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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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Structural Analysis of Compressor Connecting Rod Using Finite Element Simulation in SolidWork Luchyto Chandra Permadi; Bella Cornelia Tjiptady; Ratna Fajarwati Meditama; Kiki Darmawan; Mojibur Rohman; Faisol Khoufi Asshadiqi; Candra Pradhana
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7504

Abstract

The connecting rod in a compressor plays a critical role in transmitting the reciprocating motion from the piston to the crankshaft, making it a vital component that is constantly subjected to cyclic loads and stresses. This study aims to evaluate the structural strength and reliability of a compressor connecting rod by utilizing Finite Element Analysis (FEA) through SolidWorks Simulation software. The connecting rod was modeled with realistic geometric dimensions and material properties commonly used in household refrigerator compressors, such as aluminum alloys or medium-carbon steel. The simulation was performed by applying realistic boundary conditions, including compressive forces, reaction loads from the crankshaft, and constraints reflecting actual operational conditions. The results of the finite element simulation provided insights into the stress distribution, deformation patterns, and safety factors of the connecting rod under various load conditions. The maximum von Mises stress was identified in the transition area between the rod and the crank pin, which is consistent with typical failure points found in previous studies. From the analysis, it was concluded that the existing design provides an acceptable safety factor under normal working conditions, but optimizations in material thickness and fillet radius at critical regions could further enhance durability and reduce the risk of fatigue failure. This study highlights the importance of structural analysis in improving the reliability and longevity of compressor components through simulation-based design validation.
Three Phase Motor Speed Monitoring and Control System Using Raspberry Pi and Node RED in Molding Production at PT XYZ Muhammad Nashruddin Alie; Denny Irawan
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7514

Abstract

PT XYZ is a company that produces the largest automotive tools in Gresik. In producing the tool, a molding process is needed as a mold maker. In the molding process at PT XYZ, furan resin is used as a bonding agent and mixed with a catalyst in the appropriate proportion to produce a sand mold. Three-phase motor speed control in the molding process is very much needed so that the production process reaches maximum targets. The use of VFD in motor speed control can facilitate operators in the process of mixing materials for molding. Raspberry Pi combined with Node RED is an alternative as a cheap and efficient 3-phase motor speed monitoring and control system. The speed control of 3 phase motors on VFD can be done using Raspberry Pi with the help of Node RED as a communication bridge with VFD with Modbus protocol. The speed of 3 phase motors on VFD has an error percentage of 1.362% when compared to the UNI-T 373 tool. So that the monitoring and control system of 3 phase motors using Raspberry Pi and Node RED in molding production at PT XYZ is in accordance with the researcher's expectations and the system that has been designed can be implemented at PT XYZ.
Classification of Remission Data for Prisoners in Tangerang Class IIA Correctional Institution using K-Nearest Neighbor Algorithm Refa Maulana Abdillah; Halim Agung; Syaipul Ramdhan
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7532

Abstract

The classification of remission eligibility for prisoners is a critical issue in correctional institutions, as it directly impacts prison management and the rehabilitation process. Special remission is a reduction of sentence granted to prisoners based on specific criteria, including religious status and the type of remission granted. This research aims to address the challenge of classifying special remission data for prisoners at the Class IIA Tangerang Correctional Facility using the K-Nearest Neighbor (KNN) algorithm. The dataset used in this study includes four indicators: Length of Sentence, Remaining Sentence, Crime Type, and Risk Dimension, which are analyzed to predict the remission status to be granted. The KNN model, with a parameter of k=1, achieved an accuracy of 93.94%. However, the model struggled to accurately classify the "No Remission" class, resulting in failures to detect prisoners who are not eligible for remission. The data processing steps included converting categorical data into numerical format, data normalization, and splitting the data into training and testing sets. Model evaluation was conducted using Confusion Matrix, Precision, Recall, and F1-Score. The findings suggest that while the KNN algorithm can be effectively used to classify remission status, further improvements are needed to address class imbalance and optimize results.
Mental Health Diagnosis (Chronic Fatigue Syndrome and Depression) using Decision Tree Algorithm Ach. Zubairi; Ahmad Homaidi; Irma Yunita; Jarot Dwi Prasetyo; Hermanto Hermanto
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7595

