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TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Published by Universitas Muhammadiyah Cileungsi
ISSN : 20873336     EISSN : 27214729     DOI : https://doi.org/10.37373/tekno.v13i2
Core Subject :
Aim and Scope Aim The aim of this journal publication is to disseminate the fundamental ideas or ideas that have been accomplished and the study findings in technology, science and informatics. In terms of community sector study outcomes, the Journal of Technoscience primarily reports on the main issues. Scope Science issues Scopes related to this topic include: Agriculture, Climate, Mathematics & Statistics, Applied Physics, Fundamental Science in Engineering, Bioscience & Biotechnology. Engineering and Technology issues Scopes related to this topic include: Mechanical & Structures, Electrical, Communications & Systems, Fuel and Energy, Material, Termal Management, Safety System and Technology, Maintenance Technology, Automotive . Information and Technology issues Scopes related to this topic include: Artificial Intelligence, Computer Science, E-learning & Curriculum, Information Science, Multimedia, Science Technologies, Information Networks, Internet & Mobile Computing, Machine Learning, Information Science.
Arjuna Subject : -
Articles 222 Documents
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Implementation of design thinking method in designing consultation booking features on education platforms Erlin Anggraeni; Ina Maryani; Cindyra Galuhwardani; Saghifa Fitriana
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1804

Abstract

Education plays a crucial role in developing high-quality, competitive, and adaptive human resources in response to rapid changes. Technology has become indispensable in enhancing the quality and efficiency of learning, but final-year students continue to face difficulties in arranging academic consultations in a flexible manner. This issue can hinder thesis completion and disrupt academic progress. Through this research, a digital solution is proposed by focusing on the design of the user interface (UI) and user experience (UX) for a consultation booking feature on an educational platform. The design thinking process was carried out across five sequential steps: emphatize, define, ideate, prototype, and test. Data were obtained from literautre studies and online surveys, forming the basis for design requirements. Usability testing with 55 users demonstrated that the prototype was generally perceived as easy to operate, effective, and supportive of flexible supervision, yielding an overall satisfaction score of 87.27%. These findings demonstrate that design thinking is effective in producing user-centered digital solutions and highlight the potential of the proposed feature to improve academic support services in higher education.
Numerical simulation and analysis of splitting tensile strength of jute/epoxy laminated composites using ANSYS Workbench 2022 Achmad Jusuf Zulfikar; Bonar Sari Monang Naibaho; Mulia; Samuel Marpaung
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1837

Abstract

This study investigates the mechanical behavior of jute/epoxy laminated composites when applied as external reinforcement to cylindrical concrete specimens subjected to splitting tensile stress. Natural fiber-reinforced composites, such as jute, have gained significant attention in recent years due to their environmental sustainability, low cost, and reasonable mechanical performance. The primary objective of this research is to evaluate the effectiveness of jute laminate sheathing in improving the tensile strength of cylindrical concrete structures using numerical simulation. A finite element method (FEM) approach was implemented in ANSYS Workbench 2022 to model and simulate various configurations, including specimens without laminates and with one, two, and three layers of jute/epoxy laminates. The model geometry was based on standard cylindrical specimens with a diameter of 50 mm and a height of 150 mm. Material properties were defined based on experimental data, and appropriate mesh and boundary conditions were applied. Results showed that the addition of jute laminates significantly enhanced the splitting tensile strength, with the highest increase of 241% observed in specimens with three layers. The simulation results were validated against experimental data using ANOVA, confirming a strong correlation (p = 0.5). This indicates that the ANSYS-based FEM simulation is a reliable tool for predicting the mechanical behavior of natural fiber-reinforced composites in structural applications.
Crusher machine design for plastic bottle cap waste recycling process to support sustainability Herry Syaifullah; Indra Setiawan; Albertus Aan Dian Nugroho; Dinda Lutfiah; Dwima Septiar Priambada; Arka Baswara Bimo Sakti
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1860

