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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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Sistem Diagnosis Penyakit Pada Tanaman Melon Menggunakan Metode Forward Chaining - Certainty Factor Irfan Aprison; Nurul Hidayat; Budi Darma Setiawan
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

Knowledge of melon plants is a must for the cultivators of melon plants, one of the knowledge is the diseases that can attack melon plants. Melon plant disease is one of the obstacles that faced by cultivators of melon plants. However, lack of understanding owned by the cultivators and the unavailability of disease experts in horticultural crops is one of the main factors that hold up the development of agriculture in melon plants. Thus, in melon plant problems can be developed melon plant disease diagnosis system. The method used is Certainty Factor, this method can accommodate uncertainty and describe the level of confidence of an expert against the facts. The melon plant diagnosis system receives input from the user and then the input will be calculated based on the trust level based on the user and the expert. After that, it will be compared with every single disease where the disease has the largest percentage that is believed to attack the melon plant. This research coantains 36 symptoms and 10 types of diseases in melon plants. In testing, this research used validation testing (black box) and accuracy testing. In the validation test obtained functionality level of 100% indicating the system in accordance with the list of needs. The accuracy rate of this system is 80% gain from accuracy test which indicates that this system is able to function well using Certainty Factor.
Prediksi Produktivitas Padi Menggunakan Jaringan Syaraf Tiruan Backpropagation Gandhi Ramadhona; Budi Darma Setiawan; Fitra A. Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Rice is very important for human beings, especially to the ASEAN community. Indonesia is one of the ASEAN countries that cultivate rice. In 2015, Indonesia ranked as the third-highest in terms of the world's largest rice producer. However, Indonesia still have to import rice every year due to its high demand and to fulfil Indonesian's per-capita consumption. The other reason is the different amount of harvest on each areas resulting in a scarcity of rice because the country can not be able to optimize the farming techniques that are used. This research use the methods of backpropagation neural network to predict the results of the rice productivity. In its implementation, the data is normalized using the min - max normalization and weighting initialization using Nguyen - Widrow. Based on the results of testing the parameters for the method of backpropagation, shows the most minimum RMSE i.e. 8.6918 with parameter values learning rate = 0.8, hidden layer neurons, hidden = 3 = 4 with the number of epoch 10000 against 135 training and 13 test data. Based on result of 5 fold cross validation against the stability testing data gets an average RMSE of 8.2126.
Perbandingan Holt's dan Winter's Exponential Smoothing untuk Peramalan Indeks Harga Konsumen Kelompok Transportasi, Komunikasi dan Jasa Keuangan Achmad Fahlevi; Fitra Abdurrachman Bachtiar; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Consumer Price Index (CPI) is one of the most commonly used indicators in measuring the inflation rate. CPI's group of Transportation, Communication and Financial Services have the second largest proportion on living cost with 19.15%. As the group who categorize as administered price (the price are ruled by the government), forcasting this group would help some parties involved in taking neccessery decision and avoiding significant inflation rate. In this research, forecasting were performed using two Exponential Smoothing method which is, Holt's Exponential Smoothing and Winters Exponential Smoothing. This method was evaluated by calculating average error rate using Mean Absolute Percentage Error (MAPE) method. There will be 120 data from January 2017 until December 2017 that used which taken from Bank Indonesia official websites. The results of the test was the best parameter value for Holt's Exponential Smoothing which is 𝛼 = 0.7 dan β = 0.1 and for Winters Exponential Smoothing 𝛼 = 0.1, β = 0.4 dan γ = 0.8. And from this parameter's value, MAPE's value obtained for Holt's Exponential Smoothing which 0.474% and for Winters Exponential Smoothing is 1.503%. Both of them got MAPE value under 10% that can be categorize as very good on forcasting CPI group of Transportation, Communication and Financial Services. And can be conclude either that Holt's Exponential Smoothing have better accuration rather than Winters Exponential Smoothing in Cosumer Price Index's group of Transportation, Communication and Financial Services.
