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International Journal Science and Technology (IJST)
Published by Asosiasi Dosen Muda Indonesia
ISSN : 28287223     EISSN : 28287045     DOI : https://doi.org/10.56127/ijst.v1i2
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
International Journal Science and Technology (IJST) is a scientific journal that presents original articles about research knowledge and information or the latest research and development applications in the field of technology. The scope of the IJST Journal covers the fields of Informatics, Mechanical Engineering, Electrical Engineering, Information Systems and Industrial Engineering. This journal is a means of publication and a place to share research and development work in the field of technology.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 12 Documents
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Search results for , issue "Vol. 4 No. 3 (2025): November: International Journal Science and Technology" : 12 Documents clear
Artificial Intelligence–Based Load Classification and Imbalance Detection Using Vibration Signals in Drum-Type Washing Machines Michael J. Carter; Emily R. Dawson; Liam P. O’Connor
International Journal Science and Technology Vol. 4 No. 3 (2025): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v3i2.1479

Abstract

Vibration and noise in drum-type washing machines are primarily driven by load variability and mass imbalance, which can amplify resonance response, reduce user comfort, and accelerate component wear. Reliable state recognition from vibration signals is therefore essential to enable adaptive operational strategies and safer spin-up behavior. Objective: This study aims to develop a physically grounded AI-ready framework for load classification (empty/dry/wet) and imbalance-risk detection using vibration measurements, so that operational states can be inferred and mapped into vibration-mitigation decisions. Methodology: The research used a quantitative experimental design with controlled operating conditions (empty, 2 kg dry, 4 kg wet) and two damper configurations (OEM and high-damper). Vibration responses were characterized using free-decay and FRF-based identification, producing parameters such as effective mass, natural frequency, damping ratio, stiffness, damping coefficient, and peak transmissibility. These parameters were then organized into an AI-ready label structure to support supervised and semi-supervised learning pipelines. Findings: The results show a clear mechanical signature for load separability, with natural frequency decreasing monotonically as load increases (2.95 Hz → 2.77 Hz → 2.63 Hz). Under the same wet load, the high-damper configuration substantially increased the damping coefficient (190 → 235 N·s/m) and reduced peak transmissibility (2.00 → 1.45), indicating a strong reduction in resonance amplification and transmitted vibration. Implications: The findings support the use of vibration-based state recognition as an input to adaptive spin control, enabling conservative decision rules to minimize resonance dwell and reduce vibration transmission without requiring major suspension redesign. The framework also facilitates scalable model development when labeled data are limited by leveraging physically interpretable anchors for validation. Originality: This study contributes a novel integration of repeatable vibration identification (free-decay/FRF/spin-up) with an AI-ready state and labeling framework for load classification and imbalance-risk inference, providing an interpretable bridge between vibration physics and supervised/semi-supervised learning for engineering deployment.
Predicting Defensive Formation Effectiveness in Football Using Random Forest and LSTM Models Nurdiyanto Yusuf
International Journal Science and Technology Vol. 4 No. 3 (2025): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v4i3.2271

Abstract

Defensive strategies are fundamental to football success, yet the evaluation of formation effectiveness often remains subjective. This study proposes a data-driven approach to predict the most effective defensive formations by integrating machine learning models. Using tracking-derived features from 150 professional European matches (2018–2023), Random Forest (RF) and Long Short-Term Memory (LSTM) models were applied to assess defensive outcomes. The results indicate that the 5-3-2 formation consistently achieved the highest predicted defensive success across direct, wing, and central attacks, followed by 4-4-2, while the 4-3-3 formation exhibited the weakest defensive stability. RF identified key static features such as line height, block width, and compactness, while LSTM captured temporal dynamics of coordinated player movements, yielding superior predictive performance. This study concludes that combining interpretable ensemble models with sequence-based neural networks offers a robust framework for tactical analysis. The findings provide actionable insights for coaches and analysts, supporting evidence-based decision-making in optimizing defensive strategies in modern football.
Comparative Analysis of the RAB for the Kampi Sunter Hotel Development Project Structural Work Package between AHSP 2024 and AHSP 2025 Afif Budi Santoso; Yuliyanti, Ervina
International Journal Science and Technology Vol. 4 No. 3 (2025): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v4i3.2290

