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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 132 Documents
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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.
Study of WF Profile Analysis as a Compression Element Reviewed Based on the Weight to Strength Ratio Using the LRFD Method Kharisma Nur Cahyani; Yoganata, Yehezkiel Septian; Khusniah, Rif’atul; Purwitasari, Kartika
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.v4i3.2407

Abstract

This study investigates the efficiency of WF steel profiles as compression members by evaluating the strength-to-weight ratio using the Load and Resistance Factor Design (LRFD) method. The analysis was conducted on seven variations of WF profiles made of ASTM A36M steel (Fy = 250 MPa, Fu = 450 MPa). The primary parameters considered were axial compressive capacity and profile weight, which were used to determine the strength-to-weight ratio as an indicator of material efficiency. This study contributes to existing research by integrating a systematic strength-to-weight–based evaluation to support optimal WF profile selection beyond conventional strength verification. The results indicate that the strength-to-weight ratio ranges from 592.15 to 611.31, with the highest value obtained for profile 300.300.9.14. In contrast, the maximum compressive capacity of 260,599 kg was achieved by profile 300.300.11.17. Overall, WF profiles with 300×300 dimensions demonstrate superior performance compared to 250×250 profiles in terms of both strength and efficiency. The findings suggest that profile selection may be adapted to design priorities, emphasizing either material efficiency or maximum load-carrying capacity.
Internal Force Analysis on Simple Truss Structure: Evaluation of the Cramer’s Rule Method Rif'atul Khusniah; Cahyani, Kharisma Nur; Yoganata, Yehezkiel Septian
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.v4i3.2408

Abstract

Penelitian ini melakukan analisis gaya internal pada struktur rangka batang sederhana dengan menggunakan metode aturan cramer. Analisis dilakukan melalui pendekatan matematis, di mana model matematis dari struktur rangka batang sederhana disusun dalam bentuk sistem persamaan linear yang didasarkan pada keseimbangan gaya di setiap simpul. Sistem persamaan gaya yang diperoleh kemudian diubah menjadi matriks koefisien dan diselesaikan menggunakan metode aturan cramer untuk menghitung gaya internal pada setiap batang rangka. Selain itu, penelitian ini juga menilai dampak kesalahan numerik dalam proses komputasi. Hasil penelitian mengindikasikan bahwa metode Aturan Cramer efektif untuk struktur kecil, namun sangat peka terhadap kesalahan pembulatan dan koefisien yang mendekati nol, sehingga penggunaan metode numerik sangat penting dalam analisis struktur sipil.
Digital Transformation of Poultry Farming Through Artificial Intelligence Fitrah, Laeli; Husni, Hari Setiabudi
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.v4i3.2297

Abstract

The global poultry sector is under pressure to increase efficiency, sustainability, and animal welfare amid growing demand and resource constraints. Artificial Intelligence (AI) has emerged as a key enabler of digital transformation in poultry farming, yet evidence on practical adoption remains fragmented, especially for smallholder and UMKM contexts. Objective: This study systematically maps AI applications in poultry farming, classifies their functional domains and technological approaches, evaluates reported benefits and limitations, and identifies research gaps related to real-world implementation. Method: A PRISMA 2020-guided Systematic Literature Review (SLR) was conducted on 28 peer-reviewed, open-access, Scopus-indexed journal articles published between 2020 and 2025. Data were extracted on AI techniques, data modalities, application domains, implementation settings, and reported outcomes, then synthesized using thematic analysis. Findings: AI applications concentrate on disease detection and health monitoring, environmental control, behavior and welfare analysis, feed optimization, and productivity forecasting. Deep learning and computer vision dominate image/video-based tasks, while conventional machine learning supports multivariate prediction. Most studies report laboratory or pilot validation rather than full field deployment. Common barriers include high initial costs, limited digital literacy, infrastructure constraints (e.g., connectivity), and scarce localized datasets challenges that are particularly salient in developing-country settings. Implications: Adoption is most feasible through affordable, modular monitoring and decision-support solutions, supported by local dataset development, capacity building, and multi-stakeholder partnerships to translate pilots into sustained deployments. Originality/Value: This review integrates functional classification, technological mapping, and implementation maturity into a unified framework, offering an operational perspective on how AI can be scaled inclusively in poultry farming.
Design and Development of a Press Machine for Biobriquettes Made from Patchouli Distillation Waste and Rice Husk Tandiapa, Vincen; Pantow, Rifan; Simanjuntak, Simon; Manoppo, Friani; Raphaela, Josephine; Saroinsong, Tineke; Mekel, Alfred Noufie; Motulo, Firmansyah Reskal; Muaja, Estrela Bellia
International Journal Science and Technology Vol. 5 No. 1 (2026): March: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v5i1.2378

Abstract

The increasing availability of biomass residues such as patchouli distillation waste and rice husk presents an opportunity for renewable energy production; however, their utilization remains limited due to the lack of efficient and safe small-scale processing equipment. Developing practical briquette production systems is therefore essential to support sustainable energy use at household and MSME levels. Objective: This study aims to develop and evaluate a hydraulic briquette press capable of producing biomass briquettes from patchouli distillation waste and rice husk while enhancing operational safety, maintenance efficiency, and usability for small-scale production. Method: The research employed an engineering research-and-development approach involving machine design, prototype fabrication, and functional testing. Data were collected through technical observation and performance monitoring of pressing cycles, followed by descriptive analysis to evaluate operational functionality, safety response, and cleaning effectiveness. Findings: The developed press integrates a pressure-sensor-based safety system and an automatic pneumatic cleaning mechanism. The machine is capable of forming six briquettes per cycle at an operating pressure of approximately 50 kg/cm². The integrated systems functioned as intended, supporting stable operation, reducing manual cleaning needs, and improving operational safety. Implications: The proposed design demonstrates potential for improving briquette production efficiency and reliability in small-scale applications. By reducing downtime and enhancing safety, the system can support wider adoption of biomass briquette technology and contribute to community-level renewable energy utilization. Originality/Value: This study offers a novel integration of hydraulic pressing, automatic pneumatic cleaning, and pressure-based safety monitoring within a single multi-cavity briquette press, providing a practical and user-oriented solution for transforming agricultural waste into renewable energy products.
Industrial Artificial Intelligence Methods for Fabric Color-Defect Detection in Textile Manufacturing Kim, Byung-ho; Jae, Hee-Sung
International Journal Science and Technology Vol. 5 No. 1 (2026): March: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v5i1.2600

