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G-Tech : Jurnal Teknologi Terapan
Published by Universitas Islam Raden Rahmat Malang
ISSN : 25808737     EISSN : 2623064X     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering
Jurnal G-Tech bertujuan untuk mempublikasikan hasil penelitian asli dan review hasil penelitian tentang teknologi dan terapan pada ruang lingkup keteknikan meliputi teknik mesin, teknik elektro, teknik informatika, sistem informasi, agroteknologi, dll.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 897 Documents
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Work Accident Risk Analysis in Water Treatment Plant Laboratory of PT XYZ using JSA and HIRARC Methods Azumah Islahiyah; Moh. Jufriyanto
G-Tech: Jurnal Teknologi Terapan Vol 9 No 4 (2025): G-Tech, Vol. 9 No. 4 October 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i4.8061

Abstract

PT. XYZ produces fertilizers and chemicals for agro-industrial solutions. To maintain product quality, quality control is carried out in the water treatment laboratory. The increasing complexity of laboratory activities increases the risk of workplace accidents, such as inhaling reactive chemicals that can irritate the respiratory system and cause poisoning, or slipping while taking samples, which can cause injury. This study aims to analyze potential hazards and design control recommendations using the Job Safety Analysis (JSA) and Hazard Identification, Risk Assessment, and Risk Control (HIRARC) methods. Data were collected through interviews with employees and questionnaires assessing the likelihood and severity of hazards. The results of the study identified 12 potential hazards spread across 4 work activities. There were 2 very high-level hazards, 9 high-level hazards, and 1 moderate-level hazard. This study provides control recommendations to reduce risks, such as controls including the use of appropriate Personal Protective Equipment (PPE) etc., thereby supporting improved workplace safety at the PT. XYZ laboratory.
Evaluation of Work Posture Using RULA and REBA Methods and Ergonomic Intervention Design in a Brownies SME in Bogor Novia Rahmawati; Purana Indrawan; Annisa Kartinawati; Derry Dardanella; Fattah Jati Pangestu; Aurelia Rafandita; Akhfas Zidan; Cinthya D. Masithoh; Desvita Anggraeni; Dyanchalenda H. Yunanto; Kaila F. Ocsadira; Najwa S. Nainggolan
G-Tech: Jurnal Teknologi Terapan Vol 9 No 4 (2025): G-Tech, Vol. 9 No. 4 October 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i4.8065

Abstract

This study aims to analyze ergonomic conditions and occupational safety in one of brownies SME, particularly in activities involving raw material lifting, gas cylinder handling, and product packaging. The methods employed include RULA and REBA to evaluate working postures, as well as direct observation of environmental factors. The findings indicate that most worker activities fall into the medium to high risk categories, which may lead to MSDs. The RULA and REBA assessment scores indicated high ergonomic risk levels, with scores of 7 and 10 for the sack-carrying posture, 4 and 5 for the water gallon lifting posture, and 5 and 9 for the squatting posture during packaging, respectively. Workplace environmental factors were also found to be suboptimal, with poor cleanliness and sanitation that could endanger workers. As corrective measures, this study proposes the design of a multi-purpose handling trolley for transporting sacks and gas cylinders, along with an ergonomic table and chair to support workers during the packaging process. These interventions are expected to reduce injury risks, improve comfort and hygiene, and enhance worker productivity. Thus, the application of ergonomics and occupational safety principles is proven essential in creating a safe, healthy, and efficient working environment in small-scale food industries.
Predicting Digital Literacy Levels in Higher Education: A LightGBM Model Integrating Feature Selection for Improved Accuracy Arman Haqqi Anna Zili; Selly Anastassia Amellia Kharis
G-Tech: Jurnal Teknologi Terapan Vol 9 No 4 (2025): G-Tech, Vol. 9 No. 4 October 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i4.8077

Abstract

Digital literacy has become an essential skill in higher education, particularly in online and distance learning settings. This study explores the use of Light Gradient Boosting Machine (LightGBM) to classify digital literacy levels among 10,393 students at Universitas Terbuka. To improve both efficiency and clarity of interpretation, feature selection was carried out using SelectKBest, which reduced the dataset to 33 predictors. The final model, evaluated through stratified 5-fold cross-validation, achieved an accuracy of 0.964 and a weighted F1-score of 0.964. The results show that limiting the number of features did not weaken predictive performance, while also making it easier to identify which aspects of digital literacy are most influential. Interestingly, the strongest predictors were not only technical skills but also ethical behavior, digital citizenship, and online communication. These findings highlight that digital literacy is multidimensional and that effective assessment tools must account for social and behavioral factors alongside technical competence. Taken together, applying feature selection with LightGBM offers an effective way to assess digital literacy in higher education. The method achieves strong predictive accuracy while keeping the model interpretable, giving universities clearer guidance for shaping interventions and curricula in online learning contexts.
Stormwater Runoff Control Analysis Using Rain Garden Implementation in the Drainage System of GKB, Universitas Negeri Malang Camila Aysha Putri Bachtiar; Vita Ayu Kusuma Dewi; Titi Rahayuningsih; Mega Septia Sarda Dewi
G-Tech: Jurnal Teknologi Terapan Vol 9 No 4 (2025): G-Tech, Vol. 9 No. 4 October 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i4.8062

