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All Journal Jurnal Rekayasa Sistem Industri Teknik dan Ilmu Komputer Sinergi Jurnal Teknologi Pertanian Jurnal Ilmiah Teknik Industri Jurnal Bakti Masyarakat Indonesia Prosiding Seri Seminar Nasional International Journal of Application on Economics and Business Jurnal Mitra Teknik Industri
Wilson Kosasih
Program Studi Teknik Industri, Fakultas Teknik Universitas Tarumanagara
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Social Sciences Transportation Other

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ANALISIS PENGARUH ANGKATAN KERJA DAN LEMBAGA PELATIHAN KERJA TERHADAP PRODUK DOMESTIK REGIONAL BRUTO KABUPATEN/KOTA DI JAWA TIMUR Clayren Nathanniel; Luh Juni Asrini; Dian Retno Sari Dewi; Ig. Jaka Mulyana; Wilson Kosasih
Jurnal Mitra Teknik Industri Vol. 4 No. 3 (2025): Jurnal Mitra Teknik Industri
Publisher : Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jmti.v4i3.35800

Abstract

Gross Regional Domestic Product is one of the good indicators to measure the economy of a region. In this study, GRDP modeling was conducted with the independent variables of the employed workforce (X1) and the number of job training institutions (X2) using spatial regression and Ordinary Least Square (OLS). The purpose of this study was to determine the spatial regression model of GRDP with these two predictors or independent variables, to determine the interaction of the proximity of districts/cities with neighboring districts/cities, and to determine the effect of the employed workforce (X1) and the number of job training institutions (X2) on the GRDP value. The results showed that based on the Robust Lagrange Multiplier test, the appropriate spatial regression was the SAR model. The coefficient of determination and MAPE in the OLS model were 57.8% and 1.888, while in the spatial regression model were 68.72% and 0.4139. These results indicate that spatial regression is better than OLS in modeling GRDP in East Java, because the coefficient of determination of the spatial regression model was larger and the MAPE was smaller than the OLS model. The interaction of the proximity of a district/city with neighboring districts/cities indicates that the district/city economy is influenced by the economy of neighboring districts/cities. The two independent variables, namely the employed workforce (X1) and the number of job training institutions (X2) have a positive influence on the GRDP value.
QUALITY IMPROVEMENT ANALYSIS USING THE SEVEN NEW QUALITY TOOLS AND POKA YOKE IN A SAFETY SHOES MANUFACTURING COMPANY Nathaniel; Wilson Kosasih; Lithrone Laricha Salomon
Jurnal Mitra Teknik Industri Vol. 4 No. 3 (2025): Jurnal Mitra Teknik Industri
Publisher : Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/mv4y6h87

Abstract

This safety shoe company is a manufacturing company that faces various quality issues, such as defects in stitching, leather, mismatched shoe pairs, and incomplete components. Based on production data from March 2024 to February 2025, the most dominant defects were “Mismatched Pairs” and “Incomplete Components,” with a total of 3,694 defective pairs out of 120,000 produced, resulting in a DPMO value of 7,695.83. This study aims to identify the root causes of these defects and design quality improvement solutions using the New Seven Quality Tools and PokaYoke methods. Data were collected through field observations and literature reviews, then analyzed using tools such as the Pareto Diagram, Affinity Diagram, Interrelationship Diagram, Tree Diagram, and Matrix Analysis. The results show that immediate corrective actions include the development of standard operating procedures (SOPs), routine socialization, daily briefings, improved lighting, and component replacement. Long- term solutions, such as adding conveyor belts and implementing preventive maintenance, could not yet be executed due to time and cost constraints. Implementation efforts focused on developing a Poka Yoke-based SOP at the packing station as a concrete step toward improving product quality.
STRATEGI PENURUNAN DOWNTIME DAN SETUP TIME PADA MESIN HEAT SEAL MENGGUNAKAN PENDEKATAN LEAN MAINTENANCE Michelle Roselyn Ong; Lithrone Laricha Salomon; Wilson Kosasih
Jurnal Mitra Teknik Industri Vol. 4 No. 3 (2025): Jurnal Mitra Teknik Industri
Publisher : Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/8wtj9758

