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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmu Komputer MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Perfecting a Video Game with Game Metrics Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Ilmiah Kursor International Journal of Local Economic Governance Journal of Enviromental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Jurnal Ilmiah Teknologi Informasi Asia Knowledge Engineering and Data Science Indonesian Journal of Electrical Engineering and Computer Science Indexia : Informatics and Computational Intelligent Journal Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Bulletin of Culinary Art and Hospitality Bulletin of Social Informatics Theory and Application
Wayan Firdaus Mahmudy
Brawijaya University
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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Regression Modelling for Precipitation Prediction Using Genetic Algorithms Asyrofa Rahmi; Wayan Firdaus Mahmudy
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 3: September 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i3.4028

Abstract

This paper discusses the formation of an appropriate regression model in precipitation prediction. Precipitation prediction has a major influence to multiply the agricultural production of potatoes in Tengger, East Java, Indonesia. Periodically, the precipitation has non-linear patterns. By using a non-linear approach, the prediction of precipitation produces more accurate results. Genetic algorithm (GA) functioning chooses precipitation period which forms the best model. To prevent early convergence, testing the best combination value of crossover rate and mutation rate is done. To test the accuracy of the predicted results are used Root Mean Square Error (RMSE) as a benchmark. Based on the RMSE value of each method on every location, prediction using GA-Non-Linear Regression is better than Fuzzy Tsukamoto for each location. Compared to Generalized Space-Time Autoregressive-Seemingly Unrelated Regression (GSTAR-SUR), precipitation prediction using GA is better. This has been proved that for 3 locations GA is superior and on 1 location, GA has the least value of deviation level.
Hybridizing PSO With SA for Optimizing SVR Applied to Software Effort Estimation Dinda Novitasari; Imam Cholissodin; Wayan Firdaus Mahmudy
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.2812

Abstract

This study investigates Particle Swarm Optimization (PSO) hybridization with Simulated Annealing (SA) to optimize Support Vector Machine (SVR). The optimized SVR is used for software effort estimation. The optimization of SVR consists of two sub-problems that must be solved simultaneously; the first is input feature selection that influences method accuracy and computing time. The next sub-problem is finding optimal SVR parameter that each parameter gives significant impact to method performance. To deal with a huge number of candidate solutions of the problems, a powerful approach is required. The proposed approach takes advantages of good solution quality from PSO and SA. We introduce SA based acceptance rule to accept new position in PSO. The SA parameter selection is introduced to improve the quality as stochastic algorithm is sensitive to its parameter. The comparative works have been between PSO in quality of solution and computing time. According to the results, the proposed model outperforms PSO SVR in quality of solution
Optimizing Laying Hen Diet using Multi-Swarm Particle Swarm Optimization Gusti Ahmad Fanshuri Alfarisy; Wayan Firdaus Mahmudy; Muhammad Halim Natsir
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 4: August 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i4.7765

Abstract

Formulating animal diet by accounting fluctuating cost, nutrient requirement, balanced amino acids, and maximum composition simultaneously is a difficult and complex task. Manual formulation and Linear Programming encounter difficulty to solve this problem. Furthermore, the complexity of laying hen diet problem is change through ingredient choices. Thus, an advanced technique to enhance formula quality is a vital necessity. This paper proposes the Multi-Swarm Particle Swarm Optimization (MSPSO) to enhance the diversity of particles and prevent premature convergence in PSO. MSPSO work cooperatively and competitively to optimize laying hen diet and produce improved and stable formula than Genetic Algorithm, Hybridization of Adaptive Genetic Algorithm and Simulated Annealing, and Standard Particle Swarm Optimization with less time complexity. In addition, swarm size, iteration, and inertia weight parameters are investigated and show that swarm size of 50 for each sub-swarm, total iteration of 16,000, and inertia weight of 6.0 should be used as a good parameter for MSPSO to optimize laying hen diet.
Optimizing SVR using Local Best PSO for Software Effort Estimation Dinda Novitasari; Imam Cholissodin; Wayan Firdaus Mahmudy
Journal of Information Technology and Computer Science Vol. 1 No. 1: June 2016
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (810.339 KB) | DOI: 10.25126/jitecs.2016117

