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Contact Name
Mochamad Sulaiman
Contact Email
m.sulaiman@uniramalang.ac.id
Phone
+6282331527189
Journal Mail Official
m.sulaiman@uniramalang.ac.id
Editorial Address
Fakultas Sains dan Teknologi Universitas Islam Raden Rahmat Malang Jl. Raya Mojosari 02 Kepanjen-Malang
Location
Kota malang,
Jawa timur
INDONESIA
G-Tech : Jurnal Teknologi Terapan
ISSN : 25808737     EISSN : 2623064X     DOI : -
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.
Articles 897 Documents
Extraction of Pacitan Sweet Orange Peel Pectin as a Bioadsorbent on the Adsorption Process of Fe Metal in FeCl3 Solution Nadhifatuz Zalfa Nur Aisyah; Camelia Asiah Putri Anwar; Nurul Widji Triana
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.v9i3.7085

Abstract

One alternative to treating waste that contains heavy metals is by bioadsorption process from natural materials as adsorbents. In this study, Pacitan sweet orange peel raw material was used as a FeCl3 metal bioadsorbent. This study aims to obtain pectin as a bioadsorbent for Fe metal in FeCl3 solution with the influence of extraction time and temperature on pectin extraction. In this study, pectin was extracted using the direct extraction method with HCl solvent. To prove the characteristics of pectin, FTIR analysis was conducted by observing the C=O group contained in pectin. Atomic Adsorption Spectrophotometer (AAS) analysis was then used to perform pectin adsorption in a FeCl3 solution. The research results show that optimum conditions are achieved at a temperature of 80°C, a contact time of 90 minutes with the addition of a pectin mass of 90 mg obtained an adsorption efficiency of 60.52%. From the isotherm adsorption analysis, Freundlich isotherm was applied to the adsorption of FeCl3 metal with a determination coefficient (R2) of 0.968.
Formulation of Granular Fertilizer from Elephant Grass Ash and Urea with Tapioca Binder Yuriko Tiara; Meriska Diva Nadia Putri Amrulloh; Ketut Sumada
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.v9i3.7101

Abstract

Elephant grass remains underutilized, despite its ash containing high levels of potassium and its potential as a raw material for fertilizer production. This study aims to evaluate the effect of mixing ratios of elephant grass ash and urea with tapioca starch binder on fertilizer composition in accordance with quality standards, and to examine how binder concentration influences the characteristics of the resulting granules. The process began by burning elephant grass into charcoal, followed by ashing in a furnace at 600°C for 4 hours. The ash was then mixed with urea and tapioca starch at various compositions. The variables included urea additions of 20%, 25%, 30%, 35%, and 40% (w/w), and binder concentrations of 6%, 7%, 8%, 9%, and 10% (w/w). The resulting granules were analyzed for N, P₂O₅, and K₂O content to determine the optimal formulation. The study found that granules with 20% urea met the standard of Indonesian Ministry of Agriculture Regulation No. 209/Kpts/SR.320/3/2018, while granules with 10% tapioca binder had the longest disintegration time at 413 minutes. This research contributes to the development of sustainable fertilizers derived from elephant grass biomass waste.
Design and Manufacture of Speedometer Covers using the House of Quality (HOQ) Approach Elka Faizal; Nurlia Pramita Sari; Hangga Wicaksono; Bayu Pranoto; Nicky Suwandhy Widhi Supriyanto; Subagiyo Subagiyo
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.v9i3.7119

Abstract

This study aims to design and fabricate a speedometer cover for Yamaha Aerox and N-Max 155 motorcycles using 3D printing technology, guided by the House of Quality (HOQ) framework. The increasing consumer demand for motorcycle accessories motivated this research. A structured design process was implemented, beginning with a consumer needs analysis conducted through questionnaires and surveys to identify user expectations. These needs were systematically translated into technical requirements using the HOQ method. The design stage utilized 3D CAD modeling and 3D scanning to ensure accurate fitting to the speedometer unit, followed by prototyping using fused deposition modeling (FDM) 3D printing. The final prototype exhibited key consumer-desired attributes such as heat resistance, structural durability, and a secure fit. Results indicate that integrating the HOQ approach with digital fabrication methods effectively aligns product design with user expectations. This study demonstrates the potential for further development of customizable motorcycle accessories using a consumer-driven and technology-supported design process.
Experimental Investigation of Air-to-Kapok Oil Ratio Effects on Flame Height and Morphology in a Bunsen Burner Bayu Pranoto; Nicky Suwandhy Widhi Supriyanto; Chandra Gunawan; Supa Kusuma Aji; Muhammad Arif Nur Huda
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.v9i3.7120

