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All Journal JURNAL PASTI (PENELITIAN DAN APLIKASI SISTEM DAN TEKNIK INDUSTRI) JARES (Journal of Academic Research and Sciences) Journal of Industrial Engineering Journal Publicuho Advance Sustainable Science, Engineering and Technology (ASSET)
Muhammad Asrol
Bina Nusantara University
Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Transportation

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The Relationship between Job Stress and Employee Performance in Manufacturing Industry in Indonesia Deasy Lastya Sari; Ribka Intan Putri Sinaga; Helen Storyna; Fergyanto E. Gunawan; Muhammad Asrol; A.A.N. Perwira Redi
JARES (Journal of Academic Research and Sciences) Vol 6 No 2 (2021): September 2021
Publisher : Universitas Islam Balitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35457/jares.v6i2.1640

Abstract

One-fourth of Indonesia's Gross Domestic Product or GDP is from the manufacturing industry sector. Indonesia's government has proactively encouraged companies to increase their production capacity to meet the global demands, leading to strong demand for employees to work harder, affecting the workers' health. Overwork is often associated with fatigue, stress, and various health problems. Moreover, stress due to excessive work is a general problem many industries face and frequently influences workers' performance. Therefore, this research intends to examine the relationship between work stress and workers' performance, particularly in the manufacturing industry in Indonesia. The sample data are collected from ninety-three workers at the staff level across various companies in the manufacturing sector. The relationships between the determining factors and the Employee Productivity are evaluated by using the multivariate regression analysis. At the correlation coefficient of 0.972, we found a statistically strong relationship between the work environment and Stress to the workers' performance. The condition of low performance is attributed to the non-standard working hours and low quality of the relationship between colleagues and their superiors. Finally, the research recommends improved management of workers' stress by companies involving the adoption of flexible working hours and better communication between parties via discussion forums and meetings. Therefore, employees will be more motivated to improve work productivity.
DISCRETE EVENT SIMULATION MODELING WITH ARENA FOR COMBINATION OF MANUAL QUEUE AND FAST TRACK QUEUE IN HOSPITAL Febrian Krisnawati; Dhoni Muhamad Room Anugroho; Laura Yunita Rachmawati; Muhammad Asrol
Jurnal PASTI (Penelitian dan Aplikasi Sistem dan Teknik Industri) Vol 16, No 3 (2022): Jurnal PASTI
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/pasti.2022.v16i3.001

Abstract

In this study an analysis of the patient queuing system will be carried out by developing a queuing system, namely adding aspects of patient registration status and the registration process with a system or machine or through the hospital's web by downloading an application. This study aims to improve the efficiency of patient service management in clinics and develop a patient care management simulation model so that the number of patient rejections and patient waiting time in clinics. Discrete Event Simulation (DES) with ARENA and compare it with manual processes and with applications or machines in the registration process. The results show that patient rejection can be reduced to 1%, and the average patient time to be seen by a doctor is 0.7145 hours. If converted into minutes, each type of patient takes about 10 minutes in the doctor's office.
SUPPLY CHAIN PERFORMANCE MEASUREMENT OF DOWNSTREAM WOODWORKING INDUSTRY Natalia Hartanto; Muhammad Asrol; Muhammad Noor Badruddin
JARES (Journal of Academic Research and Sciences) Vol 8 No 1 (2023): March 2023
Publisher : Universitas Islam Balitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35457/jares.v8i1.2734

Abstract

People’s needs of wood toward increase. Along with the development of technology, the woodworking industry exists to balance the fulfilment of human needs of wood and to increase the value added of timber forest resources. The objective of this study is to identify the supply chain configuration and to measure the supply chain performance of the downstream woodworking industry. Metrics validation using the supply chain operation reference (SCOR) framework that is adjust to industry activities through discussions with stakeholders. Performance metrics are weighted using the Analytical Hierarchy Process (AHP). The result of the supply chain performance measurement of the downstream woodworking industry obtains a value 76.21 in the good category indicating that XYZ has achieved the target of 59%. 41% need to improve performance, namely 32% in the Average category, 5% in the Marginal category, and 4% in the Poor category.
Quality Improvement of Low Pressure Flush Column Reflux Pumps Using PDCA Method: A Case Study in an Urea Plant Heri Kurniawan; Gde Windar Lesmana; Muhammad Asrol
JIE Scientific Journal on Research and Application of Industrial System Vol 8, No 1 (2023)
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/jie.v8i1.4161

