ALGORITMA PREDIKSI PEMELIHARAAN MESIN MANUFAKTUR MENGGUNAKAN METODE NAÏVE BAYES (STUDI KASUS:PT.BAHTERA CAHAYA MAS)

MUHAJJIR, ABDUL RIFKI (2023) ALGORITMA PREDIKSI PEMELIHARAAN MESIN MANUFAKTUR MENGGUNAKAN METODE NAÏVE BAYES (STUDI KASUS:PT.BAHTERA CAHAYA MAS). S1 thesis, Universitas Mercu Buana Bekasi.

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Abstract

Perkembangan teknologi 4.0 masuk ke setiap aspek kehidupan. Pemanfaatan teknologi tersebut salah satunya dalam pemeliharaan mesin manufaktur pada perusahaan. PT. Bahtera Cahaya Mas merupakan perusahaan yang bergerak di bidang manufactur vacum metalizing, injeksi plastik dan cetakan plastik dimana mesin merupakan salah satu elemen terpenting dalam pembuatan produk dan penunjang proses produksi dalam suatu perusahaan. Jika suatu mesin mengalami kerusakan, dapat melumpuhkan proses produksi, menghentikan proses produksi, meningkatkan biaya perawatan, dan menurunkan kualitas produk yang dihasilkan. Tujuan penelitian ini adalah memprediksi kebutuhan spare part pada mesin agar saat terjadi kerusakan dapat mempercepat pebaikan mesin oleh bagian maintenance. Dalam proses analisa data, data riwayat kerusakan pada mesin akan dioleh dan digunakan untuk menentukan komponen mana yang memiliki potensi kerusakan paling tinggi menggunakan metode naïve bayes sehingga perusahaan dapat menyediakan sparepart tersebut. Data yang diolah, diambil dari komponen kritis pada mesin manufaktur. Hasil dari implementasi metode naïve bayes pada prediksi pemeliharaan mesin manufaktur diharapkan dapat membantu perusahaan dalam menyediakan sparepart yang diperlukan dan mempercepat perbaikan mesin oleh bagian maintenance. Kata Kunci : Prediksi, Pemeliharaan Mesin, Metode Naïve Bayes, Mesin Manufaktur, Spare part Technological developments 4.0 enter every aspect of life. One of the uses of this technology is in the maintenance of manufacturing machines at the company. PT. Bahtera Cahaya Mas is a company engaged in the manufacturing of vacuum metalizing, plastic injection and molded plastic where the machine is one of the most important elements in product manufacturing and supporting the production process in a company. If a machine is damaged, it can paralyze the production process, stop the production process, increase maintenance costs, and reduce the quality of the products produced. The purpose of this study is to predict the need for spare parts on the machine so that when damage occurs it can speed up engine repair by the maintenance department. In the data analysis process, history of damage to the machine will be obtained and used to determine which components have the highest damage potential using the Naïve Bayes method so that the company can provide these spare parts. The processed data is taken from critical components on manufacturing machines. The results of the implementation of the naïve Bayes method in predicting manufacturing machine maintenance are expected to help companies provide the necessary spare parts and speed up machine repairs by the maintenance department. Keywords: Prediction, Machine Maintenance, Naïve Bayes Method, Machine Manufacturing, Spare Parts

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