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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 Vektor Bobot Learning Vector Quantization Menggunakan Algoritme Genetika untuk Penentuan Kualitas Susu Sapi Karina Widyawati; Budi Darma Setiawan; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Milk has a complete nutrition that important for body so every people can consume milk with high quality. Determination of milk quality can by tools called Milkoscope Julie c2 or Lactoscan to test the chemical contents. That tools can identified the chemical content which includes 7 parameters. From 7 parameters, 3 parameters are provisions of SNI and 4 parameters are not listed in porvisions of SNI. If we determine milk quality only from 3 parameter in SNI, the result is not the best. Based on that problems, we need a system that can help us to determine quality of milk considering 7 parameters. Method that can be used for this problem is Learning Vector Quantization (LVQ) but LVQ need an optimazion method to produce the best weight vector and increase accuracy using Genethic Algorithm (GA). Best weight vector of GA will be used for LVQ training and the latest wight vector of training used for testing. The result of this research obtained the highest accuracy average is 88% with best parameters such as population size 30, crossover rate 0,5, mutation rate 0,5, generation 75, alpha 0,6, and alpha decrement 0,3.
Optimasi Parameter Support Vector Regression Dengan Algoritme Genetika Untuk Prediksi Harga Emas Muthia Azzahra; Budi Darma Setiawan; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Gold is one of the precious metals that many people interested as commodity to invest because of its resistance to inflation. Fluctuations can occur so extreme that affect the value of gold. Therefore, prospect of gold value in the future is quite important for the investors. One of prediction methods is Support Vector Regression (SVR), but the sensitivity of SVR parameters could influence the prediction result, therefore Genetics Algorithm (GA) can be applied, this method is flexible enough to be hybridized. This study discuss about the optimization of SVR parameters using GA to predict gold prices. Based on the testing result, the best mean absolute percentage error (MAPE) is 0.2407% with SVR loop 50, GA's generation 95, population size 70, crossover rate 0.01, mutation rate 0.99, elitism percentange 80%, range of 1x10-7-1x10-4, range of 0.01-5, range of 1x10-7-1x10-4, range of 1x10-5-1x10-4, and range of 1x10-3-0.1.
Optimasi Vektor Bobot Pada Learning Vector Quantization Menggunakan Algoritme Genetika Untuk Identifikasi Jenis Attention Deficit Hyperactivity Disorder Pada Anak Raissa Arniantya; Budi Darma Setiawan; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of mental disorder which common happened on children under 7 years old. Child with ADHD characterized by lack of ability to concentrate, excessive behavior, and behavior that spontaneously out of control. Type of ADHD are inattention, hyperactive and impulsive. If child with ADHD unidentified early, it will causes psychosocial problem but not many people are aware about ADHD so they need a system for identify the type of ADHD. System uses classification methods Learning Vector Quantization. Some cases classification, LVQ has weak accuracy so it needs optimization methods Genetic Algorithm (GA) for improve the accuracy. LVQ's weight vector will be optimized by GA through genetic process until generated optimum weight vector which LVQ uses for training and testing process. Testing against LVQ and LVQ-GA generate LVQ's accuracy 77% and LVQ-GA's accuracy 92% with best parameters are population size is 75, crossover rate is 0.6, mutation rate is 0.4, number of generation is 80, learning rate is 0.001, learning rate decrement is 0.1, maximum epoch is 1000 and learning rate minimum is 10-16.One of mental disorder which common happened on children under 7 years old. Child with ADHD characterized by lack of ability to concentrate, excessive behavior, and behavior that spontaneously out of control. Type of ADHD are inattention, hyperactive and impulsive. If child with ADHD unidentified early, it will causes psychosocial problem but not many people are aware about ADHD so they need a system for identify the type of ADHD. System uses classification methods Learning Vector Quantization. Some cases classification, LVQ has weak accuracy so it needs optimization methods Genetic Algorithm (GA) for improve the accuracy. LVQ's weight vector will be optimized by GA through genetic process until generated optimum weight vector which LVQ uses for training and testing process. Testing against LVQ and LVQ-GA generate LVQ's accuracy 77% and LVQ-GA's accuracy 92% with best parameters are population size is 75, crossover rate is 0.6, mutation rate is 0.4, number of generation is 80, learning rate is 0.001, learning rate decrement is 0.1, maximum epoch is 1000 and learning rate minimum is 10-16.One of mental disorder which common happened on children under 7 years old. Child with ADHD characterized by lack of ability to concentrate, excessive behavior, and behavior that spontaneously out of control. Type of ADHD are inattention, hyperactive and impulsive. If child with ADHD unidentified early, it will causes psychosocial problem but not many people are aware about ADHD so they need a system for identify the type of ADHD. System uses classification methods Learning Vector Quantization. Some cases classification, LVQ has weak accuracy so it needs optimization methods Genetic Algorithm (GA) for improve the accuracy. LVQ's weight vector will be optimized by GA through genetic process until generated optimum weight vector which LVQ uses for