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RABIT: Jurnal Teknologi dan Sistem Informasi Univrab
Published by Universitas Abdurrab
ISSN : 24772062     EISSN : 2502891X     DOI : https://doi.org/10.36341/rabit
Core Subject : Science, Engineering,
Computer Science & IT Engineering
This journal is called RABIT, where the name comes from two words namely, RAB which means Abdurrab University and IT which means information technology, it can be interpreted as a journal of this journal Journal of Informatics Engineering Study Program Pekanbaru Abdurrab University. This RABIT journal contains various sciences related to the world of computers especially information technology and information systems, namely, this journal is published twice a year where the initial publication is on January 10 while for the second issue which is on July 10.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 696 Documents
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IMPLEMENTASI CONVOLUTIONAL NEURAL NETWORK (CNN) UNTUK KLASIFIKASI 30 JENIS REMPAH BERBASIS WEBSITE Mohammad Faizul Irsyad; Syamsi Ruhama; Winda Widya Ariestya; Diny Wahyuni; Ida Astuti
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7043

Abstract

Indonesia is rich in natural resources, including spices that are widely used as flavor enhancers in food and as traditional herbal medicine. This study aims to develop a web-based spice classification system using a Convolutional Neural Network with the DenseNet121 architecture. The dataset is multi-class and consists of 3,600 images representing 30 types of spices, including fennel, andaliman, tamarind, onion, shallot, garlic, coriander seed, star anise, clove, kaffir lime leaf, basil leaf, coriander leaf, bay leaf, ginger, cumin, cardamom, cinnamon, sappan wood, candlenut, cubeb, aromatic ginger, kluwek, turmeric, pepper, galangal, nutmeg, saffron, lemongrass, vanilla and sesame. The system was developed using the Cross-Industry Standard Process for Data Mining (CRISP-DM) which consists of six stages namely business understanding, data understanding, data preparation, modeling, evaluation and deployment. The dataset was divided into training and testing sets with four proportions 90:10, 80:20, 70:30 and 60:40 to compare model performance. The experimental results show that the 80:20 proportion achieved the best performance with 99% training accuracy, 95% validation accuracy and 95% accuracy as the main performance metric, and this model successfully classified all spice categories. The trained model was then deployed into a website using the flask framework which enables practical use for spice image classification.  
TATA KELOLA TI PADA ORGANISASI KESEHATAN: TINJAUAN LITERATUR SISTEMATIS MENGENAI FRAMEWORK, TANTANGAN, DAN MANFAAT : IT GOVERNANCE IN HEALTHCARE ORGANIZATIONS: A SYSTEMATIC LITERATURE REVIEW OF FRAMEWORKS, CHALLENGES, AND BENEFITS Maharani Swastika; Taufik Akbar; Aris Puji Widodo; Kusworo Adi; Bambang Sugeng Suryatna
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7061

Abstract

Information Technology (IT) in the healthcare sector has driven the growing need for effective IT governance to ensure the security, efficiency, and quality of healthcare services. This study provides a comprehensive review of Information Technology (IT) Governance used in the healthcare sector, particularly in hospitals, by analyzing frameworks, their implementation challenges, and evaluating their impact on service quality and operational efficiency. The method used is a systematic literature review based on PRISMA guidelines of 34 international articles published between 2020 and 2025. The sources identified that COBIT is the dominant best practice framework used to align IT with organizational goals and ensure regulatory compliance. In addition, TOGAF is relevant for auditing, risk management, and enterprise architecture design. Specialist frameworks such as blockchain are proposed for higher data security and integrity. Although these frameworks support improved patient outcomes, data security, and operational efficiency, their implementation is hampered by leadership challenges, technical (such as poor infrastructure and legacy system integration), and complex data regulatory compliance issues.
IMPLEMENTASI TEKNIK ROTOSCOPING PADA VISUALISASI ANIMASI 2D SENI BELA DIRI KARATE Al Latif Ramadhan; Dani Arifudin; Deuis Nur Astrida
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7082

