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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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Implementasi Metode Exponential Smoothing Untuk Prediksi Bobot Kargo Bulanan Di Bandara Internasional I Gusti Ngurah Rai Amaliah Gusfadilah; Budi Darma Setiawan; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Goods are important objects to meet people's needs and sometimes the procurement of goods can be done by transferring goods. Transfer of goods can use shipping via air transportation. However, the weight of the cargo indirectly can affect the speed of delivery. So that it demands the airport to always improve the provision of adequate facilities to meet the needs of cargo weight. To be able to meet these demands a mature prediction is needed. The prediction of cargo weight aims to determine cargo weight data in the future by using cargo weight data in the past. The prediction method used in this study uses the Exponential Smoothing method. Exponential Smoothing is a method that continually perfects predictive results by smoothing past values ​​of a data sequence by decreasing time. In this study comparing 3 Exponential Smoothing methods including Single Exponential Smoothing, Double Exponential Smoothing, and Triple Exponential Smoothing, where the method is used to generate predictive values ​​and then evaluate the results of predictions using the Mean Absolute Percentage Error (MAPE). The smallest MAPE is found in the Triple Exponential Smoothing method spanning 5 years with parameter values ​​α = 0.9, β = 0.1, and γ = 0.1 of 13.563. Based on the MAPE values ​​that have been obtained between 10 and 20, the Triple Exponential Smoothing method is included in the good criteria.
Prediksi Tingkat Pemahaman Siswa Dalam Materi Pelajaran Bahasa Indonesia Menggunakan Naive Bayes Dengan Seleksi Fitur Information Gain Siti Utami Fhylayli; Budi Darma Setiawan; Sutrisno Sutrisno
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 Language Subjects are generally regarded as easy lessons and do not need to be studied by students and society. Based on this, various learning problems arose involving instructors, Indonesian language subjects, students who received lessons, teaching methods, facilities, ways to obtain, and the objectives of Indonesian language learning (Moeljono, 1989). The difference between each student in different learning differences. This causes the teacher to have limitations in measuring the level of understanding of students. Then a system is needed to predict the level of understanding of students. This prediction uses the classification method with the Naive Bayes algorithm. The class that will be used in this study is that students understand, are quite understanding and lack understanding. In this study, the authors used the Information Gain (IG) feature selection. The selected feature will be processed with the Naive Bayes classification algorithm, then the accuracy will be seen if it is not maximized, then the previous feature selection process will be done again to get the desired verification. From the tests that have been conducted, the results obtained which have a Gain value of more than 0.2 have the largest rating, reaching 90%. The features chosen from 17 included features of family members, residence status, mother's work, caregivers, family support, joining extracurricular activities, repeating lessons at home, length of study at home, reading at home, reading time at home.
Implementasi Metode Time Invariant Fuzzy Time Series Untuk Memprediksi Jumlah Keberangkatan Penumpang Pelayaran Dalam Negeri Di Pelabuhan Tanjung Priok Dwi Damara Kartikasari; 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

Maritime transportation is considered to have an important contribution in advancing the national economy in Indonesia, considering that 75% of Indonesia's territory is in the ocean. Maritime transportation has also become an alternative of transportation between islands recently. Moreover with the increase in the number of vehicles on land from year to year resulting in congestion on the highway, of course this will further increase public interest in making maritime transportation an alternative to their transportation. But in every cruise, the number of passengers always decreases or increases. The uncertainty of the number of passengers must be predictable, so that further policies can be made from the port to anticipate the number of passengers in the future, in order to increase economic benefits in the sea transportation sector. The method used to make predictions in this research is Time Invariant Fuzzy Time Series with the data used is the number of cruise passenger departures at Tanjung Priok Port in the period January 2006 to December 2015. Based on the results of the test, the smallest of Mean Average Percentage Error (MAPE) is 17.39% using the number of fuzzy sets = 5; training data = 108, 96, 84, and testing data = 12.
Penerapan Metode Fuzzy Tsukamoto untuk Menentukan Harga Sewa Hotel (Studi Kasus: Gili Amor Boutique Resort, Dusun Gili Trawangan, Nusa Tenggara Barat) Rudito Pujiarso Nugroho; Budi Darma Setiawan; M. 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

Gili Trawangan is a place that is popular in the lndonesian and foreign traveler. ln the hospitality industry in Gili Trawangan they have 3 seasons, namely; low season, high season, and peak season. Gili Amor Boutique Resort is one of the hotels located on Gili Trawangan that has problem to determining the hotel rental price because they only estimates the hotel price to be rented based on the current season. Based on the problem, Fuzzy Tsukamoto was chosen because it has a monotone logic on each rules, which is each consequence of lF-THEN rules must be represented by a fuzzy set with a monotonus membership function. Fuzzy logic is use to solve periods in an linguistically or variabels that contain uncertainties rather than the numbers. The Tsukamoto Method has 3 stages, namely; fuzzification, fuzzy inference system, and defuzzification. Fuzzification functions to change the crisp value to fuzzy value. Fuzzy inference system are conclusions based on fuzzy rules. Defuzzification is the process of turning fuzzy output into a crisp value using weighted average concept. ln this research, the rules will be searched automatically by the system based on the data that has been inputted. The data that has been inputted will be added “event” to distinguish holidays, significant price, and etc. The result of this research obtained an error using MAPE amounting to 28.41% for data test with Studio type of rooms and 27.85% for data test with Premiere type of rooms.
Klasifikasi Pola Sidik Bibir Untuk Menentukan Jenis Kelamin Manusia Dengan Metode Gray Level Co-Occurrence Matrix Dan Support Vector Machine Eka Novita Shandra; Budi Darma Setiawan; Yuita Arum Sari
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

Identification is one way that can be done to recognize individual characteristics. Identification is needed to find out the clarity of personal identity, for both deceased and living people. In the world of forensic medicine, the role of identification is very important. Like fingerprints, lip prints also have unique characteristics for each individual. Lip prints can be used as a means to identify forensic and non-forensic cases. For nonforensic cases, lip prints can determine the sex of an individual. To help in the process of identifying gender based on lip prints, a classification system is needed that can classify the sex of women and men. The process begins with collecting lip print images which are then preprocessed and extracted texture features using the Gray Leveled Co-ocurrence (GLCM) method. There are 4 features that are used namely ASM, Contrast, Correlation and IDM with angles of 0o, 45o, 90o and 135o. Then the feature value is used by data for the training and testing process using the Support Vector Machine (SVM) method. The training data used in the test is 60 data. The results of this study have not provided a good level of accuracy because the system is only able to provide an accuracy of 51.4% by testing the GLCM parameter, namely distance = 1 and SVM parameters λ (lambda) = 0.5, C (complexity) = 1, constant (gamma) = 0.01, and itermax = 100.
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.
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