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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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THE BENEFIT ANALYSIS OF P2P LENDING USING SVM WITH TEXTUAL FEATURE AUGMENTATION: ANALISIS MANFAAT P2P LENDING BERBASIS SVM DAN AUGMENTASI FITUR TEKS Rengganis Nurul Aini H; Riza Adrianti Supono
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.5870

Abstract

This study focuses on sentiment analysis of user reviews from the top 10 peer-to-peer (P2P) lending applications using Support Vector Machines (SVM) enhanced with linguistic feature augmentation. A total of 73,955 reviews—approximately 60% in Indonesian and 40% in English—were analyzed. The research included descriptive analysis, text preprocessing, word weighting, data labeling, and data visualization. Textual feature augmentation included sentiment polarity scores, part-of-speech (POS) tag frequencies, and domain-specific keywords extracted from a curated corpus to enrich the input space for classification. The SVM model with a Radial Basis Function (RBF) kernel achieved 91.29% accuracy in classifying positive and negative sentiments. Results indicated a predominantly positive perception among users, as reflected in frequently used terms such as “good,” “easy,” and “fast,” suggesting high user satisfaction. However, concerns regarding security and technical issues were also present, captured by terms such as “verification” and “data.” Word cloud visualizations highlighted key sentiment trends. These findings suggest that while public distrust persists in certain areas, positive sentiments significantly outweigh negative concerns. This provides actionable insights for service providers and policymakers to enhance platform reliability, address user pain points, and foster greater trust in P2P lending services.
MODEL KEPUTUSAN PEMILIHAN ASISTEN LABORATORIUM MENGGUNAKAN LOGIKA FUZZY TSUKAMOTO : LABORATORY ASSISTANT SELECTION DECISION MODEL USING TSUKAMOTO FUZZY LOGIC Mhd. Galih Khairi; Armansyah
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.5881

Abstract

The selection of the right laboratory assistant is very important to support the smooth running of the practicum process in the academic environment. However, conventional selection methods still have weaknesses, such as subjectivity in assessment and time-consuming processes. Therefore, this study develops a decision model based on Tsukamoto fuzzy logic to improve the objectivity and efficiency of laboratory assistant selection. This model uses five main criteria in the assessment, namely academic grades, expertise, ethics, programming tests, and communication skills. The results of the study indicate that the Tsukamoto fuzzy method can produce more transparent and accurate decisions compared to conventional methods. Trials with several candidates show that this model is able to categorize candidates based on the level of eligibility with high accuracy and a margin of error of 0%. Thus, the implementation of this method is expected to improve the effectiveness of the laboratory assistant selection process more fairly and efficiently.
PENGEMBANGAN SISTEM MONITORING ALAT PEMADAM API RINGAN (APAR) BERBASIS WEBSITE DENGAN METODE AGILE Winanti Winanti; Muhammad Raihan; Riyanto Riyanto; Jumiran Jumiran; Nurasiah Nurasiah; Jainuri Jainuri
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.5888

Abstract

The Light Fire Extinguisher (APAR) Monitoring System at PT. Erje London Chemical in this case known as PT XYZ is currently not integrated. Several problems in APAR management are data that is not well documented, information on the location, condition, and maintenance schedule of APAR is still done manually so that it is difficult to arrange a periodic maintenance schedule. A Monitoring APAR information system is needed in the form of a Website-based application that is able to provide information on APAR in real time and facilitate data access. The system is designed to facilitate monitoring of APAR conditions, facilitate reporting, and ensure that APAR is ready to use. The data collection method is carried out through literature studies from previous research and books and based on the results of interviews with stakeholders. The system is built based on a website and the system development uses the Agile method and testing is carried out using blackbox testing, the results of which are that all features have been tested and the results are all successful. The system that is built provides fast and accurate information that is able to overcome problems that occur, reduce the risk of fire, improve work safety, and support the sustainability of company operations at PT. XYZ. The results of this study indicate that the use of the APAR Monitoring information system can provide benefits in terms of managing safety equipment and compliance with work safety standards.
KONSEP VISUALISASI PADA DATA PENGUNJUNG KERAJAAN KASEPUHAN CIREBON: KONSEP VISUALISASI PADA DATA PENGUNJUNG KERAJAAN KASEPUHAN CIREBON Ezra Balqis Alka Ceria; Tora Fahrudin; Ersy Ervina; Azhar Muhammad Fuad
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.5910