Implementasi Metode Backpropagation untuk Prediksi Harga Batu Bara Miracle Fachrunnisa Almas; Budi Darma Setiawan; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Coal is a natural resource that belongs to one of the fossil fuels. Indonesia is one of the countries with the largest quantity of coal production and export in the world. Coal becomes an important component in the running of a large-scale industrial company as an industrial fuel. Predicted coal prices are needed because coal prices released by the government usually takes a long time. Coal price data is in the form of time series. The data used is coal price data starting from January 2009 to September 2017 with trademark of Gunung Bayan I. This research discusses Backpropagation method that is used to predict the coal price. In this research, the effect of change parameter value from Backpropagation in predicting coal price it can be seen. Output generated by the system is in the form of predicted coal price in the next month. The results of the tests are, the lowest MSE (Mean Square Error) value of 0,00205284 with a combination of 10 neurons on the input layer, 10 neurons in the hidden layer, 1 neuron produced as output, learning rate of 0.1 and the number of iterations of 500.
Prediksi Hasil Panen Benih Tanaman Kenaf Menggunakan Metode Support Vector Regression (SVR) Pada Balai Penelitian Tanaman Pemanis dan Serat (Balittas) Robih Dini; Budi Darma Setiawan; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Kenaf (Hibiscus cannabinus L.) is a fiber plant that has many benefits. Kenaf is grown by seed so it is necessary to handle the seeds in order to ensure the quality of the seed is not decreased so as to increase the productivity of the kenaf. Balai PenelitianTanaman Pemanis dan Serat (Balittas) as the producer of the seeds has constraint to predict the yields of kenaf seed for the proper handling preparation of kenaf seeds. Therefore in this research proposed regression method using Support Vector Regression (SVR) by using Radial Basis Function (RBF). Hopefully this research can help Balittas to prepare the handling of the harvested of kenaf seeds properly. The research used 100 data about the characteristics of kenaf plants measured from the beginning of planting until the time of harvest. From the testing results that have been done, the result of prediction show the error value using Mean Absolute Percentage Error 3,5371% by using the best SVR parameters value which is cLR = 0,01, σ = 0,25, ε = 1 x 10-7, C = 0,5, λ = 0,6, and the number of iterations = 25000.
Implementasi Performance Improved Holt-Winters Untuk Prediksi Jumlah Keberangkatan Domestik di Bandar Udara Soekarno Hatta Revinda Bertananda; Budi Darma Setiawan; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Air transportation in Indonesia is experiencing a rapid increase. Given the developments that occur, it's not impossible that in the future air transport will be a superior transportation again. But every flight in an airport doesn't always carry the same number of passengers each month. The number of these unconfirmed passengers should always be predictable so that the airport can determine policies to adjust the increase or decrease the number of passengers in the future. Prediction done in this research using Performance Improved Holt-Winters method. This method can predict time series data that has a data pattern with seasonal variation. In its calculations, Performance Improved Holt-Winters method involves trend and seasonality and is based on three smoothing equations: overall smoothing (level), trend smoothing, and seasonal smoothing. The data used in this study is the data of domestic departure at Soekarno Hatta airport from January 2012 to December 2017 which obtained from the official website of Central Bureau of Statistics Indonesia (www.bps.go.id). From the results of tests that have been done, the result of the smallest MAPE value is 2,976% with the parameter value α (alpha) = 0,04; β (beta) = 0,002; Υ (gamma) = 0,1; the number of training data = 60, and testing data = 12.
Optimasi Jumlah Produksi Metal Roof Menggunakan Algoritme Genetika (Studi Kasus: PT. Comtech Metalindo Terpadu) Febri Ramadhani; Budi Darma Setiawan; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Manufacturing industry in Indonesia continues to increase, especially in the molding industry. PT. Comtech Metalindo Terpadu is one of molded goods industry company located in Pekanbaru City. The company is an industrial company that produces metal roof. The metal roof is printed using Prepainted Galvalum (PPGL) raw material or more commonly referred to as coil, the raw material is imported from other countries. The ordering of raw materials takes 2 months until the raw material arrives. There are 3 types of metal roof products sold are spandek, zigzag and zigzag charcoal. All three items have the composition of raw materials, as well as providing benefits that are different. Setting the right amount of production is the thing that must be taken into account by the owner of the company in order to obtain optimal benefits. Based on these problems to get the right amount of production on the use of the remaining raw materials, it is necessary to optimize the number of metal roof production based on the existing demand and the remaining stock of raw materials. Optimization is used to regulate the amount of existing production so that the remaining raw materials can be used optimally and provide optimal benefits as well. Genetic Algorithms are used to optimize the 3 genes that represent each product. The value of the gene represents the original value of the existing query with the integer type. In the reproduction, the crossover method that used is the extended intermediate crossover. Whereas the mutation is performed by reviving the gene values of a randomly selected chromosome. For the selection process used elitism selection to screen the best individual and used random injection method to prevent early convergence. Based on testing of parameters that have been done with 5 times each parameter is got the best population size 90, the combination of cr = 0.1 and mr = 0.9, and total of best generation equal to 225 with average fitness value 7.12126.
