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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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Penerapan Metode K-Nearest Neighbor (KNN) dan Metode Weighted Product (WP) Dalam Penerimaan Calon Guru Dan Karyawan Tata Usaha Baru Berwawasan Teknologi (Studi Kasus : Sekolah Menengah Kejuruan Muhammadiyah 2 Kediri) Nihru Nafi' Dzikrulloh; Indriati Indriati; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 5 (2017): Mei 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

World of particular employment agencies Vocational High School, many a teacher or school employee who less clever in technology of the current technological developments. Actually, it is in need of teachers and school administration employees who have qualified human resources high in the knowledge of science and technology. The school is in need it is because it affects how do learning on students in school. To meet the desired standards of quality teachers, during The Vocational High School Muhammadiyah 2 Kediri is selection and recruitment of teachers by means of manual employees. The selection has been done manually through the test phase 4 aspects of your application letter and attachments GPA averages, academic test, test general knowledge of science and technology (IPTEK), and interview. The data collection process for the selection still use manual. Therefore, we need a web-based system so that the selection acceptance of new teacher candidates can run more effectively and efficiently. On this website using K-Nearest Neighbor (KNN) and the method of Weighted Product (WP). K-Nearest Neighbor used to determine the weight of each criterion to classify the good or bad. After classifying the KNN method, the selection of prospective teachers will be recruited by the school Vocational High School Muhammadiyah 2 Kediri using Weight Product (WP). Weight Product used to determine the results of the classification by KNN method to perform a ranking in order to take the best results. Tests conducted consisting of, testing the accuracy of the value of K means and accuracy testing of the WP value criteria weighting method. The accuracy of the test results obtained suitability accuracy value by 94%, precision 80%, and recall 80%.
Algoritme Genetik untuk Optimasi Pembentukan Fungsi Regresi Linier dalam Menentukan Kebutuhan Volume Air Penyiraman Tanah Hendra Pratama Budianto; Budi Darma Setiawan; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 9 (2017): September 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Seed Laboratory BPTP East Java is one of provincial government work units that have assignment as the technical implementer to conduct a study in seed growth. Currently at this place is being developed automatic watering device based on soil humidity sensor, but the device cannot predict the volume of water needed in order to keep the moist of seed growth media. With the help of humidity sensor on device and expert's knowledge, the observations dataset of soil moisture to the needs of waters volume has been obtained. This study was conducted to apply linear regression method so that the device can perform predictions based on dataset patterns as an equation. The accuracy of prediction results with this method is measured by the coefficient of determination. The coefficient of determination can be decreasing due to the arising of observation outliers because Inaccuracy of observation results. The solution from this study is using genetic algorithm with information criteria as comparison for detecting observation outliers to eliminated. After eliminating 6 observations outliers were detected by genetic algorithms in this study, shows increase in the coefficient of determination from 0.9673 to 0.9935.
Optimasi Support Vector Regression (SVR) Menggunakan Algoritma Improved-Particle Swarm Optimization (IPSO) untuk Peramalan Curah Hujan Husin Muhamad; Imam Cholissodin; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Climate change that happens because of global warming also cause change in rainfall patterns. Knowing rainfall patterns is really important for some activity and works. So, rainfall forecasting is needed to understand the rainfall patterns in the future. One of the method used in forecasting is Support Vector Regression. But, SVR still has weakness in determining the right values for the parameters. So, an optimization algortithm is needed to help determining the values of the parameters in SVR. The purpose of this research is to do rainfall forecasting in Pujon area, Malang using Support Vector Regression that's been optimized by Improved-Particle Swarm Optimization. Optimization of SVR is done for getting the optimal values of SVR's parameters. The optimized SVR's parameters are (learning rate constants), (complexity), (Hessian's coefficient), (error rate) dan (kernel's coefficient). The rainfall forecasting for the first ten days of January from 2007 until 2015 by using IPSO-SVR resulted value of 0.213389 in RMSE compared to using only SVR which resulted value of 25.839085 in RMSE. This proved that optimization of SVR using IPSO is better compared to using the unoptimized SVR.