Abstract

Abstract. In the software industry world, it’s known to fulfill the tremendous demand. Therefore, estimating effort is needed to optimize the accuracy of the results, because it has the weakness in the personal analysis of experts who tend to be less objective. SVR is one of clever algorithm as machine learning methods that can be used. There are two problems when applying it; select features and find optimal parameter value. This paper proposed local best PSO-SVR to solve the problem. The result of experiment showed that the proposed model outperforms PSO-SVR and T-SVR in accuracy. Keywords: Optimization, SVR, Optimal Parameter, Feature Selection, Local Best PSO, Software Effort Estimation
Rainfall Forecasting Using Backpropagation Neural Network Andreas Nugroho Sihananto; Wayan Firdaus Mahmudy
Journal of Information Technology and Computer Science Vol. 2 No. 2: November 2017
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (390.659 KB) | DOI: 10.25126/jitecs.2017229

Abstract

Rainfall already became vital observation object because it affects society life both in rural areas or urban areas. Because parameters to predict rainfall rates is very complex, using physics based model that need many parameters is not a good choice. Using alternative approach like time-series based model is a good alternative. One of the algorithm that widely used to predict future events is Neural Network Backpropagation. On this research we will use Nguyen-Widrow method to initialize weight of Neural Network to reduce training time. The lowest MSE achieved is {0,02815;  0,01686; 0,01934; 0,03196} by using 50 maximum epoch and 3 neurons on hidden layer.
Rainfall Forecasting in Banyuwangi Using Adaptive Neuro Fuzzy Inference System Gusti Ahmad Fanshuri Alfarisy; Wayan Firdaus Mahmudy
Journal of Information Technology and Computer Science Vol. 1 No. 2: November 2016
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (590.164 KB) | DOI: 10.25126/jitecs.20161212

Abstract

Rainfall forcasting is a non-linear forecasting process that varies according to area and strongly influenced by climate change. It is a difficult process due to complexity of rainfall trend in the previous event and the popularity of Adaptive Neuro Fuzzy Inference System (ANFIS) with hybrid learning method give high prediction for rainfall as a forecasting model. Thus, in this study we investigate the efficient membership function of ANFIS for predicting rainfall in Banyuwangi, Indonesia. The number of different membership functions that use hybrid learning method is compared. The validation process shows that 3 or 4 membership function gives minimum RMSE results that use temperature, wind speed and relative humidity as parameters.
Hybrid Genetic Algorithm and Simulated Annealing for Function Optimization Tirana Noor Fatyanosa; Andreas Nugroho Sihananto; Gusti Ahmad Fanshuri Alfarisy; M Shochibul Burhan; Wayan Firdaus Mahmudy
Journal of Information Technology and Computer Science Vol. 1 No. 2: November 2016
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (879.719 KB) | DOI: 10.25126/jitecs.20161215

Abstract

The optimization problems on real-world usually have non-linear characteristics. Solving non-linear problems is time-consuming, thus heuristic approaches usually are being used to speed up the solution’s searching. Among of the heuristic-based algorithms, Genetic Algorithm (GA) and Simulated Annealing (SA) are two among most popular. The GA is powerful to get a nearly optimal solution on the broad searching area while SA is useful to looking for a solution in the narrow searching area. This study is comparing performance between GA, SA, and three types of Hybrid GA-SA to solve some non-linear optimization cases. The study shows that Hybrid GA-SA can enhance GA and SA to provide a better result
Optimization of Vehicle Routing Problem with Time Window (VRPTW) for Food Product Distribution Using Genetics Algorithm Rayandra Yala Pratama; Wayan Firdaus Mahmudy
Journal of Information Technology and Computer Science Vol. 2 No. 2: November 2017
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (233.572 KB) | DOI: 10.25126/jitecs.20172216