Abstract

Keraton Kasepuhan is one of the historical relics in Cirebon, West Java, which is currently the centre of cultural preservation and development. As a cultural tourism destination, a data-driven strategy is required for visitation management and promotion of sustainable tourism development. The purpose of this study is to present a visual representation of tourist visitation data in Kasepuhan Cirebon for the period between June and August 2024. This presentation will facilitate the analysis of visitation trends based on ticket type, time of visit and payment method. The resulting visualisation will provide a more accessible representation of complex data. This research uses a data visualisation methodology. The initial dataset was sourced from Curaweda and then subjected to graphical analysis using techniques such as bar charts, pie charts and tree maps. The purpose of these visualisations was to facilitate the understanding of complex data. This research study explores the integration of data visualisation and technology frameworks in the context of tourism management in Keraton Kasepuhan Cirebon. The analysis uses data visualisation techniques to examine visitation trends, focusing on differentiating factors such as ticket type, time of day and payment method. The results showed that the pass (Kawasan, Museum Pusaka and Dalem Agung Pakungwati) contributed the most revenue (41.7%), with the highest number of visitors in the afternoon. The study also revealed that cash payment methods still dominate compared to digital payment methods. These findings highlight the important role of technology in facilitating transactions, online promotions and real-time data management. The research offers several solutions, including optimising opening hours, implementing special promotions and using data analytics technology to improve management efficiency. The research provides a comprehensive framework for cultural destination managers looking to implement data-driven strategies to increase visitor capacity and economic contribution. This research can visualise tourism visitation trends to support the strategic management of Keraton Kasepuhan. The findings can be used for more effective and sustainable cultural tourism planning and development. This research demonstrates the importance of data visualisation technology in supporting data-driven management of tourist destinations.
SISTEM INFORMASI GEOGRAFIS REKOMENDASI SERVIS KOMPUTER BERBASIS ANDROID: METODE MULTI ATTRIBUTE UTILITY THEORY DAN ALGORITMA A-STAR: GEOGRAPHIC INFORMATION SYSTEM FOR COMPUTER SERVICE RECOMMENDATION BASED ON ANDROID: MULTI ATTRIBUTE UTILITY THEORY METHOD AND A-STAR ALGORITHM Walad Hidayat; Zara Yunizar; Nunsina
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.5997

Abstract

This study developed an Android-based Geographic Information System to recommend computer repair service shops in Lhokseumawe City, addressing the gap in previous studies that have not integrated recommendation and route-finding systems into a single mobile application. Data were collected through surveys of 17 active shops using weighted questionnaires and interviews. The Multi Attribute Utility Theory (MAUT) method is used to evaluate seven criteria, such as years of operation, repair coverage, spare part availability, service cost, warranty, number of technicians, and rating. The A-Star algorithm was applied to calculate the shortest route based on GPS coordinates. Results showed that “JCom” achieved the highest recommendation score (0.810), and the optimal route from the starting point (Informatics Engineering Building, Unimal) to the selected shop was 11,793.74 meters, based on node accumulation. The system proved effective in providing accurate recommendations and efficient navigation, assisting users in choosing the best service shop through a single Android application.
MODEL PERANCANGAN SISTEM TERDESENTRALISASI UNTUK KEAMANAN DATA GENETIKA MANUSIA BERBASIS BLOCKCHAIN DAN IPFS Tri Stiyo Famuji; Alya Masitha; Maulana Muhammad Jogo Samodro; Galih Pramuja Inngam Fanani; Yuniariana Pertiwi
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6015

