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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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Prediksi Ketinggian Gelombang Laut Menggunakan Metode Jaringan Saraf Tiruan Backpropagation Nurhana Rahmadani; Budi Darma Setiawan; Sigit Adinugroho
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

Sea wave height prediction is difficult thing to do. One factors become wave generator is wind that influenced by wind direction and wind speed. These factors are difficult to calculate and predict manually, because wind conditions change any time. Wave height prediction is important because useful for shipping safety. Many prediction methods can used to make predictions, one of them is ANN Backpropagation used in this study to predict wave height in the next hour. Time-series data used in this study is wave height, wind direction, and wind speed data every one hour in East Java Sea from 2013 to 2014. The application of ANN Backpropagation in prediction of wave height is through by several phases, there are data normalization, weight initialization using Nguyen-Widrow, training, testing, and forecasting. The training data used is wave height, wind direction, and wind speed data every one hour from January to December 2013 and the test data used is data from January to June 2014. The training process used learning rate 0.5 ,4 neurons input layer,3 neurons hidden layer,1 neuron output layer, error limit MAPE training of 13,2% and maximum of 30000 iterations.The combination of these parameters produces average MAPE test value of 17.53182%.
Perbandingan Kualitas Hasil Klaster Algoritme K-Means dan Isodata pada Data Komposisi Bahan Makanan Reza Wahyu Wardani; Budi Darma Setiawan; Candra Dewi
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

Health is the most important part of human beings. One way that can be done to maintain health to regulate diet. Setting diet can be done by calculating the amount of daily nutrient content that enters body. Problems related to nutrition in community are malnutrition or condition where body doesn't get enough nutrition according to daily needs. This happens because most people dont understand how to regulate and classify food according to portion nutrients body. Fulfillment daily nutrition can be done if food has been in group based on nutritional similarity. Food grouping algorithm is needed so that people can find out enough daily nutritional alternatives based on potential commodities in Indonesia. Data used in study amounted 250 data sourced from Indonesian Ministry of Health regarding composition of food ingredients. Purpose of this study is examine which method is best by comparing K-Means and Isodata clustering algorithms based on the quality of clusters produced. Cluster quality measurements using Silhoutte Coefficient method. Based on tests conducted, Silhoutte Coefficient K-Means algorithm is 0.996762 and Isodata algorithm is 0.996910. Both these methods have small difference value but Isodata algorithm has greater Silhouette Coefficient value than K-Means algorithm in clustering Food Composition Data.
Klasifikasi Status Gunung Berapi dengan Metode Learning Vector Quantization (LVQ) Chelsa Farah Virkhansa; Budi Darma Setiawan; Candra Dewi
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

There are 129 active volcanoes and 500 inactive volcanoes located in Indonesia. Residents who live around areas that are susceptible to volcanic eruptions are quite numerous, which is as much as 10% of Indonesia's population. From the number of volcanoes that are still active there are only 69 mountains monitored, so there are still many active volcanoes which are not well monitored, which is around 40%. So that information on the status of the volcano is needed as quickly and accurately as possible to reduce the impact caused by the volcanic eruption. In this research, volcanic status classification will be carried out using the Learning Vector Quantization method. this study uses data totaling 110 data. The data was obtained from the website of the Volcanology Center and Geological Disaster Mitigation (PVMBG). From the tests that have been done, the highest accuracy is 88% when using the learning rate 0.1, the learning rate deduction is 0.1 and the minimum learning rate is 0.01.
Prediksi Harga Bekatul menggunakan Metode Fuzzy Time Series Oky Krisdiantoro; Budi Darma Setiawan; Muhammad Tanzil Furqon
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

Rice bran is one of the raw materials used as a mixture of animal feed concentrates, the use of rice bran in animal feed concentrates is 10% -30% from about 10 other types of raw materials mixed. with the number of percentages used, the company needs to pay attention to the availability of rice bran and also the price that changes every month, if the price of rice bran is too expensive it will change the basic price of animal feed concentrate, so the company must be able to predict the price of rice bran in the next month so that they can supply more rice bran when the prices would increase. To predict prices, we can use the fuzzy time series method with reference to historical data from the previous months, with which we can find out the price predictions of rice bran in the following month. The results of this study are expected to be able to help animal feed concentrate companies to be able to predict the price of bran in the coming months, in this study the best predictions resulted in a MAPE value of 4.43% with a number of training data 36 and interval length 12.
Optimasi Kombinasi Bahan Makanan untuk Mencegah Stunting pada Balita dengan menggunakan Algoritme Genetika Tria Melia Masdiana Safitri; Imam Cholisoddin; Budi Darma Setiawan
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

The number of good nutrients provided to kids in Indonesia has been a common problem and has yet to be solved. The lack of nutritional intake can cause malnutrition and stunting (the lack of height growth). Indonesia has become the fifth biggest country in terms of the numbers of toodlers suffering stunting, whose numbers have risen to nearly 9 million toddler. Stunting in toddlers can be caused by many factors, one of which is the lack of knowledge possessed by the parents of the combination of a variety of food ingredients which must be fed to the toddler in order to provide a perfectly balanced supply of nutrients. Providing a single dish does not always provide a perfectly balanced supply of nutrients. Providing a stable supply of perfectly balanced nutrients can be achieved by a variety of food ingredient combinations that contain roughly the same amount of nutrients. In this research, a recommendation of food compositions was provided through the course of 7 days using a genetic algorithm to assist parents in combining food ingredients which corresponded with a toddler's nutritional needs. Based on the testing parameters of the genetic algorithm, the optimal results from the combination of Cr:Mr test was 0,7:0,3 and the fitness results had an average score of 97,412. The testing results on the optimal size of the population was discovered to be 90 with an average fitness score of 96,95. Testing of the most optimal number of generations that need to be generated were 350 generations with an average fitness score of 96,664. The result of the test was capable of saving the parents expenses as much as 35,77% with the average cost of a dish was Rp.19269,21.
Implementasi High Order Fuzzy Time Series Multifactor pada Prediksi Harga Ayam Broiler di Pasar Malang Fanny Aulia Dewi; Budi Darma Setiawan; Randy Cahya Wihandika
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

