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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Disability Studies Journal of Environmental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer Register: Jurnal Ilmiah Teknologi Sistem Informasi Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Budi Darma Setiawan
Fakultas Ilmu Komputer , Universitas Brawijaya
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Mechanical Engineering Social Sciences

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Optimasi Fuzzy Time Series Dengan Algoritme Genetika Untuk Meramalkan Jumlah Pengangguran di Jawa Timur Radifah Radifah; Budi Darma Setiawan; Rendi Cahya Wihandika
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

Unemployment becomes one of the important points that are occurred in Indonesia. High unemployment rate has an impact on the economic and poverty levels of Indonesians especially in East Java. The increase number of unemployment can reduce the income and productivity of society. Several factors that are causing the increase of unemployment make the government difficult to overcome the numbers of unemployment annually that experience ups and downs. So, by predicting the number of unemployment in East Java, it can facilitate the government in overcoming the unemployment rate and expanding the workforce especially in East Java. The method that is used in this study is Fuzzy Time Series that use Genetic Algorithm. The best genetic algorithm parameter values are by testing to the genetic algorithm parameters and producing the best average fitness value. The result of genetic algorithm parameter test are with the population size of 525, the combination of crossover rate and mutation rate of 0,8 and 0,2 and at generation of 1200 which reaches the most optimal average fitness value is 13,840314614 with Root Mean Square Error(RMSE) value equal to 0,0722526928.
Peramalan Jumlah Kasus Penyakit Menggunakan Jaringan Saraf Tiruan Backpropagation (Studi Kasus Puskesmas Rogotrunan Lumajang) Andika Harlan; Budi Darma Setiawan; Marji Marji
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

Changes in the number of cases of disease is very influential on health improvement efforts both in terms of medicines availability, targeted medicines, damaged medicines and so forth. Knowing the pattern of the number of cases of disease is very important for some activities and jobs that exist. Therefore it is necessary to forecast the number of cases of disease to determine the pattern of the number of cases of disease in the future. One of the most common method of artificial neural network forecasting is Backpropagation. This study aims to forecast the number of cases of disease by using the case study of puskesmas Rogotrunan, Lumajang using Backpropagation method. Backpropagation parameters tested are the amount of data (n), alpha (α), and the number of iterations (epoch). Forecasting the number of disease on cases with test data from January to December of 2016 conducted using Backpropagation resulted in the value of MSE 115 and the accuracy of 0.0088.
Optimasi Fuzzy Time Series Menggunakan Algoritma Particle Swarm Optimization Untuk Peramalan Jumlah Penduduk Di Kabupaten Probolinggo Cahyo Adi Prasojo; Budi Darma Setiawan; Marji Marji
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

Population growth occurs due to the increasing number of births. The impact of population growth is affecting human welfare, Both in the economic, health, social, politic and cultural fields. Therefore it is necessary to forecast the population, to know how fast the rate of population growth. One of the most commonly used forecasting methods is the Fuzzy Time Series (FTS). However, this method still has a deficiency that is on the determination of the value of the interval that is less precise. therefore it is necessary the optimization algorithm to find the optimal value of the interval. This study aims to perform population forecasting in Probolinggo District by using FTS method which will be optimized using Particle Swarm Optimization (PSO) algorithm. Optimization is performed to obtain optimal interval value on FTS and optimal parameter value on PSO. The parameters in the optimized PSO are (Inertial Weight), (velocity constant 1) and (velocity constant 2). The result of the test, that is got the best fitness , and value, is 0,559140, 0,535084 and 0.621134 and parameter value are 0,6, 1.8 and 2.4. Get the best fitness value of the forecasting, is 0.445334.
Optimasi Peramalan Jumlah Kasus Penyakit Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation Dengan Algoritma Genetika Gilang Ramadhan; Budi Darma Setiawan; Marji Marji
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