Abstract

The problem of plastic waste in Indonesia is becoming increasingly urgent every day due to the increase in plastic consumption. The increasing number of plastic bottle caps will have a negative impact on the environment. This problem can be overcome by converting this waste into economically valuable products. One effective solution is recycling, but the current obstacle is the lack of effective tools to optimally crush plastic bottle cap waste. Therefore, it is necessary to design and manufacture a special crusher machine to process plastic bottle cap waste. This study aims to develop a crusher machine specifically designed to process plastic bottle cap waste to support sustainable recycling. . The purpose of this research is to develop innovative technology for crushing plastic bottle cap waste. The method used in this research is the CDIO approach, the research includes stages of problem identification, machine design, prototype fabrication, and performance testing. Several improvements were implemented, including blade geometry modification, addition of a secondary shaft, gear reducer ratio adjustment, and frame redesign for safety enhancement. Test results show that the prototype effectively crushes various types of plastic caps, with improved cutting speed after modifying the gear reducer from 1:30 to 1:20 and adding forked blades. This development supports the recycling industry by providing a more efficient and reliable plastic crushing process. The purpose of this research is to develop innovative technology for crushing plastic bottle cap waste. The method used in this research is the CDIO (Conceive, Design, Implement, Operate) approach, starting from problem identification, design, prototyping, and performance testing. Several innovations were made, such as modifying the shape and thickness of the cutting blade, adding a shaft, changing the gear reducer ratio, and improving the frame design to increase safety and efficiency. The test results showed that the machine can crush various types of plastic, such as bottles and gallon caps, effectively. Changing the gear reducer ratio from 1:30 to 1:20 increased the rotation speed, while modifying the blade to form a branch accelerated the crushing process. This research is important to meet the needs of the industry that continues to grow along with technological advances, so that the process of recycling plastic bottle cap waste can run more efficiently.
Traditionally available street food the market free from harmful chemical additives Shalihat Afifah Dhaningtyas; Aditia Fajar Putra Wibowo; Hanif Khoiry Syammakh; Muhammad Surya Anggara; Qurrota A’yun; Olivia Rahmadhani
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1900

Abstract

All living organisms, including humans, require food to sustain life. Unsafe food leads to health problems. Therefore, this study evaluates the chemical parameters of commonly consumed food items. The research was conducted in a laboratory using a descriptive observational approach to analyze chemical components in selected food samples. A purposive sampling method was employed for sample selection. Testing for borax using the ethanol method, while testing for formalin, rhodamine B, and methyl yellow using a test kit. The results revealed that all tested food samples were free from harmful chemical additives. Specifically, salted fish and wet noodles tested negative for formalin; meatballs and cilok were free of borax; chicken noodle sauce and red sausage did not contain rhodamine B; yellow crackers and yellow tofu tested negative for methyl yellow.  The conclusion of this study was that all food samples tested were safe for consumption
Measurement of SC logistics performance with SCOR-FUZZY AHP method Lusi Mei Cahya Wulandari; Lilis Nurhayati; Ravael Dimas
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1965

Abstract

Sector Logistics plays an important role in maintaining the smoothness and efficiency of national and global supply chains, especially for third-party logistics ( 3PL ) service providers who face demands for reliability and speed of service amidst global competition. The complexity of the logistics process creates the need for a structured and measurable performance evaluation model. This study aims to apply the Supply Chain Operations Reference ( SCOR ) model in identifying and prioritizing key performance indicators ( KPI ) in a 3PL company . The method used involves distributing questionnaires to decision makers in operational and managerial fields. The weights of SCOR performance attributes including reliability, responsiveness, flexibility, cost measures, and asset management efficiency are calculated using the Fuzzy Analytic Hierarchy Process ( FAHP ) method. Furthermore, the Technique for Order Preference by Similarity to Ideal Solution ( TOPSIS ) is used to determine KPI priorities at PT.X. The results of the study show that there are 17 indicators to measure the performance of the freight forwarding sector with the largest weight being operator reliability (0.251) on the reliability attribute, the number of on-time deliveries (0.694) on the responsiveness attribute, load flexibility (0.317) on the flexibility attribute, shipping costs per km (0.379) on the cost attribute and cash-to-cash cycle time (0.479) on the asset management attribute. The SCOR model has proven effective as an initial framework in measuring the performance of 3PL logistics service providers, because it is able to integrate various aspects of performance systematically and quantitatively.
Automated identification of tomato leaf pathologies using deep learning via ResNet18 and a Tailored CNN Architecture Yanto Supriyanto
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1762