Malang is the second largest population after Surabaya in East Java Province. Malang, which has increased its population every year, has resulted in the need for staples, especially broiler chicken meat, to increase. Broiler chicken meat is one of the sources of nutritious animal protein. Broiler chicken meat can be consumed by all levels of society so that there is an increase in demand every year. The availability of broiler chicken meat must always be fulfilled in the market and must pay attention to the price too. Broiler chicken meat prices on religious holidays (such as Eid al-Fitr, Eid Al-Adha, Christmas) there is a very striking increase compared to prices on normal days. The traders who need information about the price of broiler chickens every day in order to arrange sales so as not to miss. Therefore, a settlement is needed in forecasting the price of chicken using 72 data obtained from BPS in the period January 2013-December 2018. Based on the results of this study, the best MSE is 1,430 based on the highest number of orders.
Klasifikasi Berat Badan Lahir Rendah Pada Bayi Dengan Fuzzy K-Nearest Neighbor Muhammad Rizkan Arif; Budi Darma Setiawan; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The number of infant mortality (IMR) is a measure of the success of health services in an area. The lower the IMR, the better the health services in the area. However, in 2015, the IMR value in Indonesia was very far from the agreed target as an indicator of the success of health service development. In 2013, there was an increase in LBW cases during the 2009-2013 period to 16% according to data from WHO and UNICEF. If viewed from the cause of death, low birth weight babies still rank high. As many as 2.79% of infants died from LBW in East Java in 2010. This percentage increased to 3.32% in 2013 so that LBW was classified as the main cause of neonatal death, which was 38.03% of the total birth rate. The existence of an early detection system is likely that LBW is expected to be able to help reduce infant mortality. One method that can be applied to predict the possibility of LBW is Fuzzy K-Nearest Neighbor (FK-NN). This method is proven to be able to carry out LBW classification with an accuracy rate of 79%.
Prediksi Permintaan Semen Dengan Metode Fuzzy Time Series Yosendra Evriyantino; Budi Darma Setiawan; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cement is a material that is used as an adhesive for solid materials namely bricks or concrete blocks into a strong and sturdy unit, usually used for making houses, walls, foundations, roads, or other buildings. In Indonesia, cement production is quite high. In 2017, the total cement production in Indonesia has reached 107.9 million tons. However, high cement production in Indonesia is not matched by the number of requests. As a result, Indonesia experienced an oversupply of cement which caused the price of cement in the market to experience a decline. Therefore, research on predicting cement demand needs to be done as a solution for cement producers in estimating the amount of cement that needs to be produced. In this study, discussing the Fuzzy Time Series method used to predict the amount of demand for cement. The data used is data collected from PT. Semen Indonesia from 2006 to 2018 for each month. From the test results, the smallest MAPE error value was obtained at 10.42% with a parameter value of 80 intervals for 24 test data and 96 training data.
Pengaruh Seleksi Fitur Information Gain pada K-Nearest Neighbor untuk Klasifikasi Tingkat Kelancaran Pembayaran Kredit Kendaraan Ulfah Mutmainnah; Budi Darma Setiawan; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Intermittent credit is one of the problems or risks that are often faced by some auto loan service providers. The problem stems from the debtor's behavior, namely not paying the installments on time. In determining the smoothness of credit payments depends on the analysis of debtor data, but analyzing for large amounts of data can take up more time. This study uses the Information Gain feature selection and the K-Nearest Neighbor algorithm to overcome the problem of effectiveness and determine the accuracy of the classification level of the smoothness of auto loan payments so as to determine the effect of feature selection. Information Gain feature selection which is used to reduce feature dimensions so that relevant features can be obtained. The selected features are then processed for classification using the K-Nearest Neighbor algorithm. Based on testing from this study, the highest accuracy obtained is 94.44% when testing with a balanced class distribution using the number of features 3 and the value of K = 4 while the lowest accuracy is obtained at 33.33% using the number of features 10 with a value of K = 5 when testing with uneven class distribution. Features that produce the highest accuracy are jobs, income and price on the road (OTR). The three features are features with the largest order of gain values and have a gain value of more than 0.1.
Penerapan Algoritma Support Vector Regression Pada Peramalan Hasil Panen Padi Studi Kasus Kabupaten Malang Dhan Adhillah Mardhika; Budi Darma Setiawan; Randy Cahya Wihandika
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

Rice is one of the important resources in human life, in several surveys it was found that more than 59% of the world's population used rice from rice as food staple. But in another theory stated that the human population will continue to develop exponentially while it is difficult to be followed by the growth of food products, especially in this case rice. Support Vector Regression (SVR) method is a method that will be used in this study, this method has been used in several previous studies such as forecasting gold prices and forecasting electricity consumption. In this study we will focus on testing whether the Support Vector Regression (SVR) method is suitable for use in predicting rice yields, using a number of predetermined parameters, and by applying changes to the parameters, namely the number of iterations, Complexity, Epsilon, Sigma, cLR , Lambda. The best results obtained in this study reached MAPE error rate of 10.133%, these results were achieved with the following parameter values, Number of iterations: 50, Complexity: 1, Epsilon: 0.01, Sigma: 1, cLR: 0.1, Lambda: 1
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