Abstract

This study focuses on the problems in the use and maintenance of centrifugal pumps at PT Pupuk Kalimantan Timur (PKT) in Indonesia. This study specifically looks at the 110-J pump, which is critical to the production process as its failure can result in a shut down of the factory. The study analyzes the history card of the pump over the period of 2015 to 2021 and identifies that there have been multiple repairs due to high vibration, shaft bending, and other internal damage caused by differences in throat bushing sizes. The study calculates that the average loss due to these issues is around IDR 122,012,857 annually and that the repair work takes about 5 working days. The study uses quality improvement tools plan, do, check, action (PDCA) identify the problems and formulate improvement efforts to increase the usage period and reduce maintenance costs. This study is important for improving the reliability of the production process and ensuring the availability of urea and NPK fertilizer, particularly in Indonesia. Result of this research is the decrease in the frequency of pump repairs from 3.7 times per year to none and accelerate pump assembly from 5 days to 3 working days.Keywords: Centrifugal pumps, shaft bending, maintenance, quality improvement tools, vibration
ANALISIS PEMELIHARAAN PREDIKTIF KENDARAAN OPERASIONAL MENGGUNAKAN ALGORITMA NAÏVE BAYES DAN DECISION TREE Islamia Nuraini; Arnowo Hari Wibowo; Muhammad Asrol; Taufik; Dyah Lang Wilis
Journal Publicuho Vol. 7 No. 2 (2024): May - July - Journal Publicuho
Publisher : Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35817/publicuho.v7i2.412

Abstract

Utilizing the team to carry out operational vehicle maintenance activities is crucial to maintaining smooth mobility. Well-scheduled maintenance can prevent unexpected problems and minimize disruption to vehicle operations. The problem is that the implementation of operational vehicle maintenance policies is not yet optimal. The aim of this research is to focus on operational vehicles so that use is not disrupted and mobility runs smoothly, maintenance scheduling is needed. Completion of this research method will use the Naïve Bayes and Decision Tree data mining applications. This research produces a comparison of the two data mining applications to determine maintenance performance with an accuracy level of the Naïve Bayes method of 33.33% and a Decision Tree at 75.00%. The results of the best algorithm performance analysis are used as a reference for implementing vehicle maintenance scheduling.
Data-Driven Machine Learning Models for Steam Turbine Efficiency Prediction Prima Arifa Alfariza; Hasna Fauziyah; Nikita Tjandra; Muhammad Asrol
Advance Sustainable Science Engineering and Technology Vol. 8 No. 4 (2026): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i4.2378

Abstract

Increased electricity consumption in Indonesia requires coal-fired power plants to operate at high efficiency. This study proposes a data-driven approach to predict the efficiency of coal-fired steam turbines by utilizing 844 historical operational data points from the XYZ coal-fired power plant. Input variables include main steam pressure and temperature, main steam flow, final feedwater temperature, and condenser vacuum pressure. Four machine learning algorithms, namely Random Forest, Extra Trees, XGBoost, and Support Vector Regression, were evaluated using R², RMSE, and MAE. Based on the results of the study, it can be concluded that predictive models using Random Forest, Extra Trees, and XGBoost can predict steam turbine efficiency with high accuracy, especially after hyperparameter adjustments that increase the R² value and reduce the RMSE and MAE values in all models. The Extra Trees model proved to be the best model with an R² value of 0.8655 and an MAE of 0.5612, demonstrating its ability to capture the complex relationship between operational variables and turbine efficiency. This approach has practical implications for continuous improvement strategies in coal-fired power plant operations.
Co-Authors Anak Agung Ngurah Perwira Redi Arnowo Hari Wibowo Deasy Lastya Sari Dhoni Muhamad Room Anugroho Dyah Lang Wilis Febrian Krisnawati Fergyanto E. Gunawan Gde Windar Lesmana Hasna Fauziyah Helen Storyna Heri Kurniawan Islamia Nuraini Laura Yunita Rachmawati Muhammad Noor Badruddin Natalia Hartanto Nikita Tjandra Prima Arifa Alfariza Ribka Intan Putri Sinaga Taufik