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All Journal Prosiding SNATIF JURNAL REKAYASA SISTEM INDUSTRI Jurnal Tecnoscienza G-Tech : Jurnal Teknologi Terapan Jurnal Teknik Industri Terintegrasi (JUTIN) INTERNATIONAL JOURNAL OF EDUCATION, INFORMATION TECHNOLOGY, AND OTHERS Nawadeepa: Jurnal Pengabdian Masyarakat
Kusuma, Harun Indra
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Analisis Optimalisasi Waktu Proses Kerja pada Divisi Welding Menggunakan Metode Jalur Kritis Mayrosa, Indila; Kusuma, Harun Indra; Rahmawati, Dewi; Rizki, Yulizan
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 9 No. 1 (2026): January
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v9i1.52633

Abstract

This study aims to analyze the optimization of work process time in the welding division using the Critical Path Method (CPM). This method is used to identify the critical path and calculate the slack variable for each production activity. The data used are the sequence of activities, dependency relationships, and production process time in 2024. The analysis process is carried out through the preparation of a network diagram, forward pass and backward pass calculations, and determining the slack value. The results show that the critical path is found in the series of activities A–B–C–D–E–F–G–H with a total duration of 17 minutes. All activities have a slack value of 0, so any delay has the potential to delay the entire process. These findings confirm that the production process in the welding division has been running optimally. The company is advised to maintain the existing work pattern and ensure the appropriate duration of each activity to maintain production efficiency. 
Analisis Situation Awareness Pengendara Sepeda Motor Berdasarkan Usia, Pengalaman Berkendara, dan Kondisi Waktu Menggunakan Situation Present Assessment Method (SPAM) Pramudita, Rahmad Hendri; Kusuma, Harun Indra; Sutantio, Erian
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 9 No. 1 (2026): January
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v9i1.53508

Abstract

Traffic accidents remain a global challenge, with WHO reporting high mortality rates among individuals aged 5–29 years. In Indonesia, accident trends also show a consistent increase, with an average rise of 6.90% per year from 2019 to 2023, predominantly involving motorcycle riders. This condition highlights the importance of cognitive factors, situation awareness (SA), which plays a role in recognizing, understanding, and predicting events while riding. This study aims to investigate the SA levels of motorcycle riders based on riding experience, age, and time of day using Situation Present Assessment Method (SPAM). This study involves laboratory research and uses primary data in quantitative. The findings indicate that younger and less experienced riders exhibit lower SA levels, and that SA performance at night is lower than in the morning. These results recommend the need for safety training programs that focus on SA development, the preparation of simulation-based educational modules, and the establishment of minimum SA standards for obtaining a driving license.
Application of Holt’s Double Exponential Smoothing for Electrical Energy Demand Forecasting in an Assembly and Welding Manufacturing Facility Harun Indra Kusuma; Yulizan Rizki; Bambang Darmono; Liza Mahera; Dita Aulia; Muhammad Tegar Irsyadi; Muhammad Zeinny Hasbunallah Sasmita; Ruli Haris; Femy Novalia
G-Tech: Jurnal Teknologi Terapan Vol 10 No 2 (2026): G-Tech, Vol. 10 No. 2 April 2026
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v10i2.9456

Abstract

This study aims to accurately forecast short-term electrical energy demand in a Jabodetabek industrial facility to support sustainable manufacturing and precise utility management. To address the highly dynamic and non-stationary nature of energy consumption, this research applied Holt’s Double Exponential Smoothing method. A 24-month historical dataset, spanning from January 2024 to December 2025, was analyzed to generate a six-month operational projection. Model performance was rigorously evaluated using Mean Absolute Deviation (MAD), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE). The forecasting demonstrated outstanding predictive accuracy, yielding a MAPE of 1.26%, a MAD of 20,79, and an MSE of 690.40. The projection indicates a consistent linear escalation, with energy demand expected to reach 2.020,72 MWh by mid-2026.These findings confirm that Holt’s algorithm effectively captures underlying linear trends without seasonal behaviors. Integrating this precise mathematical model into standard procedures provides crucial early warning signals for capacity planning, mitigates utility shortages, and strongly supports the strategic mandate of green operations.
Co-Authors Ahmad Faisal Ridho alfikri, m reza Aulia, Dita Bambang Darmono Dewi Rahmawati Dita Aulia Femy Novalia Hadi Purnomo Irsyadi, Muhammad Tegar Liza Mahera Mardhika, Dimas Ayu Mariyatul Qibtiyah Mayrosa, Indila Muhammad Miftahul Abid Muhammad Tegar Irsyadi Muhammad Zeinny, Muhammad Zeinny Hasbunallah Sasmita Muhammad, Katon Novalia, Femy Pramudita, Rahmad Hendri Rani Aulia Imran Rizki, Yulizan Ruli Haris Sutantio, Erian Ulfia, Yessi Nasia Wardani, Ega Yulizan Rizki