Abstract

The rapid development of genomic technology has heightened the urgency to address vulnerabilities in centralized systems managing sensitive human genetic data. This study proposes a decentralized system integrating blockchain and IPFS to enhance data security, integrity, and accessibility. Blockchain ensures immutable audit trails and dynamic access control via smart contracts, while IPFS provides scalable off-chain storage using cryptographic hashes (CIDs). The hybrid design separates raw data storage (encrypted via homomorphic encryption) on IPFS from access management on the Ethereum blockchain. A user interface built with React.js and Web3.js enables encrypted data uploads, role-based access requests, and real-time audit monitoring, complying with GDPR/HIPAA standards. Testing demonstrated the system’s effectiveness in preventing unauthorized access and ensuring data traceability. Challenges such as energy efficiency and regulatory compliance were addressed through sharding, layer-2 protocols, and selective data deletion mechanisms. This framework supports secure cross-institutional collaboration in genomic research, promoting public participation and accelerating biomedical innovation. Future work will focus on optimizing computational efficiency and expanding datasets.
ANALISIS FORENSIK DIGITAL PADA FILE STEGANOGRAFI MENGGUNAKAN FTK IMAGER DAN WINHEX DALAM KASUS PEREDARAN NARKOBA DENGAN LIVE FORENSICS Aulia Fitriani Shabira; Fahmi Fachri
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6020

Abstract

Drug trafficking in the digital era is increasingly sophisticated with the utilization of information technology, one of which is the use of steganography techniques to hide information in digital media. This research analyzes the digital evidence hidden in steganography files using the Live Forensics approach. The method used in this research is the National Institute of Standards and Technology (NIST), which consists of four main stages: collection, examination, analysis, and reporting. Digital evidence acquisition was conducted on active devices to obtain data stored in RAM as well as traces of activity in the TOR Browser and Telegram apps. The analysis process used forensic tools such as FTK Imager, WinHex, and Steghide to detect and extract hidden messages in the steganography files. During the investigation, there were several technical challenges, such as the use of TOR Browser which made it difficult to trace the source of the data traffic, as well as other anti-forensic techniques that attempted to erase traces of communication and file storage locations. Addressing these challenges requires live forensics strategies and the utilization of volatile memory to access information that is not permanently stored. The results show that the Live Forensics method is effective in uncovering digital evidence related to drug communication and trafficking, including the storage location of evidence disguised through steganography. With these findings, steganalysis techniques can be used as anti-forensic mitigation in cyber crime investigations. This research contributes to the development of the digital forensics field by demonstrating the successful application of a combination of live forensics acquisition and steganalysis techniques in real-life situations. In addition, the findings generated can be used as a reference in designing standard procedures for investigating cybercrime cases that utilize steganography techniques.
IMPELEMENTASI METODE WEIGHTED SUM MODEL (WSM) DALAM PENYELEKSIAN PESERTA PASKIBRAKA TERBAIK PADA SMAN 1 KUALUH SELATAN BERBASIS WEB: IMPELEMENTATION OF WEIGHTED SUM MODEL (WSM) METHOD IN THE SELECTION OF THE BEST PASKIBRAKA PARTICIPANTS AT SMAN 1 KUALUH SELATAN BASED ON WEB Ade Risky Paradika; Ali Ikhwan
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6022

Abstract

Paskibra adalah pasukan pengibar bendera yang dibentuk dari kalangan siswa-siswi di sekolah. Kegiatan ini merupakan bagian dari materi pembinaan generasi muda yang diatur dalam Keputusan Menteri Pendidikan dan Kebudayaan No. 0416/U/1984 tentang Pendidikan Pendahuluan Bela Negara di sekolah. Aktivitasnya mencakup Peraturan Baris‑Berbaris (PBB), Tata Upacara Bendera (TUB), serta Latihan Kepemimpinan Siswa tingkat Perintis dan Pemula. Penelitian ini dilaksanakan di SMAN 1 Kualuh Selatan untuk menyeleksi calon paskibraka terbaik menggunakan metode Weighted Sum Model (WSM). Pembangunan sistemnya mengikuti model waterfall. Diharapkan, hasil penelitian ini menghasilkan proses pemilihan paskibraka yang lebih objektif karena bobot tiap kriteria telah disesuaikan dengan ketentuan di SMAN 1 Kualuh Selatan. Hasil implementasi menunjukkan sistem mampu memberikan hasil seleksi dengan akurasi sebesar 95%, waktu proses kurang dari 5 menit, serta memperoleh tingkat kepuasan pengguna dengan skor rata-rata 4,5 dari 5. Sistem juga menunjukkan konsistensi 100% dalam perhitungan dan diterima oleh 85% panitia sebagai alat bantu seleksi yang efektif dan efisien
OPTIMISASI HYBRID YOLOV9C-VGG16 UNTUK KLASIFIKASI JERUK LOKAL PADA SISTEM SORTASI OTOMATIS PADA INDUSTRI PERTANIAN Inna Fatahna; Danar Putra Pamungkas; Danang Wahyu Widodo
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6024