The number of disease cases has increased and decreased every month. This has an impact on the unbalanced of medicine availability such as, lack of supply of medicine, waste of medicine, medicine that are not on target, damaged medicine and so on. Therefore forecasting on number of disease cases is needed to determine the number of disease cases within a certain time. One of forecasting method that can be used is backpropagation neural network method. This method can be optimized using genetic algorithm to produce optimal results. The optimized parameters are weight and bias which will be used in backpropagation algorithm. The purpose of this study is to forecast the number of disease cases at Puskesmas Rogotrunan, Lumajang using backpropagation method optimized by genetic algorithm. From this study the optimal parameters of genetic algorithm are population=180, combination of cr and mr respectively 0,4 and 0,6, generation=100. The optimal parameters of backpropagation algorithm are total data=16, input neuron=6, iteration=1000, alfa=0,1. Accuray obtained with MSE=87,2 with data test of the number of disease cases in january to desember 2016. From the value of MSE obtained using backpropagation method optimized by genetic algorithm can be used to forecast the number of disease cases.
Identifikasi Gangguan Kepribadian Dramatis Menggunakan Metode Learning Vector Quantization (LVQ) M Kevin Pahlevi; Budi Darma Setiawan; Tri Afirianto
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

Personality disorder is one of the health problems experienced and felt by the community. Group B or so-called dramatic is more common due to increased suicide rates, high social media access, still happening brawl and bullying all over, then many phenomena about people who want to steal attention with a physical look or style of language that is not commonly, this can increase the risk of people affected personality disorders, especially the dramatic group. This study try to identify dramatic personality disorders. This dramatic personality disorder is divided into 4 classes. The method used is Learning Vector Quantization. Data obtained from questionnaires using 32 parameters and managed to get data as much as 90 data. This research conducts 4 test scenarios that result in a learning rate of 0.2, a multiplier learning rate of 0.4, a minimum learning rate of 0.001, and a training data of 60. The result of accuracy is 70%.
Support Vector Regression Untuk Peramalan Permintaan Darah: Studi Kasus Unit Transfusi Darah Cabang - PMI Kota Malang M. Raabith Rifqi; Budi Darma Setiawan; Fitra Abdurrachman Bachtiar
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

PMI is responsible for meeting blood demand from hospitals. The management of the blood storage center has a very important task, to predict the requirement of blood components to minimize the ex less and the lack of blood supply. Blood has only a life span of 35 days since donated. If it is past the time then it can not be used anymore. Excess or lack of blood supply at the site should not occur, because it can affect the number of patients death. In order to reduce the losses that if it occurs, it is necessary to do research that uses the prediction method of blood predict that is implemented in a system. One of them with Support Vector Regression method that is suitable for blood demand forecasting. Implement SVR using normalized min - max data and use RBF kernel function. Based on the test results for the SVR method that has been done, the result of the minimum MAPE value is 3.899% with the parameter value lambda = 10, sigma = 0.5, cLR = 0.01, C = 0.1, epsilon = 0.01, number of data features = 4 and number of iterations of 5000, of the 12 test data used. The resulting MAPE value is <10% and can be categorized as good for predicting the amount of blood demand.
Algoritme Genetika Untuk Optimasi K-Means Clustering Dalam Pengelompokan Data Tsunami Dwi Anggraeni Kuntjoro; Budi Darma Setiawan; Rizal Setya Perdana
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

Tsunami is one of the most deadly disaster causing damage and loss of life and wealth. It happens in a sudden and unpredictable. Lack of awareness often leads to a great damage and worsening the impact of tsunami itself. This research implements genetic algorithm optimization into K-Means method for classify tsunami data. By optimazing the initial cluster center it will used as an input on K-Means method. The method result more optimal preference than the conventional K-Means method since the central point is optimized by genetic algorithm. It was proved on this research where fitness value resulted from Silhouette Coefficient to observe how suitable data with cluster. Chromosome representation used here is real code to initialize centroid value. Extended intermediate crossover applied for crossover method. For mutation method, random mutation is run here. Also for selection method it uses elitism selection. Based on testing result, the most optimum parameter accomplished are 50 population, 70 generation, and Cr =0.9 and Mr =0.1 combination with fitness value around 0.995934
Optimasi Fuzzy Inference System Tsukamoto Menggunakan Algoritme Genetika Untuk Mengetahui Lama Waktu Siram Pada Tanaman Strawberry Muhammad Khaerul Ardi; Budi Darma Setiawan; Mochammad Ali Fauzi
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