Abstract

The automotive battery manufacturing industry faces challenges in the effectiveness of its machine maintenance systems, particularly in the heat seal machine, which recorded the highest downtime with a total of 12,722 minutes and 434 occurrences from April 2024 to March 2025. This study aims to identify waste in breakdown maintenance activites, analyze the root causes, and provide improvement recommendations based on lean maintenance, The method used is Maintenance Value Stream Mapping (MVSM) to identify value-added (VA) and non-value-added (NVA) activities, and to calculate maintenance efficiency using indicators such as MTTO, MTTR, MTTY, and MMLT. In addition, root cause analysis is conducted using the five whys method and data collection through observation, interviews, and focus group discussion (FGD). The results show that maintenance efficiency is only 32.97% with NVA activities dominating at 67.03%. The identified types of waste include waiting, motion, process, and defects. The proposed improvements include the implementation of floation technicians, addition of trolleys, digitalization of the maintenance system using a Computerized Maintenance Management System (CMMS), and placement of toolboxes and equipment trolleys on the production floor. The implementation of the future state map shows an increase in efficiency to 38.22% and a reduction of NVA activities to 61.78%. These results indicate that the lean maintenance approach through systems.
OPTIMASI KINERJA RANTAI PASOK PERUSAHAAN MAKANAN RAMEN X DENGAN PENDEKATAN HOR-MOORA Elena Cecilia Lam; Lithrone Salomon; Wilson Kosasih
Jurnal Mitra Teknik Industri Vol. 5 No. 1 (2026): Jurnal Mitra Teknik Industri
Publisher : Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jmti.v5i1.38718

Abstract

Ramen X is part of PT. XYZ that runs a restaurant business in the Food and Beverage sector. The food they sell can go bad quickly so there are a lot of risks involved in getting it from one place to another. If these risks are not managed properly, they can cause problems with the way the business runs and lead to losses. This study focuses on analyzing and mitigating supply chain risks in Ramen X using the SCOR 12.0 framework and an integrated HOR-MOORA approach. The study found that supply chain mapping using the SCOR 12.0 model identified 14 activities across the five main processes, plan, source, make, deliver, and return. From these activities, 22 risk events and 24 risk agents were identified throughout the supply chain. Furthermore, 14 priority risk agents were selected based on the ARP values in HOR phase 1 and 14 mitigation actions determined using the values in HOR phase 2. In addition, the MOORA analysis ranked these mitigation actions based on values, with PA9, PA2, PA5, PA13, PA1, PA4, PA7, PA12, PA3, PA8, PA14, PA6, PA11, and lastly PA10. Both HOR and MOORA consistently indicate that the top three mitigation actions are PA9, PA2, and PA5. Therefore, these three mitigation actions are recommended as the best strategies to handle Ramen X’ supply chain risk problems.
Co-Authors Adianto , Adianto Adianto . Adrian, Kevin Ahmad Ahmad . Ahmad Ahmad Ahmad Ahmad Ahmad Ahmad Ahmad Ahnad Ajipangestu, Mario Albert, Jonathan Alvan Prayogo Andres Andres Andres Andrian Andrian Andrian Andrian Angelo, William Calvin Santoso Chang, Michael Jordy Clayren Nathanniel Daniella, Edeline Vanessa Dian Retno Sari Dewi Dian Trihastuti Doaly, Carla Olivia Doaly, Carla Olyvia Eilen Celsia Elena Cecilia Lam Elisha Sanjaya Erickson . Eunike Hazael Faisal Mustaqim Florencia, Gabby Frans Jusuf Daywin Frans Jusuf Daywin Frans Jusuf Daywin Harnawan, Christianto Helena Juliana Kristina helena juliana kristina helena juliana kristina Hendrawan . I Wayan Sukania Ig. Jaka Mulyana Iphov Kumala Sriwana Iwan A Soenandi Iwan Aang Soenandi Joses Julius Juyanto, Jennifer Kevin Wiliam Kristina, Helena Juliana lamto widodo Lilyana Jap Lina Gozali Lithrone Laricha Lithrone Laricha Lithrone Laricha S Lithrone Laricha S Lithrone Laricha S. Lithrone Laricha Salomon Lithrone Laricha Salomon Lithrone Laricha Salomon Lithrone Laricha Salomon Lithrone Laricha Salomon Lithrone Laricha Salomon Lithrone Salomon Luh Juni Asrini M.Agung Saryatmo Marcella Darmawan Marsella Marsella Marsella Michelle Roselyn Ong Mohammad Agung Saryatmo Mutiara, Maitri Widya Nathaniel Nathaniel Ong, Michelle Roselyn Ongan, Freddy Bano Ricko Ricko Rico Adhesi Rizkika, Adelia Dwi Rumayar, Christania Putri S., Lithrone Laricha Salomon , Lithrone Laricha Salomon, Lihrone Laricha Sandrina, Laura Santoso, Elizabeth Clara Saputra, Natalia Lydia Saryatmo, Mohammad Agung Sauw Oscar Angkasa Sauw Oscar Angkasa Sherline Leonica Silvi Ariyanti Siti Rohana Nasution Sunantha, May Calysta Sylvia Tjhia, Andres Tjoe, Jerry Chandra Utama, Didi Widya Vera Veliria Vieren Yulies Triyani Vioren, Venny Wijaya, Leonardo Agusta Winda Jeania Purnama Winda Jeania Purnama Wirahata, Christie Yennie Salim Yoseph