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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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SYSTEMATIC LITERATURE REVIEW BLOCKCHAIN UNTUK TATA KELOLA E-GOVERNMENT: MEKANISME TRANSPARANSI, AKUNTABILITAS, AUDITABILITY, PRIVASI, DAN ADOPSI DI SEKTOR PUBLIK Ucu Nugraha; Sri Titi Handayani; Hernalom Sitorus; Irawan Afrianto; Estiko Rijanto; Irfan Dwiguna Sumitra
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.v11i1.7516

Abstract

Digital transformation in government has intensified the need for public service governance that is transparent, accountable, auditable, and privacy-compliant. Blockchain and smart contracts can strengthen governance through immutability, traceability, and rule automation, yet they introduce transparency–privacy trade-offs, cross-agency interoperability constraints, and socio-technical adoption barriers. This study conducts a Systematic Literature Review (SLR) to synthesize governance mechanisms—transparency, accountability, auditability, and privacy—together with technical implementation patterns and adoption factors in e-government. We searched Scopus using a TITLE-ABS-KEY query with Open Access and English-language filters; PRISMA screening yielded 118 included studies. Results map dominant use cases (general e-government services, digital identity/credentials, e-voting, and cross-agency data sharing) and show that evidence maturity is still prototype-heavy (63/118). A critical finding is pervasive under-reporting of key technical descriptors that weakens synthesis and comparability: 72/118 studies do not specify the blockchain type and 85/118 do not report the platform; 109/118 also omit on-chain/off-chain design. The SLR contributes an evidence map and governance mechanism taxonomy, and can be operationalized as an assessment checklist for governments/consultants to question governance mechanisms, planned outcome metrics, and transparency–privacy trade-offs prior to deployment.
ANALISIS QOS JARINGAN PEMERINTAH MENGGUNAKAN TEKNIK DEEP PACKET INSPECTION Julius Samosir; Tomi Loveri; Anton Zulkarnain Sianipar
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.v11i1.7527

Abstract

Digital transformation in the government sector positions computer networks as critical infrastructure to support administrative processes, cross-unit coordination, and online public services. The high dependency on digital services requires network performance that is not only technically reliable but also stable from the user’s perspective. This study aims to analyze the performance of a government network based on Quality of Service (QoS) parameters, including throughput, delay, jitter, and packet loss, using Deep Packet Inspection (DPI) techniques. Measurements were conducted over five working days using Wireshark to capture and analyze network traffic in detail. In addition to technical measurements, user experience validation was performed using the Mean Opinion Score (MOS) method through structured interviews. The results show that delay and packet loss values fall into the very good category according to ITU-T standards, while the average jitter value of 206.0 ms is classified as poor. The study reveals an interesting anomaly in which the physical infrastructure demonstrates excellent delay and packet loss performance, yet high traffic instability (jitter) significantly degrades user experience quality. This condition is consistent with MOS results, which indicate decreased user satisfaction, particularly during online meetings. These findings suggest that the primary issue lies not in physical infrastructure but in the absence of traffic management and prioritization. The study recommends implementing priority-based Quality of Service policies to enhance network stability and support digital bureaucracy optimization.
SISTEM REKOMENDASI FILM BERBASIS CONTENT-BASED FILTERING MENGGUNAKAN NAIVE BAYES rahmad wardhani; Arif Nur Rohman
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.v11i1.7534

Abstract

The rapid growth of the digital film industry has resulted in a significant increase in available content, causing users to experience difficulties in finding movies that match their personal preferences. This condition highlights the need for an effective and personalized recommendation system. This study proposes a movie recommendation system based on a Content-Based Filtering (CBF) approach using the Naive Bayes algorithm to generate recommendations according to movie content characteristics and users’ preference histories. The MovieLens dataset obtained from Kaggle is used in this research. The research process includes data preprocessing, user profile construction, implementation of the Naive Bayes-based CBF model, and performance evaluation using Mean Absolute Error (MAE), Precision@5, Recall@5, and Mean Average Precision (MAP). The evaluation was conducted through ten repeated experiments with different training and testing data splits to ensure the reliability and stability of the results. The experimental results show that the Naive Bayes algorithm is able to effectively model the relationship between movie content attributes and user preferences. The evaluation achieved an average MAE of 0.368, Precision@5 of 0.82, Recall@5 of 0.11, and MAP of 0.42. The relatively high Precision@5 and MAP values indicate that the recommended movies are highly relevant and well-ranked at the top positions, while the low MAE value reflects satisfactory rating prediction accuracy. These results demonstrate that the proposed Naive Bayes-based Content-Based Filtering approach is capable of producing relevant, personalized, and stable movie recommendations, particularly in scenarios involving new or sparsely rated items.
PENERAPAN ALGORITMA NAÏVE BAYES DENGAN TEKNIK SMOTE UNTUK KLASIFIKASI SENTIMEN KURSUS ONLINE SKILL ACADEMY: APPLICATION OF THE NAÏVE BAYES ALGORITHM WITH SMOTE TECHNIQUE FOR SENTIMENT CLASSIFICATION OF SKILL ACADEMY ONLINE COURSES Arsellina Milka Martin; Arif Nur Rohman
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.v11i1.7545