Abstract

Food distribution process is very important task because the product can expire during distribution and the further the distance the greater the cost. Determining the route will be more difficult if all customers have their own time to be visited. This problem is known as the Vehicle Routing Problem with Time Windows (VRPTW). VRPTW problems can be solved using genetic algorithms because genetic algorithms generate multiple solutions at once. Genetic algorithms generate chromosomes from serial numbers that represent the customer number to visit. These chromosomes are used in the calculation process together with other genetic operators such as population size, number of generations, crossover and mutation rate. The results show that the best population size is 300, 3,000 generations, the combination of crossover and mutation rate is 0.4:0.6 and the best selection method is elitist selection. Using a data test, the best parameters give a good solution that minimize the distribution route.
Cost Optimization of Multi-Level Multi-Product Distribution Using An Adaptive Genetic Algorithm Mohammad Zoqi Sarwani; Wayan Firdaus Mahmudy; Agus Naba
Journal of Information Technology and Computer Science Vol. 1 No. 2: November 2016
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (561.249 KB) | DOI: 10.25126/jitecs.20161218

Abstract

Distribution is the challenging and interesting problem to be solved. Distribution problems have many facets to be resolved because it is too complex problems such as limited multi-level with one product, one-level and multi-product even desirable in terms of cost also has several different versions. In this study is proposed using an adaptive genetic algorithm that proved able to acquire efficient and promising result than the classical genetic algorithm. As the study and the extension of the previous study, this study applies adaptive genetic algorithm considering the problems of multi-level distribution and combination of various products. This study considers also the fixed cost and variable cost for each product for each level distributor. By using the adaptive genetic algorithm, the complexity of multi-level and multi-product distribution problems can be solved. Based on the cost, the adaptive genetic algorithm produces the lowest and surprising result compared to the existing algorithm
Implementation of Genetic Algorithm to Solve Travelling Salesman Problem with Time Window (TSP-TW) for Scheduling Tourist Destinations in Malang City Gusti Eka Yuliastuti; Wayan Firdaus Mahmudy; Agung Mustika Rizki
Journal of Information Technology and Computer Science Vol. 2 No. 1: June 2017
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (617.611 KB) | DOI: 10.25126/jitecs.20172122