Abstract

Oranges have provided the benefits of vitamin C to the human body, so it is necessary to cultivate local orange fruit varieties using the implementation of computer vision technology. With the optimization of accuracy results using the CNN method, one of which is a combination of YoloV9c and VGG-16 can be realized on local oranges to overcome the problem of inaccuracy in the inefficiency of the classification process influenced by human visual subjectivity so as not to produce inconsistency in local orange fruit defect detection. Optimization was carried out to obtain the best accuracy results of 97% in this study, compared to the accuracy results using the YoloV9c method alone of 74% or the VGG-16 method alone of 59%. The accuracy optimization used a frame rate dataset of 2,221 images which were divided into 1,555 training data, 444 testing data, and 222 validation data images with a percentage of sorting of 70% for training data, 20% for testing data, and 10% for validation data. With this research, it provides new insights and knowledge to combine the YoloV9c method with VGG-16, where VGG-16 is used in the data pre-processing stage using feature extraction and fine-tuning with a batch size of 32 while YoloV9c is used to classify the results of local orange fruit quality detection with 100 epochs. With the combination of the CNN algorithm, it can increase the accuracy value of the detection results.
DETEKSI DAUN HERBAL DAN BERACUN MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK UNTUK KLASIFIKASI TANAMAN HERBAL DAN BERACUN: HERBAL AND POISONOUS LEAF DETECTION USING CONVOLUTIONAL NEURAL NETWORK FOR HERBAL AND POISONOUS PLANT CLASSIFICATION Della Adelia; Zahratul Fitri; Cut Agusniar
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6025

Abstract

Indonesia is one of the tropical countries with the greatest biodiversity in the world, including around 50,000 plant species and around 7,500 used by the community as raw materials for traditional medicine. However, the large number of plant species poses a challenge in distinguishing between edible plants and those that contain toxins, because herbal and toxic plants often have similar morphological characteristics of their leaves. Therefore, this study was conducted to design a classification system to distinguish between herbal and toxic plant leaves, which is expected to be utilized by the community as a preventive measure to reduce the risk of poisoning due to incorrect plant identification. The system was built using a Convolutional Neural Network (CNN) architecture implemented through the Flask framework and equipped with a rule-based system to determine plant categories based on the model's prediction results. The dataset consists of 960 images with 8 classes of local Indonesian plant leaves, where four categories include herbal plants (moringa, mint, betel, and basil) and four categories of poisonous plants (saga rambat, bandotan, gympie-gympie, and jelatang). This study conducted experiments on several CNN architectures, including custom and pretrained models (EfficientNetB0, MobileNetV2, and ResNet50V2). The best results were obtained from the EfficientNetB0 model trained using images with an input shape of 224×224 pixels, a batch size of 24, and the Adam optimizer, achieving a training accuracy of 99.51% and validation accuracy of 98.96%. This model demonstrated superior accuracy compared to other models, such as the custom model (93.88%), MobileNetV2 (99.50%), and ResNet50V2 (99.38%). The evaluation results show that the EfficientNetB0 model has excellent performance, with an overall classification accuracy of 99.00%, precision of 99.00%, recall of 99.00%, and an F1-score of 99.00%.

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