Abstract

The rapid growth of online learning has led to the emergence of various e-learning platforms, including Skill Academy. However, not all courses are able to maintain learner engagement, partly due to discrepancies between user expectations and the quality of the provided materials. This study aims to classify user sentiment toward course titles by applying the Multinomial Naïve Bayes algorithm combined with the Synthetic Minority Oversampling Technique (SMOTE) to address class imbalance. Data were collected through web scraping from five main public course pages, including information on course titles, prices, ratings, number of raters, release dates, and topic categories. Sentiment labels were assigned based on rating values, where ratings ≥ 4.0 were categorized as positive and ratings < 4.0 as negative. Text feature extraction was performed using the TF-IDF method. The experimental results show that the model developed without SMOTE achieved an accuracy of 89.36% but completely failed to identify the negative class, as indicated by a recall value of 0%. After applying SMOTE to the training data, the recall for the negative class increased significantly to 64% demonstrating a substantial improvement in the model’s ability to detect previously overlooked negative sentiment. Although a slight decrease in accuracy was observed in several testing scenarios, the improvement in recall and F1-score for the minority class represents the primary contribution of this study. These findings confirm that SMOTE is effective in mitigating class imbalance and enhances sentiment analysis performance for short text data on online course platforms.
KLASIFIKASI SENTIMEN ULASAN PRODUK SAMSUNG PADA PLATFORM E-COMMERCE TOKOPEDIA MENGGUNAKAN ALGORITMA NAIVE BAYES Rahayu; Bambang Irawan; Otong Saeful Bachri
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.v11i1.7557

Abstract

The rapid growth of e-commerce in Indonesia has positioned customer reviews as a primary source of information reflecting consumer satisfaction and dissatisfaction with products. This study analyzes sentiment in Samsung product reviews on Tokopedia using natural language processing techniques. Data were collected from reviews on the official Samsung store on Tokopedia, followed by text pra-pemrosesan stages including cleaning, slang normalization, noise removal, selective stemming with the Sastrawi library, and stratified data splitting (80% training, 20% testing). Feature extraction was performed using Term Frequency–Inverse Document Frequency (TF-IDF) with n-gram integration (1-2), followed by training a Multinomial Naïve Bayes model optimized through GridSearchCV hyperparameter tuning. The primary objective was to develop an accurate sentiment classification model and identify dominant word patterns that reflect customer opinions. Evaluation results demonstrated an overall accuracy of 91.28%, with macro-average precision of 0.9112, recall of 0.9123, and F1-score of 0.9117. The negative class achieved the highest precision (0.9263), while the positive class showed strong recall (0.9079). TF-IDF analysis and word cloud visualization revealed that the words “barang” (product) and “kirim” (send) dominated across the dataset, with negative patterns centering on “lambat” (slow), “kecewa” (disappointed), and “rusak” (damaged), and positive patterns dominated by “bagus” (good), “cepat” (fast), “original”, and “mantap” (excellent). This study concludes that the Multinomial Naïve Bayes model is effective for sentiment analysis of unstructured Indonesian-language e-commerce reviews and provides valuable insights for official Samsung sellers to improve delivery services and product descriptions. Limitations in handling ambiguous or sarcastic reviews suggest opportunities for future research using transformer-based models such as IndoBERT or data augmentation techniques.
PERANCANGAN DAN EVALUASI ANTARMUKA UI/UX APLIKASI KURSI RODA CERDAS SMATSI BERBASIS USER-CENTERED DESIGN: DESIGN AND EVALUATION OF THE UI/UX INTERFACE OF SMATSI SMART WHEELCHAIR APPLICATION BASED ON USER-CENTERED DESIGN marcelinus erix; Jeki Kuswanto; 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.v11i1.7573

