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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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IMPLEMENTATION OF FORWARD CHAINING AND NAÏVE BAYES TO DETERMINE THE SEVERITY OF MEASLES IN TODDLERS Andi Husnul Khatimah
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7654

Abstract

Measles is a contagious disease that often affects toddlers and can cause serious complications if not treated appropriately. This study aims to implement the Forward Chaining and Naïve Bayes methods to determine the severity of measles in toddlers. This study does not develop a software-based system, but rather focuses on conceptual implementation and manual calculations using decision tables, rule bases, and probability calculations. The research data were obtained from 20 patients who underwent discussion and validation with experts at Lanto Dg Pasewang Regional General Hospital. A total of 16 symptoms were used as research variables in the analysis process. The Forward Chaining method was applied to determine the diagnosis based on rules designed in accordance with expert knowledge, while the Naïve Bayes method was used to calculate statistical classification probabilities based on available case data.The results showed that both methods were able to effectively determine the severity of measles. However, the Naïve Bayes method produced a higher level of accuracy, while the Forward Chaining method had a lower accuracy rate. The accuracy percentages obtained were 75% for Forward Chaining and 85% for Naïve Bayes. Thus, the probabilistic-based approach provides more optimal determination results than the rule-based approach in the context of this study.
PENGEMBANGAN APLIKASI BERBASIS AUGMENTED REALITY SEBAGAI MEDIA INFORMASI DAN PROMOSI PADA LPK “ZARAYA LIHAY”: DEVELOPMENT OF AN ANDROID-BASED AUGMENTED REALITY APPLICATION FOR INSTITUTIONAL INFORMATION AND PROMOTION: A CASE STUDY OF THE ZARAYA LIHAY VOCATIONAL TRAINING CENTER awang pradana; Annida Zakkiah Az-zahra
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7660

Abstract

Augmented Reality (AR) has emerged as an innovative medium for delivering interactive information beyond the limitations of traditional promotional tools such as brochures. This study presents the design, development, and evaluation of an Android-based AR application for vocational training institutions. The system employs a marker-based approach to provide interactive three-dimensional visualizations of institutional information, including instructors, training packages, vehicles, and learning materials. Performance testing under various lighting conditions consistently achieved a 100% detection rate, while marker occlusion tests reported an average success rate of 78.33%. The usability evaluation explicitly involved 20 respondents and produced a final overall score of 4.94 out of 5 (98.92%), indicating excellent learnability, efficiency, and user satisfaction. The findings confirm that the proposed AR application offers a practical, innovative, and user-friendly solution for enhancing institutional information delivery and promotional effectiveness.
IMPLEMENTATION OF AN INTERNET OF THINGS (IOT) BASED WATER QUALITY MONITORING AND CONTROL SYSTEM FOR DAMS USING ESP 32 amrosi
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7661

Abstract

Clean water quality is a crucial factor in supporting community health and activities, particularly in the Situbondo region, which has dam water sources of uncertain quality due to high turbidity and excessive nutrient content. Conventional water quality monitoring still relies on laboratory testing, which is time-consuming, costly, and requires limited site access. Although previous studies have developed Internet of Things (IoT)-based water quality monitoring systems, most have focused on a single platform and have not integrated a real-time notification system that is easily accessible to users. The gap in this research lies in the lack of a water quality monitoring system that combines a visualization platform, automatic validation, and instant notification in a single integrated architecture. This research presents a novelty in the form of the integration of ESP32 and DHT22 sensors. This sensor was transformed into a water turbidity sensor using the Blynk platform as a data visualization system and Telegram as a real-time notification medium. The research method used was a prototype method, which included stages of listening to customers, building/revising mock-ups, and mock-up trials by customers. The results showed that this system is capable of monitoring water quality in real-time, transmitting sensor data stably via a Wi-Fi network, and providing automatic notifications when water parameters exceed specified thresholds. This system has proven responsive, accurate, and effective in reducing the need for manual monitoring, thus potentially supporting sustainable water quality management.
KLASIFIKASI BUAH SAYUR FRESH DAN ROTTEN MENGGUNAKAN MOBILENETV2 DAN XCEPTION Nur Nafiiyah; Ahmad Fauzil Adhim Febrian
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7664