Identifikasi Ujaran Kebencian Pada Facebook Dengan Metode Ensemble Feature Dan Support Vector Machine Aditya Kresna Bayu Arda Putra; Mochammad Ali Fauzi; Budi Darma Setiawan; Eti Setiawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In the beginning, social media is used for socializing and interacting with other people. One of the most used social media for socializing is Facebook, with users amounting to over hundred million people around the world. Nowadays, on Facebook, its often found there's hate speech writing being shared at massive pace. Of course an assistance from language expert is a must for identifying hatespeech on Facebook because there's not yet an automatic system that can identify a hatespeech. The system in this research are made using Ensemble feature and Support Vector Machine. Ensemble feature is used for combining some of the feature extracted from each writing to ease the process of identifying a hatespeech. Support Vector Machine then used to identifying a hatespeech from a writing based on feature that are combined using ensemble feature. According to the result of testing, we acquired a 70% accuracy for the system so we can conclude that ensemble feature and support vector machine is good to use for identifying hatespeech on social media Facebook.
Klasifikasi Aduan Masyarakat pada SAMBAT Online Kota Malang Menggunakan NW-KNN dan Seleksi Fitur Information Gain - Genetic Algorithm Rosi Afiqo; Agus Wahyu Widodo; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

SAMBAT Online is an application system used to accommodate complaints from the public against to the government of Malang. The incomplete features of SKPD selection related to the system made it difficult for Diskominfo of Malang City to report the complaint to the related SKPD. This is because the complaint grouping based on related SKPD is still done manually. Therefore, a system that can group complaints based on the relevant SKPD is required for time efficiency. NW-KNN is classification method which can be used to handle balanced issues that work by involving all training data in the process. The feature selection techniques that will be used are information gain and genetic algorithm to get a small number of features and high f-measure. Stages performed in the system get the best features of the first is pre-processing data, second is feature selection by using information gain, and the third is selection features by using genetic algorithm. The results of the tests performed resulted 0.22 in average of f-measure for unbalanced data and 0.39 for balanced data. These results have increased up to 0.04 for unbalanced data and 0.22 for balanced data from classification results without using feature selection process. Based on these results, it can be concluded that the classification using NW-KNN and information gain-genetic algorithm feature selection can be used to improve the classification results.
Optimasi Penjadwalan Ujian Akhir Semester Menggunakan Algoritme Genetika (Studi Kasus: SMAN 5 Malang) Ni'mah Firsta Cahya Susilo; Budi Darma Setiawan; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Scheduling is an activity with detailed division of time for various purposes in various fields. Scheduling of the semester final exam at SMAN 5 Malang in practice there are still some obstacles such as limited examination supervisors and the distribution of the subjects tested is less suitable. SMAN 5 Malang has applied the exam schedule by dividing subjects based on national examination subjects and other subjects. This study aims to determine the effect of parameter changes on genetic algorithms and find a scheduling solution for the semester final exam at SMAN 5 Malang with a genetic algorithm. Scheduling the final semester exam in this study is divided into subject scheduling and scheduling of exam supervisors. The testing of individual subjects and supervisors is carried out 5 times with population size of 100, number of generations 500 and combination of crossover rate 0.5 and mutation rate 0.5. Testing results in an optimal population for 180 subjects while for supervisors a total of 150. In testing the combination of Cr and Mr values ​​found a combination of optimal values ​​for individual subjects is Cr = 0.7 and Mr = 0.3 and a combination of Cr = 0.6 and Mr = 0.4 for individual supervisors with an optimal number of generations in individual subjects is 200 generations while in individual supervisors is 400 generations.
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