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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 40 Documents
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A Backpropagation-Based Artificial Neural Network Model for Predicting Pharmaceutical Demand Muhtadin Akbar; Carlos Guterres; Ana de Araújo
Jurnal Riset Ilmu Teknik Vol. 3 No. 1 (2025): May
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v3i1.155

Abstract

Drug inventory management is a vital component of the healthcare system because it ensures the continuity of essential drug supply and pharmaceutical logistics efficiency. However, most pharmaceutical facilities still rely on manual forecasting methods based on historical trends that are linear in nature and unable to capture the nonlinear relationship between morbidity rates and drug demand. As a result, there is a mismatch between stock and actual demand, leading to shortages or surpluses and an increased risk of drug expiration. This study aims to develop an artificial neural network (ANN) model for predicting drug demand using a backpropagation algorithm to improve the accuracy of estimates and the effectiveness of stock planning. The data used included five years of drug usage records and the prevalence of the ten most common diseases in the Pharmacy Installation. The model was designed with a multilayer perceptron architecture (25–70–25–1) using a log-sigmoid activation function and a trainCGF training algorithm. The training results showed optimal performance with 94.2% accuracy, MSE 0.0135873, and MAPE 5.793%, accompanied by a strong correlation between the target and output (R = 0.99935). This demonstrates the model's ability to learn nonlinear patterns and produce stable and reliable predictions. The implementation of the JST model enables the optimization of drug distribution by reducing the risk of stockouts and overstocking, while also reducing waste due to expiration. This prediction system has the potential to become an adaptive and sustainable decision-making tool in public pharmaceutical supply chain management, in line with the principles of resource efficiency and sustainability of health services.
Evaluating Based E-Learning Platforms In Nigerian Higher Education: An SEM-PLS Analysis Based On The Delone And Mclean Model Ayotunde Alaba, Fadele; Nasiru Yakubu; Iwalewa Oluwajana, Dokun; Babafemi, Adetokunbo; Adewale, Oluchi
Jurnal Riset Ilmu Teknik Vol. 3 No. 1 (2025): May
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v3i1.152

Abstract

The Federal University of Technology Minna (FUT Minna) serves as the case study, representing a technology-focused institution facing post–COVID-19 challenges in digital education delivery. The research investigates how system quality, information quality, and service quality influence use, user satisfaction, and net benefits in an emerging economy context. A quantitative explanatory design was employed using Structural Equation Modeling–Partial Least Squares (SEM-PLS). Data were collected from 60 academic staff members through a structured questionnaire based on validated indicators of the DeLone and McLean model. The analysis was performed using SmartPLS 4.0, encompassing outer model validation (convergent validity, reliability) and inner model testing (path coefficients, R², f², and Q²). The results reveal that system quality and service quality significantly influence system use (t = 2.384, p = 0.018; t = 3.617, p = 0.000, respectively), while information quality exerts a weaker effect. User satisfaction emerged as a key mediator linking system quality to perceived net benefits (t = 3.124, p = 0.002). The model explained 26.8% of variance in use, 23.1% in user satisfaction, and 16.6% in net benefit, confirming moderate explanatory power. These findings highlight that e-learning success in Nigerian universities depends not only on technical reliability but also on continuous service responsiveness and user-centered support. The study suggests that higher education institutions in developing economies should prioritize improving system stability, standardizing instructional content, and strengthening technical support to enhance user satisfaction and learning outcomes. Institutional investment in digital literacy and feedback-driven service improvement can maximize the long-term benefits of e-learning systems. This study extends the application of the DeLone and McLean model to a Sub-Saharan African context, providing empirical evidence on e-learning adoption dynamics in resource-constrained environments. The integrated SEM-PLS approach offers a validated framework for assessing e-learning success and guiding strategic digital transformation in higher education.
Experimental Analysis of the Effect of Valve Clearance Variations on the Performance and Emissions of Suzuki G15A Gasoline Engines in the Philippines Mark Anthony Eduardo; Emilio Carlojay; Tonieli Jomaric; Angelo Ramirez
Jurnal Riset Ilmu Teknik Vol. 3 No. 1 (2025): May
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v3i1.162