Abstract

In doing travel to some destinantions, tourist certainly want to be able to visit many destinations with the optimal scheduling so that necessary in finding the best route and not wasting lots of time travel. Several studies have addressed the problem but does not consider other factor which is very important that is the operating hours of each destination or hereinafter referred as the time window. Genetic algorithm proved able to resolve this travelling salesman problem with time window constraints. Based on test results obtained solutions with the fitness value of 0,9856 at the time of generation of 800 and the other test result obtained solution with the fitness value of 0,9621 at the time of the combination CR=0,7 MR=0,3.
Co-Authors A.N. Afandi Abdul Latief Abadi Achmad Arwan Achmad Basuki Achmad Ridok Adyan Nur Alfiyatin Adyan Nur Alfiyatin Agung Mustika Rizki Agung Mustika Rizki Agung Mustika Rizki Agung Mustika Rizki, Agung Mustika Agung Setia Budi Agus Naba Agus Wahyu Widodo Agus Wahyu Widodo Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Afif Supianto Aji Prasetya Wibawa Alfiani Fitri Alfita Rakhmandasari Amalia Kartika Ariyani Amalia Kartika Ariyani Amalia Kartika Ariyani Anam, Syaiful Anantha Yullian Sukmadewa Andi Hamdianah Andi Maulidinnawati A K Parewe Andi Maulidinnawati A. K. Parewe Andreas Nugroho Sihananto Andreas Pardede Andreas Patuan G. Pardede Angga Vidianto Aprilia Nur Fauziyah Aprilia Nur Fauziyah Arief Andy Soebroto Arinda Hapsari Achnas Arviananda Bahtiar Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi, Asyrofa Bagus Priambodo Bagus Priambodo Bayu Rahayudi Binti Robiyatul Musanah Buce Trias Hanggara Budi Darma Setiawan Candra Dewi Candra Fajri Ananda Cleoputri Yusainy Dea Widya Hutami Diah Anggraeni Pitaloka Dinda Novitasari Diny Melsye Nurul Fajri Dita Sundarningsih Diva Kurnianingtyas Durrotul Fakhiroh Dyan Putri Mahardika Edy Santoso Edy Santoso Eko Widaryanto Elta Sonalitha Ervin Yohannes Ervin Yohannes, Ervin Evi Nur Azizah Fais Al Huda Faiz Alqorni Farid Jauhari Fatchurrochman Fatchurrochman Fatwa Ramdani, Fatwa Fauziatul Munawaroh Fendy Yulianto Fita Lathifatul Mu’asyaroh Fitra A. Bachtiar Fitra A. Bachtiar Fitri Anggarsari Fitria Dwi Nurhayati Garsinia Ely Riani Gayatri Dwi Santika Ghenniy Rachmansyah Ghozali Maski Grady Davinsyah Gusti Ahmad Fanshuri Alfarisy Gusti Ahmad Fanshuri Alfarisy Gusti Eka Yuliastuti Hafidz Ubaidillah Herman Tolle Herman Tolle Hilman Nuril Hadi Ida Wahyuni Imada Nur Afifah Imam Cholisoddin Imam Cholissodin Imam Cholissodin Indriati Indriati Irvi Oktanisa Irvi Oktanisa Ishardita Pambudi Tama Ismiarta Aknuranda Kuncahyo Setyo Nugroho Kuncahyo Setyo Nugroho Luh Putu Ratna Sundari Luthfi Hidayat M Chandra Cahyo Utomo M Shochibul Burhan M. Chandra Cahyo Utomo M. Shochibul Burhan M. Zainal Arifin M.Shochibul Burhan Mabafasa Al Khuluqi Mar'i, Farhanna Marji Marji Mayang Anglingsari Putri Mochammad Anshori Moh. Zoqi Sarwani Mohammad Zoqi Sarwani Mohammad Zoqi Sarwani Mohammad Zoqi Sarwani Muh Arif Rahman Muh. Arif Rahman Muhaimin Rifa’i Muhammad Ardhian Megatama Muhammad Faris Mas'ud Muhammad Halim Natsir Muhammad Isradi Azhar Muhammad Khaerul Ardi Muhammad Noor Taufiq Muhammad Rivai Muhammad Rofiq Mukhammad Wildan Alauddin Nadia Roosmalita Sari Nadia Roosmalita Sari Nadia Roosmalita Sari Nadya Oktavia Rahardiani Nashi Widodo Nindynar Rikatsih Nindynar Rikatsih Novi Nur Putriwijaya Nurizal Dwi Priandani Philip Faster Eka Adipraja Prayudi Lestantyo Purnomo Budi Santoso Putra, Firnanda Al Islama Achyunda Putu Bagus Arya Putu Indah Ciptayani Qoirul Kotimah Rafiuddin Rody Rani Kurnia Rayandra Yala Pratama Reiza Adi Cahya Retno Dewi Anissa Ria Febriyana Rifki Setya Armanda Rinda Wahyuni Rizal Setya Perdana Rizdania Dermawi Rizka Suhana Rizki Ramadhan Ruth Ema Febrita Ryan Iriany S, M Zaki Samaher . Santika, Gayatri Dwi Saragih, Triando Hamonangan Sari, Nadia Roosmalita Sari, Nadia Roosmalita Selly Kurnia Sari Sudarto Sudarto Sutrisno . Sutrisno Sutrisno Syafrial Syafrial Syafrial Syafrial Syandri, Hafrijal Tirana Noor Fatyanosa Titiek Yulianti Titiek Yulianti Titiek Yulianti Tomi Yahya Christyawan Tri Halomoan Simanjuntak Ullump Pratiwi Utaminingrum, Fitri Vitara Nindya Putri Hasan Vivi Nur Wijayaningrum Vivi Nur Wijayaningrum Wahyuni, Ida Widdia Lesmawati Windi Artha Setyowati Yeni Herawati Yogi Pinanda Yogie Susdyastama Putra Yudha Alif Aulia Yudha Alif Auliya Yulia Trianandi Yusuf Priyo Anggodo Yusuf Priyo Anggodo Yusuf Priyo Anggodo Yusuf Priyo Anggodo