Abstract

the dynamics of the building materials market and labor costs. Therefore, a constantly updated reference is needed to ensure accurate and efficient project cost estimates. One such reference is the Work Unit Price Analysis (AHSP) which is released by the government periodically. This study aims to analyze and compare the Cost Budget Plan (RAB) value for structural work on the Kampi Sunter Hotel construction project based on the Work Unit Price Analysis (AHSP) versions 2024 and 2025. The method used is a quantitative approach through cost estimation calculations using both versions of the AHSP. The results show that the total cost of structural work based on the 2024 AHSP is Rp15,384,577,550, while based on the 2025 AHSP it is Rp13,830,592,539. There is a difference of Rp1,553,985,011 or a decrease of approximately 10.1% in the 2025 AHSP. This decrease is caused by changes in the unit price of materials, one of which is the price of Ready Mix Concrete K300 which decreased from Rp1,048,722.00 (2024) to Rp931,683.00 (2025). Therefore, it is important for project planners to always update the AHSP reference used to match the applicable year to be more relevant.
Effects of Fuel Injector Seat Angle on Power, Torque, and Exhaust Emissions of a Single-Cylinder Four-Stroke Engine Surjadi, Eko; Wijoyo, Wijoyo; Septiawan, Diama Rizky
International Journal Science and Technology Vol. 4 No. 3 (2025): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v4i3.2347

Abstract

This study aims to examine the relationship and comparison of motor performance based on different fuel injector angles in a fuel injection system, and to identify the optimal injector angle for improved engine performance. Fuel injection is a control technology that regulates the air–fuel mixture entering the combustion chamber with speed, precision, and proportional balance. An experimental method was employed using a 2020 motorcycle with a 108 cc engine. The tests conducted included torque, power, and exhaust emission measurements. Torque and power were measured using a dynamometer, while exhaust emissions were analyzed with a gas analyzer. The study compared injector mounting angles of 60°, 70°, and 80°. Results showed that torque increased significantly from low engine speeds (around 3000 rpm) and peaked between 3500–3750 rpm before gradually declining. Among the tested angles, the 80° injector position produced the highest torque across most speed ranges, reaching approximately 15 Nm at 3500 rpm. The 70° angle yielded moderate performance, while the 60° angle demonstrated the lowest torque, especially at medium to high speeds. Overall, the study found that increasing the injector angle enhances torque and power output, with average increases of 6.1% in power and 6.4% in torque.
Computational Analysis of Bioethanol Production from Arenga Pinnata Sap using Rice Husk Biomass Heating: Statistical Modeling of Fermentation Time Effects on Alcohol Yield Saroinsong, Tineke; Mekel, Alfred Noufie; Motulo, Firmansyah Reskal
International Journal Science and Technology Vol. 4 No. 3 (2025): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v4i3.2348

Abstract

This study presents a comprehensive computational analysis of sustainable bioethanol production from Arenga pinnata sap using rice husk biomass as a renewable heating source. The research investigated fermentation time effects on alcohol yield through systematic experimentation and Python-based statistical modeling across four conditions: fresh sap, 1-day, 3-day, and 18-day fermentation periods. Distillation processes utilized 8.5 kg rice husk biomass at 80°C for 1.42 hours, producing 600 ml bioethanol per batch. Statistical analysis revealed a highly significant inverse correlation (r = -0.965, p < 0.05) between fermentation duration and alcohol content. Fresh palm sap yielded optimal alcohol concentration of 39.67 ± 7.76%, while 18-day fermentation reduced yield to 2.50 ± 2.50%, representing 93.7% decrease. The exponential decay model (R² = 0.984) demonstrated superior predictive accuracy compared to linear regression. The integrated system achieved 70.6 ml bioethanol per kg rice husk with positive energy balance (1.23 MJ output per MJ input), confirming commercial viability for rural renewable energy applications. This computational framework establishes optimal processing parameters for agricultural waste-powered biofuel systems, supporting circular economy principles and rural energy independence through effective biomass utilization in tropical regions.
The Effect of Temperature Variations on Sheet Press Machines on the Hardness and Toughness of PP (Polypropylene) and HDPE (High Density Polyethylene) Materials Slat, Winda Sanni; Runtuwene, Steven Johny; Djefry Hosang; Agnes Wakkary; Yenni Sigalingging
International Journal Science and Technology Vol. 4 No. 3 (2025): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v4i3.2376