Abstract

This study analyzes the effect of intake valve-clearance variation on the performance and exhaust-emission characteristics of the Suzuki G15A four-stroke gasoline engine, widely used in light commercial vehicles in the Philippines such as the Suzuki APV and Super Carry. The research was motivated by the country’s rising fuel consumption—about 31 million barrels per year—and the high contribution of gasoline vehicles, which account for around 70 % of CO emissions in Metro Manila. Experimental tests were performed using four valve-clearance settings (0.10, 0.15, 0.20, and 0.25 mm) under controlled tropical conditions (30 ± 2 °C, 80 % humidity) with Petron RON 91 fuel. The results show that increasing the valve clearance to 0.25 mm raised cylinder pressure from 13.9 to 14.9 kg/cm² and improved indicated power from 16.9 kW to 63.6 kW at engine speeds between 1000 and 3500 rpm. The Brake Specific Fuel Consumption (BSFC) decreased from 100.88 to 44 g/kWh, indicating higher combustion efficiency. Emission analysis revealed that a 0.15–0.20 mm clearance produced the best balance between power and low emissions: CO and HC levels decreased while CO₂ increased up to the optimum point at 2500–3000 rpm, reflecting more complete combustion. The study’s findings suggest that the 0.15–0.20 mm clearance range offers the optimal compromise between fuel economy, power output, and emission reduction. This research provides novel experimental evidence on the G15A engine under Philippine tropical conditions, and its outcomes can support the development of a national adaptive valve-clearance standard to promote energy efficiency and environmental sustainability in the country’s transportation sector.
Application Of Quality Function Deployment (QFD) Method In Developing Eco-Friendly Cup Holder Design Rani Azizi Alatas; Alesa Putri; Tono Subroto
Jurnal Riset Ilmu Teknik Vol. 3 No. 1 (2025): May
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v3i1.168

Abstract

The rapid growth of Indonesia’s food and beverage industry has increased the need for innovative and environmentally friendly packaging, especially for takeaway drinks. This study aims to develop a cup holder design to replace plastic bags by integrating customer needs using the Quality Function Deployment (QFD) method. QFD was chosen because it can translate the Voice of Customer (VoC) into measurable technical specifications through the House of Quality (HoQ) matrix. The research used a descriptive quantitative approach with 30 café customers selected through purposive sampling. Validity testing using the Pearson Product Moment showed that 11 out of 20 statements were valid (r > 0.36), and the reliability test achieved a Cronbach’s Alpha value of 0.870, indicating high consistency. The results of the VoC and HoQ analysis identified eleven important customer needs such as capacity, ease of use, material strength, design, and price efficiency. Three alternative cup holder designs were evaluated using the Pugh Matrix, and the best concept scored +4, featuring a kraft paper material with 300 gsm thickness, moisture resistance, ergonomic shape, and the ability to hold four cups while displaying café branding. This design improves customer comfort, strengthens brand image, and reduces plastic waste. The study demonstrates how QFD can effectively link customer preferences to engineering design, offering a practical example for small and medium cafés to develop sustainable packaging that supports both product functionality and environmental responsibility.
Fuel Distribution Route Optimization Model Based On Hybrid Cheapest Insertion–Tabu Search Akhrizal Awaludin; Nazaruddin, Nazaruddin
Jurnal Riset Ilmu Teknik Vol. 3 No. 1 (2025): May
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v3i1.175

Abstract

Purpose – This study aims to optimize the fuel distribution routes of PT Pertamina Patra Niaga Sei Siak by comparing the performance of the Cheapest Insertion Heuristic (CIH) and Tabu Search (TS) algorithms in minimizing total distance, travel time, and operational costs. Methodology– The research employs a quantitative–computational approach using operational data collected from real distribution activities in Pekanbaru, Riau Province. A Vehicle Routing Problem (VRP) model was developed with constraints on vehicle capacity, service time, and depot–station relations. CIH and TS algorithms were implemented using Python for comparative optimization. Validation was performed through correlation analysis between baseline and computational results. Findings – The results demonstrate that the Tabu Search algorithm significantly improved route efficiency, reducing total distance and travel time by 27.2% and 26.6% in Shift 2, and by 5.1% and 4.5% in Shift 1 compared to existing routes. The integration of CIH as an initial heuristic seed improved TS convergence stability, with optimal solutions achieved within the 13th iteration. Cost analysis indicates that the optimization yields daily savings of approximately IDR 119,600 per vehicle, leading to substantial monthly reductions in total logistics expenses. Practical Implications – The hybrid CIH–TS framework provides an adaptive and computationally efficient decision-support tool for PT Pertamina Patra Niaga to design shorter, faster, and more economical delivery routes. The approach is scalable and can be integrated into real-time routing systems to improve service reliability and operational sustainability. Originality– This study is among the first to apply a hybrid heuristic–metaheuristic approach to the Indonesian fuel-distribution industry using real operational data. The novelty lies in the empirical validation of algorithmic optimization within a live logistics network, demonstrating tangible economic and time-based efficiency improvements that support national energy-distribution reliability.
Strengthening Institutions and Governance in the Palm Oil Sector for Smallholder Empowerment: A Soft-Structural-Analytical Systems Model Valentina Febi Gurning; Yance Bernat; Gusman Adiyat; Viktor Kusri
Jurnal Riset Ilmu Teknik Vol. 3 No. 2 (2025): September
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v3i2.181

