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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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PEMANFAATAN MACHINE LEARNING MODEL INDOBERT UNTUK MENGIDENTIFIKASI CYBERBULLYING PADA KOLOM KOMENTAR SOSIAL MEDIA YOUTUBE: artikel Hendra Pasaribu; Daniel Septian Feri Bancin; Dian Karina Sembiring; Joyakim Simarmata; Vrendy Gusman Gulo
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.v11i2.8092

Abstract

The growth of social media, particularly YouTube, has led to increased user interaction through comment sections. The high volume of comments has also given rise to various forms of negative content, such as insults, harassment, sarcasm, and verbal attacks, which can be categorized as Cyberbullying. Therefore, an automated system capable of identifying Cyberbullying comments is needed. This study aims to develop a Cyberbullying detection system for Indonesian-language YouTube comments using the IndoBERT model. The dataset was collected through a YouTube comment scraping process using the YouTube Data API from Indonesian content videos published between 2019 and 2024. The research stages included data preprocessing, manual labeling, dataset balancing, tokenization, model training, model evaluation, and the implementation of a web-based system using Laravel and FastAPI. The final dataset consisted of 9,298 comments categorized into Cyberbullying, Non-Bullying, and Undifine/Invalid Data classes. The training process utilized the indobenchmark/indobert-base-p1 model with an 80:20 split between training and testing data. Based on the evaluation results, the model achieved an accuracy of 81.45%, precision of 85.49%, recall of 79.64%, F1-score of 81.87%, and an AUC score of 93.90%. These results indicate that the IndoBERT model is capable of effectively classifying Cyberbullying comments in Indonesian-language YouTube comments. Furthermore, the developed system can assist in the automatic identification of Cyberbullying comments and demonstrates that the IndoBERT model is effective for analyzing Indonesian-language social media text.
PERANCANGAN ANIMASI 3D MASKOT SEBAGAI MEDIA UNTUK MENINGKATKAN BRAND AWARENESS PADA BENGKEL MOBIL PANDAWA AUTOWORKS : DESIGN OF A 3D MASCOT ANIMATION AS A MEDIA TO INCREASE BRAND AWARENESS AT PANDAWA AUTOWORKS CAR WORKSHOP Mochamad Zidan Nur kamal; Aulia Hamdi; Muhammad Syaiful 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.v11i2.8095

Abstract

The automotive workshop industry in Indonesia has experienced significant growth along with the increasing number of motor vehicles. This condition has intensified competition among workshops, making effective visual communication strategies essential for improving brand awareness. Pandawa Autoworks has shown promising digital performance; however, it does not yet have a mascot that consistently represents its brand identity in promotional media. This study aims to design and develop a 3D animated mascot as a visual communication medium to enhance the brand awareness of Pandawa Autoworks. The research employed the ADDIE method, consisting of Analysis, Design, Development, Implementation, and Evaluation stages. The development process was carried out using Blender software through modeling, coloring, rigging, animation, and rendering stages. The resulting mascot animation was implemented in one of Pandawa Autoworks’ Instagram promotional contents. Evaluation was conducted using the Alpha Testing method involving Afif Nur Zaky, the owner of Pandawa Autoworks, and Khoerul Anam as an animation expert. The evaluation results showed an average score of 88.40 from the workshop representative and 87.30 from the animation expert, with an overall average score of 87.85, categorized as Very Good. The findings indicate that the developed 3D animated mascot is feasible as a visual communication medium and can support efforts to improve Pandawa Autoworks’ brand awareness on social media..
TATA KELOLA TI BERBASIS COBIT 2019 PADA PT PETROSIDA GRESIK DENGAN KEMATANGAN TI BELUM OPTIMAL M Rohid Nur Fajrian; Widyasari Puspa Permata Witra
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.v11i2.8096