Soil is a crusial component for plant growth. There are many parameters that used for soil examination, and one of its parameter is soil's dampness. Laboratorium Benih Balai Pengkajian Teknologi Pertanian Jawa Timur is one of the work units that has a duty to examine the soil for plant nursery purpose. However, due to the conventional tools that they used sometimes the examination result is not as accurate as they expected. Because of that problem the author did some research to make a smart computing system that can be implemented on a tool that can maintain the soil's dampness automatically. Fuzzy Inference System Tsukamoto is used to calculate how long does it take to water the plants by using two variable inputs; initial dampness and water volume. Genetic algorithm is used to get an optimal membership function by optimizing the boundaries of each membership function. The output of this research will display the optimal time to water the plants. From the examination result we got an error value for about 4,9570, but after optimization the number is reduced to 0,3790. With that result we can conclude that using Fuzzy Inference System Tsukamoto and optimized with genetic algorithm is able to calculate how much time that it takes to water the plants and still able to get a good outcome.
Identifikasi Awal Pengguna Narkoba Menggunakan Metode Learning Vector Quantization (LVQ) Yulfa Hadi Wicaksono; Budi Darma Setiawan; Tri Afirianto
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

Drug abuse is one of the major problems for Indonesian country. This is due to drug users can cause psychiatric disorders, health and even death. From various surveys conducted, the number of cases of drug users increase every time. In this study, the research will try to do initial identification for users with Learning Vector Quantizationmethod. This study uses the data of drug users from Badan Narkotika Nasional (BNN) in Malang Regency. From 119 data, there will be divided into 3 parts. There are 4 data for initial weight vectors, 103 for training data and 12 for test data. Then, in this data have 16 parameters and 4 classes. In this study, 6 tests were performed, resulting in 0.1 for the learning level with an average score of 74.8%. Then, 0.9 for a learning rate multiplier with an average rating of 79.8%. Then, 0.01 for the minimum level of learning with an average grade. The amount of training data is 60% with average value. The maximum of 14 lawer iterations with average values. Then, for LVQ training stops on which best condition is at maximum iteration 14. Therefore, the minimum of learning rate condition can be ignored. From those results, the average of final accuracy after testing with K-Fold Cross Validation is 78.4%.
Optimasi Penjadwalan Mata Pelajaran Pondok Pesantren Mahasiswa Menggunakan Algoritme Genetika (Studi Kasus: Yayasan Bina Insani Sukses Malang) Rudy Usman Azzakky; Budi Darma Setiawan; Satrio Hadi Wijoyo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 11 (2018): November 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The process of drafting schedules manually felt less efficient because it takes a long time. The problem of drafting the schedule will be complex if the number of components is larger amount of data from each component. The expected schedule is not just a schedule that does not clash, but a schedule that can adapt to some constraints that must be met within the schedule. Genetic Algorithms are algorithms that are iterative, self-adjusting and probabilistic algorithms in search for global optimization. The process of chromosome initialization generated from teacher assignment data by integer representation of each gene containing randomly generated assignment codes. Each chromosome with the highest fitness value is a representation of the subject schedule solution. From the testing process that has been done, has obtained the parameters of Genetic Algorithm is the best population number is 100, the value of the combination of Cr and Mr is 0.5 and 0.5, and the number of generations as much as 1000. The process of finding solutions using these parameters obtained the value of fitness that is 0.9977.
