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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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Klasifikasi Emosi Lirik Lagu menggunakan Improved K-Nearest Neighbor dengan Seleksi Fitur dan BM25 Febrina Sarito Sinaga; Indriati Indriati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 6 (2019): Juni 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Emotions is a person's reaction or feeling into a situation. Emotion is temporary that can occurred by a stimulus because of some people around and the environment. One of example an environment that can trigger someone's emotion is from the song being listened to. Song lyrics are the parts that can build emotions. Choosing the right words for lyrics are very important because it will create the right emotion. In this case the emotional classification of song lyricis will be done classifying process using several methods are Improved K-Nearest Neighbor, BM25 and feature selection. The proses of classification have seome stages, which is the stage of pre-processing documents, stages of calculation the BM25 score and sorting document, and the classification stage with using the algorithm is Improved K-Nearest Neighbor. The testing for classifications was done uses 6 times K-fold and use the confusion matrix. This research is the amount of training data used by 100 documents, and testing data used by 20 testing documents. In the all the tests have done obtained the best average results when the value K = 55 with a result of f-measure is 0.6693, recall is 0.6582, and precision is 0.7427.
Optimasi Multiple Travelling Salesman Problem (M-TSP) Pada Angkutan Sekolah Dengan Algoritme Genetika (Studi Kasus: Yayasan Pembina Muslim Daarussalaam Sangatta) Ageng Wibowo; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 7 (2019): Juli 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Pembina Muslim Daarussalaam Foundation is an educational institution located in Swarga Bara, North Sangatta, East Kutai Regency, East Kalimantan. The Foundation provides 8 school transports which are used to provide shuttle services for 160 Daarussalaam Islamic Kindergarten and Elementary students. The route for the shuttle is determined by the school transport driver. This research is conducted to determine the optimal shuttle route that will help school transport driver. The problem of this research is Multiple Traveling Salesman Problem (M-TSP) and one of the optimization methods that can help solve this problem is genetic algorithm. This research use a permutation representation, chromosome representation divided into 3 clusters, penjemputan (cluster 1), pengantaran 1 (cluster 2), and pengantaran 2 (cluster 3). Then the reproductive process is done by crossover with ordered crossover method and mutation with swap mutation method then the selection process is done by elitism selection method. With genetic algorithm that are 10.000 generations, population size 90, and combination of cr value = 0,6 and mr value = 0,4. The average fitness value in this research is 3,047. With the result of this research, Pembina Muslim Daarussalam Foundation can reduce the mileage by 400,82 KM and travel time around 877 minutes.
Pengelompokan Wilayah Berdasarkan Kesejahteraan Sosial Menggunakan Algoritme Self-Organizing Maps Dengan Perbaikan Missing Value K-Nearest Neighbors Dese Narfa Firmansyah; Sigit Adinugroho; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 7 (2019): Juli 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Persons with Social Welfare Problems (PMKS) are social groups that live below the community welfare line and are one of component for determining policies in East Java. The study aim to find out the characteristics of the region in East Java based on the PMKS dataset. The method proposed in this study is clustering with the Self-Organizing Maps algorithm and K-Nearest Neighbors (KNN) missing value imputation. KNN used to overcome the amount of missing value in PMKS dataset. First, missing value is filled using KNN imputation. Furthermore, the clustering done with training in SOM network and the result of cluster is evaluated using Silhouette Coefficient. The best parameters for SOM are learning rate=0.1; neighborhood coefficient=0.2; max epoch=160 and neuron size=2x2. The best parameter for KNN is K=2. K=2 gives an increase in Silhouette Coefficient value of 3.4% compared to clustering without missing value imputation KNN. Using best parameter, the highest Silhouette Coefficient obtained is 0.351 which categorized as weak structure. The shape of the cluster produced is a cluster with a proportion of 1:37. The five attributes with the highest difference between the two clusters were Neglected Elderly, Homeless and Psychotic Homeless, Scavengers, Beggars and Minority Groups.
