into two categories that are habitable and unhabitable. Backpropagation method is one of the classification method that has excellent performance. This algorithm is very effective in performing various predictions on a problem. This study also uses nguyen widrow for initialization of initial weight. The final test of this research yields the highest accuracy score of 59% by using 15 input layer, 3 hidden layers, learning rate of 0.2.
Implementasi Metode Support Vector Machine (Svm) Untuk Klasifikasi Rumah Layak Huni (Studi Kasus: Desa Kidal Kecamatan Tumpang Kabupaten Malang) Weni Agustina; Muhammad Tanzil Furqon; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

House is an important part in the aspect of life. A habitable house that is good to be used is clean, safe, and comfortable. Lack of knowledge about the function of house in the society, more difficult to imply the realization of a habitable house. Government gets difficulty in assessing the habitable house. In fact, the unpreety house has high income. Government's assistance often misplaced, many people complain because of this. To overcome the problem, then the government needs a system that classifies habitable house and inhabitable house. The system for classification of habitable house was made using the Support Vector Machine (SVM) method. this study uses 160 data that is divided into two types that are habitable and inhabitable. The method used is Support Vector Machine (SVM) method is a good classification method. Support Vector Machine (SVM) method is linear, but SVM method can also be used to solve non-linear problem. The experiment result shows an average accuracy of 98,75% using K-fold Cross Validation test method with k = 10, and SVM method parameters are = 0,5, = 0,001, = 1, = 2, maximum iteration = 10 iteration and using the Polynomial of degree kernel.
Co-Authors Abdullah Harits Abdurrahim, Ahmad Azmi Abhiram, Muhammad Tegar Achmad Choirur Roziqin Achmad Ridok Adam Hendra Brata Ade Wahyu Muntizar Adi Mashabbi Maksun Adi Maulana Rifa'i Adi, Tri Adinda Putri, Lintang Gladyza Adinugroho, Sigit Aditya Septadaya Aditya, Nathanael Chandra Afif Ridhwan Ageng Wibowo Agus Wahyu Widodo Agus Wahyu Widodo, Agus Wahyu Ahmad Afif Supianto Ahmada Bastomi Wijaya Aldi Bagus Sasmita Aldous Elpizochari Alfarisi, Raihan Alfian Reza Pahlevi Alip Setiawan Allifira Andara Hasna Alvian Akmal Nabhan Amaliah Gusfadilah Andhi Surya Wicaksana Andro Subagio Angga Wahyudi Kurniawan Pratama Anggi Novita Sari Anne Diane Rachmadani Arif Indra Kurnia Arina Rufaida Aristides, Joy Vianoktya Arjun Nurdiansyah Arsan, Danish Alif Arsti Syadzwina Fauziah Audia Refanda Permatasari Ayezha Halidar Putri Irwanda Ayuda Dhira Pramadhari Bachtiar, Harsya Bafagih, Novel Bagas Laksono Bastian Dolly Sapuhtra Basuki, Akbar Lucky Bisma Anassuka Brillian Aristyo Rahadian Buce Trias Hanggara Budi Darma Setiawan Cahyo Gusti Indrayanto Candra Dewi Candra Dewi Chandra, Ardhya Khrisna Christina Sri Ratnaningsih Cindy Cynthia Nurkholis Dahnial Syauqy Daniel Agara Siregar Dany Primanita Kartika Sari Dany Primanita Kartikasari Davia Werdiastu Dedy Surya Pradana Dese Narfa Firmansyah Devi Nazhifa Nur Husnina Dhaifa Farah Zhafira Dhimas Wida Syahputra Dhiva Mustikananda Diamanta, Ananda Dian Eka Ratnawati Dian Ratnawati Dian Sisinggih Dimas Adi Syahbani Achmad Putra Djoko Pramono Djoko Pramono Dloifur Rohman Alghifari Dwi H Sulistyarini Dwija Wisnu Brata Dwija Wisnu Brata Dwija Wisnu Brata Dzulkarnain, Tsania Dzulkarnain, Tsania - Edgar Maulana Thoriq Edy Santoso Eko Wahyu Hidayat Ellita Nuryandhani Ananti Ema Rosalina Eni Hartika Harahap Fadilah Islamawan, Adam Faiz Abiyandani Faizatul Amalia Fajar Pangestu Faradila Puspa Wardani Faris Febrianto Farizky Novanda Pramuditya