Abstract

The advancement of artificial intelligence and computer vision has enabled automated quality assessment in agricultural products to reduce subjectivity and inefficiency in manual inspection. This study aims to compare the performance of two transfer learning architectures, MobileNetV2 and Xception, for fruit and vegetable freshness classification. The dataset was obtained from Kaggle and focused on eight classes: fresh and rotten apples, bananas, cucumbers, and tomatoes. To address data imbalance and improve model generalization, data augmentation techniques including rotation, horizontal flipping, and vertical flipping were applied. Both pre-trained models were enhanced by adding a Global Average Pooling layer, a 128-neuron Dense layer, and Batch Normalization. The models were trained using the Adam optimizer with a learning rate of 0.0001 for 20 epochs. Performance evaluation was conducted using accuracy, precision, and recall metrics. Experimental results show that MobileNetV2 achieved an accuracy of 99.43%, while Xception obtained 99.39%, with consistently high precision and recall values. These findings demonstrate that the transfer learning approach is highly effective for fruit and vegetable freshness classification and provides competitive performance compared to previous studies.
KLASIFIKASI ULKUS KAKI DIABETIK MENGGUNAKAN CONVNEXT-TINY, DENSENET201, MOBILENETV2, RESNET50 Nur Nafiiyah; Ahmad Farish Subbanuddin Alawy
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7666

Abstract

Diabetic Foot Ulcer (DFU) is a serious complication of diabetes that may lead to amputation if not diagnosed early. Manual visual identification of DFU is challenging due to the heterogeneous characteristics of ulcer shape and texture. This study proposes an automatic DFU classification approach based on transfer learning using four Convolutional Neural Network (CNN) architectures: ConvNeXt-Tiny, DenseNet201, MobileNetV2, and ResNet50. The dataset consists of 1,055 original images (512 ulcer and 543 normal) used as testing data, while the training data were generated through augmentation techniques including rotation, horizontal flip, vertical flip, contrast adjustment, and brightness enhancement, resulting in 5,275 training images. All models were trained with 224×224×3 image input, using the SGD optimizer with a learning rate of 0.0001 for 30 epochs and a batch size of 2. Model performance was evaluated using accuracy, precision, and recall metrics. Experimental results indicate that ResNet50 achieved the best performance with 99.60% accuracy, 99.33% precision, and 99.88% recall. ConvNeXt-Tiny and DenseNet201 also demonstrated competitive performance with accuracy above 98%, while MobileNetV2 achieved 92.85% accuracy. Comparative analysis with previous studies shows that the proposed approach achieves competitive results. The findings demonstrate that transfer learning combined with appropriate data augmentation can produce an accurate and reliable DFU identification system to support computer-aided diagnosis.
PENINGKATAN KEAMANAN DALAM UJIAN BERBASIS KOMPUTER MELALUI PENGENALAN WAJAH MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORKS (CNN) faris mushlihul amin
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7698

Abstract

  The increasing adoption of Computer-Based Testing (CBT) necessitates reliable security mechanisms to ensure examination integrity. This study aims to develop and evaluate a face recognition-based security system using Convolutional Neural Networks (CNN). The system is built using a dataset of 1,000 facial images from 100 individuals with variations in lighting, expression, and pose, and is designed for real-time identification and verification of examinees. The CNN model is employed to automatically extract facial features and perform identity classification. Experimental results show that the model achieves an accuracy of 95%, with false positive and false negative rates of 3% and 2%, respectively. The average recognition time of 0.75 seconds per individual indicates that the system is capable of real-time operation. Furthermore, the system demonstrates robustness against spoofing attacks, achieving detection rates of 98% for 2D photo attacks and 95% for video-based attacks. The system also integrates automated monitoring and anomaly detection mechanisms to enhance overall security. The results indicate that the CNN-based approach is effective in improving CBT security, reducing the risk of cheating, and maintaining the integrity of computer-based examinations.
PENGEMBANGAN SISTEM WEB UNTUK RESERVASI TEMPAT ONLINE DI MADAME HO SKY LOUNGE SEBAGAI SOLUSI OPTIMALISASI PEMESANAN DAN PENGELOLAAN TEMPAT BAGI PELANGGAN Hilda Fredela Gasendra; Heru Supriyono
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7701

Abstract

The restaurant industry is now adopting digitalization to optimize operational management and improve service quality. Madame Ho, an exclusive restaurant with panoramic city views, is a prime destination for activities ranging from private banquets to business meetings. In line with its service vision of offering an intimate dining atmosphere with custom décor, a systematic reservation mechanism is required to ensure timely service. With a limited capacity of seven tables per day, errors in scheduling and an inefficient manual reservation process can potentially lead to irregularities in booking management. These issues highlight the need for a system capable of managing reservations in a more structured manner.This research aims to develop a web-based reservation system that allows customers to select packages, schedule arrival times, and make payments online. The system also features an admin feature for data management (CRUD) and a sales statistics dashboard. Using the Waterfall method, the system was built using HonoJS as the backend, PostgreSQL as the database, and Vercel as the hosting deployment. The system was evaluated using a Black-box Testing approach, confirming that each system feature operated optimally. Furthermore, a System Usability Scale (SUS) test involving 30 respondents yielded a score of 83.58%, placing it in the "Excellent" category within the acceptable range. The results demonstrate that the system effectively improves operational efficiency and simplifies the online reservation process for customers at Madame Ho.
ANALISIS KUALITAS WEBSITE PT.POS INDONESIA MENGUNAKAN PENDEKATAN WEBQUAL 4.0 MENURUT PERSEPSI ONLINE SELLER Apit Priatna; Arif Maulana Yusuf; Ulia Rahma; Vera Wati; Muhammad Edi Iswanto; Joko Irawan
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7713