Abstract

This study formulates a model for strengthening the institutions of independent oil palm farmers in Kalimantan through a systemic and participatory approach. The weaknesses of independent oil palm farmers' institutions remain a major obstacle to increasing productivity, competitiveness, and the sustainability of farming businesses. This research method integrates Soft Systems Methodology (SSM), Interpretative Structural Modelling (ISM), and Analytical Hierarchy Process (AHP) to identify key elements, map structural relationships between variables, and determine institutional strengthening strategy priorities. The SSM results show that the root causes of institutional problems include low member participation, weak coordination between parties, and limited access to capital and information. The ISM analysis reveals that government support and farmers' willingness to change are the main driving elements, while professional human resource development and access to capital serve as connecting elements. Meanwhile, the AHP results show that developing partnerships among stakeholders (0.529) is the highest strategic priority, followed by improving organizational management (0.211) and enhancing training and mentoring (0.156). These findings emphasize the importance of synergy between the government, financial institutions, farmer associations, and palm oil companies in building strong, adaptive, and sustainable farmer institutions. Theoretically, this research contributes to the development of an integrated systems approach in strengthening agricultural institutions in Indonesia, particularly in the smallholder palm oil sub-sector.
Analysis of Prestress Loss and Structural Performance of Box-Type Prestressed Concrete Girders on the Cakung Flyover Aldo Dion Selvistre; Viona Yeni; Putut Keswardi
Jurnal Riset Ilmu Teknik Vol. 3 No. 2 (2025): September
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v3i2.187

Abstract

The increasing traffic congestion in East Jakarta, particularly at the Cakung intersection, prompted the construction of the Cakung Flyover, designed with a prestressed concrete box-girder system. However, field observations revealed several serviceability issues, including hairline cracks (0.10–0.28 mm), vertical deflections of 18–25 mm, and a 30.5 % reduction in effective prestress compared with theoretical design values. This research aimed to analyze prestress losses and their structural implications through an integrated analytical–empirical approach combining field measurements, theoretical modeling, and validation using SAP2000 and MATLAB simulations. The results showed that the box-girder section (A = 5.65 m², Wa = 5.43 m³, Wb = 2.76 m³) exhibited satisfactory flexural rigidity but experienced frictional losses at tendon angular deviations, particularly near anchorage zones. The tropical environment—average temperature 33 °C and relative humidity 85–90 %—accelerated creep, shrinkage, and relaxation in the 7-wire low-relaxation strands. Consequently, measured prestress losses were 1.3–1.6 times higher than those predicted by standard codes. This study confirms that tropical humidity significantly amplifies prestress degradation and highlights the need for climate-specific calibration of SNI 2847:2019 coefficients. The research contributes a calibrated correlation between tendon eccentricity (eₛ ≈ 1.195 m), deflection, and stress relaxation, enabling more accurate prediction and control of structural performance. The proposed framework provides practical guidelines for tendon configuration, prestress monitoring, and maintenance strategies for prestressed concrete flyovers in humid tropical regions such as Jakarta.
Sustainable Quality Transformation In Agro-Industrial Manufacturing: A Six Sigma–Kaizen Model For Thailand’s Crude Palm Oil Sector Saswattecha Nantakrit Yodpijit; Somjai Wangrakdiskul; Nattaya Charoensuk; Kanyarat Phromphat; Chalita Boonmee
Jurnal Riset Ilmu Teknik Vol. 3 No. 2 (2025): September
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v3i2.195