Sistem Pakar Diagnosis Penyakit Schizophrenia Menggunakan Metode Bayesian Network Rima Diah Wardhani; Rekyan Regasari Mardi Putri; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Schizophrenia is a severe mental disorder that contains thoughts, language, perceptions, and self-awareness. There are several types of schizophrenia. The relationship between the type of schizophrenia and its symptoms has uncertainty, where a symptom A is not necessarily only result in schizophrenia type X, but can lead to schizophrenia type Y. In rural areas, mental health facilities are still inadequate, so that the people there treat patients with schizophrenia with unnatural as at the brackets even in stocks. Actually, people with schizophrenia can be handled with the provision of drugs and psychological therapy with regular. Based on these problems, the authors create expert systems that are able to find solutions as do an expert in diagnosing and providing treatment solutions in patients with schizophrenia. Thus, general practitioners in small community clinics or hospitals in small areas can diagnose patients suffering from the schizophrenia. This expert system uses Bayesian Network method, PHP programming language and MySQL database. Experimental functional test results show all functional requirements can run well. In addition, the highest accuracy test results in testing the variation of training data is 92.86%. With the results of such accuracy, this expert system has a good performance to make the diagnosis of schizophrenia disease
Optimasi Fuzzy Inference System Mamdani Menggunakan Algoritme Genetika untuk Menentukan Lama Waktu Siram pada Tanaman Strawberry Agung Nurjaya Megantara; Budi Darma Setiawan; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
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. Soil Laboratory 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 Mamdani 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 2,516651, but after optimization the number is reduced to 0,000121. With that result we can conclude that using Fuzzy Inference System Mamdani 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. Keywords: Plants, fuzzy inference system, Mamdani, genetic algorithm, optimization
Prediksi Waktu Panen Tebu Menggunakan Gabungan Metode Backpropagation dan Algoritma Genetika Dwi Ari Suryaningrum; Dian Eka Ratnawati; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Before sugar cane was milled by the factory, the first process is analysis of sugar cane maturity. The best sugar cane condition to be ground is mature cane that can be seen from several factors such as garden area, age, stem diameter, the average segment per stem and the average length per stem. These factors are used as attributes in the research conducted. To simplify the process, then we proposed this research on the prediction of sugar cane harvest time. With so much data being used and repeated processes, it will be difficult to process manually and takes a long time. In addition, the manual process does not close the possibility of an increasing error. This research uses a combination of genetic algorithm and backpropagation in the process of predicting the harvest time. Genetic algorithms are the best solution used to optimize prediction results by weight selection and bias. Backpropagation method is used to calculate Mean Square Error (MSE) value, which will be used in calculation of fitness value and also on prediction of data test. In this research will be done five kinds of testing, as follows generation test, population size test, test combination of crossover rate and mutation rate, testing of learning rate and testing of Average Forecasting Error Rate (AFER). The result of this research are predictions of harvest time, the value of fitness and AFER. The best result is result of AFER value is 0,0205%.
Aplikasi Perencanaan Wisata di Malang Raya dengan Algoritma Greedy Akhmad Eriq Ghozali; Budi Darma Setiawan; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Malang raya is one of regions which becomes the main objective place to visit because it has many tourism places. The thing which has to be noticed is determining the tourism schedule, every tourist must choose the shortest distance and time to be able to reach that destination because they can save the time. To reach that destination, it is used greedy algorithm with knapsack problem to assist the optimation process against searching the shortest traveling time and how many tourism places which can be visited from the possessed time. Time allocation which is possessed by the user to tour is used as an integrity in calculating this application, while the traveling time at each tourism locations which are also used as an integrity is time data which is gotten from google maps. With thats data, the application with greedy algorithm will calculate the most optimal location to be visited with the time which belongs to the user. According to the result of testing application with ten sample of problem cases gets accuracy result 90% from two models of greedy algorithm calculation in searching location which can be visited by the allocation time which is owned. While the result of optimal tour accuracy that is visited is 0% from the first model of calculation and 80% from the second calculation.