Abstract

Climate change and rapid urbanization have intensified stormwater runoff in urban areas, including Malang City, while conventional drainage systems often lack the capacity to manage excess flow. This study aims to design and evaluate a rain garden model as a sustainable green infrastructure for reducing stormwater runoff in the GKB area of Universitas Negeri Malang, which frequently experiences inundation of up to 20 cm. The methodology involved rainfall analysis, probability distribution testing, and peak discharge estimation to determine the design parameters. The rain garden’s performance was assessed by comparing its storage capacity with the calculated runoff volume. Results indicate that for a two-year return period (0.134 m³/s), the proposed rain garden can fully accommodate runoff within its designed capacity. These findings demonstrate the potential of rain gardens as an effective nature-based solution to improve drainage efficiency and enhance urban flood resilience.
Fertilizer Factory Port Conveyor Optimization Design System With Outseal PLC and HMI Rovi Maulidani Syela; Denny Irawan
G-Tech: Jurnal Teknologi Terapan Vol 9 No 4 (2025): G-Tech, Vol. 9 No. 4 October 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i4.8073

Abstract

The development of automation systems in industry is increasingly rapid, especially in the field of material control and distribution. Automation systems are designed to simplify human work and stabilize the performance of industrial machines to be more efficient and reliable. This article discusses the design and implementation of a prototype of an automatic conveyor system in the port area that functions to support the material distribution process to the fertilizer factory. This system uses the Outseal Nano Programmable Logic Controller (PLC) as the main controller and the Haiwell Human Machine Interface (HMI) as a remote monitoring and control system. The main objective of the design is to reduce buildup and prevent material spillage during the transportation process from the port to the production area. Test results show that the automatic conveyor system is able to operate stably at an operational temperature of 45°C and a Moisture Quantity (MQ) value of at least 30%, without significant disruption to the transportation process. The implementation of this system resulted in an increase in material distribution efficiency of 27.8% compared to the manual system, and reduced material handling time by up to 22%. In addition, the error rate in material distribution was reduced by up to 15%, which contributed to increased accuracy and work safety in the port area. Overall, this automation system has been proven to increase the efficiency and reliability of the material distribution process, as well as being an effective solution to overcome logistical and operational problems in the port industry environment.
Optimizing Water Quality in Carp Farming through an IoT-based Dissolved Oxygen Monitoring System Khusnul Hayati; Faishal Arham Pratikno; Putri Gesan Prabawa Anwar; Healty Susantiningdyah
G-Tech: Jurnal Teknologi Terapan Vol 9 No 4 (2025): G-Tech, Vol. 9 No. 4 October 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i4.8074

Abstract

Dissolved oxygen (DO) is a critical parameter in common carp (Cyprinus carpio) aquaculture, as low DO levels can cause stress, inhibit growth, and lead to fish mortality. Conventional measurement methods, such as manual titration or DO meters, are limited because they cannot provide continuous or real-time monitoring. Therefore, this study aims to develop an Internet of Things (IoT)-based dissolved oxygen monitoring system using the Waterfall development method to maintain optimal water quality in carp ponds. The system utilizes an ESP32 microcontroller, a DO sensor, and the Blynk platform as a real-time remote monitoring interface. It continuously measures DO levels, displays data locally on an LCD, and sends automatic notifications when the DO value falls below 5 mg/L. Field testing was conducted for one week at the Rama Graha carp pond, showing that the system achieved an accuracy of 92.7%, an error rate of 7.3%, and a precision of 98%. The developed system effectively supports farmers in maintaining stable water quality and reducing fish mortality. This study contributes to the development of practical, low-cost IoT technology for sustainable freshwater aquaculture management. 
Comparative Analysis of Concrete QTO Using BIM and Conventional on XYZ Project Rizki Adithya Wibowo; Putri Ayu Dwiyana; Junita Eka Susanti
G-Tech: Jurnal Teknologi Terapan Vol 9 No 4 (2025): G-Tech, Vol. 9 No. 4 October 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i4.8075

