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JRST (Jurnal Riset Sains dan Teknologi)
Published by Universitas Muhammadiyah Purwokerto
ISSN : 25799118     EISSN : 25499750     DOI : http://dx.doi.org/10.30595/jrst
Core Subject : Science, Engineering,
Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering
JRST (Jurnal Riset Sains dan Teknologi) adalah jurnal peer reviewed dan Open-Acces. JRST merupakan jurnal yang diterbitkan oleh Lembaga Publikasi Ilmiah dan Penerbitan (LPIP) Universitas Muhammadiyah Purwokerto. JRST mengundang para peneliti, dosen, dan praktisi di seluruh dunia untuk bertukar dan memajukan keilmuan di bidang sains dan teknologi yang meliputi bidang Matematika, Kimia, Biologi, Teknologi Rekayasa dan Keteknikan, Farmasi, Geografi, Komputer dan Teknologi Informasi. Dokumen yang dikirim harus dalam format Ms. Word dan ditulis sesuai dengan panduan penulisan. JRST terbit 2 kali dalam setahun pada bulan Maret dan September.
Arjuna Subject : Energi (semua kategori) - Energi (Lain-Lain)
Articles 214 Documents
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Optimization of CNN Architectures for Accurate Brain Tumor Classification: A Comparative Study Nurul Huda; Herman Yuliansyah; Maulany Citra Pandini
JRST (Jurnal Riset Sains dan Teknologi) Volume 9 No. 2 September 2025: JRST
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/jrst.v9i2.26398

Abstract

Automatic classification of brain tumors from MRI images is crucial for supporting early diagnosis and improving treatment planning. However, manual diagnostic processes remain limited by subjectivity and resource constraints. This study aims to optimize brain tumor classification by conducting a comparative analysis of six Convolutional Neural Network (CNN) architectures: VGG16, VGG19, MobileNet, InceptionV3, AlexNet, and Xception. The MRI datasets were sourced from open repositories and processed through normalization, noise reduction, segmentation, and data augmentation. All CNN models were implemented using transfer learning and trained under consistent parameters. Model performance was evaluated based on accuracy, sensitivity, specificity, and F1-score. The results revealed that the Xception and InceptionV3 architectures achieved the highest classification performance, with validation accuracies of 97.9% and 96.1%, respectively. MobileNet also performed competitively at 95.6%, offering notable computational efficiency. In contrast, VGG19 and AlexNet yielded lower validation accuracies and exhibited signs of overfitting. These findings highlight the effectiveness of modern CNN architectures that incorporate depthwise separable convolutions and residual connections in extracting complex features from brain MRI images. Therefore, models such as Xception and MobileNet are strong candidates for implementation in computer-aided diagnosis systems in resource-constrained clinical environments.
Soil-Derived Endospore-Forming Bacillus Bacteria Producing Protease Mazidah Noer Inayah; Suci Indah Budiarti; Rizal Khoirun Alfisah
JRST (Jurnal Riset Sains dan Teknologi) Volume 9 No. 2 September 2025: JRST
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/jrst.v9i2.26600

Abstract

Proteases are widely utilized in many industries, including waste treatment, textiles, detergents, food processing, and medicines. This encourages researchers to discover novel sources of these enzymes. Exploration and isolation of putative proteolytic bacteria from the soil is one promising approach. The purpose of this study is expected providing the bacterial isolates that will produce superior proteases. Proteolytic bacteria were isolated from soil samples using the spread plate technique and selective skim milk agar media. The formation of clear zones and the determination of the proteolytic index were the starting point for a qualitative analysis of protease activity. Protease activity was determined quantitatively. The substrate is 1% casein dissolved in a 0.2 M tris-HCl buffer at pH 7.5, while the standard is tyrosine. The quantitative measurement of protease activity was carried out concurrently with the bacterial growth curve determination. The proteolytic bacteria P02 was successfully isolated in this research, having a protease enzyme activity of 0.867 U/mL and a proteolytic index of 0.8 ± 0.1. Protease activity peaked when the bacterial growth was in the logarithmic phase. Proteolytic bacterial P02 was Gram-positive and possesses the ability to form endospores and has a rod-shaped cell morphology. According to the outcomes of biochemical physiological testing, the bacterial P02 is considered to be the genus of Bacillus sp. The proteolytic bacteria P02 has potential to provide a sustainable and renewable source of protease, which is widely employed in industry and biotechnology.
Analysis of the Implementation of Drug Control Category A with MMSL in Hospital Pharmacy Installation on Drug Values, ITOR and Stock Out Herayanti Hermawan; Yusi Anggriani; Hesty Utami Ramadaniati; Cipto Darmodjati Kumolo
JRST (Jurnal Riset Sains dan Teknologi) Volume 9 No. 2 September 2025: JRST
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/jrst.v9i2.26723

Abstract

Effective drug management is crucial for enhancing both economic performance and patient health outcomes in healthcare settings. This study aims to evaluate the implementation of drug inventory control using the Minimum Maximum Stock Level (MMSL) method at Hospital “X” in Purwakarta. Employing an experimental research design, this study conducted a comparative analysis of drug consumption before and after the application of the MMSL method, focusing on key metrics such as inventory value, inventory turnover (ITOR), and stock-out rates. The study's population comprised Category A medications, totaling 106 items, with an investment value of constituting 70.6% based on ABC analysis. Data were analyzed using the Wilcoxon signed-rank test to assess the significance of the MMSL method's impact. Our findings revealed notable differences in inventory value, ITOR, and stock-out rates between the baseline consumption (Rp. 830,213,174; ITOR 2.47; stock-out Rp. 6,967,778) and the MMSL implementation period (Rp. 627,919,174; ITOR 3.15; stock-out Rp. 3,776,316), with statistical significance levels of 0.045, 0.000, and 0.300, respectively. The results indicate that the MMSL method significantly enhances drug inventory management in the hospital setting, underscoring its effectiveness in optimizing pharmaceutical resource allocation.
Implementation of Smart Contracts in Electronic Voting (Case Study: Election of the President and Vice President POLNES Student Executive Board) Rahmat Wahyudi; Muhammad Farman Andrijasa; Noor Alam Hadiwijaya
JRST (Jurnal Riset Sains dan Teknologi) Volume 9 No. 2 September 2025: JRST
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/jrst.v9i2.26902

Abstract

The election of the candidates for President and Vice President of the Samarinda State Polytechnic Student Executive Board (BEM) still relies on conventional paper-based voting, which is susceptible to manipulation, ballot damage, and time-consuming vote counting. This research seeks to develop design and test for blockchain-based e-voting system prototype utilizing smart contracts to enhance efficiency, security, and transparency. Employing the Waterfall methodology, the research includes requirement analysis, system design using flowcharts and UML use case diagrams, smart contract implementation in Solidity on a local Ethereum network (Ganache), and testing via unit testing for smart contracts using Truffle and BlackBox testing for the user interface. Results demonstrate the system’s ability to automate the election process, including candidate and voter registration, identity verification via student ID, prevention of double voting, and real-time vote counting. Blockchain technology ensures immutability, transparency and guarantees data integrity. The results of this research can be an alternative solution that is more efficient, secure and transparent, by minimizing the risk of data manipulation, saving logistics costs, potential damage to voting media and accelerating the vote counting process which is automatically calculated by smart contracts. Overall, this system proves the potential of blockchain technology and smart contracts as a modern alternative to electronic voting systems.

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