Abstract

The growing global demand for energy highlights the limitations of fossil fuel resources. This makes innovation in alternative energy development crucial, and one promising avenue is the use of vegetable oils like kapok oil. Kapok oil has a complex chemical composition, composed of various triglycerides of fatty acids and glycerol, where each fatty acid component contributes unique combustion characteristics. The interaction of the complexity of this content as a whole affects the flame pattern of kapok oil. Furthermore, the air-fuel mixture ratio (AFR) plays a significant role in determining the characteristics of the resulting flame. Therefore, this study aims to explore in depth the effect of AFR variations on the combustion characteristics of kapok oil. Experiments were conducted by burning a mixture of kapok oil vapor and air on a burner with controlled AFR settings. The results showed that the variation of AFR significantly changed the flame height and morphology. Flame height initially increased with increasing AFR (from 1.34 cm at AFR 0.143:1 to 4.429 cm at AFR 1.526:1) before decreasing (to 0.264 cm at AFR 4.011:1) until it reached the lift-off condition and went out.
Feasibility Study for the Construction of the Dekranasda Gallery Building in Pangkalpinang City Putri Ayu Dwiyana; Junita Eka Susanti
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.v9i3.7158

Abstract

The construction of the Dekranasda Gallery Building in Pangkalpinang City is planned as part of a strategy to strengthen the creative economy sector and increase the added value of local craft products. This study aims to identify the priority location for the construction of the Dekranasda Gallery Building by evaluating three alternative sites from technical, economic, social, and environmental perspectives. Each aspect is analyzed by considering the availability of basic infrastructure, land use suitability, investment value, and community perception and social support for the gallery's construction. The assessment is carried out comparatively to obtain the most optimal location recommendations. The analysis results show that Alternative Location 1 (Taman Mandara) has the highest overall score, relatively complete infrastructure support, good social suitability, and an estimated investment requirement of IDR 13,929,500,000. Alternative Location 2 (Tampuk Pinangpura) shows a reasonably good feasibility value but is not yet optimal from a technical perspective. Meanwhile, Alternative Location 3 (Tugu Kepiting) has limited infrastructure and a low social score, requiring a higher investment of IDR 14,229,500,000. Considering all aspects of feasibility, Alternative Location 1 is recommended as a priority location for constructing the Pangkalpinang City Dekranasda Gallery Building.
Design and Implementation of an IoT-Based Automatic Irrigation and Monitoring System for Bird’s Eye Chili Plants with Telegram and Blynk Platform Integration Ellys Kumala Pramartaningthyas; Siti Ma’shumah; Abdullah Al Hannan
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.v9i3.7160

Abstract

The development of an Internet of Things (IoT)-based automatic watering and monitoring system for cayenne pepper plants, integrated with Telegram, aims to simplify the process of maintaining optimal soil moisture levels. By enabling real-time monitoring via smartphones, this system helps ensure that plants receive adequate water without experiencing overwatering or drought stress. The system utilizes a capacitive soil moisture sensor to detect moisture levels and a NodeMCU ESP8266 microcontroller, which includes an integrated WiFi module, for network connectivity. A relay module is used to control the water pump based on sensor readings. Experimental results—detailed in Chapter IV—demonstrate that the system operates effectively, as reflected by successful automatic irrigation and timely notification delivery through Telegram. Furthermore, the system's performance, evaluated in accordance with Telecommunications and Internet Protocol Harmonization Over Networks (TIPHON) standards, recorded average communication delays of 2.0 seconds and 2.5 seconds respectively. These results support the claim of reliable and responsive system communication, as further substantiated by the performance data presented in the results section.
Advanced Machine Learning Techniques for Assessing Water Quality: A Comparative Study Using Ensemble, Neural Networks, and Instance-Based Models Muhammad Hafiz; Johan Iswara; Bari Fakhrudin; Widitra Nararya Rama; Avellino Vincent Juwono; Gilang Raka Rayuda Dewa
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.v9i3.7162