Co-Authors Abdul Fatih Achmad Basuki Achmad Fahlevi Addin Sahirah, Rafifa Adinugroho, Sigit Aditya Chandra Nurhakim Aditya Kresna Bayu Arda Putra Agung Nurjaya Megantara Agus Wahyu Widodo Ahmad Afif Supianto Akhmad Eriq Ghozali Akmal Subakti Wicaksana Alfi Nur Rusydi Almira Syawli, Almira Amaliah Gusfadilah Andhi Surya Wicaksana Andika Harlan Angga Dwi Apria Rifandi Anjasari, Ni Luh Made Beathris Aria Bayu Elfajar Asghany, Yusrian Ashidiq, Muhammad Fihan Azmi Makarima Yattaqillah Baihaqi, Galih Restu Barlian Henryranu Prasetio Bayu Rahayudi Bintang, Tulistyana Irfany Budi Santoso Cahyo Adi Prasojo Candra Dewi Candra Dewi Chelsa Farah Virkhansa Cindy Inka Sari Cinthia Vairra Hudiyanti Civica Moehaimin Dhewanty Deby Chintya Dellia Airyn Delpiero, Rangga Raditya Dewi, Buana Dhan Adhillah Mardhika Dian Eka Ratnawati Diva, Zahra Dwi Anggraeni Kuntjoro Dwi Ari Suryaningrum Dwi Damara Kartikasari Edo Fadila Sirat Eka Novita Shandra Eka Yuni Darmayanti Eti Setiawati Fadhlillah Ikhsan Fajar Nur Rohmat Fauzan Jaya Aziz Fajar Pradana Fanny Aulia Dewi Fattah, Rafi Indra Fatwa Ramdani, Fatwa Febri Ramadhani Fikri Hilman Fitra Abdurrachman Bachtiar Fitria, Tharessa Fitrotuzzakiyah, Shafira Puspa Gandhi Ramadhona Gembong Edhi Setiawan Gilang Ramadhan Hendra Pratama Budianto Husin Muhamad Imam Cholisoddin Imam Cholissodin Imam Cholissodin Imam Cholissodin Indah Larasati Indriati Indriati Indriati Irawati Nurmala Sari Irfan Aprison Irma Lailatul Khoiriyah Irma Nurvianti Irma Ramadanti Fitriyani Ismiarta Aknuranda Issa Arwani Issa Arwani Jobel, Roenrico Karina Widyawati Keintjem, Arthurito Khairunnisa, Alifah Kholifa&#039;ul Khoirin Koko Pradityo Lailil Muflikhah Lathania, Laela Salma M Kevin Pahlevi M. Ali Fauzi M. Raabith Rifqi M. Rikzal Humam Al Kholili M. Tanzil Furqon Mahar Beta Adi Sucipto, Ekmaldzaki Royhan Mahendra Data Mahendra Data Marji Marji Masayu Vidya Rosyidah Maulana, M. Aziz Mayang Arinda Yudantiar Meilia, Vina Mimin Putri Raharyani Mindiasari, Irtiyah Izzaty Miracle Fachrunnisa Almas Moch. Khabibul Karim Mochamad Chandra Saputra Mohamad Alfi Fauzan Muhammad Arif Hermawan Muhammad Dimas Setiawan Sanapiah Muhammad Harish Rahmatullah Muhammad Khaerul Ardi Muhammad Rizkan Arif Muhammad Syaifuddin Zuhri Muhammad Tanzil Furqon Mustofa Robbani Muthia Azzahra Nadia Natasa Tresia Sitorus Nainggolan, Cesilia Natasya Nanda Agung Putra Nashrullah, Nashrullah Nelli Nur Rahma Ni&#039;mah Firsta Cahya Susilo Nihru Nafi&#039; Dzikrulloh Noval Dini Maulana Novanto Yudistira Nur Intan Savitri Bromastuty Nurfansepta, Amira Ghina Nurhana Rahmadani Nurudin Santoso Nurul Hidayat Oky Krisdiantoro Olive Khoirul L.M.A. Panjaitan, Mutiharis Dauber Pindo Bagus Adiatmaja priharsari, diah Purnomo, Welly Putra Pandu Adikara Putra, Octo Perdana Putri, Rania Aprilia Dwi Setya Rachmatika, Isnayni Sugma Radifah Radifah Rafely Chandra Rizkilillah Rahmadi, Anang Bagus Rahmat Faizal Raissa Arniantya Ramadhianti, Fatiha Randy Cahya Wihandika Ratna Candra Ika Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Rekyan Regasari MP, Rekyan Regasari Rendi Cahya Wihandika Retiana Fadma Pertiwi Sinaga Revanza, Muhammad Nugraha Delta Revinda Bertananda Reza Wahyu Wardani Rhobith, Muhammad Ridho Agung Gumelar Rima Diah Wardhani Rinda Wahyuni Rizal Setya Perdana Rizal Setya Perdana Rizki Agung Pambudi Rizky Haqmanullah Pambudi Robih Dini Rosi Afiqo Rudito Pujiarso Nugroho Rudy Usman Azzakky Ryan Mahaputra Krishnanda Sabriansyah Rizkiqa Akbar Santoso, Nurudin Satrio Hadi Wijoyo Shelly Puspa Ardina Sigit Adinugroho Silfiatul Ulumiyah Sintiya, Karena Siti Fatimah Al Uswah Siti Utami Fhylayli Sri Wahyuni Suryani Agustin Sutrisna, Naufal Putra Sutrisno Sutrisno Tahajuda Mandariansah Talitha Raissa Tibyani Tibyani Tri Afirianto Tria Melia Masdiana Safitri Ulfah Mutmainnah Vina Meilia Wayan Firdaus Mahmudy Wildannantha, Jawadi Ahmad Yerry Anggoro Yosendra Evriyantino Yuhand Pramudita, Rezzy Yuita Arum Sari Yuita Arum Sari Yulfa Hadi Wicaksono Zubaidah Al Ubaidah Sakti