Abstract

Rotoscoping is a 2D animation technique capable of producing accurate visualizations of human movement through frame-by-frame tracing of video references. In this study, the rotoscoping technique is applied to visualize six basic karate movements, which are characterized by dynamic motion, rhythmic patterns, and high visual precision. The aim of this research is to evaluate the effectiveness of rotoscoping in generating accurate, realistic, and efficient motion animation using the ADDIE development model. The analysis stage was carried out through observation and interviews with karate practitioners to determine the movements used as animation objects. The design stage included creating a storyboard and establishing the 2D visual style. The development stage consisted of recording the movements, trimming the footage, and converting it into an image sequence. The implementation stage involved frame elimination, key frame selection, smear frame creation, and the rotoscoping process using Clip Studio Paint. The evaluation stage was conducted through alpha testing based on three main aspects: motion accuracy, visual and aesthetic quality, and rotoscoping efficiency. The results show that most evaluation indicators were categorized as “Appropriate.” The animated movements appear natural, proportional, and consistent with the reference video. The frame elimination process successfully reduced 75%–83% of the original frames without significantly reducing motion clarity. Although minor frame rate inconsistencies were found, they did not affect the overall continuity of the animation. Therefore, the rotoscoping technique is proven effective in producing precise 2D karate animations and has strong potential for further development as a digital learning medium.
IMPLEMENTASI TEKNIK ALONG PATH ANIMATION SEBAGAI MEDIA SIMULASI VISUAL JALUR TRANS BANYUMAS Danu Iqbal Maulana; Dani Arifudin; Suliswaningsih
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7087

Abstract

This study implements the Along Path Animation technique to visualize the Trans Banyumas bus route, aiming to present travel flow and route direction in a clear, consistent, and accurate visual simulation. The study is motivated by a decline in Trans Banyumas ridership, which has been associated with limited access to and clarity of service information related to routes, travel flow, and operational procedures. Media development was conducted using the ADDIE (Analysis, Design, Development, Implementation, Evaluation) model. Visual assets were designed and animated using Adobe After Effects, applying the Along Path Animation technique to enable the bus object to move precisely along predefined route paths. The animation was evaluated through alpha testing and expert validation, focusing on technical aspects such as motion smoothness, path accuracy, orientation consistency, visual synchronization, and overall animation performance. The results indicate that the application of Along Path Animation reduced the number of keyframes from 17 to 9, or approximately 47%, improving motion consistency and production efficiency. Overall, the technique is considered reliable and practical for public transportation route visualization. Future research is recommended to involve end-user testing and real-time mobility data integration to further assess animation effectiveness.
PERANCANGAN FILM ANIMASI 2D CERITA RAKYAT SAMBAS ”PERISTIWA DI TANJUNG DATOK” DENGAN METODE MDLC Agung Damar Jati; Yuda; Noferianto Sitompul; Narti Prihartini; Naufal Aulia Fiermeiza; Vanie Wijaya; U Heri Mulyanto; Lang Jagat; Sri Wahyuni; Erifa Syahnaz
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7088

Abstract

Temajuk Village, located in Paloh District, Sambas Regency, West Kalimantan, boasts a unique natural landscape, culture, and rich history. One important part of this village's cultural heritage is the folktale "The Events at Tanjung Datok," which contains moral values, local wisdom, and the philosophy of life of the local community. Unfortunately, this story is still limited to oral tradition and has not been visually documented. The lack of interest in literacy among some Sambas residents means that knowledge of this story remains limited to the community around Tanjung Datok. Until now, the story has not been transformed into a more effective medium to keep up with current developments so that it can reach a wider audience, one of which is through 2D Animation visualization. The development method used in making 2D animated films is the Multimedia Development Life Cycle (MDLC), which consists of six stages: concept, design, material collection, production, testing, and distribution. This method was chosen because it is able to provide a systematic and structured approach to the animation production process. The creation of a 2D animated film of Sambas folklore entitled "Events in Tanjung Datok" aims to document and visualize the Sambas folklore located in Tanjung Datok in the form of a 2D animated film. This animated media is expected to be an educational resource that can increase public understanding of local history and culture. This research is expected to produce an interesting and informative 2D animation, so that the moral message and cultural values ​​of the story "Events in Tanjung Datok" can be conveyed effectively to the audience, while strengthening the local cultural identity of Temajuk Village. Based on the questionnaire test results using the Likert scale technique, conducted on two material experts and two media experts, with a total score of 81% and 97% respectively. In addition, the questionnaire was also tested on 30 members of the general public with a score of 93%. Based on the test results, it can be concluded that, in general, respondents gave a very good assessment, and this film is worthy of publication. It is hoped that it can later become an educational medium that can be used by the public, especially in the world of education.
ANALISIS PERBANDINGAN KINERJA ALGORITMA SVM, NAÏVE BAYES, DAN KNN DALAM KLASIFIKASI SENTIMEN ULASAN APLIKASI PINTEREST DENGAN SMOTE DAN PSO Muhamad Dimas Firmansyah; R. Rhoedy Setiawan; Yudie Irawan
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7095