Abstract

Global plastic waste continues to grow, making recycling essential for supporting a circular economy. Process parameters, especially heating temperature during sheet pressing, strongly influence the quality of recycled products. Objective: This study investigates how heating temperature affects the impact toughness and hardness of recycled Polypropylene (PP) and High-Density Polyethylene (HDPE) produced using a sheet press machine, and identifies the optimal processing temperature for improved mechanical performance. Methodology: This research used a quantitative experimental approach. Recycled PP and HDPE were shredded, then heated at 160°C, 170°C, 180°C, and 190°C for 120 minutes, and molded into sheet specimens using a sheet press machine. Mechanical properties were evaluated using Charpy impact testing in accordance with ASTM D6110 and Rockwell hardness testing (M scale) following ASTM D785. Results were compared across temperature variations to determine performance trends. Findings: Both materials showed improved impact toughness and hardness as temperature increased up to 180°C, indicating better melt uniformity, fewer voids, and stronger molecular bonding. For HDPE, impact toughness increased from 2.3 J at 160°C to 8.675 J at 170°C, reaching its peak at 180°C, then decreased at 190°C, suggesting early thermal degradation. For PP, the highest average hardness was 15.52 HRM at 180°C, followed by a decline at 190°C, consistent with structural softening and reduced crystallinity. Implications: The results suggest that controlling heating temperature particularly around 180°C can enhance the manufacturing efficiency and product quality of recycled plastic sheets, supporting more reliable and sustainable material utilization. Originality: This study provides practical evidence on the temperature–property relationship for sheet-pressed recycled PP and HDPE under controlled heating conditions and confirms 180°C as an optimal temperature before thermal damage reduces structural integrity.
Earned Value Analysis on the Tayan Bulking Station Project in East Kalimantan Yohanes Godman Ora Etlatius Woda Sidi; Triana, Masca
International Journal Science and Technology Vol. 4 No. 3 (2025): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v4i3.2377

Abstract

This study aims to analyze the cost and schedule performance and to estimate the final cost and completion time of the Tayan Bulking Station Project in West Kalimantan. The method used is Earned Value Analysis (EVA) by analyzing three main parameters: Budgeted Cost of Work Scheduled (BCWS), Budgeted Cost of Work Performed (BCWP), and Actual Cost of Work Performed (ACWP). Secondary data was obtained from PT. Sarana Remaja Mandiri, including the budget plan, S-curves, and weekly progress reports up to the 23rd week. The analysis continued by calculating variances (SV, CV), performance indices (SPI, CPI), and final estimates (EAC, ETC, ETS, EAS). The results indicate that the project's cost performance fluctuated. In the early project stages (weeks 1-9), there was a cost overrun (CPI < 1). However, in the subsequent period (weeks 10-23), cost performance improved significantly with cost efficiency (CPI > 1, reaching 2.35). Overall, the estimated final cost (EAC) is IDR 34.99 billion, which aligns with the initial budget (BAC). On the other hand, schedule performance tended to be delayed (SPI < 1) for most of the observation periods (weeks 1-14 & 18-23), although there was acceleration in weeks 15-17. The estimated project completion time (EAS) is 35 weeks, indicating a 1-week delay from the planned schedule of 34 weeks. The Earned Value method proved effective in identifying project performance. It is concluded that the Tayan Bulking Station Project is efficient in terms of cost but inefficient in terms of time, with a final delay of one week. This study recommends a greater focus on schedule control and improvement for this project and similar future projects.
Analysis of Material Inventory Control Management for Structural Works using Economic Order Quantity, Reorder Point, and Safety Stock Methods in a 2.5-Storey Boarding House Construction Project Kurniawan, Wyldan Candra; Triana, Masca Indra
International Journal Science and Technology Vol. 4 No. 3 (2025): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v4i3.2381