Abstract

Mental health is an important aspect that affects an individual's life, impacting productivity, social relationships and overall quality of life. The World Health Organization (WHO) states that one in four people worldwide will face mental health challenges. With the increasing incidence of conditions such as depression and Chronic Fatigue Syndrome (CFS), effective detection and intervention methods are urgently needed. Data mining, specifically using Decision Tree algorithms, presents a promising approach to address this challenge. This study utilizes a quantitative methodology to classify depression and CFS patients using a public dataset. The data collection from Kaggle included variables such as demographics and clinical evaluations, consisting of 1,000 records and 15 predictive attributes. Data preprocessing addressed noise, specifically missing values, to ensure model accuracy above 80%. A Decision Tree was implemented, displaying the interpretability of the method by partitioning the data based on the selected attributes. Evaluation metrics such as accuracy, precision, recall, and F1 score showed accuracy of 99% and precision and recall of 100%. The results emphasize the potential of the Decision Tree in distinguishing between depression and CFS, enabling early intervention through accurate patient identification. This study advocates the integration of such machine learning models into clinical practice to improve mental health diagnostics and management, by addressing an important aspect of public health.
Analysis of Determinants of Competitiveness of Small Industries Using Fuzzy AHP Approach (Case Study At Mandiri Mitra Sejati Balikpapan) Tunggul Parasian Lumbantobing; Arini Anestesia Purba; Alvin Muhammad ‘Ainul Yaqin
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7652

Abstract

UMKM Mandiri Mitra Sejati Balikpapan is a local business engaged in non-metallic mining in the form of handmade brick crafts. This SME faces challenges such as the use of traditional technology, low human resource competence, waste management, and suboptimal production efficiency. This study aims to identify and analyze priority factors, as well as formulate strategies to enhance competitiveness using the Fuzzy Analytical Hierarchy Process (Fuzzy AHP) approach. Research data was obtained through interviews and the distribution of questionnaires to six respondents, including 1 owner and 5 workers, analyzed into three different weighting scenarios: 60:40, 75:25, and 50:50. The results of this study indicate that the Quality Criteria (K4) is the most dominant factor in determining competitiveness with a weight of approximately 0.4043-0.4107, followed by the Human Resources Criteria (K3) with a weight of approximately 0.3135-0.3328. The most significant sub-criteria are in the quality aspect of the production process. The sensitivity analysis results reinforce Criteria K4 and K3 as the main factors. The recommended strategy is to improve production quality through employee training programs and operational technology modernization. The results of this study are expected to serve as a basis for strategic decision-making by similar SMEs to enhance their competitiveness.
Dynamic System Model for Optimizing Clean Water Distribution in Balikpapan City Lasti Ningsih; Christopher Davito Prabandewa Hertadi; Bayu Nur Abdallah
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7666

Abstract

Balikpapan City, as one of the supporting cities for the Nusantara Capital City (IKN) in East Kalimantan, faces significant challenges in meeting the demand for clean water. The increase in population due to migration and infrastructure development following the relocation of the IKN has led to a continuous rise in the demand for clean water. The rate of water loss, or Non-Revenue Water (NRW), is quite high, reaching 25.85%. This situation has resulted in low distribution efficiency and highlights a gap between the available clean water distribution system and the actual needs of the community. As a result, clean water service coverage reached only 80.07% in 2022. This study aims to identify the factors influencing clean water distribution, develop a dynamic system model, and formulate optimal scenarios. The research method used is a dynamic systems approach, which enables comprehensive analysis of the cause-and-effect relationships between variables in the clean water distribution system, as well as simulation of various policy scenarios to find the most effective and sustainable solutions. Simulation results show significant dynamics in clean water distribution. From 2023 to 2035, pipeline length increased from 1.4 million meters to 1.6 million meters, yet clean water consumption decreased to 23.67 million m³ in 2029 and 23.15 million m³ in 2035. Of the three designed scenarios, Scenario 3, which involves a 4.2% annual increase in pipeline repair rates and a 1.47% annual increase in the number of customers, proved to be the most effective. This scenario successfully reduces pipeline leakage rates and significantly improves distribution coverage.
The Effect of Solvent and Amine Concentration on the Modification of Silica Sand Waste by Grafting Method as an Adsorbent Dominica Edora Stella Raharjanto; Dwi Ana Anggorowati; Nanik Astuti Rahman
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7718

