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All Journal Journal of Industrial and Engineering System Bulletin of Information Technology (BIT) SAINTEK
Fibi Eko Putra
Universitas Pelita Bangsa
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Transportation

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Analisis Safety Performance Index Dengan Pendekatan Behavior-Based Safety Pada Industri Manufaktur Komponen Otomotif Yayan Saputra; Murwan Widyantoro; Fibi Eko Putra; Putri Nika Andini
Journal of Industrial and Engineering System Vol. 2 No. 1 (2021): Juni 2021
Publisher : Program Studi Teknik Industri, Fakultas Teknik, Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/jies.v2i1.492

Abstract

Occupational health and safety is one of the necessary things in the industrial world. The problems that arose in the industrial era were the need for workers and increased productivity to be able to produce quality products. Health conditions and the availability of employee safety protections can affect work productivity. So that the safety and work safety culture in the workplace can be realized and can increase the safety performance index, an approach is implemented in the form of methods that can be applied to all organizations in the enterprise, one of which is behavior-based safety methods. The analysis of the data obtained shows that the factors that cause work accidents due to behavior are taken from the validity test, namely the factors of perception, communication and environment, because these three factors are very easily ignored by employees and company management. Environmental factors and personal protective equipment have no effect on work accidents as management always provides periodic education to its employees and enforces strict rules on the use of personal protective equipment. The magnitude of the influence of the variables studied in Behavior-Based safety in an effort to improve safe behavior was 79.7% and the remaining 20.3% was influenced by other unexamined items. The value of 79.7% consists of perception, communication and environment.
Klasifikasi Kebutuhan Sparepart Dengan Algoritma K-Nearest Neighbor Untuk Meningkatkan Penjualan Sparepart Virza Putra Virza; Gatot Tri Pranot; Fibi Eko Putra
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.729

Abstract

Adequate supply of spare parts will be a supporting factor for consumer confidence in the company. The classification method approach can be applied in analyzing data to apply data mining with the classification method for spare parts needs generated by utilizing data testing consisting of 100 record datasets with a ratio of 90% training data (training data) and 10% test data (data testing). . Implementation of the K-Nearest Neighbor algorithm model on test data (data testing) of 100 data objects, obtaining results that show a new insight in the form of classification of low and high level needs based on 2 categories. No is a category of light needs, consisting of 89 data objects, the category Yes is a category of high needs. Performance evaluation and testing using the RapidMiner Sstudio application is able to provide optimal results with the scenarios that are modeled. This algorithm model has an Accuracy value of accuracy: 93.00% +/- 6.40% (micro average: 93.00%).
Analisis Total Productive Maintenance Pada Industri Percetakan Farid Marhaban; Dwi Indra Prasetya; Fibi Eko Putra
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

In the production process there is still a lot of damage suffered on the machine, one of which is the production target that was not achieved due to the defective product. In the production process, one of the machines in the printing industry is the HD Speed ​​Master’s machine which often has problems, the HD Speed ​​Master’s machine used in the production process serves as a paper printing machine. A common problem with this machine is the high frequency of damage, so that the printing paper suffers from defects such as blurred ink, skewed process results, torn paper and there are parts that are not printed so as to interfere with production process. The purpose of this study was to identify the effectiveness of HD Speed ​​Master’s machine using Overall Equipment Effectiveness (OEE) approach. Based on the analysis conducted on the HD Speed ​​Master’s machine, the result from the OEE calculation is 81%. Does not meet the company's standard of 85%. The low OEE value is due to the large amount of downtime that occurs in the machine, so the machine does not work effectively and efficiently. Keywords: Maintenance, downtime, Total Productive Maintenance, Overall Equipment Effectiveness
Aplikasi Lean Manufacturing System Berbasis Value Stream Mapping Pada Industri Otomotif Aprilia Andeyu; Muhammad Aldi Albana; Fibi Eko Putra
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

The manufacturing industry competes in improving product quality and productivity by minimizing production costs. System changes directly or indirectly include machines, materials, people, methods, and the environment by adopting lean concepts. This Value Stream Mapping method aims to focus on improvement and waste areas, especially in the production process of painting the 15 k seat cowl product. The results of this study show that the implementation of Future State Mapping can help reduce the following: production lead time decreased by 58.9%, total cycle time decreased by 7.08% and total non-value added decreased by 7.12 %. This proves that adopting the Value Stream Mapping method can make significant improvements. Keywords: Lean Manufacturing System, Value Stream Mapping, Waste
Co-Authors Aprilia Andeyu Dwi Indra Prasetya Farid Marhaban Gatot Tri Pranot Muhammad Aldi Albana Putri Nika Andini Virza Putra Virza Widyantoro, Murwan Yayan Saputra