Abstract

Information technology governance in a large-scale company needs to be supported by clear role structures, asset management, information systems, and control mechanisms. PT Petrosida Gresik has complex business processes across several directorates, yet its current IT governance practices are still not fully optimal. The main problems are reflected in asset recording that still relies on Excel, the absence of formal parameters for determining used-asset status, low user trust in iDempiere ERP data, weak budgeting control within the system, and unclear division of IT responsibilities in the organizational structure. The proposed solution is the design of IT governance based on COBIT 2019 to clarify processes, controls, roles, and evaluation mechanisms. This study used a descriptive qualitative method with a case study approach through document study, observation, and interviews. The results show that the relevant COBIT 2019 processes include EDM01, APO01, APO02, APO03, APO06, APO07, BAI09, DSS01, DSS06, dan MEA01. The proposed design includes gap mapping, RACI mapping, IT asset management procedures, centralized asset data, ERP validation, RKAP-based budget control, and strengthening of the IT organizational structure. The recommended structural changes include adding a Project Manager as a cross-directorate coordinator, strengthening the Information System and IT Governance Manager as the person responsible for systems, data, assets, security, and IT services, and dividing IT Department Staff into specific functions, namely information systems, database and ERP, network infrastructure, data security, IT assets, and helpdesk. This design is expected to improve accountability, data reliability, asset control, and IT alignment with organizational objectives.
COMPARATIVE PERFORMANCE ANALYSIS OF YOLOv5, YOLOv8, AND YOLOv9 SMALL AND MEDIUM VARIANTS FOR EXPLAINABLE PNEUMONIA DETECTION IN CHEST X-RAY IMAGES Faishal Luthfi Maulana Hakim; Cinantya Paramita
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.v11i2.8099

Abstract

Pneumonia is a lung infection disease that remains one of the leading causes of death worldwide, particularly among children and vulnerable populations. The diagnosis process using Chest X-Ray (CXR) images still faces several challenges, including the limited number of radiologists and the potential for human error in medical image interpretation. This study aims to perform a comparative analysis of YOLOv5, YOLOv8, and YOLOv9 small and medium variants for bounding box-based pneumonia detection on chest X-Ray images. The dataset was obtained from Kaggle and processed using Roboflow through preprocessing stages including auto-orient and image resizing to 640×640 pixels. The dataset was divided into 70% training, 20% validation, and 10% testing data. The training process was conducted using the Ultralytics YOLO framework for 50 epochs on an NVIDIA Tesla T4 GPU in Google Colaboratory. Model evaluation was carried out using Precision, Recall (Sensitivity), mAP50, and mAP50-95 metrics. The testing results showed that the YOLOv9m model achieved the best performance with a Recall value of 0.982759 and an mAP50-95 value of 0.717609. In addition, YOLOv5m produced the highest Precision value of 0.948602 and mAP50 of 0.969271. Based on the experimental results, the YOLOv9 architecture demonstrated the most optimal performance for pneumonia detection on Chest X-Ray images compared to the other models.  
EKSTRAKSI INFORMASI NOTA BELANJA INDONESIA MENGGUNAKAN INDOBERT DAN PENANGANAN NOISE BERBASIS FUZZY STRING MATCHING Niko Felix Chandra Arisco; Agus Sidiq Purnomo
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.v11i2.8103

Abstract

Indonesian shopping receipts have essential information like items, prices, taxes, and totals; however, their language is unstructured and susceptible to Optical Character Recognition (OCR) errors, such as misidentified characters and incomplete tokens. These problems make entity extraction less accurate, especially on numeric fields. Also, rule-based methods don't scale well, and deep learning models need a lot of labelled data. This study concentrates on developing a resilient information extraction system capable of handling text noise in Indonesian receipts. This method refines IndoBERT for Named Entity Recognition utilising the Consolidated Receipt Dataset (CORD), which has been manually re-annotated using the BIO scheme to identify four entities: ITEM, PRICE, TAX, and TOTAL, comprising 800 training instances, 100 validation instances, and 100 test instances, alongside Levenshtein Distance-based Fuzzy String Matching and rule-based validation. The fuzzy module is evaluated in two configurations, pre-processing and post-processing, via a six-scenario ablation study (S1-S6) in conjunction with OCR typo augmentation. The test findings indicate that the optimal configuration is S6 (IndoBERT + augmentation + FSM post-processing + rule-based validation), achieving a macro F1-Score of 0.7807, surpassing both the pre-processing placement (S5: 0.7733) and the pure IndoBERT baseline (0.7601). Rule-based validation yields the greatest contribution, with an F1 improvement of up to +0.028 due to enhanced recall. The conclusion is that fuzzy string matching is more effective as a post-processing technique, and the pipeline is implemented in a Streamlit-based online prototype that generates structured JSON output.
SELEKSI SISWA ELIGIBLE CALON PESERTA SNBP MENGGUNAKAN METODE ANALYTICAL HIERARCHY PROCESS (AHP) PADA SISWA SMA MUHAMMADIYAH KUDUS KELAS XII sucimaula adelia; Eko Darmanto; Arif Setiawan
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.v11i2.8104