Abstract

Tomato leaves (Solanum lycopersicum) are susceptible to various diseases that significantly impact both yield and quality in agricultural production. To enhance the effectiveness of precision agriculture, deep learning-based image classification techniques have emerged as reliable tools for automatically detecting disease symptoms. In this study, two deep learning models are investigated for this purpose: a custom-built Convolutional Neural Network (CNN) and the ResNet18 architecture, which leverages transfer learning. The experimental workflow encompasses preprocessing of input images, data augmentation strategies, architectural development of the custom CNN, and the fine-tuning phase of the ResNet18 model. The evaluation was conducted on a validation dataset comprising 1,000 images evenly distributed across ten disease categories. Results show that the ResNet18 model attained a validation accuracy of 74%, whereas the custom CNN model achieved 55%. While the latter demonstrated lower predictive performance, it offers advantages in computational simplicity and execution speed. These findings suggest that transfer learning with ResNet18 is more suitable for complex, multi-class classification problems on limited datasets, whereas the lightweight CNN model may be better positioned for deployment on low-resource, edge-based agricultural systems.
Comparison of multi-modal deep learning models on medical data Syamsul Dahlan Sugimin; Oktafian Dyah Pangesti; Devytha Nur Alfi; Rajnaparamitha Kusumastuti
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 2 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i2.1987

Abstract

Artificial intelligence-based respiratory disease diagnosis faces challenges in selecting a model training strategy that suits the characteristics of multi-modal data. This study aims to evaluate the effectiveness of fine-tuning compared to baseline models in respiratory disease classification using chest X-ray images, respiratory sound recordings, and clinical tabular data. Four public datasets were used: the COVID-19 Radiography Database (21,165 images, 4 classes), Chest X-Ray Images Pneumonia (5,863 images, binary classification), Respiratory Sound Database (920 recordings, 4 classes), and Lung Cancer Survey Data (309 tabular samples). The baseline models applied to each modality included a simple CNN and frozen ResNet50 for images, a feedforward neural network for audio, and a Random Forest for tabular data. The fine-tuning strategy was carried out by opening the last 10 layers of ResNet50 and VGG16, deepening the neural network architecture for audio, but not applying Random Forest. The evaluation used accuracy, precision, recall, F1-score, and AUC-ROC metrics with 5-fold stratified cross-validation. The results show that fine-tuning improved the accuracy of COVID-19 Radiography from 55% to 66%, with a reduction in false positives from 18% to 9%. The Chest X-Ray Pneumonia and Respiratory Sound datasets showed stable performance at 82% without any improvement from fine-tuning. In contrast, the Lung Cancer Survey dataset experienced a drastic drop from 97% to 65% due to overfitting of the neural network on a limited sample. These findings confirm that fine-tuning is effective for large, complex medical images, while conventional models are more optimal for small tabular data and simple classification tasks.
Structural evaluation of textile machine monitoring system support frame using finite element method Deni Kurnia; Alif Firizky; Nanang Roni Wibowo; Raka Pratindy
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1988

Abstract

The development of an Internet of Things (IoT)-based textile machine monitoring system requires a reliable and mechanically safe support structure. A key issue in current practice is the design of control and monitoring frameworks that rely only on previous models without adequate testing and validation. This study aims to evaluate the structural strength of the textile machine monitoring system support frame using a Finite Element Method (FEA) approach. The 3D frame model was designed using CAD software and analyzed numerically through static simulation with a loading scenario of 100–150 N on the upper part of the structure. The material used is mild steel with mechanical characteristics commonly used in industrial applications. The analysis includes evaluation of Von Mises stress, displacement, and safety factor. The simulation results show a maximum stress of 0.5582 MPa, a maximum displacement of 0.001842 mm, and a safety factor exceeding 12. These values ​​indicate that the designed structure has excellent resistance to static loads and can be categorized as safe for use in industrial environments. This study provides a strong foundation for the development of a reliable and sustainable textile machine monitoring system support structure.
Design and analysis of cooling loads in freezers based on phase change materials Boni Sena; Hadi Nurwahyudin; Kahfi Alwi Kasim; Ksatria Danuaji; Raflihuda Dwi Agusti; Faishal Dzaky Al Hakim; Ribka Bernaditta Naibaho; Nadia Amanah; Fardin Hasibuan
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 2 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i2.1993

