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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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Perbandingan Double Moving Average dan Double Exponential Smoothing untuk Peramalan Jumlah Kedatangan Wisatawan Mancanegara di Bandara Ngurah Rai Cinthia Vairra Hudiyanti; Fitra Abdurrachman Bachtiar; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Every year the number of international tourist arrivals in Bali always increases (BPS, Statistics Indonesia). Increasing the number of international tourist arrivals will have an impact on the availability of facilities, infrastructure, and services for the airport or Angkasa Pura I. Many things affect foreign arrivals, resulting in the need forecasting the number of foreign arrivals whose results can be used by Angkasa Pura I as the airport manager and local government to improve services. This research forecasting is done using Double Moving Average and Double Exponential Smoothing. Accuracy calculation is done by using Mean Absoulte Percentage Error (MAPE). The data used are 120 data, from January 2008 to December 2017, and obtained from the official website of Statistics Indonesia. From this study testing in 2017 found the best time order value for the Double Moving Average is 2 and Double Exponential Smoothing with parameter 𝛼 = 0.4. From these parameter values, the MAPE Double Moving Average value is 10,522 and the MAPE Double Exponential Smoothing value is 3,355. At Double Exponential Smoothing has a value below 10, it is said to be very good, while the Double Moving Average with a value above 10 is said to be good. It can be concluded that Double Exponential Smoothing has better accuracy than Double Moving Average in forecasting the number of arrivals of foreign tourists at Ngurah Rai Airport.
Klasifikasi Berat Badan Lahir Rendah (BBLR) Pada Bayi Dengan Metode Learning Vector Quantization (LVQ) Suryani Agustin; Budi Darma Setiawan; Mochammad Ali Fauzi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Low Birth Weight (LBW) is the condition as a birth weight of a baby less than 2500 grams or 2.5 kg.. LBW is a factor of infant mortality in Indonesia. The prevention and treatment of pregnant women when they know they will give birth to babies with LBW are very necessary, in order to minimize the death during the birth process. Therefore, it is expected that the existence of a low birth weight classification system in infant can help to identify the condition of the baby in pregnant women before the baby is born. This research use the Learning Vector Quantization (LVQ) method with 96 data and 6 features, there are age, education, parity, birth interval, hemoglobin and nutritional status. Those who will classify into two classes first is case class, which means the baby is born with LBW and the control class means that the baby is born without LBW. Based on the results of testing, the system produces an average accuracy is 60.5% using optimal parameters for learning rate 0.1, learning rate decrement 0.1 and maximum epoch is 5. In the k-fold cross validation testing the best accuracy value is 58.3% and the average accuracy is 46.85%.
Implementasi Metode Support Vector Regression (SVR) Dalam Peramalan Penjualan Roti (Studi Kasus: Harum Bakery) Noval Dini Maulana; Budi Darma Setiawan; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Bread is one of the favorite foods of the Indonesian people, the proof is the increasing import of wheat flour. One of the bakery companies that is currently developing is Harum Bakery. Constraints that are often faced by Harum Bakery are customer demand forecasting systems that are still manual and seem to be guessing. The forecasting process give a big impact on the sales process. With the forecasting of bread sales, it is hoped that Harum Bakery can help bakeries in preparing raw materials and everything needed for bread making. Support Vector Regression (SVR) is one method that can be used in forecasting. The data used is data on sales of sweet bread, cake and white bread with time series data types and uses 4 features. In this study the SVR method used to predict the results of the sale resulted in an evaluation value of RMSE for sweet breads is 0.00176, bread cake is 0.00019, and large breads is 0.00010.
Diagnosis Hama Penyakit Tanaman Bawang Merah Menggunakan Metode Neighbors Weighted K-Nearest Neighbors (NWKNN) Masayu Vidya Rosyidah; Budi Darma Setiawan; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Red onions is a a plant that is a successfull export commodity in Indonesia. Red onions have many benefits, can be a seasoning cook to medical ingredients. Behind that, during the planting period these plants often run the risk of crop failure caused by pests and diseases of red onions. In addition, there is still a lack of understanding of farmers in controlling pests and diseases causing inevitable losses. One way to overcome this problem is to build a system that can diagnose pests and diseases on red onions, namely the expert system. The expert system that is built to diagnose pests and diseases on red onions in this study using the Neighbors Weighted K-Nearest Neighbors (NWKNN) method with parameters k =2 and e = 4 produces an accuracy of 100%.
Penerapan Penjadwalan Program Kerja Indonesian Future Leaders Chapter Malang Menggunakan Algoritme Genetika Rafely Chandra Rizkilillah; Budi Darma Setiawan; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesian Future Leaders is a youth-led Non-Governmental Organization concerning on social activies education and youth empowerment. Indonesian Future Leaders is moved by implementing a variety of work programs that have been created and designed by Indonesian Future Leaders itself. Indonesian Future Leaders work programs are required to be done in a structured way. The programs that are being implemented by Indonesian Future Leaders takes about one year. The problems that Indonesian Future Leaders has is they didn't have structured work program schedules from the start of the beginning starting period. The data that is used by this research are all the work programs of Indonesian Future Leaders. Afterwards, the data will be proceeds with Genethics Algorithm with various of steps, such as cromosom representation, crossover, mutation, evaluation, and selection. The results of the schedule from Genetic Algorithm examination is the best fitness schedule has value of 0,001524 , which has 180 generation combination, 240 populations, and value of 0,7 cr and 0,3 mr.