training and testing process. Testing against LVQ and LVQ-GA generate LVQ's accuracy 77% and LVQ-GA's accuracy 92% with best parameters are population size is 75, crossover rate is 0.6, mutation rate is 0.4, number of generation is 80, learning rate is 0.001, learning rate decrement is 0.1, maximum epoch is 1000 and learning rate minimum is 10-16.One of mental disorder which common happened on children under 7 years old. Child with ADHD characterized by lack of ability to concentrate, excessive behavior, and behavior that spontaneously out of control. Type of ADHD are inattention, hyperactive and impulsive. If child with ADHD unidentified early, it will causes psychosocial problem but not many people are aware about ADHD so they need a system for identify the type of ADHD. System uses classification methods Learning Vector Quantization. Some cases classification, LVQ has weak accuracy so it needs optimization methods Genetic Algorithm (GA) for improve the accuracy. LVQ's weight vector will be optimized by GA through genetic process until generated optimum weight vector which LVQ uses for training and testing process. Testing against LVQ and LVQ-GA generate LVQ's accuracy 77% and LVQ-GA's accuracy 92% with best parameters are population size is 75, crossover rate is 0.6, mutation rate is 0.4, number of generation is 80, learning rate is 0.001, learning rate decrement is 0.1, maximum epoch is 1000 and learning rate minimum is 10-16.
Implementasi Algoritme Genetika Dalam Optimasi Knapsack Problem Penentuan Objek Wisata Wilayah Malang Raya Abdul Fatih; Budi Darma Setiawan; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Tourism has become commodity that can't be separated from human's life. There are some areas in Indonesia make tourism into the specific characteristics of their region which one is Malang Raya. The form of attention in the tourism sector is activated the building of new tourism objects. There was more tourism object than before will be more coddling for the tourists and also give a new problem. The tourist have knapsack problem which the tourist must decided all of tourism objects list that visited with the limited time. The optimization of knapsack problem can be resolved by using genetic algorithm. The genetic algorithm will make a formation of chromosome as representation of solution. The structures of genetic algorithm consist of initialization, reproduction, evaluation, and selection. The process of genetic algorithm did in the 50 generations with 100 populations whereas the pc value is 0, 7 and the value of pm is 0, 8. Result of processing genetic algorithm towards case study that has been tested gave the solution resemble to nearby tourism areas list and grouping in the certain areas.
Optimasi Fungsi Keanggotaan Fuzzy Mamdani menggunakan Algoritme Genetika untuk Penentuan Kesesuaian Lahan Tanam Tembakau Fikri Hilman; Budi Darma Setiawan; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of the requirements for good quality tobacco is a good land use. Improved quality of the land will result in increased quality and quantity of tobacco plants produced. The main constraints experienced by tobacco farmers in determining land suitability are the limited knowledge and difficulty of obtaining correct data on the quality of land suitable for tobacco plants. Therefore, a computerized system is needed to assist farmers in making decisions on prospective land to be used. This system is implemented using Fuzzy Inference System (FIS) Mamdani and optimized using Genetic Algorithm. Some of the factors used in this system include the percentage of land affected by the disease, the openness of the region, the degree of weight of the soil, the thickness of the layer, the ease of irrigation, terrain conditions, and soil pH. The reproduction method used is extended intermediate crossover and random mutation, while the selection method used is elitism. Based on the results of the tests that have been done, the most optimum solution obtained on the total number for 90 population , the combination of cr and mr value of 0.2 and 0.8 respectively and the number of generations of 500, with the average of fitness value generated of 0,917. The Accuracy generated by this system is 80 % using 10 test data.
Optimasi Penjadwalan Asisten Praktikum pada Laboratorium Pembelajaran Menggunakan Algoritme Genetika (Studi Kasus : Fakultas Ilmu Komputer Universitas Brawijaya) Nadia Natasa Tresia Sitorus; Imam Cholissodin; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Scheduling is an important thing to be prepared carefully for the sake of an activity doing well.Good and effective scheduling will make the activities work and be well organized. Practicumis a routine activity for the application of materials that have been accepted by students.Practicum can work well if the teaching schedule of the practicum assistant does not collidewith the lecture schedule or their other activities. Genetic algorithm is one of algorithm thatcan complete the teaching schedule of practicum assistant through computation process. Thedata in conducting the research is the data from practicum schedule, practicum assistant andthe schedule of the assistant's willingness. The code of the practicum assistant is representedon the chromosome using the permutation method. The sequence of genes on thechromosomes represents the code of the practicum schedule. The crossover method appliedis one-cut-point, with mutation method using reciprocal exchange, and elitsm selectionmethod. The test result obtained optimal genetic algorithm parameter with total population5000, generation 500, with cr and mr value is 0,9 and 0,1. The output of the system is theteaching schedule of the laboratory teaching assistant.