Abstract

This study presents a comprehensive computational analysis of material inventory control management for structural works in a 2.5-storey boarding house construction project located in Jelambar, West Jakarta. The research utilizes the integrated Economic Order Quantity (EOQ), Safety Stock (SS), and Reorder Point (ROP) methods to determine optimal order quantities, safety buffers, and ordering trigger points for key structural materials. The study adopts a quantitative descriptive approach with a case study method. Data was collected through interviews, site observation, and analysis of secondary documents, including the Bill of Quantities (BoQ) and the time schedule (S-curve). The analysis focused on seven major materials, including cement, reinforcing steel (D13 and Ø8), and Class III timber. The calculated EOQ values, which minimize the sum of ordering and holding costs, showed that the project should order, for example, 271 sacks of cement, 85 bars of D13 steel, and 586 pieces of Class III timber. Corresponding Safety Stock levels were calculated using a 95% service level , resulting in a required buffer of 95 sacks of cement and 113 bars of D13 steel. The Reorder Point (ROP) values indicate when a new order should be placed, such as 313 sacks of cement and 400 bars of D13 steel. A cost comparison demonstrated that the project's initial total inventory cost was IDR 20,005,302. Applying the EOQ-only policy resulted in a cost efficiency of 34.88%. Crucially, the combined implementation of the EOQ, Safety Stock, and Reorder Point policy led to a significant reduction in total inventory costs to IDR 9,750,733, achieving a cost efficiency of 51.26% compared to the initial condition. This confirms that the integrated quantitative approach is highly effective for optimizing material ordering, mitigating stock-out risk, and substantially reducing inventory costs in small-to-medium scale urban construction projects with site constraints.
Computer Vision-Based Automated Waste Sorting System for Plastic and Organic Waste Classification Using Color and Shape Features Rick Resa Wahani; Michael Edward G. Kimbal; Deko Trio Desembara; Leonardo Frando Pasla; Motulo, Firmansyah Reskal
International Journal Science and Technology Vol. 4 No. 3 (2025): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v4i3.2384

Abstract

The increasing volume of municipal solid waste demands low-cost, real-time sorting solutions to improve recycling efficiency and reduce landfill burden. Objective: This study develops and evaluates a low-cost, real-time computer vision system to classify plastic waste and organic leaf waste for automated sorting. Methodology: The system uses a standard RGB camera (640×480, 30 fps) and OpenCV-based processing, including Gaussian blurring, HSV color-space conversion, morphological operations, contour detection, and geometric feature extraction (circularity, solidity, aspect ratio, and extent). Classification is performed using a hierarchical rule-based logic that combines HSV color masks with a proposed overlap ratio to quantify the spatial correspondence between object contours and leaf-color regions. Findings: Experimental testing under controlled illumination (500–1000 lux) achieved 89% overall accuracy with an average processing time of 45 ms/frame and an operational throughput of approximately 7 objects/min. The system correctly classified 8 plastic items and 7 leaf samples in the initial test set. Implications: The proposed approach supports practical deployment in small-scale or resource-constrained waste management facilities by enabling real-time sorting without large, labeled datasets or GPU hardware. Originality: This work introduces an interpretable hybrid decision framework that integrates a mask-based overlap ratio with multiple geometric shape descriptors, improving discrimination between plastic and leaf waste while maintaining computational efficiency.
Intelligent Robotic Arm Control System with Adaptive Learning Algorithm Based on Motion Pattern Recognition Excellsdeo Ndahawali; Jonah Mekel; Jaqlin Tamaka; GheridsDipipi, GheridsDipipi; Rick Resa Wahani; Michael Edward G. Kimbal; Deko Trio Desembara; Motulo, Firmansyah Reskal
International Journal Science and Technology Vol. 4 No. 3 (2025): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v4i3.2386

Abstract

Robotic-arm deployment beyond specialized facilities is often constrained by time-intensive programming and the need for expert operators, while gesture-based control can lose reliability due to sensor noise, drift, and inter-user variability. Objective: This study develops a low-cost, embedded robotic arm control system that learns from human demonstrations. Methodology: A quantitative experimental prototyping approach was used by building a 3-DOF robotic arm with an MPU6050 IMU and an Arduino Mega 2560. Multi-user gesture trials were collected, and system performance was analyzed through end-to-end evaluation of recognition accuracy, response time, learning efficiency, and motion replication error. Findings: The system achieved 85% gesture recognition accuracy, a 195 ms average response time, and a 4.2° mean absolute joint-angle error (SD = 2.1°), reaching target performance within ≤5 adaptation iterations while operating within microcontroller memory limits. Implications: The results support the feasibility of real-time, gesture-driven robotic arm control on resource-constrained embedded hardware for educational and light industrial use, enabling faster setup and user personalization without extensive pre-training. Originality: This work integrates embedded motion pattern recognition with error-based adaptive learning in a low-cost 3-DOF platform and reports consolidated end-to-end evidence (accuracy–latency–learning convergence–replication fidelity) to demonstrate practical feasibility.

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