Abstract

Improving energy efficiency and temperature stability in freezer systems is a critical issue due to high energy consumption and thermal fluctuations that can degrade the quality of frozen products. Previous research has generally focused on compressor optimization and active refrigeration systems, while the use of Phase Change Materials (PCMs) as passive energy storage media in small-scale freezers is still limited. This study aims to analyze the effect of adding PCMs on the cooling load and thermal performance of the freezer. The methods used include designing a three-layer wall model (aluminum–polyurethane–PCM), calculating conduction energy, sensible heat, and latent heat, and comparing seven types of PCMs using an analytical approach and CoolTools-based thermal simulation. The results show that dry ice gel provides the best performance with the lowest total cooling load of 29.02 W and latent heat of 5.40 × 10⁵ J/kg. The system has a COP of 2.36 with a thermodynamic efficiency of 53.74%. PCM integration has been proven to reduce temperature fluctuations and reduce system workload, thus contributing scientifically to the development of energy-efficient freezer designs based on passive thermal energy storage.
Design and performance analysis of a stick making machine to support the sustainability of palm oil leaf waste Wahyudi; Indra Setiawan; Eduardus Dimas Arya Sadewa; Fattiya Hamada Sakti Isa Putri; Muhammad Rifa'i; Ibnu Ferianto; Nurani Adristi Bunga Nirvana; Gusti Ivan Indie Mahardika
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.2014

Abstract

The palm oil industry is a key sector in Indonesia, yet it produces significant amounts of leaf waste, which has been underutilized and has the potential to pollute the environment. The fundamental problem currently lies in the largely manual process of utilizing leaf waste, making it inefficient for large-scale production. This research aims to design a machine for making palm leaf stick-making from palm leaf waste to support sustainability principles. The method used is Reverse Engineering to analyze and improve the existing machine design, with a focus on the function, capacity, and safety aspects. This data collection was done through field surveys and Focus Group Discussions (FGD). The expected result of this research is a more efficient palm leaf and frond separating machine design, with a target performance of 1.5 kg per 10 minutes (9 kg/hour). The design's advantage lies in the ease of maintenance, especially in removing and replacing shaft and chopping blade components. This research can answer the needs of industry and society for environmentally friendly appropriate technology, thus supporting sustainable waste management. The palm oil industry is a cornerstone of Indonesia's economy, yet it generates substantial amounts of leaf waste that remain largely underutilized, presenting a significant environmental management challenge. The fundamental problem lies in the reliance on manual processing methods, which are inefficient and unsuitable for large-scale waste valorization. This study aimed to design and analyze a stick machine to process palm oil leaf waste, thereby supporting sustainability principles and circular economy initiatives. The research methodology applied was Reverse Engineering, which was used to systematically evaluate and improve upon an existing machine design, with specific attention to enhancing function, operational capacity, and safety. Data collection was conducted through comprehensive field surveys and Focus Group Discussions (FGD) with stakeholders to ensure the design met practical needs. The resulting prototype, powered by a 3 HP electric motor, demonstrated a calculated processing capacity of 9 kg per hour (equivalent to 1.5 kg per 10 minutes). Structural analysis confirmed the machine's robustness, with a calculated shaft safety factor of 3.48, ensuring reliability under operational loads. The design prioritizes ease of maintenance, featuring a mechanism that simplifies the removal and replacement of the shaft and chopping blade components. Furthermore, the machine's operation is environmentally friendly, contributing to waste reduction. In conclusion, this research successfully developed a feasible, efficient, and sustainable technical solution for managing palm oil leaf waste, offering a valuable appropriate technology for both industry and local communities.

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