Abstract

The rapid growth of social media usage has led to a continuous increase in the volume of user reviews, necessitating automated analysis based on machine learning techniques. This study focuses on the development of a sentiment classification model for Pinterest application reviews on the Google Play Store by evaluating three algorithms: Support Vector Machine (SVM), Naïve Bayes, and K-Nearest Neighbors (KNN), combined with Synthetic Minority Oversampling Technique (SMOTE) and Particle Swarm Optimization (PSO). A total of 10,000 reviews were collected through web scraping and processed through preprocessing stages, lexicon-based labeling using InSet, TF-IDF feature extraction, and an 80:20 data split. SMOTE was first applied to balance the class distribution, followed by PSO for parameter optimization of each classification algorithm. The experimental results indicate that SVM achieved the best performance, attaining 95% accuracy with a more balanced F1-score after the application of SMOTE and PSO, while Naïve Bayes and KNN remained sensitive to class imbalance. As the final output, this study developed a Streamlit-based prediction dashboard to display sentiment results in real time, thereby supporting practical and efficient analysis of user perceptions. These findings confirm the effectiveness of combining SVM, SMOTE, and PSO as an optimal approach for sentiment classification on imbalanced review data.  
SMARTSCAN-DFU: SISTEM DETEKSI DINI LUKA KAKI DIABETES MENGGUNAKAN DEEP CONVOLUTIONAL NEURAL NETWORK (CNN) Indah Hairunisah; Ida Nurhaida; Revaldo Ilfestra Metsi Zen
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7101

Abstract

Diabetes mellitus is a chronic non-communicable disease with a continuously increasing global prevalence. The number of adults living with diabetes worldwide has reached approximately 589 million, with 252 million remaining undiagnosed. One of the most serious complications is Diabetic Foot Ulcer (DFU). This study developed SmartScan-DFU, an early detection system for diabetic foot ulcers based on deep learning, by comparing four model architectures: Custom CNN, EfficientNet-B3, ResNet-18, and ResNet-50. The dataset consists of 4,446 images obtained from the Roboflow Universe platform. Evaluation results show that ResNet-50 achieved the best performance with an accuracy of 87.19%, precision of 0.87, recall of 0.87, and F1-score of 0.87. This model outperformed ResNet-18 (81.22%), EfficientNet-B3 (72.44%), and Custom CNN (61.00%). The comparison indicates that more advanced CNN architectures, particularly ResNet-50, demonstrate superior spatial feature extraction and generalization capabilities for DFU image variations. The best-performing model was then integrated into a Flask-based web interface, enabling automatic, fast, and accurate classification of DFU images. This system is expected to assist in the early digital diagnosis of diabetic foot ulcers, accelerate clinical decision-making, and contribute to achieving the Sustainable Development Goals (SDG) point 3 on good health and well-being.
ANALISIS KOMPARATIF ARSITEKTUR XCEPTIONNET DAN EFFICIENTNETB0 UNTUK ATRIBUSI PROVENANCE CITRA DEEPFAKE MULTI-KELAS: COMPARATIVE ANALYSIS OF XCEPTIONNET AND EFFICIENTNETB0 ARCHITECTURES FOR MULTI-CLASS DEEPFAKE IMAGE PROVENANCE ATTRIBUTION Ronaldus Morgan James
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7104

