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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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Journal : Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer

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Penerapan Algoritma C4.5 Untuk Memprediksi Nilai Kelulusan Siswa Sekolah Menengah Berdasarkan Faktor Eksternal Rizky Haqmanullah Pambudi; Budi Darma Setiawan; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Education in the life of a country plays a very important role to ensure the survival of the state and nation. Statistics show that Portugal's education level is at the bottom of the list due to many students dropping out of school. External factors affect the failure of students in completing the field of study, especially the field of study of mathematics. Algorithm C4.5 is one method of data mining to predict students' ability in completing the field of study seen from the external factors of students. The C4.5 algorithm is used to find out the accuracy of the prediction ability of high school students. The feature selection parameters are the factors that affect the ability of high school students in the field of mathematics studies. Testing and analysis results show that the Decision Tree C4.5 algorithm is accurately applied to predict the final grade of high school students with a 60% accuracy rate.
Optimasi Interval Fuzzy Time Series Menggunakan Particle Swarm Optimization pada Peramalan Permintaan Darah : Studi Kasus Unit Transfusi Darah Cabang - PMI Kota Malang Angga Dwi Apria Rifandi; Budi Darma Setiawan; Tibyani Tibyani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Blood is an important fluid that naturally produced in the human body. When a human lost a lot of blood, a blood transfusion is needed . Blood for the transfusion is provided by a blood storage center in charge of estimating blood demand to minimize the excessive amount of blood in storage or wasted blood. Lack of blood supply can affect to the increased death of the patient, while an oversupply of blood until passes it shelf life (35 days) should also be avoided. In order to minimize the loss, a method to forecast the blood demand is needed, that is fuzzy time series. To increase the accuracy, the method is optimized with particle swarm optimization to determine the best interval in fuzzy time series. Based on the results of a series of tests, the optimum solution with average of cost value (MSE) of 60435,685 is obtained on 40 particles, 30 dimensions, 1.5 and 1.5 for the combination of and value respectively, the weight of inertia of 0.3, and the maximum number of iterations of 950. By using 12 testing data, the error rate generated by this system (MAPE) is 7.50330%.
Optimasi Fungsi Keanggotaan Fuzzy Inference System Tsukamoto dengan Particle Swarm Optimization pada Penentuan Jumlah Produksi Gula (Studi Kasus : Pabrik Gula Kebonagung Malang) Nur Intan Savitri Bromastuty; Budi Darma Setiawan; Indriati Indriati
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 is an activity that resulted in goods and services with the usage of resources called production factor. The usual factors for sugar productions is farming area, sugar cane rendement, sugar cane amount, amount of labors, mechine operations, supporting materials and grinding time. Based on previous studies, the major factors that applies to PG. Kebonagung Malang are sugar cane amount, rendement, labor, and machine operations. Studies that estimate sugar production amount already exist, but it's still not optimal. This research was meant to optimize the estimation of sugar production of PG. Kebonagung Malang with particle swarm optimization method to optimize tsukamoto fuzzy inference system. Testing was done with varying particle counts and varying iteration. Computation speed decreases when the number of iterations and particles count increases. Every test with different particle count and iterations results in different fitness value.
Optimasi Fuzzy Times Series Untuk Memprediksi Besar Nilai Penjaminan Kredit KUR dengan Algoritme Genetika (Studi Kasus : Perum Jamkrindo Cabang Kendari) Sri Wahyuni; 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

Every businessmen would want to expand his business to be bigger, to do that it needs a lot of funds. The bank can provide kredit usaha rakyat with some of reqruitment collateral that has be obeyed by bussinesmen, one of them is to provide guarantee, the problem is not all the bussinesment can provide the guarantor. Therefore bussnismen need guarantor institution help in order to fulfill the requiment. As the Demand from banks for credit guarantee to increase every month, it ensures that the guarantor institution must increase its budget to guarantee the kredit usaha rakyat. Therefore a system that is able to predict the amount of guarantee value will be needed in order to meet the demand of the bank. In this research the method used to predict is Fuzzy Time Series which will be optimized using Genetic Algorithm. A chromosome is used to represent the interval of a membership function. The reproduction method is one-cut-point crossover and uniform mutation. And do the selection process by using elitism selection. The optimal results obtained with the length of chromosome as much as 100, the population size of 350, cr and mr of 0.3 and 0.6 and the number of generations as much as 1000. The error and fitness value generated by 0.00901% for MAPE and 110.95098192994908 for fitness value.
Optimasi Vehicle Routing Problem With Time Windows (VRPTW) Pada Rute Mobile Grapari (MOGI) Telkomsel Cabang Malang Menggunakan Algoritme Genetika Moch. Khabibul Karim; Budi Darma Setiawan; Putra Pandu Adikara
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

Sales Operation and Outlet (SOO) is one of Telkomsel's divisions. Sales Operation in transportation field is called Mobile Grapari (MOGI). Mogi operates every day, looking for sales points, but those points hasn't been effective in sales operation. The previous system was a manual scheduling by coordination between one MOGI with the other, causing occuring problem which is an empty point. This problem also leads to scheduling ineffectiveness at sales point which gives less than optimal results. One of causes is Vehicle Routing Problem with Time Windows (VRPTW). To overcome this problem, an optimization method called genetic algorithm is applied. Genetic algorithm is applied for solving point routes and sales profits. The test is performed to find the parameters that produce the best fitness value. The result of the test shows that the best population size is 450 with 2700 generation iteration and the combination of crossover and mutation rate are 0,2 and 0,9 respectively. Through this test, we get the best selection method that is elitism selection. The fitness value of best parameters is 0,5581. The effective route solution that is generated on Monday, First Car is in Arjosari (Terminal Area), Singosari (Samsat Singosari), and Karang Ploso Rest Area. Second Car is in Gadang (Terminal Hamidrusdi), Sudimoro (Pujas front SM Futsal Zone), and Kawi Atas Street. Third Car is located in Merjosari (Lap. Merjosari), Sigura-gura Street, (Home Aston Printer) and Tlogomas (Ruko Kopi Sosial) with Rp. 5.114.167.00 profit and Rp. 35.584.167,00 for a week.
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%.
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 Irfan Aprison Irma Lailatul Khoiriyah Irma Nurvianti Irma Ramadanti Fitriyani Ismiarta Aknuranda Issa Arwani Issa Arwani Jobel, Roenrico Karina Widyawati 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 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