Optimasi K-Means untuk Clustering Kinerja Akademik Dosen Menggunakan Algoritme Genetika Budi Santoso; Imam Cholissodin; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Lecturers are teacher for students, besides teaching, lecturers also have many other activities by utilizing the expertise they have to develop the potential of the lecturer. Some of the characters that each lecturer are so different, such as education, research, dedication, administration, and support. The difficulties faced by the campus, one of them is related to the grouping of assignments to lecturers. The assignment is related to further studies, recommendations, structural related positions, filling an event, commission, etc.So that required a system that can classify the academic performance of lecturers optimally. In this study to classify the academic performance of lecturers using K-Means method is optimized with genetic algorithm. Genetic algorithm acts to optimize the cluster's initial center on K-Means.Data algorithm used in this research is the data of lecturers in UB's Computer Science faculty in 2016. The data obtained from GJM faculty of computer science of Universitas Brawijaya. The result of clustering test of academic performance of lecturer using GA-Kmeans algorithm has higher cluster quality that is 2,74% compared to K-Means algorithm without genetic algorithm, where the cluster quality obtained using Silhouette Coefficient method.
Optimasi Menu Makanan Untuk Pemenuhan Gizi Penderita Kanker Dengan Algoritme Genetika Dellia Airyn; Imam Cholissodin; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of the most feared disease in the world today is cancer. For cancer patients, various ways have been done, one of them is chemotherapy. But in chemoteraphy, patients will experience digestive and absorption of nutrients disorder, thus affecting the nutritional status of patients. So, the menu orders for cancer patients become the most important thing to reduce the side effect of chemoteraphy, especially in term to fulfill the needs of energy and protein. In this study, there are 111 food menu, consist of 31 foods source of carbohydrate, 34 foods source of animal protein, and 46 foods source of plant protein.The method in this study using genetic algorithm, which is an optimization algorithm that similar to evolution theory in case determining the chromosomes or individual.The representation used is a permutation representation, with One-Cut Point Crossover and Reciprocal Exchange Mutation methods. The results and analysis of crossover rate and mutation rate combination against the average fitness value showed 0,6;0,4 has the largest average value, which is 762,19. In population test, the highest average fitness score was 631,16 in the 300th population. While in generation test, the highest average fitness value was 666,22 in the 200th generation.
Peramalan Harga Saham Menggunakan Support Vector Regression Dengan Algoritme Genetika Nanda Agung Putra; 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

Stock is a proof of investing in a corporation and stock holders have the right to claim part of corporation's earning and assets. Stock holders can gain a lot ot of benefit such receiving dividens and selling their stocks with higher value (capital gain). Stock holders need to be careful to manage their assets because stock prices keep changing over time. Stock holders usually monitor stock prices change and analyze them by forecasting. Support Vector Regression (SVR) is one of forecasting methods that performs well in both linear and non linear data. SVR can obtained a fitted model that is neither overfit nor underfit. However SVR has one drawback. The performance of SVR is greatly affected by its parameter. So finding the right parameter value on SVR is needed to gain a good forecasting result. One of optimization algorithms is Genetic Algorithm. Genetic Algorithm is used in order to get the right value of SVR parameter. SVR that is optimized by Genetic Algorithm is capable of getting a good result in forecasting. The test shows error rate/MAPE of forecasting is 0.165% which is smaller than using SVR which is 1.612% with best parameters such as population size 50, generation 200, crossover rate 0.4, mutation rate 0.6, range of sigma 0.5-1, range of epsilon 10-7-10-3, range of C 0.001-5, and range of gamma 10-5-10-3.
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