Abstract

The rapid evolution of generative artificial intelligence (AI) models such as DALL·E, Midjourney, and Stable Diffusion has intensified the risk of visual disinformation, as synthetic images increasingly resemble real ones. Traditional binary detection methods (real vs. fake) have become insufficient, creating a growing need for provenance attribution, i.e., identifying the specific generative model responsible for producing an image. This study presents a comparative evaluation of two Convolutional Neural Network (CNN) architectures—XceptionNet and EfficientNetB0—for multi-class attribution of synthetic images. The primary objective is to evaluate and compare the effectiveness of both architectures in attributing images to four specific source classes: DALL·E, Midjourney, Stable Diffusion, and real images. Both models were trained and tested using a transfer learning approach on a balanced dataset of 2,000 samples and assessed using accuracy, precision, recall, and F1-score. Experimental results show that EfficientNetB0 outperforms XceptionNet, achieving 95.2% accuracy compared to 93.5%, while also exhibiting more stable training behavior and stronger discriminative capability for visually similar classes. The findings indicate that EfficientNetB0 offers a more reliable balance of computational efficiency and feature extraction performance, making it a suitable architecture for provenance attribution tasks involving generative AI imagery.  
IMPLEMENTASI BLOCKCHAIN TERINTEGRASI ANDROID SEBAGAI IDENTITAS DIGITAL DALAM DSCUMI Muh. Rafianto; Erick Irawadi Alwi; St. Hajrah Mansyur
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7110

Abstract

Conventional digital identity systems often rely on centralized authorities that are vulnerable to data breaches and manipulation. The Developer Student Club Universitas Muslim Indonesia (DSC UMI) community requires a membership verification mechanism that is credible, secure, and preserves user privacy. This research aims to implement a decentralized digital identity system fully integrated on the Android platform using blockchain technology and Zero-Knowledge Proofs (ZKP), where the entire system logic—including blockchain interactions and cryptography—is processed independently on the client side (backendless) without dependence on intermediary servers. The development method applies a Minimum Viable Product (MVP) approach with a mobile-first architecture. The system is built on native Android using the Kotlin language, integrated with the Polygon Amoy Testnet network via the Web3j library. Authentication utilizes local biometric sensors to generate cryptographic proofs based on SHA-256 hashes without storing raw data on the server. White box testing results show that the application successfully connects to the MetaMask digital wallet, validates anti-duplication logic on the Smart Contract, and automatically issues a Soulbound Token (NFT) as legitimate proof of membership. In conclusion, blockchain integration on mobile devices is proven effective in delivering Self-Sovereign Identity (SSI) that is transparent and auditable without compromising the privacy of community member data.  
MENINGKATKAN AKURASI SENSOR SUHU PADA KURSI RODA CERDAS SMATSI MELALUI IMPLEMENTASI ALGORITMA REGRESI LINEAR Muhammad Zakyul Fikri; Wahid Miftahul Ashari; Firman Asharudin
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7111

Abstract

Non-contact infrared (IR) temperature sensors on Smart Wheelchairs are important for thermal health monitoring, but they are susceptible to a significant decrease in accuracy (bias) due to non-contact factors and dynamic operational environment variations, such as outdoor exposure. This research aims to improve the accuracy of the MLX90614 IR Sensor on the SMATSI Smart Wheelchair using the Linear Regression (LR) algorithm as a computationally light calibration solution. Data collection was carried out in four crucial scenarios, including Controlled Indoor and Exposed Outdoor conditions. The initial analysis results showed that the Raw IR sensor's Absolute Error reached 0.81℃ in the outdoor scenario, which is much higher than the contact sensor's (0.24℃–0.27℃), validating the presence of extreme environmental bias. The developed Linear Regression model achieved a very high fit, evidenced by a Coefficient of Determination (R²) of 0.995, a Mean Absolute Error (MAE) of 0.056℃, and a Root Mean Square Error (RMSE) of 0.11℃. The calibration implementation successfully reduced the Absolute Error substantially in the Exposed Outdoor scenario, dropping from 0.81℃ to just 0.49℃, proving the efficacy of LR in neutralizing dynamic environmental bias. This calibration model is specific and optimal for non-contact sensors, but is not suitable for contact sensors whose baseline accuracy is already high.

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