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JSAI (Journal Scientific and Applied Informatics)
Published by Universitas Muhammadiyah Bengkulu
ISSN : 26143062     EISSN : 26143054     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal terbitan dibawah fakultas teknik universitas muhammadiyah bengkulu. Pada jurnal ini akan membahas tema tentag Mobile, Animasi, Computer Vision, dan Networking yang merupakan jurnal berbasis science pada informatika, beserta penelitian yang berkaitan dengan implementasi metode dan atau algoritma.
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Articles 538 Documents
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Deteksi Kecurangan Akademik Berdasarkan Dokumen Tulisan Tangan Menggunakan Siamse ResNet Approach Azhar Andika Putra; Bakhtiar K; Firga Abel Astiawan; Muhammad Al Hapiz
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 3 (2025): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i3.9388

Abstract

Academic cheating, particularly involving the forgery of handwriting documents, has become a significant challenge in the field of education. One of the most difficult modes to detect is identity misuse, where an individual writes or completes tasks on behalf of someone else. This study aimed to develop an academic cheating detection model based on handwriting using the Siamese Network approach and cosine similarity. The experiment was conducted using an HP Z8 G5 device equipped with two NVIDIA RTX 6000 GPUs, and the dataset used came from Universitas Sjakhyakirti. The dataset consisted of 101,475 pairs of handwriting images, each labeled as 1 (similar) for pairs from the same writer and 0 (dissimilar) for pairs from different writers. The data was divided into 70% for training, 15% for validation, and 15% for testing. This research dataset was sourced from handwriting documents of 450 different students, consisting of 450 positive pairs (label = 1) and 101,025 negative pairs (label = 0). The model was evaluated using a cosine similarity threshold of 0.5, with training accuracy reaching 95.34%, validation accuracy at 84.12%, and testing accuracy at 83.87%. This study contributes to the development of a handwriting-based academic cheating detection system that can be implemented in higher education institutions.
Klasifikasi Spesies Ikan di Sumatera Selatan Berdasarkan Citra Bawah Air Menggunakan ResNet-50 Lemi Iryani; Nia Umilizah; Firga Abel Astiawan; Muhammad Al Hapiz
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 3 (2025): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i3.9389

Abstract

Fish species classification in underwater ecosystems posed a significant challenge, particularly due to poor lighting that affected the quality of underwater images and decreased the accuracy of species identification. This study aimed to improve the accuracy of fish species classification in South Sumatra based on underwater images by utilizing the Super-Resolution Generative Adversarial Network (SRGAN) to enhance image quality and ResNet-50 for species classification. The research employed a Dell XPS 13 9310 device with an Intel Core i7 processor and 16GB of RAM for model training. Fish image data were collected from Google Images and YouTube according to predefined fish species, including Oreochromis mossambicus (Mujair), Oreochromis niloticus (Nila), Johnius trachycephalus (Gulamah), Eleutheronema tetradactylum (Senangin), and Chanos chanos (Bandeng). The data was divided into 70% for training, 15% for validation, and 15% for testing. The experimental results showed that the developed model achieved a training accuracy of 94.10%, validation accuracy of 88.25%, and testing accuracy of 84.68%. This research contributed to the field of underwater image classification and can be applied to conservation and monitoring of fish species in aquatic ecosystems.
Analisis Sentimen Layanan Kesehatan Klinik Yamet Komentar Instagram Dengan Naive Bayes Reina Salsa Kinanty; Ari Wedhasmara; Rizka Dhini Kurnia
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 3 (2025): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i3.9394

Abstract

The rapid advancement of information technology has driven the healthcare sector to adopt digital platforms in order to enhance service efficiency and accessibility. Yamet Clinic Palembang, as a therapy center for children with special needs, has utilized social media as its primary communication channel, although its official website has not yet been fully optimized. The main issue addressed in this study is the lack of understanding regarding public perception of the clinic’s digital services. Therefore, this research aims to analyze public sentiment toward Yamet Clinic Palembang’s services through comments posted on its official Instagram account. The Naïve Bayes algorithm was selected due to its strong performance in text classification tasks involving limited datasets and low computational complexity. The research process includes text preprocessing, feature weighting using Term Frequency–Inverse Document Frequency (TF-IDF), and the application of the Synthetic Minority Over-sampling Technique (SMOTE) to balance data distribution among sentiment categories. The experimental results indicate that the developed model successfully classified public opinions into three categories—positive, neutral, and negative—with an accuracy rate of 70%. The combination of TF-IDF, Naïve Bayes, and SMOTE proved effective in capturing public perceptions of digital health services. Practically, the findings provide valuable insights for Yamet Clinic Palembang in developing a more adaptive digital communication strategy and theoretically contribute to the advancement of sentiment analysis research within the healthcare service context in Indonesia.
Implementasi SPBE-FORGE(6D) sebagai Framework Enterprise Architecture dalam Percepatan Transformasi Digital Pemerintah Daerah Setiawan Assegaff; Lola Yorita Astri; Kurniabudi
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 3 (2025): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i3.9402

