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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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Analisis Perbandingan Algoritme K-Means dan Isodata untuk Klasterisasi Data Kejadian Titik Api di Wilayah Sumatera pada Tahun 2001 hingga 2014 Edo Fadila Sirat; Budi Darma Setiawan; Fatwa Ramdani
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

Fire phenomenon is a familiar phenomenon in Indonesia. The high number of fire incidents in Indonesia requires special attention from the government, so that any natural disasters such as forest fires can be overcomed. Satellite monitoring results are recorded on a data file of fire points with a large enough data numbers so that the data is difficult to be processed to become information that is easily received by the user. Based on data obtained from the EOSDIS site recorded as many as 289,256 fire spots occurrence in the region of Sumatra in the timeframe between 2001 to 2014. It takes an algorithm to segment the data or cluster the data, so that large data can be processed into a good information for the user. In this study a comparative study of clustering algorithms between K-Means and Isodata was conducted. Both algorithms used in this study were assessed based on the quality of the clusters produced. The algorithm used in measuring the quality of cluster in this research is Silhouette Coefficient (SC). The final result value of Shilhouette Coefficient K-Means method is 0.999997187 and Isodata method is 0.999957161, so in this case, K-Means algorithm has a higher SC value compared to the Isodata algorithm in clustering the data of fire spots with a small SC value difference.
Penentuan Portofolio Saham Optimal Menggunakan Algoritme Genetika Terdistribusi Talitha Raissa; Agus Wahyu Widodo; 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

In conducting stock investment, it is necessary to verify or spread the investment in order to form a stock portfolio with the proportion or optimal weight of every stock, good profit, and risk that can be borne by investors. Therefore, a system that can determine the optimal stock portfolio must be made by implementing distributed genetic algorithm. Distributed genetic algorithm generate chromosomes randomly at the certain interval as the representation of the stocks proportion. Then reproduction, evaluation and selection can be done based on the largest fitness derived from the calculation with single index model to find the return and risk. Distributed genetic algorithm has migration mechanism that able to maintain a diversity of individual variation. It is necessary to find out a broader solution which can produce a diverse and optimal stock portfolio. From the test result, distributed genetic algorithms can be applied properly and produce an optimal stock portfolio. The best parameter of the popsize test result is 80, the number of generations 150, 0.8 crossover rate (cr), and 0.2 mutation rate (mr) and the number of sub-optimal population of 10 to produce an optimal stock portfolio.
Pemilihan Aturan Fuzzy Inference System Mamdani Menggunakan Algoritme Particle Swarm Optimization Dalam Sistem Penyiraman Otomatis Pada Tanaman Tomat Indah Larasati; Budi Darma Setiawan; Mahendra Data
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

Laboratorium Tanah Benih Balai Pengkajian Teknologi Pertanian (BPTP) East Java is one of the institutes to do some research on plant nursery. One of soil testings which have been done in Laboratorium Tanah BPTP East Java is the parameter testing soil humadity. The research laboratory, right now, is developing an automatic watering based on soil humadity sensory to predict the amount of water needed to keep the humadity of the growing seed media. This research will figure out how much water plant volume with two input variables which are the initial humadity and flushing duration using Fuzzy Inference System Mamdani method. The two variables can cause often repeated rule based fuzzy or the same rule used more than once. Thus, to prevent these things to be happened, it needs fuzzy rule base fuzzy choice by using Particle Swarm Optimization algorithm. The testing was done in ten times trials by applying the amount of particles which is 250, value of inertia quality (w), which is 0,7, combination value of C1 and C2, which are 1,4 and 1,3, and the maximum iteration, which is 2500, and then it obtained the highest fitness value is on the seventh trial, which is 0,39949 with Root Mean Square Error (RMSE) value, which is 1,50319. The result from the highest fitness value is able to change the system from 27 arrangements to eight arrangements.
Prediksi Indeks Harga Konsumen (IHK) Kelompok Perumahan, Air, Listrik, Gas, dan Bahan Bakar Menggunakan Metode Extreme Learning Machine Irma Ramadanti Fitriyani; Budi Darma Setiawan; Rizal Setya Perdana
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

The Consumer Price Index is one of the indicators to measure the inflation rate in Indonesia. In 2017 inflation in Indonesia by expenditure group in general is 3,61%. The group of housing, water, electricity, gas, and fuel become the biggest contributor of inflation compared to six other groups with 5,14%. Therefore, the prediction needs to be done to anticipate and reduce domestic inflation rate. Prediction done in this research using method of Extreme Learning Machine (ELM) with initialization of weight using Nguyen-Widrow initialization. The data used in this research are 84 Consumer Price Index data of housing, water, electricity, gas, and fuel from January 2011 until December 2017. The data obtained from the official website of Bank Indonesia (www.bi.go.id). The result of this research is the minimum RMSE value of 0,72 with the number of features = 7, the amount of training data is 30 and the testing data is 11, the number of hidden neurons = 7, and the activation function is sigmoid binary function.
Peramalan Tingkat Produksi Gula Menggunakan Multi Factor Fuzzy Time Series yang Dioptimasi dengan Algoritme Genetika Kholifa'ul Khoirin; Budi Darma Setiawan; Agus Wahyu Widodo
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

Sugar is one of the strategic commodities that affect the Indonesia's economy. This is because sugar is one of a essencial staple for Indonesian society. But on the other hand, the large demand of sugar consumption in Indonesian cannot meet with the low production of sugar. One of sugar factories is PG Candi Baru Sidoarjo. Besides production processing's factors, the factory is experiencing difficulties in its planning. Which in the production planning, the sugar factory will set targets that must to be achieved in future production. In an effort to overcome these problems, this study is expected to provide forecasting to see the possibility of achieving sugar production targets. Multi Factor Fuzzy Time Series method optimized with Genetic Algorithm by considering several factors influencing sugar production process such as number of milling days in one month, percentage of rendeman, and number of milled sugarcane. The genetic algorithm is used to perform subinterval optimization. Forecasting results of sugar production using a combination of these two methods get RMSE of 424,70. These results are smaller than the Multi Factor Fuzzy Time Series method without optimizing the subintervals that yield RMSE 6168,7437. Thus, it can be concluded that the proposed method is capable of forecasting better results than the unoptimized Multi Factor Fuzzy Time Series method.
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.
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