Optimasi Komposisi Menu Makanan bagi Penderita Penyakit Diabetes Melitus Tipe 2 dan Komplikasinya menggunakan Hybrid Algoritme Genetika dan Simulated Annealing Muhammad Jibril Alqarni; Imam Cholisoddin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 8 (2019): Agustus 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Diabetes mellitus is a common disease among the people. One of the active preventive things to deal with type 2 diabetes mellitus is to do regular exercise, and eat nutritious foods and have adequate nutrition for 1 day. In getting enough calories or energy according to the needs of patients, calculations can be done manually. But if the process is done manually, it will take a long time so that if this is implemented in a health institution, it will be very inefficient given the large number of patients in the queue. This problem can be solved by using an artificial intelligence system using a genetic algorithm that is performed hybridization with simulated annealing. Simulated Annealing can help the genetic algorithm come out of optimum local conditions, due to its nature that can accept solutions that are not better or better than the previous solution. Simulated Annealing was successfully added to help the genetic algorithm out of optimum local conditions, this was indicated by the highest fitness value of 0.998, with the percentage difference between the patient's actual needs of calories by 0.18%, carbohydrate by 0.20%, protein by 0.69% and the last is fat at 0.27%.
Penerapan Metode Fuzzy Analitycal Hierarchy Process dalam Penetapan Panitera Pengganti di Pengadilan Negeri Malang Haryuni Siahaan; Nurul Hidayat; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 8 (2019): Agustus 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In the world of law as in Indonesia, a court is needed to conduct a trial. An institution that has the authority to deal with the case is the District Court, where there are parties who assist in resolving it. The substitute registrar is the party in charge and handles incoming officers. Determination of what is done in choosing who carries out the task is still done by appointment. This results in the appointment of a substitute clerk indirectly affecting the handling of case decisions to be resolved due to several criteria considerations. However, in determining the replacement clerks there is still no assessment for each criterion that will be used so that the results obtained are less than optimal. Fuzzy Analytical Hierarchy Process (F-AHP) is one method that is able to overcome this problem. The test uses the Spearman correlation test method in determining the substitute clerks based on the results of expert rankings with system rankings. The results of testing the level of the system ranking relationship to the ranking of experts using 496 datasets obtained the results of the Spearman correlation average of 0.370376 which means having a moderate relationship. So that it can be concluded that the incompatibility of expert ranking results with system ranking is because there is a large correlation test value that is inversely proportional to the data specified.
Penentuan Waktu Terakhir Penggunaan Ganja Menggunakan Multidimensional Hierarchical Classification Khairul Rizal; Sigit Adinugroho; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Drug abuse in Indonesia increases every year. One type of narcotics that often consumed freely without obtaining permission from the pharmaceutical industry is cannabis which can make the user experience euphoria (excessive joy without cause). The handling of drug addicts can be done through government rehabilitation services and one of the services is giving medical rehabilitation to aburses based on their level of dependency. Therefore, classification of determining last time use of cannabis is carried out which can help in determining the right type of rehabilitation service for abusers. The method that used by researcher is Multidimensional Hierarchical Classification (MHC) because this method focuses on determining the best path in the classification process and using the Naive Bayes Classifier to find probabilities that have high values ​​from the data. Data that used were 1885 secondary data form UCI Machine Learning with the title Drug Consumption which is divided into 7 classes based on the last time use of cannabis. Steps of this research conducting MHC training process and testing process using MHC. Testing process were carried out using 3 testing process, K-Fold Cross Validation with k = 5, testing with overall data and with balanced data. Testing results shows that the highest accuracy value is 42,86% using testing with balanced data.