Abstract

Digital transformation within local governments requires a standardized architectural framework to ensure service integration, data consistency, and efficient information technology governance. This study examines the implementation of SPBE-FORGE(6D) as an Enterprise Architecture framework designed to support the acceleration of Indonesia’s Electronic-Based Government System (SPBE). The evaluation employed Enterprise Architecture Success Metrics, including architecture artefact quality, system interoperability, application efficiency, and data consolidation indicators. The results show that SPBE-FORGE(6D) improved architecture artefact quality by 35–36%, reduced application duplication by 41%, decreased data silos by 44%, and enhanced digital service integration by 150%. These findings demonstrate that SPBE-FORGE(6D) effectively strengthens IT governance, improves cross-domain architectural integration, and significantly contributes to accelerating local government digital transformation in an efficient, standardized, and sustainable manner.
Integrasi Perhitungan BMI dan TDEE pada Aplikasi Pemantauan Gaya Hidup Sehat Ulya Nidaul; Irma Handayani
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 3 (2025): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i3.9414

Abstract

This study aims to evaluate the performance of a healthy lifestyle monitoring application integrated with Body Mass Index (BMI) and Total Daily Energy Expenditure (TDEE) calculations. The evaluation focuses on three primary aspects: usability using the System Usability Scale (SUS), adherence through usage consistency monitoring, and effectiveness through pre–post statistical analysis. The study involved 30 respondents for usability assessment and 30 participants for adherence measurement and statistical testing. The findings show that the application demonstrates excellent usability with an SUS score of 82.4. User adherence reached 63.3%, surpassing the minimum target set for the study. Additionally, the statistical test resulted in p = 0.003, indicating a significant difference between pretest and posttest conditions. These results suggest that the application provides a positive user experience, maintains user engagement, and has a measurable impact on users’ understanding and behavior in monitoring their health status and daily energy needs.
Perancangan Aplikasi Rawi pada Android Mobile Siti Zahrotul Fajriyah; Nurul Ilmi; Rana Zaini Fathiyana; Hesmi Aria Yanti; Aisyah Novfitri
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 3 (2025): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i3.9427

Abstract

The digital transformation has shifted religious literacy consumption patterns towards mobile platforms requiring high accessibility. However, existing Rawi applications are predominantly image-based, limiting display flexibility and readability for users across different ages, especially the elderly. This study aims to design a Rawi application on Android Mobile implementing an offline-first approach to ensure fast and inclusive content access. The research method employs a Mixed Method with Design Thinking, comprising Empathize, Define, Ideate, Prototype, and Test stages. The application is designed based on the Flutter framework with imaging SQLite local database and Firebase synchronization. The design testing involves functional testing and non-functional testing (Heuristic Evaluation, Cognitive Walkthrough, and First-Click Testing). The results indicate that all functional requirements are met, and the design is considered intuitive with a First-Click success rate of 91.6%, exceeding the feasibility threshold of 87%. This study concludes that the digital text-based Rawi application design successfully enhances accessibility and user experience through personalization features such as font resizing, advanced searching, as well as bookmark and favorite management.
A SISTEM PENDUKUNG KEPUTUSAN MEMILIH PERGURUAN TINGGI MENGGUNAKAN METODE ANALYTICAL HIERARCHY PROCESS (AHP) Anton Topadang; Yusni Nyura; M. Zainul Rohman
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 3 (2025): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i3.9435

Abstract

Choosing a university is a multi-criteria decision-making process that requires a systematic approach to ensure objective and transparent recommendations. This study applies the Analytical Hierarchy Process (AHP) to determine the priority weights of criteria in university selection. The research stages include constructing a decision hierarchy, conducting pairwise comparisons, calculating weights, and performing consistency validation. The results indicate that criterion K1 is the most dominant factor with a weight of 0.447, followed by K2 with 0.227 and K5 with 0.161. Meanwhile, K3 and K4 have relatively lower weights. The Consistency Ratio (CR) value of 0.038 confirms that the judgments are consistent and meet the acceptable threshold of CR < 0.1. These findings demonstrate that AHP provides a robust and measurable evaluation framework for university recommendation systems. The proposed model supports users in making informed decisions based on systematic and justifiable preference weighting.
Implementasi Fuzzy Mamdani untuk Klasifikasi Kualitas Laptop Berdasarkan Parameter Spesifikasi Bambang Cahyono; Agusdi Syafrizal; Subhan Hartanto
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 3 (2025): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i3.9436

Abstract

This study implements the Mamdani fuzzy logic method to classify laptop quality based on key technical specifications, including processor performance, RAM capacity, storage type, and price. The fuzzy model was developed using linguistic membership functions and rule-based inference to represent expert judgment patterns. System performance was evaluated using the Mean Absolute Error (MAE) metric, which measures the average deviation between the model output and expert reference values. The results show that the Mamdani fuzzy model provides highly accurate and consistent classifications, indicated by a MAE value of 0.027 (2.7%). The error values for each laptop sample ranged from 0.02 to 0.04, demonstrating the model’s stability and effectiveness across various specification levels. These findings confirm that Mamdani fuzzy logic is suitable for laptop quality classification and can serve as a foundation for the development of intelligent recommendation systems for consumer electronics.

Page 54 of 54 | Total Record : 538

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