Abstract

Perkembangan teknologi digital pada perangkat medis cerdas mendorong pemanfaatan aplikasi pendukung guna meningkatkan efisiensi dan akurasi kerja tenaga kesehatan, khususnya dalam proses pemantauan dan pencatatan data vital pasien. Kursi Roda Cerdas SMATSI merupakan inovasi berbasis Internet of Things (IoT) yang dirancang untuk mendukung mobilitas pasien sekaligus memfasilitasi pemantauan kondisi kesehatan secara terintegrasi. Keberhasilan implementasi sistem tersebut tidak hanya ditentukan oleh akurasi sensor, tetapi juga oleh kualitas antarmuka pengguna dan pengalaman pengguna aplikasi pendukungnya. Penelitian ini bertujuan untuk merancang dan mengevaluasi User Interface (UI) dan User Experience (UX) aplikasi pendukung Kursi Roda Cerdas SMATSI dengan menerapkan metode User-Centered Design (UCD). Pengumpulan data dilakukan melalui penyebaran kuesioner, wawancara, dan observasi kepada tenaga kesehatan sebagai pengguna utama di beberapa fasilitas kesehatan untuk mengidentifikasi kebutuhan pengguna dan permasalahan usability. Hasil analisis kebutuhan diwujudkan dalam bentuk wireframe dan high-fidelity prototype yang mencakup fitur utama berupa dashboard hasil pengukuran, persiapan pengukuran, serta pengelolaan perangkat. Evaluasi usability dilakukan melalui usability testing menggunakan parameter Time-on-Task (ToT) dan System Usability Scale (SUS) untuk mengukur efektivitas, efisiensi tugas, dan tingkat kepuasan pengguna secara kuantitatif. Hasil pengujian menunjukkan bahwa rancangan UI/UX yang dikembangkan mampu mengurangi kompleksitas penggunaan sistem, meningkatkan efisiensi tugas, serta memberikan pengalaman penggunaan yang lebih intuitif dan efisien bagi tenaga kesehatan dalam konteks kerja klinis. Prototipe akhir memperoleh skor System Usability Scale (SUS) sebesar 86,4 yang termasuk dalam kategori excellent, dengan nilai Time-on-Task (ToT) rata-rata sebesar 8,5 detik. Dengan demikian, penerapan metode User-Centered Design (UCD) terbukti efektif dalam menghasilkan rancangan UI/UX yang teruji dan actionable untuk aplikasi medis berbasis IoT, serta memberikan bukti empiris mengenai efektivitas pendekatan UCD dalam konteks pengembangan teknologi kesehatan cerdas.
ASSOCIATION RULE MINING PADA POLA PEMBELIAN FURNITURE ONLINE STUDI KASUS DATASET SPARSE TAHUN 2025: ASSOCIATION RULE MINING–BASED ANALYSIS OF ONLINE FURNITURE PURCHASING PATTERNS: A CASE STUDY USING THE 2025 SPARSE DATASET Selvi Wijayanti; MY Teguh Sulistyono
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.v11i1.7575

Abstract

The rapid growth of e-commerce has driven an increase in household product transactions, including furniture, resulting in large-scale and diverse transactional data. However, most furniture transaction datasets exhibit sparse characteristics, as each order typically contains only one or a small number of items, making it difficult to generate frequent itemset combinations in association rule analysis. This study applies the Apriori algorithm to analyze online furniture sales transaction data from 2025, consisting of 1,938 records and 14 attributes. The research stages include data cleaning, transaction transformation, one-hot encoding, and the determination of a minimum support threshold of 0.0005 and a minimum confidence threshold of 0.1, adjusted to the characteristics of the dataset. The results indicate the formation of 421 frequent itemsets that meet the specified criteria, with a dominance of single-item itemsets caused by the low variation of items within each transaction. The analysis further shows that the generation of association rules is highly limited and fails to produce meaningful product relationship patterns. This limitation is primarily attributed to the highly sparse nature of the dataset, with an average of one item per transaction. This study demonstrates that applying the Apriori algorithm to highly sparse datasets results in very limited patterns and is dominated by single-item itemsets. These findings serve as an empirical study and a cautionary tale regarding the limitations of the Apriori algorithm when applied to transaction data with an average of one item per transaction, particularly in generating longer itemsets. Overall, this research contributes as an empirical warning on the limitations of applying the Apriori algorithm to highly sparse transaction datasets and emphasizes the importance of analyzing data characteristics prior to implementing association rule mining on e-commerce platforms.  
PERBANDINGAN KINERJA MODEL SUPPORT VECTOR MACHINE DAN NAÏVE BAYES UNTUK ANALISIS SENTIMEN SUPER APP POLRI Bagastian; Ryan Randy Suryono; Amarudin
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.v11i1.7582