Abstract

The selection of eligible students for the National Selection Based on Achievement (SNBP) at SMA Muhammadiyah Kudus requires an objective, structured, and accountable decision-making process. Manual selection may cause delays in data processing, calculation errors, and subjectivity because it tends to focus mainly on the average report card score. This study aims to develop a web-based Decision Support System (DSS) using the Analytical Hierarchy Process (AHP) method to determine eligible students for SNBP. The data used in this study consisted of 105 twelfth-grade students of SMA Muhammadiyah Kudus from classes XII F1, XII F2, XII F3, and XII F4. The assessment criteria include report card scores from semesters 1–5, score consistency, and class ranking. The AHP method is used to determine the priority weight of each criterion through a pairwise comparison matrix and consistency testing. The calculation results show that the report card score criterion obtains the highest weight of 0.6334, followed by score consistency with 0.2605, and class ranking with 0.1062. The Consistency Ratio (CR) value obtained is 0.033327, indicating that the pairwise comparison matrix is consistent because the CR value is less than 0.10. The system is developed using Laravel as the main application and Python as the calculation engine. The system provides features for student data management, CSV import, AHP matrix input, calculation details, ranking results, and report export. The results show that the system can assist guidance counselors and the principal in determining eligible students for SNBP more effectively, objectively, transparently, and measurably.
SISTEM PENDUKUNG KEPUTUSAN PENENTUAN KELAYAKAN PENERIMA BANTUAN UMKM MENGGUNAKAN HYBRID ENTROPY-WEIGHTED PRODUCT : DECISION SUPPORT SYSTEM FOR DETERMINING THE ELIGIBILITY OF MSME AID RECIPIENTS USING A HYBRID ENTROPY–WEIGHTED PRODUCT METHOD Rizky Prima; Agus Sidiq Purnomo
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.v11i2.8107

Abstract

The process of determining the eligibility of Micro, Small, and Medium Enterprises (MSME) aid recipients in Joint Business Groups (KUBE) is still often done manually, making it prone to subjectivity and inaccuracy. This study aims to develop a Decision Support System (DSS) that can objectively evaluate the eligibility of MSME aid recipients using the hybrid Entropy-Weighted Product method. The Entropy method is used for objective criteria weighting based on data variation, while the Weighted Product method is used for alternative ranking. The research data consists of 22 members of KUBE Bareng Mulyo with five assessment criteria: monthly turnover, market access, length of business, number of workers, and legality. The system was developed using PHP programming language with MySQL database following the Turban model. The results show that the Entropy method produces the highest weight on the criteria of length of business (45.58%) and number of workers (28.36%), indicating these two criteria as the most significant differentiating factors. The ranking results show Endang Sri Rejeki as the first rank with a preference value of 0.1043, which is consistent with actual field conditions. The developed system can improve transparency and objectivity in the selection of MSME aid recipients.
SISTEM INFORMASI REKAPITULASI DATA OPERASIONAL BERBASIS WEBSITE PADA PT WAHANA ERA SEJAHTERA Heni Listianingrum; Valiza Niswa Audina; Sarah Aprilia; Daning Nur Sulistyowati
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.v11i2.8111