Abstract

Industrial waste is all types of waste materials or residual materials originating from the results of an industrial process. One of the industrial wastes in solid form is silica sand waste from the sandblasting process which has the potential to be used as a source of silica for adsorbents. This experiment is conducted to determine the type of solvent and the best addition volume of APTES in silica modification using amine (APTES). The process used in this experiment is a grafting process, where silica goes through a reflux process with solvents and APTES so that the amine groups attach to the surface of the modified silica. The results of the experiment is analysed using TGA and FTIR, and shows that the most optimal addition volume of APTES is 5 mL with the best types of solvents being ethanol and toluene solvents with the amount of amine loading contained in the modified silica being 1,9430 and 5,2552 mmol g aminopropyl/gram silica, respectively, but not in water solvents. The results of this study shows a successful APTES grafting of modified silica which can be used as an adsorbent for CO2 capture.
Cadmium Pollution in Soil of Rice Fields Around Lapindo Mud Using The Geoaccumulation Index (I-Geo) Listin Fitrianah; Sindi Nur Fadilah
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7617

Abstract

The Lapindo Mud Disaster is a phenomenon of overflowing mud from the earth's crust that occurred in Sidoarjo. One of the impacts of the hot mud eruption on agricultural fields. This study aims to analyze the content of heavy metal cadmium in the soil of rice fields around the Lapindo Mud. The heavy metals analyzed include Cadmium (Cd), which is used in the Geoaccumulation Index (Igeo), with Class 7 of Igeo used to determine the level of heavy metal contamination due to a disaster that occurs. The results of this study indicate the largest Cadmium (Cd) metal content in the sample in Gempol Sari village, at  1.08 mg / L and 0.007 mg/L, respectively. This exceeds the threshold set by the Environment Protection Ministry of China (EPMC) and contaminates the rice field environment. Based on the Igeo calculation (geoaccumulation index) applied to the concentration of heavy metals in rice field soil not contaminated by Cadmium, with an index value of 0 <igeo <1. Geoaccumulation Index figures in the research area, cadmium (Cd) content is within the normal range, so it is not included in the group of heavy metals that pollute the soil.
Analysis of Clean Water Demand and Availability in Prambon Village using F.J Mock Method and Direct Testing in Tugu District, Trenggalek Regency Wieke Pramesthy Artha Amalia; Vita Ayu Kusuma 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.v9i4.6206

Abstract

Drought frequently occurs in Trenggalek Regency, with Prambon Village being one of the affected areas. The prolonged droughts in Prambon Village cause the water sources to dry up. As the population increases, so does the water demand. This study used arithmetic methods to project the population size until 2032. To assess the availability of water, the study used the F.J. Mock method and direct testing. According to the F.J. Mock method, the water balance indicated a surplus, projecting that the available water supply would meet the villagers' needs through 2032. However, the water balance based on data from the PKPLH Department and direct testing shows a deficit, insufficient to meet the population's needs until 2032. To address this issue, the conservation of water resources is necessary, involving the construction of spring protections, tree planting, and rainwater harvesting to ensure that the water needs of Prambon Village residents are met. This research serves as a reference for clean water utilization in Trenggalek Regency.
DeepFake Image Detection Using Convolutional Neural Network with EfficientNet Architecture Eddy Muntina Dharma; Ni Made Satvika Iswari; I Putu Rama Astra Arimbawa
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.v9i4.7727

Abstract

The growing sophistication of generative Artificial Intelligence (AI) has intensified the threat posed by deepfake technologies, which are capable of producing highly realistic yet fabricated facial images and videos. These manipulated visuals can mislead the public, infringe on personal privacy, and damage reputations. This study aims to develop an effective deepfake image detection system using Convolutional Neural Networks (CNN) enhanced with EfficientNet architectures (B3–B5). The research adopts the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology, providing a structured data science framework that spans from problem definition to deployment. Three open-access datasets (Celeb-DF v2, DeeperForensics-1.0, and DFDC) are utilized to train and evaluate the models. Experimental results show that EfficientNet-B5 achieves the highest classification accuracy at 93.2%, outperforming both the baseline CNN and other EfficientNet variants. The proposed method demonstrates strong cross-dataset generalization and computational efficiency, making it suitable for real-world applications. This research contributes a comparative evaluation of scalable deepfake detection models, practical deployment insights, and a foundation for future work in explainable and real-time AI-based media forensics.

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