Abstract

The rapid development of information technology encourages companies to utilize websites as a medium for providing information and services to users effectively and efficiently. PT. Pos Indonesia, as a courier and logistics service company, utilizes its website to provide various digital services such as tariff information, service coverage areas, and shipment tracking. However, several issues related to website quality have been identified based on user experiences. This study aims to analyze the quality of the PT. Pos Indonesia website based on user perceptions, particularly among online sellers in Karawang Regency. The method used in this study is Webqual 4.0, which measures website quality based on three main dimensions: usability, information quality, and service interaction quality. This research employs a quantitative approach with data collection conducted through questionnaires distributed to 100 respondents who are users of the PT. Pos Indonesia website. The data were analyzed using descriptive statistics and the Importance Performance Analysis (IPA) method to determine the level of conformity between the importance and performance of website services. The results show that the average importance score is 4.39, while the average performance score is 3.03, resulting in a gap value of -1.36. The negative gap value indicates that the quality of the PT. Pos Indonesia website has not fully met user expectations. Therefore, improvements are required in several website service attributes in order to enhance digital service quality and user satisfaction.
RANCANG BANGUN DAN EVALUASI USABILITY SISTEM INFORMASI MAGANG MAHASISWA BERBASIS WEB MENGGUNAKAN RAPID APPLICATION DEVELOPMENT: DESIGN AND EVALUATION OF WEB-BASED STUDENT INTERNSHIP INFORMATION SYSTEM USING RAPID APPLICATION DEVELOPMENT Aisyah Rusdi
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7718

Abstract

Digital-based data services and management are a phenomenon of administrative and evaluation service needs that are very much needed within the Faculty, so it is considered necessary to provide a special application to manage student internship data by applying the Rapid Application Development method in creating a web-based data management application for incremental software development with a short processing time in the sense of a software process that emphasizes a short life cycle of 60-90 days. Data management through digital service media for student internship activities to prepare documentation of internship activities. The web-based student internship application was successfully created according to the wishes and needs of academics and students within the Faculty, such as making it easier for students to apply for internships such as Independent Internships and MSIB, students can also consult with study programs and faculties regarding internships they want to take or apply for without the need for face-to-face meetings and excessive filing. The questionnaire distribution was carried out and filled out by 44 respondents with details of 1 head of the dean's office, 1 staff of the dean's office, 1 head of the IT study program, 1 staff of the IT study program, 1 head of the SI study program, 1 staff of the SI study program and 38 students in order to obtain an average value of the overall results of the web-based student internship application with a result of 86% which is included in the good criteria.
STUDI PERILAKU DAN KESIAPAN PROFESIONAL DI JAKARTA DALAM MENGADOPSI TEKNOLOGI GENERATIVE AI: STUDY OF BEHAVIOR AND PROFESSIONAL READINESS IN JAKARTA IN ADOPTING TECHNOLOGY GENERATIVE AI Jefri Yushendri; Danang Rizki Ginanjar; Asti Nurafala Sahir
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7720

Abstract

The rapid development of Artificial Intelligence (AI), particularly Generative AI, has driven significant transformation across various sectors of society and the global economy. However, at the local level, particularly in DKI Jakarta as the center of national economic activity, there remains a gap between the potential utilization of AI and the readiness to adopt it. This study aims to analyze the behavior and readiness of AI users in Jakarta by comparing the public and private sectors. Data were collected through an online survey of professionals in Jakarta with a total of 805 respondents and analyzed using a quantitative approach, supported by non-hierarchical classification techniques (K-Means Clustering). The results show that the largest group of AI users falls into the Explorer category (51%), followed by the Skeptic category (25%), indicating a high level of interest in AI that is not yet matched by adequate technical readiness. The public sector demonstrates a more innovative and adaptive adoption pattern, while the private sector tends to be more cautious and efficiency-oriented. The findings of this study are expected to serve as a basis for formulating contextual and data-driven digital transformation policies in Jakarta.  

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