Abstract

Color-related fabric defects such as shade variation, off-shade, discoloration, and color bleeding remain challenging to detect consistently in textile manufacturing because camera-based inspection is highly influenced by illumination variability, fabric reflectance, and domain shift across production batches. These limitations often reduce the reliability of automated inspection systems and highlight the need for a systematic synthesis of existing Industrial Artificial Intelligence approaches. Objective: This study aims to systematically review and synthesize Industrial Artificial Intelligence methods for fabric color-defect detection to identify methodological trends, evaluation practices, and research gaps, as well as to explain why these approaches are important for improving reliability in industrial quality control. Method: The research employs a Systematic Literature Review design, collecting peer-reviewed studies through structured database searches followed by PRISMA-guided screening and eligibility assessment. The selected studies are analyzed using comparative narrative synthesis and standardized coding of method types, color representation, illumination handling strategies, datasets, and evaluation metrics. Findings: The review reveals four dominant methodological groups: classical computer vision, supervised deep learning, reconstruction-based anomaly detection, and feature-space anomaly or hybrid approaches. Across these approaches, robust performance consistently depends on a triadic design principle consisting of color-consistent representation, illumination robustness, and learning strategies aligned with label availability. The study also identifies a key evaluation gap where conventional vision metrics are rarely complemented by perceptual color-difference measures. Implications: The findings suggest that future research and industrial implementation should focus on developing color-calibrated datasets, adopting dual-axis evaluation frameworks that include perceptual color metrics, and validating models under varying illumination and fabric conditions to enhance real-world reliability. Originality/Value: This study provides an original contribution by proposing a color-defect–focused operational framework that integrates color science principles with Industrial AI method selection and deployment constraints, offering clearer guidance than previous reviews that primarily addressed structural textile defects.
Analysis of Natural Stone Wall Function Index Using Fuzzy Building Service Life (FBSL) Velantika, Griselda Junianda; Sari, Ayu Fatimah; Putri, Karina Meilawati Eka; Widowati, Elok Dewi
International Journal Science and Technology Vol. 5 No. 1 (2026): March: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v5i1.2612

Abstract

Natural stone wall claddings are widely used in residential buildings, but their functional performance often declines earlier than the building’s structural design life due to environmental exposure and installation-related deterioration. Objective: This study aims to quantify the functional condition of natural stone wall claddings using a Function Index (FI) so that maintenance decisions can be made more consistently and objectively. Methodology: A quantitative case-study approach was applied to five residential buildings in Situbondo Regency. Data were collected through field observations and building-age documentation, assessed using expert judgment, and analyzed using a fuzzy inference-based Fuzzy Building Service Life (FBSL) model to obtain a crisp FI score for each building. Findings: The results indicate that one building was classified as moderate/fair (FI = 56), while four buildings were classified as poor (FI = 0–23), implying higher maintenance urgency. When linked to the estimated Remaining Service Life (RSL) under an assumed 50-year design life and a 2020 observation year, an exploratory exponential relationship between FI and RSL was obtained (y = 12.177e0.3243x; R² = 0.7444). Implications: The FI can serve as a practical decision-support indicator to prioritize immediate repair, scheduled maintenance, or routine monitoring for façade components, even when the building still has considerable remaining design life. Originality: This research contributes by integrating a fuzzy-based functional condition index for natural stone claddings with a remaining service life perspective in a residential case-study context, bridging qualitative inspection outcomes with interpretable maintenance planning.
Circular Economy of Source-Separated Organic Waste in New York City Barua, Santunu
International Journal Science and Technology Vol. 5 No. 1 (2026): March: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v5i1.2618

Abstract

New York City (NYC) generates more than one million tons of compostable organic waste annually, most of which is still landfilled, contributing to greenhouse gas emissions and resource loss. Objective: This review aims to examine the circular economy potential of source-separated organic waste (SSOW) in NYC, with a primary focus on the residential curbside organics program. Method: This study uses a systematic literature review approach by synthesizing peer-reviewed articles, government reports, program documents, and policy records related to composting, anaerobic digestion (AD), community composting, life-cycle assessment (LCA), and NYC’s regulatory framework. Findings: The findings show that landfilling organic waste produces nearly 400 kg CO₂e per tonne, whereas composting generates net negative emissions of approximately −41 kg CO₂e per tonne and dry AD for renewable natural gas yields −36 to −2 kg CO₂e per tonne. Although NYC’s mandatory curbside composting program was fully enforced in April 2025 and collected more than 30,000 tons of organics in 2024, residential capture rates remain below 5%, indicating persistent challenges in infrastructure, public education, contamination control, and multi-family building compliance. Implications: These results imply that an integrated system combining composting, AD, and community composting can improve resource recovery, climate performance, and social participation. Originality: The originality of this review lies in its integrated analysis of technical, environmental, regulatory, and community dimensions of SSOW management within a single circular economy framework, providing a policy-relevant perspective for advancing zero-waste strategies in dense metropolitan contexts.

Page 13 of 14 | Total Record : 132

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