Abstract

Access to safe water remains a significant issue, with around 5.8 billion people lacking access to potable water globally. Rapid and accurate identification of water safety is thereby essential to reduce public waterborne diseases. However, conventional laboratory-based testing is typically time-consuming and expensive. On the other hand, machine learning provides time- and cost-effective assessments based on physicochemical properties. Unfortunately, most studies only evaluate a single model type in a small dataset, resulting in limited insight that makes it hard to determine the actual effectiveness of these models. To address this limitation, the present study conducts a comparative analysis of three machine learning paradigms: ensemble-based, neural network-based, and instance-based models. Using a publicly available dataset of 7,999 samples, each model is evaluated using key performance metrics, including accuracy, precision, and confusion matrix analysis. The evaluation results show that the ensemble-based model achieves the highest accuracy of 96.62% and precision of 96.53%, outperforming the neural network-based model, which achieves an accuracy of 94.75% and precision of 70.47%. Additionally, the instance-based model achieves an accuracy of 91.12% and a precision of 83.04%. These results indicate the effectiveness of the ensemble-based model for real-time water quality monitoring.
Diabetes Disease Prediction on Unbalanced Data Using SMOTE-Tomek Links and Random Forest Algorithm Titis Fatmah Sukamto; Cathy Lintang Prameswary; Dedi Royadi; Detin Sofia
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.v9i3.7164

Abstract

Diabetes, a chronic condition caused by the body’s incapacity to generate or apply insulin as it should, is characterized by elevated blood sugar. If not treated early, the disease can lead to serious complications. This research aims to implement a machine learning-based classification model to predict diabetes, applying the methodology known as CRISP-DM (Cross-Industry Standard Process for Data Mining). The dataset was obtained from the Health Center of Sukatani Village, Rajeg, with a total of 2,075 records and 21 columns. The SMOTE-Tomek Links resampling technique was used to resolve the data’s class imbalance. Five classification algorithms, Naive Bayes, Random Forest, Logistic Regression, Decision Tree, and K-Nearest Neighbor (KNN), were compared in this study. Experiments revealed that the Random Forest algorithm performed the best with 97% accuracy, which increased to 99.64% after the application of SMOTE-Tomek Links. This best model was implemented in a web-based application using the Streamlit framework. The combination of the CRISP-DM approach, Random Forest algorithm, and SMOTE-Tomek Links proved to be effective in predicting diabetes, so that it can help medical personnel and the community in preventing, managing, and monitoring diabetes optimally.
Production of Butanoic Acid from a Mixture of Sago and Molasses via Fermentation Process Using Clostridium acetobutylicum Echa Raniaputri Ameliya; Abdul Fattaah Naufal Riano; Mutasim Bilah
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.v9i3.7167

Abstract

Butanoic acid is a short-chain volatile fatty acid with wide applications in the chemical, pharmaceutical, and energy sectors. Conventional production of butanoic acid relies on petrochemical synthesis, which raises sustainability concerns. This research aims to produce butanoic acid through microbial fermentation using Clostridium acetobutylicum, a bacterium known for its dual-phase metabolic capability. A mixture of sago starch hydrolysate and sugarcane molasses was used as the carbon source. The study investigated the effect of different substrate ratios (1:3 to 3:1) and fermentation times (24 to 120 hours) on butanoic acid production. Hydrolysis of sago was conducted enzymatically using alpha-amylase, followed by anaerobic fermentation. Analysis using GC-MS revealed that the substrate ratio significantly influenced acid production. The 3:1 sago-to-molasses ratio produced the highest butanoic acid concentration (22.97%) after 120 hours, with no indication of a metabolic shift to solventogenesis. Conversely, the 1:1 ratio reached its peak at 17.89% in just 24 hours, followed by a rapid decline, indicating an early phase shift. These results demonstrate the importance of substrate composition in optimizing acidogenic activity and delaying solventogenesis. The findings support the potential of renewable biomass mixtures for sustainable biochemical production.
Application of Genetic Algorithm Neural Network in Identifying Buildings in Landslide-Prone Areas Bagus Gilang Pratama; Sely Novita Sari; Joko Prasojo
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.v9i3.7168

Abstract

Indonesia is a disaster-prone country, one of which is landslides, which often occur in hilly areas with high rainfall. The impact damages the environment and infrastructure, especially buildings. For effective mitigation, a risk identification system based on artificial intelligence technology is needed. This study applies Genetic Algorithm Neural Network (GANN) in identifying buildings in landslide-prone areas. GANN was chosen for its ability to optimize network weights globally through selection, crossover, and mutation mechanisms, thus avoiding suboptimal local solutions. The dataset consists of 169 data with 12 structural features of the building. The model was configured with genetic parameters such as the number of generations 500, population size of 50, mutation rate of 10%, and the Stochastic Universal Sampling selection method. To Evaluate the performance of model created from dataset, we employed accuracy, precision, recall, and F1-score. The results showed an accuracy of 81% and an average F1-score of 0.82, with the best performance in the "Unsafe" class (recall 0.84). Although it still needs improvement, GANN has proven to have the potential as a decision support tool in data-driven landslide risk mitigation.