Abstract

The rapid advancement of technology in the construction sector has encouraged the integration of digital modeling systems such as Building Information Modeling (BIM) to improve project efficiency and accuracy. This study analyzes the implementation of BIM using Autodesk Revit 2025 in the integrated design and build construction of the XYZ Project. The objective is to compare the Quantity Take Off (QTO) results between the BIM method and conventional concrete calculation for column and beam structures, as well as to evaluate the resulting cost differences. A quantitative comparative approach was employed by modeling the structure using Revit and manually calculating the quantities through conventional methods. The results show that both methods produced the same concrete volume for columns (891.6 m³), while for beams, the BIM method produced 1,104.59 m³ compared to 1,227.47 m³ from conventional calculations, yielding a difference of 122.88 m³ (11.12%) equivalent to IDR 294,831,618.37 in cost savings. The study concludes that BIM provides higher precision and reduces potential material waste, supporting more efficient budgeting and sustainable construction management.
Production of Calcium-Ammonium-Phosphate (CAP) Multinutrient Fertilizer from Acetylene Gas Industry Waste and Phosphoric Acid Saudhia Aulizya Niswatul Khusna; Tri Andini Agustin; Ketut Sumada
G-Tech: Jurnal Teknologi Terapan Vol 9 No 4 (2025): G-Tech, Vol. 9 No. 4 October 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i4.8086

Abstract

The increasing global demand for food has raised the need for effective fertilizers, while the depletion of conventional raw materials and industrial waste accumulation have become pressing issues. Acetylene gas industries generate large amounts of semi-solid lime waste containing calcium hydroxide, which is often disposed of without treatment, causing environmental problems. This study aims to utilize acetylene waste as a raw material for producing Calcium-Ammonium-Phosphate (CAP) multinutrient fertilizer through a precipitation method using phosphoric acid (H3PO4) and ammonium hydroxide (NH4OH). The variables investigated include pH values (6,7,8,9,10) and waste mass (30,35,40,45,50 g). The resulting products were analyzed using Scanning Electron Microscopy–Energy Dispersive X-ray (SEM-EDX). The results indicate that the optimum pH to obtain the highest nutrient content of calcium (Ca), phosphorus (P), and nitrogen (N) is pH 10. In addition, variations in the mass of acetylene industry solid waste were found the optimum condition was achieved at 30 g of waste, which provided the highest concentrations of calcium, phosphorus, and nitrogen. This research demonstrates the potential of acetylene industry waste as an alternative raw material for sustainable fertilizer production.
Development of a Decision Support System Based on the Weighted Product to Optimize Production Scheduling in the Furniture Industry Yessi Nasia Ulfia; Dian Eko Hari Purnomo; Fesa Putra Kristianto; Julia Dewi Ma’rifah; Taukhid Wisnu Broto; Fitri Indah Puspitaningsih
G-Tech: Jurnal Teknologi Terapan Vol 9 No 4 (2025): G-Tech, Vol. 9 No. 4 October 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i4.8090

Abstract

The furniture industry plays a crucial role in Indonesia’s manufacturing sector, which contributed 18.98% to the national GDP in 2024 with a growth rate of 4.43%. However, increasing market demand and product variety have created significant challenges in achieving efficient and timely production scheduling. Inefficient manual scheduling processes have been shown to cause substantial delays, with approximately 31% of production orders experiencing lateness due to poor scheduling and machine utilization. This study aims to design and implement a Decision Support System (DSS) based on the Weighted Product (WP) method to objectively determine production scheduling priorities using order quantity, processing time, and profit value as key criteria. The DSS was developed using Microsoft Visual Basic 6.0 and Microsoft Office Access 2016, utilizing secondary data from a furniture manufacturing company. Validation results show that the DSS achieved a 99.998% accuracy rate compared to manual Excel calculations, indicating correct implementation of the WP computational algorithm. The system effectively enhances production planning by providing objective, data-driven scheduling recommendations, reducing delays, optimizing resource utilization, and improving operational efficiency. Overall, the DSS serves as an effective managerial tool to support decision-making consistency and competitiveness in the manufacturing industry.
The Effect of AI-Based Recommendation System for Material Personalization on Vocational Student Satisfaction Intan Wulan Sari; Hilma Erliana; Cut Meurah Nurul ‘Akla; Nabilla Yudisha
G-Tech: Jurnal Teknologi Terapan Vol 9 No 4 (2025): G-Tech, Vol. 9 No. 4 October 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i4.8091

Abstract

This study analyzes the influence of artificial intelligence (AI) based recommendation systems on the satisfaction of vocational students, focusing on two main variables: feature mapping and technological readiness. The research background is driven by the need for more adaptive and personalized learning, considering that conventional methods tend to be generic and overlook individual differences. Involving 183 vocational students selected through purposive sampling, the study employs a quantitative approach with descriptive and associative methods. Data were collected using valid and reliable questionnaires with a 1–5 Likert scale and analyzed using multiple linear regression. The results indicate that both feature mapping and technological readiness have a positive and significant influence on student satisfaction. Simultaneously, these two variables explain 43% of the variation in student satisfaction. Partially, feature mapping has the most dominant influence compared to technological readiness, indicating the importance of adaptive feature design in AI-based recommendation systems. This study proves that technology-based learning material personalization if supported by adequate infrastructure can enhance the learning experience and satisfaction of vocational students. Therefore, the study recommends the development of AI-based adaptive learning models that prioritize aspects of feature design and technological readiness to improve the effectiveness and quality of vocational education.

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