Implementasi Metode Jaringan Saraf Tiruan Backpropagation Pada Prediksi Payload 4G di Telkomsel Jember M. Rikzal Humam Al Kholili; Budi Darma Setiawan; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

PT. Telkomsel is one of the largest telecommunication providers in Indonesia which also has the most customers spread throughout Indonesia. Customers of PT. Telkomsel from year to year has experienced an increase and this will result in the use of an increasing number of payloads because the payload is all packages that are received and sent by mobile to a receiver (signal receiver) and if the amount of payload usage is smaller than the number of users it will occur over lagging and users will feel uncomfortable. With these problems, it requires an implementation of several methods to predict the amount of 4G payload usage so that PT. Telkomsel can find out the number of 4G payload usage in the next day or month so that it can anticipate losses or complaints from customers. Of the many prediction methods available, the authors use the backpropagation neural network method to perform a prediction process using artificial neural network architecture 4 input node neurons, 6 hidden node neurons and 1 node output neuron. By using the MAPE calculation (Mean Absolute Precentage Error) the most optimal value is 6.0154830745999%.
Implementasi Metode Bayesian Network untuk Diagnosis Penyakit Telinga Hidung dan Tenggorokan (THT) Mustofa Robbani; Nurul Hidayat; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Ear nose and throat disease one of the harmful disease, lack of hygiene and the difficulty in keeping the communities to diagnose due to the similarity of symptoms and diseases of the ear nose and throat, in addition to the conditions in the village It is located far from hospitals - major hospitals lead to sluggish handling of the ear nose and throat. Allow the occurrence of the disease is worse so detrimental to society or to patients themselves. Then it takes a software which can help the community or patient so expect that software can help communities to diagnose diseases of the ear nose and throat. Then the software was made using Bayesian Network methods, and to facilitate operation then made software with Android-based operating system. This software has the input based on the symptoms - symptoms of the disease that is selected by the user and is processed by methods of Bayesian Network so as to generate output in the form of disease and suffered from the results of testing the accuracy of data 42 It brings the accuracy of 93.75%.
Prediksi Nilai Cryptocurrency Bitcoin menggunakan Algoritme Extreme Learning Machine (ELM) Rahmat Faizal; Budi Darma Setiawan; Imam Cholisoddin
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Bitcoin is one of cryptocurrency which is popular among people due to decentralized management, well-maintained confidentiality, and easy process. But, this type of cryptocurrency is extremely volatile which makes the owner feel aggrieved. Lots of actions have been taken to overcome this by seeing the statistic movement over and over, Taking actions without considering the future prospect, or make the the asset being untouched until the considered time. Those are inneficient regarding the goal is to get the profit.Therefore, the need of system which can predict the value of Bitcoin accurately and efficiently so it can help decreasing the risk of losing and could give another consideration on trading cryptocurrency Bitcoin. This research has a purpose to obtain the value of cryptocurrency Bitcoin using Extreme Learning Machine (ELM) algorithm. Based on the implementation and analysis conducted using Bitcoin Data from May 1th, 2018 until August 1th, 2018, it can be obtained that the smallest error value using Mean Average Percentage Error (MAPE) is 2,657% with the number of features is 2, the number of hudden neuron is 4, and the percentage of training data is 90%, also the range of with range [-1.8, 1.8].
Optimasi Fuzzy Time Series Untuk Prediksi Jumlah Produksi SAGA Leather Fashion Menggunakan Metode Algoritme Genetika Aditya Chandra Nurhakim; Budi Darma Setiawan; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Leather wallets are an item that has a lot of interest nowadays, but because the process of makingproducts handmade and the price of raw materials is increasingly expensive, so making wallets andother leather-based goods has a higher price value, which makes the producers have decreasedorders. Therefore, an effort is needed to optimize the remaining raw materials used by predicting thenumber of items to be produced in the following month. The prediction method used to solve theproblem in predicting the amount of production is fuzzy time series, which is then optimized using thegenetic algorithm method. From the results of these studies, it is expected that the predicted resultscan help producers in optimize the remaining raw materials in the production process. In this study,the best individual from genetic algorithm on wallet products produce a RMSE (Root Mean SquareError) value of 5.24611658 with an accuracy rate of 96.44%, where the RMSE value is smaller thanthe test without optimization which results in a RMSE value of 7.20507068 with an accuracy of95.06%.
Optimasi Penempatan Ruang Sidang Skripsi Menggunakan Algoritme Genetika Nelli Nur Rahma; Budi Darma Setiawan; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The main problem that often happen in room placement final presentation for thesis in Computer Science Faculty is where lecturer examine more than one sessions continuously with different room which far away. Does not rarely in room placement, lecturer will placement in different building with far away in continuous sessions so raises final presentation for skripsi process will be late from initial scheduling because moving process. With the development of science and technology management, scheduling process should be done better. One of algoritm can use for recommendation of optimal final presentation for thesis is genetic algoritm where this algorithm can use for finished complex problems with many variable and result set of optimal solutions. In the formation of chromosome that used is permutation representation, the crossover process that used is one cut point crossover method, the mutation process that used is one random mutation method, the evaluation process with get fitness value each individual, the selection method that used is elitism. In the test result of room placement final presentation for thesis in one day obtained highest average fitness value is 1,000 in combination of cr 0,5 and mr 0,5, population size is 90, and generation size is 90. Room placement solution that use system can offer optimal scheduling with does not break the constraint at all.
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