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INDONESIA
Jurnal Riset Ilmu Teknik
Published by Lembaga Penelitian dan Ilmu Pengetahuan JEPIP
ISSN : 29877261     EISSN : 29877253     DOI : 10.59976
Core Subject : Engineering,
Engineering
Jurnal Riset Ilmu Teknik is a peer-reviewed journal, Jurnal Riset Ilmu Teknik is published three times annually, in May, August and December. Jurnal Riset Ilmu Teknik provides a place for academics, researchers, and practitioners to publish scientific articles. The scope of the articles listed in this journal is related to various topics such as Industrial Engineering, Informatics Engineering, Civil Engineering, Electrical Engineering, Architecture, Mechanical Engineering, Engineering Education, and other related engineering fields.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 2 No. 3 (2024): December" : 5 Documents clear
Backpropagation Neural Network Model for Predicting Spare Parts Demand Under Dynamic Industrial Conditions Devi Puspitata Sari; Lei Hou; Zong Woo Geem
Jurnal Riset Ilmu Teknik Vol. 2 No. 3 (2024): December
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v2i3.124

Abstract

Purpose – This study aims to analyze and control spare parts inventory in pumping units at PT. XYZ using the Artificial Neural Network (ANN) method. The research addresses the challenges of surplus and shortage of spare parts, which directly affect operational continuity, production costs, and company performance. Design– A qualitative approach combined with quantitative modeling was employed. Data were collected through observation, the dataset was normalized and divided into three training-testing scenarios (70:30, 80:20, and 90:10). The ANN model with backpropagation was developed and tested using Matlab software, with accuracy evaluated through Mean Squared Error (MSE) and correlation coefficient (R). Findings – The results show that Scenario 2 (80% training and 20% testing data) provides the best balance, yielding the highest accuracy. The ANN model captured nonlinear inventory patterns, achieving very low MSE (3.1358e-12) and demonstrating predictive reliability. However, the overall correlation (R = 0.6015) indicates the need for larger datasets and model refinement to improve generalization. Practical implications – Applying ANN in inventory management helps companies minimize risks of overstock and shortages, reduce storage costs, and support reliable production planning. This contributes to supply chain resilience and enhances customer trust in operational performance. Originality – This study presents one of the first applications of ANN for spare parts inventory prediction in Indonesia’s pumping unit sector. The findings provide empirical evidence of ANN’s effectiveness and offer theoretical as well as practical contributions to the advancement of AI-based inventory management in industrial contexts.
Systematic Diagnosis of Quality Defects in Concrete Electricity Poles Through The New Seven Tools Ikrimah Hilal; Emmy Liona; Dito Ranova
Jurnal Riset Ilmu Teknik Vol. 2 No. 3 (2024): December
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v2i3.130

Abstract

This study investigates the root causes of quality defects in concrete electrical poles produced by PT. LMN using the New Seven Tools (NST) approach. The research employs a qualitative–descriptive case study to systematically identify, categorize, and analyze defect patterns arising from human, machine, method, material, and environmental factors. Data were obtained through field observation, interviews, and documentation, then processed using the NST framework comprising Affinity Diagram, Interrelationship Diagram, Tree Diagram, Matrix Diagram, Activity Network Diagram, and Process Decision Program Chart (PDPC). The findings indicate that lack of routine supervision and insufficient machine maintenance are the dominant causal factors driving product defects, with the Man and Machine categories scoring the highest in the Matrix analysis (18 and 17, respectively). Corrective actions prioritized include implementing regular inspection schedules, preventive maintenance programs, and environmental standardization to improve workflow efficiency and reduce defect rates. Furthermore, the Activity Network analysis identifies the evaporation process as the critical path contributing to extended production time, while PDPC results underscore the importance of balancing technical feasibility with cost-effective corrective strategies. The study concludes that the integration of human resource development, process standardization, and preventive maintenance can significantly enhance product reliability and align production performance with zero-defect manufacturing principles. This research provides both theoretical and practical contributions by validating the applicability of the New Seven Tools method for comprehensive quality improvement in the Indonesian manufacturing sector.
A Taguchi-Based Framework for Continuous Quality Improvement in Crude Palm Oil Production Tengku Khoirunnisa; Chellcia Mutiara Iwfanka; Melkisedek Gumi
Jurnal Riset Ilmu Teknik Vol. 2 No. 3 (2024): December
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v2i3.134