Penerapan Metode Fuzzy K-Nearest Neighbour (FK-NN) Untuk Diagnosis Penyakit Pada Kucing Hardyan Zalfi; Agus Wahyu Widodo; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cats are the animals most loved by humans with a very nice shape and fur many people make cats as their pets especially in Indonesia or the world. The population of cats is 220 million in the world. With the big populatian of cats, of course there are also many cats that have poor health with disease. The limited ability of a person to detect cat disease and the limited of veterinary experts requires a system that can diagnose disease in cats easily. The making of this cat disease diagnosis system uses the k-nearest neighbor fuzzy method which is a development of the k-nearest neighbor method where the membership value of the k-nearest neighbor results will be calculated. Based on the functional tests that have been carried out, each "test class produces conformity to system requirements. The first accuracy testing is testing accuracy based on variations in the amount of training data with a different amount of training data for each test. For this test the highest accuracy value obtained by 85% while the lowest accuracy value is 80%. The second accuracy testing is accuracy testing based on the influence of K values ​​with the same test data totaling 15 test data. The results of this test the greatest accuracy is 86% while the lowest is equal to 73%. This shows that the k-nearest neighbor fuzzy method has a pretty good accuracy to diagnose diseases in cats.
Optimasi Penjadwalan Perkuliahan menggunakan Hybrid Discrete Particle Swarm Optimization (Studi Kasus: STAI Ma'had Aly Al-Hikam Malang) Achmad Choirur Roziqin; Imam Cholisoddin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 11 (2019): November 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Generally, timetabling is done by using conventional tables or spreadsheets. As a result, its affect the quality of timetable and it could drain time and energy if data is considered in thousands. Based on these problems, it requires an intelligent system that not only automates its process but also optimizes the result. Particle Swarm Optimization (PSO) is a popular metaheuristic algorithm to solve multiparameter optimization problems. Discrete PSO is used in this study because of combinatorics problems. Various strategies are also used in this method such as transposition method for particle movement, guided random strategies, and particle's position repair strategies. The strategies is expected to improve timetabling result. With the various strategies that have been used, this study will use “Hybrid Discrete PSO” approach. The test results showed the combination of parameters that resulting the best fitness are b_loc=1, b_glob=0,8, b_rand=0, number of particle is 200 and number of iteration is 40. The resulting fitness is 0,018896357 with the total execution time is 34 minutes 16 seconds 358 miliseconds.
Pembangkitan Pohon Keputusan dengan Metode Genetic Programming pada Kasus Penentuan Penderita Diabetes Melitus Farizky Novanda Pramuditya; Agus Wahyu Widodo; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 12 (2019): Desember 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Diabetes mellitus is one of the leading causes of death a disease because it can cause many health complications. Method that can help to diagnose this disease early is sorely needed. Genetic programming is a method used in this research. Genetic programming is one evolutionary algorithm that uses parse tree as its solution representation. This method will produce decision tree as its output which will be used to diagnose patients in the testing dataset. This research will also observe the correlation between genetic programming parameters and fitness value. Tree with highest fitness value produced with population number 900, maximum iteration 300, crossover rate 0.8, mutation rate 0.1 and training data with ratio of patient with diabetes and patient without diabetes 1:2. Decision tree produced with those parameters will be used to diagnose diabetes patient in testing data. The accuracy of decision tree produced with this method is 66,11%.
Penggunaan Fungsi Aktivasi Linier dan Logarithmic Normalization pada Metode Backpropagation untuk Peramalan Luas Kebakaran Hutan Gilang Pratama; Sigit Adinugroho; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 12 (2019): Desember 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Forest fires is a disaster that often occurs in various countries in the world, especially those with many forest areas. In June 2017, Portugal hit by a forest fire with a loss of more than 565 million US Dollars. In this case, meteorological data can affect several fire indices and can be used area forecasting for extra protection to prevent excessive losses and preservation of natural resources. This paper uses the backpropagation method, which begins with the calculation of preprocessing data (min max normalization, and logarithmic normalization). The weight normalization calculation use Nguyen Widrow method, the calculation of the feed forward process to determine the output at each iteration index, the error value is calculated at the iteration index and the weight is corrected using the backpropagation process. Furthermore, the output value is normalized to return the data to the initial range. The test results are calculated using Mean Square Error (MSE) on each parameter test. Test parameters get the best learning rate value that is 0.1 with the results of MSE 6743,716, 3 hidden neurons with MSE 6745,456, 10 epoch with MSE results 6740,684, and the 10% ratio of test 90% ratio of training data which produces MSE 1881,604.
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