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All Journal Jurnal Teknologi Perikanan dan Kelautan ILMU KELAUTAN: Indonesian Journal of Marine Sciences Saintek Perikanan : Indonesian Journal of Fisheries Science and Technology Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Kursor Journal of Innovation and Applied Technology Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal POINTER Jurnal Kelautan Tropis Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer JFMR (Journal of Fisheries and Marine Research) Knowledge Engineering and Data Science Jurnal Penelitian Perikanan Indonesia Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) JAST : Jurnal Aplikasi Sains dan Teknologi Journal of Aquaculture Science J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Journal of Fisheries & Marine Jurnal Penelitian Teknik Sipil Konsolidasi
Muh. Arif Rahman
Brawijaya University
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Materials Science & Nanotechnology Other

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Journal : Knowledge Engineering and Data Science

 1 
Efficient Scheduling of Plantation Company Workers using Genetic Algorithm Wayan Firdaus Mahmudy; Andreas Pardede; Agus Wahyu Widodo; Muh Arif Rahman
Knowledge Engineering and Data Science Vol 3, No 2 (2020)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v3i22020p60-66

Abstract

Workers at large plantation companies have various activities. These activities include caring for plants, regularly applying fertilizers according to schedule, and crop harvesting activities. The density of worker activities must be balanced with efficient and fair work scheduling. A good schedule will minimize worker dissatisfaction while also maintaining their physical health. This study aims to optimize workers' schedules using a genetic algorithm. An efficient chromosome representation is designed to produce a good schedule in a reasonable amount of time. The mutation method is used in combination with reciprocal mutation and exchange mutation, while the type of crossover used is one cut point, and the selection method is elitism selection. A set of computational experiments is carried out to determine the best parameters’ value of the genetic algorithm. The final result is a better 30 days worker schedule compare to the previous schedule that was produced manually. 
Earthquake Magnitude and Grid-Based Location Prediction using Backpropagation Neural Network Bagus Priambodo; Wayan Firdaus Mahmudy; Muh Arif Rahman
Knowledge Engineering and Data Science Vol 3, No 1 (2020)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v3i12020p28-39

Abstract

Earthquakes, a type of inevitable natural disaster, is responsible for the highest average death toll per year compared to other types of a natural disaster. Even though it is inevitable, but it can be anticipated to minimize damage and casualties, such as predicting the earthquake‘s magnitude using a neural network. In this study, a backpropagation algorithm is used to train the multilayer neural network to weekly predict the average magnitude of earthquakes in grid-based locations in Indonesia. Based on the findings in this research, the neural network is able to predict the magnitude of earthquakes in grid-based locations across Indonesia with a minimum error rate of 0.094 in 34.475 seconds. This best result is achieved when the neural network is trained for 210 epochs, with 16 neurons used in the input and output layer, one hidden layer consisted of 5 neurons and a learning rate of 0.1. This result showed backpropagation has pretty good generalization capability in order to map the relations between variables when mathematical function is not explicitly available.
Co-Authors A Alfan Jauhari Abdullah Hamid Agi Putra Kharisma, Agi Putra Agus Wahyu Widodo Agus Wahyu Widodo, Agus Wahyu Aida Sartimbul Ali Muntaha Andi Khofifah Nurfadillah Andreas Pardede Arief Andy Soebroto Bagus Priambodo Berton, Freddy Toranggi Cangara, Satriawati Citra Satrya Utama Dewi Daduk Setyohadi Darmawan Ockto Sutjipto Debby Aranindy Putri Wangi Defri Yona Dewa Gede Raka Wiadnya Dewa Gedhe Raka Wiadnya Dewi Novita Sari Dian Eka Ratnawati Edy Santosa Eko Sulkhani Yulianto Farys, Sholeh Al Fawwaz Haryono, M. Naufal Feni Iranawati Fransisca Sariuli Tobing Fransiskus Cahyadi Putra Pranoto Gatut Bintoro Geoffrey Manurung, Daniel Iis Nur Rodliyah, M.Ed Imam Cholissodin Imam Subali Jonemaro, Eriq Muhammad Adams Juan, Patrick Kurnianingtyas, Diva Lailil Muflikhah Ledhyane Ika Harlyan Mihrobi Khalwatu Rihmi Mr Sunardi Muhammad Rafi Farhan Nanda Dwi Putra Miskarana Ade Nindi Nur Wulandari Nita Hellis Setyowati Novanto Yudistira Nugroho, Muhammad Alifyan Satrio Nurdin, Abd. Rahim Nurin Hidayati Nurin Hidayati Nurul Hidayat Prakoso, Gideon Aji Pramana Putra, Jody Priyanka Mondal Putra Pandu Adikara Putri, Safinatunnajah Mutiara Rahmansyah, Muhammad Dzikri Randy Cahya Wihandika Riska Oktaviana Rr Dea Annisayanti Putri Safitri Widya Ningtias Shobriyyah Afifah Nabilah Shofiatul Kholishoh Solimun, Solimun Sunardi Sunardi Sunardi, Sunardi Supapong Pattarapongpan SUTRISNO Syarifah Hikmah Julinda Sari Syarifah Hikmah Julinda Sari Syarifah Hikmah Julinda Sari Tri Djoko Lelono Tsania Humairoh Vita Rumanti Kurniawati Wahida Kartika Sari Wakhit Rhomadona Wayan Firdaus Mahmudy