Abstract

Purpose – This study aims to analyze and optimize the quality of Crude Palm Oil (CPO) using the Taguchi method. The research focuses on identifying the dominant factors affecting Free Fatty Acid (FFA), moisture, and impurity content, as well as determining the optimal parameter combination to achieve consistent product quality that meets company standards. Design/methodology/approach – The study employed an experimental design based on the Taguchi method using an orthogonal array with seven factors at two levels. Data were collected from laboratory tests on CPO samples during production, focusing on FFA, moisture, and impurities. Statistical analyses included the Signal-to-Noise Ratio (S/N), Analysis of Variance (ANOVA), and confidence interval validation to identify significant factors and optimal operating conditions. Findings – The results show that factors A (fresh fruit bunch maturity) and F (sterilizer process conditions) significantly influence CPO quality, as indicated by the highest F-ratios (4.64 and 4.86) and contribution values exceeding 15%. The optimal parameter combination successfully minimized variability in FFA and impurity levels, though overall results still slightly exceeded company standards, suggesting the need for stricter control of raw material selection and processing parameters. Confidence interval analysis confirmed that the predicted mean values for FFA, moisture, and impurities were close to the specification limits, indicating potential for further refinement. Originality– This study provides empirical evidence of the Taguchi method’s applicability in the palm oil industry, particularly for improving CPO quality under real industrial constraints. The novelty lies in integrating Taguchi analysis with confidence interval verification to assess compliance robustness, offering a structured framework for continuous process improvement in CPO manufacturing.
Forecasting–Inventory Optimization Model: Integrating Exponential Smoothing with Min–Max and Blanket Order Systems For SMEs Vivi Zibade Mutiara; Erik Halomoan Syah
Jurnal Riset Ilmu Teknik Vol. 2 No. 3 (2024): December
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v2i3.140

Abstract

Purpose –The research integrates demand forecasting using the Exponential Smoothing (ES) method to develop an adaptive and data-driven framework for cost optimization in volatile demand conditions. Methodology – A quantitative–descriptive and analytical approach was adopted by combining forecasting accuracy analysis with cost comparison modeling. Two forecasting models—Moving Average (MA) and Exponential Smoothing (ES)—were tested using 2021–2023 demand data. The most accurate model (lowest MAPE) was used to simulate inventory performance through the Min–Max and Blanket Order systems. Sensitivity analysis with ±10% demand variation was conducted to evaluate model robustness, while correlation testing validated forecast accuracy against actual demand. Findings – The Exponential Smoothing model achieved superior predictive accuracy (MAPE = 0.883%) compared with the Moving Average model (MAPE = 1.338%). The Min–Max Stock system produced lower total costs—IDR 116,269,920 (2021), IDR 123,260,400 (2022), and IDR 128,466,720 (2023)—compared with the Blanket Order system, which recorded higher and more volatile costs across the same period. The hybrid Min–Max–Forecasting approach demonstrated higher stability under demand fluctuations and improved procurement efficiency, achieving an estimated 30% cost reduction. Practical implications – This study offers SMEs an evidence-based strategy for integrating forecasting accuracy into inventory control, supporting cost reduction and production continuity in resource-constrained environments. The model can be adopted as a reference for developing adaptive inventory policies within the Indonesian SME food sector. Originality– The originality of this study lies in its hybrid integration of Exponential Smoothing forecasting within comparative Min–Max and Blanket Order frameworks, offering empirical validation for forecasting-driven inventory decisions at the SME scale. The approach provides both theoretical advancement and managerial relevance by aligning predictive accuracy with inventory cost optimization in volatile market contexts.
Sustainable GSM-Based Remote Switching System Using Conventional Mobile Phones Without Microcontroller for Low-Cost Automation Applications Ahmad Saddam Habibullah; Sutan Ali Sianipar
Jurnal Riset Ilmu Teknik Vol. 2 No. 3 (2024): December
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v2i3.145

Abstract

The development of telecommunications-based control systems has become an alternative solution in home automation and small industries, especially in areas with limited internet access. This study aims to design and test a telephone-based electrical equipment control module that utilizes conventional mobile phones as an activation medium without the aid of a microcontroller. This system consists of a tuner block, a three-stage Darlington amplifier, a Schmitt Trigger with an optocoupler, a 555 IC multivibrator, and a relay as the main actuator. Test results show that the power supply circuit is capable of maintaining voltage stability of ±0.1 V on the 5V and 9V lines, while the tuner successfully detects electromagnetic signals with a fairly stable output voltage of 0.05–0.98 V to trigger the signal amplifier. The multivibrator circuit showed a consistent flip-flop response to logic pulses from the tuner, while the relay was able to operate mechanically in two stable conditions (ON/OFF). These findings show that analog signals from mobile phones can be effectively integrated with pure electronic circuits to produce a reliable, cost-effective, and environmentally friendly remote control system. The advantage of this research lies in the approach of reusing low-end GSM technology for internet-free automation that supports the principles of circular economy and electronic waste reduction.

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