Abstract

Digital transformation of public services has driven the Indonesian National Police to develop the Polri Super App, yet faces user acceptance challenges reflected in diverse reviews. This study aims to compare the performance of Support Vector Machine (SVM) and Naïve Bayes algorithms in classifying user sentiment of the Polri Super App. The research utilized 3,997 reviews from Apple Store undergoing comprehensive preprocessing including normalization, tokenization, stopword removal, and Sastrawi stemming. Sentiment labeling employed InSet Lexicon, yielding 55.0% positive and 45.0% negative reviews. Feature extraction used TF-IDF method with 80:20 data split for training and testing. Evaluation results demonstrate SVM significantly outperforms Naïve Bayes with 91.5% versus 79.0% accuracy (12.5 percentage points difference). SVM maintains balanced F1-scores of 90.6% (negative) and 92.2% (positive), while Naïve Bayes exhibits imbalance with 87.2% recall (negative) but only 72.3% (positive). SVM's superiority stems from hyperplane optimization capability in handling high-dimensional text data without rigid feature independence assumptions. The study recommends SVM implementation for police digital service sentiment monitoring systems and exploration of ensemble algorithms and deep learning for future research.
SISTEM MONITORING SUHU DAN KELEMBAPAN BERLEBIH DI RUANGAN LABORATORIUM KOMPUTER BERBASIS IOT MENGGUNAKAN ESP32 DAN DHT22 TRI MERI WULANDARI; Nur Azizah; Firman Jaya
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.v11i1.7585

Abstract

Computer laboratories require stable temperature and humidity conditions for optimal device function and to avoid the risk of damage due to overheating or extreme humidity. However, available monitoring systems generally only display environmental data without an automatic early warning mechanism when parameters exceed safe limits. This condition has the potential to cause delays in handling, decreased device performance, increased maintenance costs, and disruption to operational activities. This study aims to design and implement an Internet of Things (IoT)-based temperature and humidity monitoring system equipped with an early warning feature. The research method used is Research and Development (R&D) with the Borg & Gall model, which includes the stages of problem identification, data collection, system design, testing, and evaluation. The system was developed using an ESP32 microcontroller and a DHT22 sensor to read temperature and humidity, with data displayed in real time through the Blynk application. In addition, the system is integrated with Telegram to send automatic notifications when environmental conditions are outside safe limits. Test results show that the system is capable of continuous monitoring and sending early warning notifications effectively. Thus, the developed system has the potential to be an effective monitoring and early warning solution to support computer laboratory environmental management.
PERANCANGAN SISTEM INFORMASI WEBSITE DESA UNTUK PELAYANAN SURAT-MENYURAT DENGAN PENDEKATAN SECURE SOFTWARE DEVELOPMENT LIFE CYCLE (SSDLC) MONA RATULIU; Nurmi Hidayasari
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.v11i1.7589

Abstract

Correspondence administration services are one of the primary services provided by village governments to the community. However, in Teluk Lancar Village, the correspondence service process is still carried out manually, resulting in various issues such as service delays, data recording errors, and potential security risks to community data. In addition, the manual system makes it difficult for the community to monitor the status of submitted correspondence requests. This study aims to design and implement a village website information system for correspondence services by applying the Secure Software Development Life Cycle (SSDLC) approach with a focus on improving system security. The implementation of SSDLC in this study focuses on three main stages, namely Secure Design, Secure Coding, and Security Testing. In the Secure Design stage, the system is designed by implementing Role-Based Access Control (RBAC) to restrict user access based on the roles of community members, operators, and village administrators. The Secure Coding stage is implemented through role-based access control, input validation, and page access protection to prevent unauthorized access. Furthermore, the Security Testing stage is conducted using OWASP ZAP to identify potential security vulnerabilities in the system. The results show that the RBAC mechanism has been successfully implemented and is able to restrict user access according to their roles. Security testing results indicate the presence of vulnerabilities categorized as High, Medium, Low, and Informational, with the majority classified as low risk. The identified high-risk finding is related to application security misconfiguration (missing security headers), which does not directly affect data confidentiality but serves as an important basis for security evaluation and remediation in subsequent development stages.

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