Abstract

This study enhances the process capability and sustainability of Thailand’s crude palm oil (CPO) production through the integration of Six Sigma DMAIC and Kaizen frameworks. Although Thailand ranks as the world’s third-largest palm oil producer, its CPO frequently fails to meet international standards due to excessive Free Fatty Acid (FFA) and moisture content. To address these persistent inefficiencies, a quantitative–descriptive approach was applied to a Krabi Province mill using 30 days of operational data. The DMAIC methodology systematically identified root causes—unstable sterilization temperature, pressing delays, and inadequate vacuum maintenance—while Kaizen interventions reinforced operator discipline and preventive control. Post-intervention analysis revealed a 19% reduction in FFA, a 36% decrease in moisture, and a 53% reduction in defect rate, accompanied by a rise in process capability index (Cp) from 0.78 to 1.24 and an improvement in sigma level from 4.09 to 4.5. Benchmarking confirmed that Thailand’s performance now closely approaches Malaysia’s automation-led systems while surpassing Indonesia in consistency and energy efficiency. The findings demonstrate that sustainable process improvement can be achieved through data-driven analysis and human-centered Kaizen culture, even in semi-automated contexts. This hybrid model supports compliance with RSPO, ISO 22000, and Bio-Circular-Green (BCG) frameworks while reducing operational waste and cost. The originality of this research lies in establishing an empirically validated Six Sigma–Kaizen hybrid applicable to ASEAN agro-industries, bridging the gap between technological advancement and behavioral quality systems toward globally competitive CPO production.
Hybrid Fuzzy–Eckenrode Model for Quantitative Evaluation of Fermented Cocoa Bean Quality in Ivory Coast Koffi Ahua René; Wim Pelupessy; Cusi Obediencia
Jurnal Riset Ilmu Teknik Vol. 3 No. 2 (2025): September
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v3i2.200

Abstract

This study aims to develop a quantitative decision-support model for assessing the quality of fermented cocoa beans in Ivory Coast, addressing the persistent inconsistency in cocoa bean quality that undermines international competitiveness. Despite being the world’s largest cocoa producer, Ivory Coast experiences frequent quality downgrades due to weak fermentation control and limited data-driven evaluation frameworks. A descriptive–analytical quantitative approach was employed, integrating the Eckenrode and Fuzzy Eckenrode methods to transform expert judgment into measurable weights for key cocoa quality attributes—namely fat content, acidity (pH), moisture, aroma, and bitterness. Field data were collected from three major cocoa-producing regions (Yamoussoukro, Daloa, and San-Pédro) through expert evaluations and sensory analyses. The hybrid fuzzy logic model was used to enhance precision in ranking attribute importance under uncertain assessments. Results revealed that fat content (0.103), pH acidity (0.092–0.106), and moisture content (0.078–0.089) are the most influential quality determinants. Cocoa Type C exhibited the most balanced fermentation and post-harvest consistency, achieving a total attribute dispersion (ΣB = 0.139) that aligns with premium-grade standards. The fuzzy hybrid model successfully reduced subjective variability and improved ranking stability compared to classical MCDM methods. This study pioneers the application of Fuzzy Eckenrode in cocoa quality evaluation within the African agroindustrial context. By linking physicochemical and sensory parameters through quantitative weighting, it provides a replicable decision-support tool that bridges traditional post-harvest practices with data-driven quality management for sustainable cocoa competitiveness in Ivory Coast.
A Hybrid Exponential Smoothing–DRP– Framework for Sustainable Distribution Optimization in a Traditional Food Rengginang Qurratu Ainun; Ferry Irawan Sutisna; Leny Andini; Irma Kinari
Jurnal Riset Ilmu Teknik Vol. 3 No. 2 (2025): September
Publisher : Lembaga Penelitian dan Ilmu Pengetahuan JEPIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59976/jurit.v3i2.204

Abstract

Purpose: Distribution Requirement Planning (DRP), and route optimization using the Saving Matrix method. The goal is to enhance inventory accuracy, minimize logistics costs, and improve delivery efficiency under fluctuating market demand. Methodology: A quantitative–descriptive analysis was conducted using primary data (field observation and interviews) and secondary data (production and sales records). Weekly demand forecasting was performed using the Exponential Smoothing method with α = 0.9, evaluated through Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE). The DRP model was used to determine gross and net requirements, while the Saving Matrix method was applied to design optimal delivery routes. Findings: The Exponential Smoothing model achieved a high predictive accuracy (MAPE = 10.33%), showing reliable short-term forecasting for MSMEs. DRP implementation with a one-week lead time and a 168-unit safety stock successfully balanced production capacity and customer demand. Integration of DRP and Saving Matrix resulted in approximately 30% reduction in total logistics cost and significant improvement in stock availability. Compared to 17 related studies (2021–2024), this hybrid model demonstrated superior efficiency and cost stability within traditional food industries. Practical Implications: The results provide MSMEs with a data-driven framework to synchronize production, inventory, and distribution planning, reducing decision-making errors and improving operational sustainability. The proposed model can serve as a replicable reference for traditional food SMEs facing fluctuating demand conditions. Value: The novelty of this study lies in combining Exponential Smoothing forecasting, DRP scheduling, and Saving Matrix routing into a unified optimization framework—rarely applied in Indonesia’s traditional food sectors. This integrative method strengthens both academic insight and managerial practice in MSME supply chain efficiency.

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