Fauzia, Sri Febrina Sarito Sinaga Ferina Kusuma Anjani Ferry Jiwandhono Fitria Yesisca Gagas Budi Waluyo Gani Kharisma Wardana Gilang Pratama Gusti Reza Maulana Haidar Azmi Rabbani Hanggara , Buce Trias Hardyan Zalfi Harris Imam Fathoni Haryuni Siahaan Hayunanda, alanela ganagisarama Heryadi Mochamad Ramdani Hidayati, Chofifa Hilmy Ramadhan, Achmad Zhafran Huda Minhajur Rosyidin Husalie, Levin Vinnu Imam Cholisoddin Imam Cholissodin Imam Cholissodin Immanuel Tri Putra Sihaloho Indriati Indriati Indriati Indriati Indriati, Indriati - Intan Sartika Eris Maghfiroh Irany Windhyastiti Irwan Shofwan Issa Arwani Issa Arwani Ivan Agustinus Jasico Da Comoro Aruan Jefri Hendra Prasetyo Jonemaro, Eriq Muhammad Adams Jumerlyanti Mase K., Anggraeni Dwi Kautsar, Ahmad Izzan Kevin Nastatur Chatriavandi Khairul Rizal Krishna Febianda Ksatria, Willyan Eka Kurnianingtyas, Diva Laila Diana Khulyati Lailil Muflikhah Liwenki Jus'ma Olivia M. Ali Fauzi M. Ali Fauzi M. Attala Reza Syahputra Made Tri Ganesha Madjid, Marchenda Fayza Marji Marji Marpaung, Veronika Oktafia Marwa Mudrikatussalamah Maulana Syahril Ramadhan Hardiono Maulana, M. Ighfar Maulidhia, Abrilian Meriza Nadhira Atika Surya Michael Eggi Bastian Mochammad Ilman Asnada Mohammad Aditya Noviansyah Mohammad Setya Adi Fauzi Mohammad Zahrul Muttaqin Muh. Arif Rahman Muhammad Ferian Rizky Akbari Muhammad Hidayat Muhammad Ikhsan Nur Muhammad Jibril Alqarni Muhammad Kevin Sandryan Muhammad Nadzir Muhammad Nurhuda Rusardi Muhammad Razan Nadhif Muhammad Reza Utama Pulungan Muhammad Shidqi Fadlilah Muhammad Syahputra Muhammad Tanzil Furqon Mukhtar Darma Hidayat, Alif Ahmad Muthia Maharani Muzayyani, Muhammad Farid Nadiah Nur Fadillah Ramadhani Najihah, Siti Waheeda Nanang Yudi Setiawan Nanang Yudi Setiawan Nanda Alifiya Santoso Putri Nashihul Ibad Al Amin Niken Hendrakusuma Wardani, Niken Hendrakusuma Nilna Fadhila Ganies Novanto Yudistira Nur M. F. Dinia Nurfadhilah, Rakhmad Giffari Nuril Haq, Muhammad Nurizal Dwi Priandani Nurul Hidayat Nurul Ihsani Fadilah Obed Manuel Silalahi Panjaitan, RE. Miracle Pascad Wijanata, Ida Bagus Prakosa, Wira Zeta Pramudita, Julina Larasati Primayuda, Averil Priscillia Vinda Gunawan Purnomo, Welly Putra Pandu Adikara Putranto, Rezky Donny Putri Ratna Sari Putri, Firda Qhafari, Abi Al Qoid A Fadhlurrahman Rafli, Mohammad Ali Rahinda, Muhammad Abiyyi Ramadhani, T. Zalfa Randy Cahya Wihandika Rani Metivianis Rasif Nidaan Khofia Ahmadah RE. Miracle Panjaitan Reinaldi Guista Pradana Ismail Reiza Adi Cahya Renaldi Muhammad Revan Yosua Cornelius Sianturi Reyhan Dzickrillah Laksmana Reza Aprilliana Fauzi Rheza Raditya Andrianto Rifwan Hamidi Riswan Septriayadi Sianturi Riza Rizqiana Perdana Putri Rizky Ardiawan Rizky Nuansa Nanda Permana Rohimatus Sholihah Roisul Setiawan Roma Akbar Iswara Rudianto Raharjo Safa S Istafada Saifurrijaal, Muchammad Salsabila, Dhea Rani Sandi Dewo Rahmadianto Satrio Agung Wicaksono Sekeon, Yerobal Gustaf Setiana, Maya Setiawan, Roisul Shafira Eka Aulia Putri Slamet Thohari Sofi Hidyah Anggraini Sugeng Santoso Sugiarto S Sugiono Sugiono Sukmawati, Annisa Sultan Saladdin Sultan, Muhammad Attharsyah Firdaus Supraptoa Supraptoa Tanica Rakasiwi Tasya Agiyola Teri Kincowati Tri Astoto Kurniawan Trias Hanggara, Buce Trio Pamujo Wicaksono Ulva Febriana Umar Basher, Nizar Umu Khouroh Vivilia Putri Agustin Wahyu Bimantara Wayan Firdaus Mahmudy Welly Purnomo Welly Purnomo Weni Agustina Wenny Ramadha Putri Wibowo, Dhimas Bagus Bimasena Wicaksono, Satrio A. Widhy Hayuhardhika Nugraha Putra Widhy Hayuhardika Nugraha Putra Widodo, Ibnu Sam Widyadhana, Fawwaz Kumudani Wiku Galindra Wardhana Wisnu Brata, Dwija Yahya, Faiz Yesaya Sergio Vito Putranta Yudi Setiawan, Nanang Yuita Arum Sari Yusuf Afandi Zhafira, Dhaifa Farah