Algoritma Genetika Untuk Optimasi Fuzzy Time Series Dalam Memprediksi Kepadatan Lalu Lintas di Jalan Tol Andhi Surya Wicaksana; Budi Darma Setiawan; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Fixed and improved traffic facilities continue to be done continuously, but the timing of uncompleted fixes that really only add to the existing traffic congestion will have an impact on the convenience and security of traffic users. Research has been done a lot to predict traffic density but not much focused on traffic on the highway. With fuzzy time series method optimized with Genetic Algorithm method, the writer wants to help solve the problem to predict traffic density on the highway, hopefully the result of research can help as a reference for improvement and improvement of facility in traffic do not increase congestion. Based on the results of top-level testing of predicted results using the Average Forecasting Error Rate (AFER) method, the result of the error rate of 16.66% is included in both qualification and successful.
Optimasi Jumlah Pinjaman Koperasi Menggunakan Fuzzy Tsukamoto Dengan Algoritme Genetika Shelly Puspa Ardina; Imam Cholissodin; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Nowadays, almost the majority of cooperatives are still performing calculations lending manually and very rarely utilize the use of computer technology so that in decision making is done less efficient. From the problems encountered, it takes a system that has a relationship with the computer so that it can accelerate and assist the process of making the decision of lending efficiently. The required system is an artificial intelligence system that helps to get the most precisely seen value of the greatest fitness as each of its calculations. The criteria that become the basis for determining the loan amount to the members using the optimized Tsukamoto Fuzzy method using Genetic Algorithm are job status, age, salary and loan duration. The results will be able to show the fitness in each of the calculations that have been optimized by using Genetic Algorithm, so it will get the most appropriate value. The result of system evaluation using Mean Absolute Percentage Error calculation with the example of a case has an error value of 0.661468035 or 1.65% with the resulting fitness value of 0.601877363.
Peramalan Jumlah Pengunjung Wisata Menggunakan Fuzzy Logical Relationship dan Algoritme Genetika (Studi Kasus Wisatawan Kabupaten Banyuwangi) Irma Lailatul Khoiriyah; Imam Cholissodin; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Tourism is one of the important sectors in Banyuwangi Regency. An unexpected increase in the number of tourists makes it difficult for tourism department to give their best service. On the contrary, if there is a reduction, it will cause the decrease of the occupancy rate and the tourism sector that already exist. Forecasting the number of tourists is needed to determine the number of visitors in the future, so the solution can be anticipated as early as possible when number of tourists is more or less than the targeted. Forecasting that conducted in this study was using Fuzzy Logical Relationship and Genetic Algorithm. Fuzzy Logical Relationship is used to forecast the number of tourist based on tourist data history, then Genetic Algorithm is used to perform optimization interval distribution that will be used on Fuzzy Logical Relationship. Data that were used as many as 144 historical data from January 2005 to December 2016, number of tourist data was achieved from the Department of Culture and Tourism of Banyuwangi Regency. The results of the tests that was conducted on forecasting the number of visitors using the FLR and GA equations produce 280x10-9 in fitness which means the difference between the average of actual data and the result of forecasting is 3572978344 in MSE.
Implementasi Algoritme Support Vector Regression Pada Prediksi Jumlah Pengunjung Pariwisata Mimin Putri Raharyani; Rekyan Regasari Mardi Putri; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 4 (2018): April 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Tourism has an important role for the economic growth of a region. One of the factors affecting the tourism revenue sector is the number of visitors. The more number of visitors can increase revenue, if the number of visitors decreased it will have an impact on the development of tourist attractions that can harm the manager of tourism. The prediction system of the number of visitors is needed as an illustration of the level of the number of tourism visitors for the period to come and can provide information to the managers of tourism to prepare better facilities and infrastructure and able to manage income and expenses to minimize losses. The prediction of the number of visitors to tourism can be done by applying the Support vector regression algorithm. Support vector regression algorithm is a method that can solve regression problems and produce good performance in the solution. In this study data used 72 data on the number of visitors monthly on tourism from 2010 to 2015. Test results show that the average value of MAPE minimum generated is 9,16% and the best MAPE value obtained is 6,98% which means The average difference between the predicted result and the actual data is 115 visitor number with sigma parameter = 925,8409 lambda = 0,3868, cLR = 0,0802, epsilon = 1,27E-10, complexity = 3234,539, maximal iteration 5000.Keywords: prediction, tourism, visitor number, support vector regression
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'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'mah Firsta Cahya Susilo Nihru Nafi' 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