Abstract

In recent years, advances in information technology (IT) have contributed significantly to improving business processes and operational efficiency. However, the adoption and utilization of IT remain suboptimal in some organizations, including PT Wahana Era Sejahtera. The company's operational data management is still carried out conventionally through external reports in the form of PDF and Microsoft Excel files, which causes the risk of duplication, data loss, and difficulties in the information retrieval process. In addition, this condition hinders the monitoring of the company's performance and increases the risk of errors in checking employee data and work tools. This research focuses on the development of a web-based operational data management system for PT Wahana Era Sejahtera to improve the efficiency of recording, storing, retrieving, and monitoring operational data. The system was developed using the Prototype model within the Software Development Life Cycle (SDLC) framework. Evaluation through User Acceptance Testing (UAT) resulted in a score of 82.32%, indicating a high level of user acceptance. The findings demonstrate that the proposed system can support operational activities by reducing the risk of data duplication and data loss, facilitate information management and retrieval, and support the process of monitoring company performance and decision-making more quickly, precisely, and accurately.  
APLIKASI PENCATATAN DAN ANALISIS PEMASUKAN SERTA PENGELUARAN TOKO ENSHA BERBASIS WEB DENGAN MENGGUNAKAN METODE K-MEANS Charrisa Berliana Nathaniela; Fatah Yasin Al Irsyadi
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.v11i2.8112

Abstract

Financial management that is still carried out manually often creates difficulties in recording and analyzing financial data. This issue is also experienced by Toko Ensha, which requires a more practical and informative financial recording system. This study focuses on designing and developing a financial recording and data analysis application by implementing the K-Means Clustering method. The system was developed using the Waterfall model, which consists of several sequential stages, including requirements analysis, system design, implementation, testing, and maintenance. The data used in this study consist of income and expenditure transactions that are compiled into monthly reports and then analyzed using the K-Means algorithm to identify financial patterns based on income, expenses, and balance. The analysis results are presented in graphical form to facilitate interpretation by the store owner. The developed application is capable of recording transactions in a structured manner, generating monthly financial reports, and providing financial analysis. Based on the testing results, the system demonstrated good performance, with all features functioning properly during Black Box Testing. Furthermore, the usability evaluation conducted using the System Usability Scale (SUS) produced an average score of 72, indicating that the system falls within the acceptable category and is considered easy to use and well accepted by users.
PENGUJIAN KINERJA EKSPERIMENTAL RESNET-18 PADA PENGENALAN 30 KARAKTER DASAR AKSARA SUNDA: Aksara Sunda, ResNet-18, Pembelajaran Mendalam, Jaringan Saraf Konvolusional, Klasifikasi Citra, Pengenalan Karakter Tulisan Tangan Arief Fadhiel Januarizky; Mohammad Nasucha
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.v11i2.8113

Abstract

Sundanese script is one of the cultural heritages that holds significant historical value for the Sundanese community. However, the use of Sundanese script in daily life has gradually declined, creating a need for preservation efforts through digital technology. One potential approach is the automatic recognition of Sundanese script using deep learning techniques. The ability of deep learning to identify visual patterns in images makes it suitable for handwritten Sundanese script classification. This study aims to evaluate the performance of the ResNet-18 architecture in recognizing 30 basic Sundanese script characters from handwritten image data. The research began with the collection of a self-created dataset obtained from 10 respondents. Each respondent was asked to write 30 basic Sundanese script characters, resulting in a total of 300 image samples. The collected images then underwent preprocessing stages, including cropping, resizing, and grayscale conversion. The processed dataset was divided into three data-splitting scenarios, namely 60:40, 70:30, and 80:20 for training and testing purposes. For each scenario, ResNet-18 was trained using both pretrained and non-pretrained approaches. After the training process, the resulting weights were saved and used during the evaluation stage. Model performance was evaluated using confusion matrices and classification metrics, including accuracy, precision, recall, and F1-score. The evaluation results from each scenario were then compared to analyze the influence of training data size on classification performance. The experimental results demonstrate that ResNet-18 is capable of classifying 30 basic Sundanese script characters with satisfactory performance. The best performance was achieved using the 80:20 data-splitting scenario with the pretrained ResNet-18, obtaining an accuracy of 98.33%, precision of 98.89%, recall of 98.33%, and F1-score of 98.22%. Furthermore, the results indicate that increasing the amount of training data contributes positively to classification performance. Based on these findings, ResNet-18 can be considered an effective approach for Sundanese script recognition and has the potential to support cultural preservation efforts through deep learning-based image processing technology.

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