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All Journal International Journal of Advances in Applied Sciences Jurnal Simetris Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Computatio : Journal of Computer Science and Information Systems Jurnal Informatika CogITo Smart Journal Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Teknoinfo INTECOMS: Journal of Information Technology and Computer Science JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Journal of Information Systems and Informatics Jurnal Teknologi Dan Sistem Informasi Bisnis JATI (Jurnal Mahasiswa Teknik Informatika) INFORMASI (Jurnal Informatika dan Sistem Informasi) JIKA (Jurnal Informatika) Infotek : Jurnal Informatika dan Teknologi Infotech: Journal of Technology Information Jurnal AbdiMas Nusa Mandiri Journal of Business and Audit Information System (JBASE) Jurnal Pengabdian dan Kewirausahaan Konstelasi: Konvergensi Teknologi dan Sistem Informasi Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Sains dan Teknologi
Francka Sakti Lee
Universitas Bunda Mulia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering 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 Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Journal : CogITo Smart Journal

 1 
Predictive Maintenance of Heavy Equipment Machines using Neural Network Based on Operational Data Ahya Radiatul Kamila; Derhass, Gerry Hudera; Andry, Johanes Fernandes; Lee, Francka Sakti; Budiyanto, Very; Anatasia, Velly
CogITo Smart Journal Vol. 11 No. 2 (2025): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v11i2.555.229-241

Abstract

Preventive maintenance is a routine maintenance strategy that aims to maximize equipment life cycle and prevent unplanned downtime which causes increased repair costs. When carrying out this maintenance, error in selecting machines need to be anticipated to avoid company losses. This research aims to reduce human error in machine selection for preventive maintenance using deep learning. The dataset used in this research is operational data of heavy equipment machine dataset from one of the palm oil companies in Indonesia with 9 independent features and 1 dependent feature. Dependent feature is a target feature contain two target classes representing effective and ineffective machines. The dataset in this study contains outlier, feature scales that are very different, and imbalanced data class. To handle outlier and standardise data scale, the Z-score method is used. Meanwhile, the over sampling method is used to handle imbalanced data classes. To obtain the best model performance, the number of epochs and two types of optimizers (adam&adamax) of neural network are selected. In selecting the number of epochs, experiments were carried out using 100 epochs. This research obtained the linearity relationship between the number of epochs and accuracy with the accuracy values using Adam and Adamax optimizers were 94.82% and 93.11% at the 100th epoch.
Co-Authors ., Ozmar Agustina, Agustina Ahya Radiatul Kamila Alvaro, Giovanni Ananda, Deah Ananda, Vincent Ray Anatasia, Velly Andrian, Andrian Andrian, Kelvin Andry, Johanes Fernandes Anwar, Sahrul Aprilia, Keysia Arron, Rivaltino Arvin, Bryan Aryani, Dini Ayu Azhari, Ozmar Bernadus Gunawan Sudarsono Bernanda, Devi Yurisca Brainard, Aryo Breliastiti, Ririn Budiyantara, Agus Budiyanto, Very Charolina, Yanthi Charolina, Yanthi - Christianto, Kevin Christy, Vania Cornelius, Wilson Delly Vera Deny, Deny Derhass, Gerry Hudera Dinata, David Freggy Doa, Fidelia Novena Dylen, Varel Eko Ariawan Endi Putro Felicia, Jennifer Fenardi, Okky Fernando, Lukas Fernando, William Geasela, Yemima Monica Geasela, Yemima Monica Ginting, Jusia Amanda Ginting, Mega Henia Br Heber, William Hendy Tannady Honni Honni Honni, Honni Honni, Honni Huang, Calvin Ignatius Adrian Mastan Isputrawan, M Fauzi Isputrawan, M. Fauzi Johanes Fernandes Andry Kamila, Ahya Radiatul Kevin Christianto KEZIA, KEZIA Lesmana, Kenvil Limawal, Isabelle Ivana Marco Antonio Narahaba Marvelino, Matthew Matthew, Randy Meyliana, Sintia Michael Pranata Monica Clara Mulyo, Jonathan Riady Nababan, Andika Jakaria Nadia Karepowan Nicholas, Martinez Nurken, Brian Prasnavira Nurprihatin, Filscha Onggo, Kallista Angelia Owen, Bryan Paramita Rosadi Piter, Dicsi Purnomo, Yunianto Putra, Rakassiwi Ayudharma Putri, Angie Wiyani Rahman, Muhammad Ryo Reynaldi Ekklesia Rudi, Ardian Brian Pratama Samuel Winata Santoso, Andi Putra Setiawan, Selly Shiang Lung Felix Stevanus Stevanus Steven Steven Sudarsono, Bernandus Gunawan Sulaeman, Asvian Suryantara, I Gusti Ngurah Tampinongkol, Felliks F Tampinongkol, Felliks F. Teady Matius Surya Mulyana, Teady Matius Verawaty Verawaty Wandy Wandy Wiedjaya, Handry Wijaya, Agustinus Frits Wijaya, Hermawan William Darma Wincent, Wincent Witari, Putu Sita Witari, Putu Sita Yusup, Christian Ronaldo