Analysis of Damage Handling in The PT Petrokimia Gresik Factory Conveyor Safety System Using The Naive Bayes Method
Analisa Penanganan Kerusakan Pada Sistem Pengaman Konveyor Pabrik PT Petrokimia Gresik Menggunakan Metode Naive Bayes
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(1) * Fashoma Yudha Anggana Alkhaqiqi
Universitas Muhammadiyah Gresik
Indonesia
(2) Denny Irawan Universitas Muhammadiyah Gresik
Indonesia
(*) Corresponding Author
Abstract
In the industrial world, the speed of the production process plays a very important role in influencing industrial profits. One of the factors that determines production speed is the conveyor. PT. Petrokimia Gresik is one of the industries that uses conveyors, which pays great attention to accuracy and control of material speed. The function of the conveyor is to send raw materials from PT Petrokimia Gresik fertilizer to be processed. Three safety devices are installed on this tool, namely the low speed switch, outlying belt and cable pull switch. However, this complex security system makes it difficult for field technicians to handle conveyor problems. Problems that occur with conveyors, especially in the electrical and instrumentation parts, are sometimes difficult to find. Therefore, the author had the idea to conduct research related to conveyor problem solving analysis using the naive Bayes classification method. The results of the calculation between naive Bayes calculations and expert opinion show 100% agreement, which is an optimal result. It is hoped that these results can help field technicians in diagnosing and resolving problems when problems occur with conveyors.
References
R. A. Putra, “SIMULASI SISTEM PENGAMAN KONVEYOR BERBASIS PROGRAMMABLE LOGIC CONTROLLER DI PT PLN NUSANTARA POWER PACITAN,” pp. 3–4, 2024.
I. I. Praja, S. S. Dahda, and D. Widyaningrum, “PENERAPAN METODE RELIABILITY CENTERED MAINTENANCE (RCM) PADA PERAWATAN MESIN CONVEYOR UNLOADING PHOSPHATE ROCK (Studi Kasus PT PETROKIMIA GRESIK),” JUSTI (Jurnal Sist. dan Tek. Ind., vol. 1, no. 1, p. 61, 2020, doi: 10.30587/justicb.v1i1.2033. DOI: https://doi.org/10.30587/justicb.v1i1.2033
A. Wisaksono, Y. Purwanti, N. Ariyanti, and M. Masruchin, “Design of Monitoring and Control of Energy Use in Multi-storey Buildings based on IoT,” JEEE-U (Journal Electr. Electron. Eng., vol. 4, no. 2, pp. 128–135, 2020, doi: 10.21070/jeeeu.v4i2.539. DOI: https://doi.org/10.21070/jeeeu.v4i2.539
A. Nugroho and Y. Religia, “Analisis Optimasi Algoritma Klasifikasi Naive Bayes menggunakan Genetic Algorithm dan Bagging,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 5, no. 3, pp. 504–510, 2021, doi: 10.29207/resti.v5i3.3067. DOI: https://doi.org/10.29207/resti.v5i3.3067
Rayuwati, Husna Gemasih, and Irma Nizar, “IMPLEMENTASI AlGORITMA NAIVE BAYES UNTUK MEMPREDIKSI TINGKAT PENYEBARAN COVID,” Jural Ris. Rumpun Ilmu Tek., vol. 1, no. 1, pp. 38–46, 2022, doi: 10.55606/jurritek.v1i1.127. DOI: https://doi.org/10.55606/jurritek.v1i1.127
A. Yulianto, K. Dwi Septiady, A. Praja, and S. Mugono, “Pemecahan Masalah Dalam Mencari Kesalahan (Trouble Shooting) Dengan Metode Sistem Pakar (Expert System) Menggunakan Teorema Bayesian Pada Mesin Kapal,” J. Cahaya Bagaskara, vol. 6, no. 1, 2021.
A. R. C. B. A and M. F. Anggamawarti, “Classification of Impact Damage on A Rubber-Textile Conveyor Belt: A Review,” no. 4, pp. 21–27, 2020. DOI: https://doi.org/10.21776/mechta.2020.001.01.4
J. Sihombing, “Klasifikasi Data Antroprometri Individu Menggunakan Algoritma Naïve Bayes Classifier,” BIOS J. Teknol. Inf. dan Rekayasa Komput., vol. 2, no. 1, pp. 1–10, 2021, doi: 10.37148/bios.v2i1.15. DOI: https://doi.org/10.37148/bios.v2i1.15
Y. Resti, F. Burlian, and I. Yani, “Performance of cans classification system for different conveyor belt speed using naïve bayes,” Sci. Technol. Indones., vol. 5, no. 4, pp. 111–116, 2020, doi: 10.26554/sti.2020.5.4.111-116. DOI: https://doi.org/10.26554/sti.2020.5.4.111-116
Copyright (c) 2024 Fashoma Yudha Anggana Alkhaqiqi, Denny Irawan
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