cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Salamun
Contact Email
salamun@univrab.ac.id
Phone
-
Journal Mail Official
Jurnal.ti@univrab.com
Editorial Address
Redaktur Jurnal RABIT Teknik Informatika Universitas Abdurrab: Gedung Universitas Abdurrab Pekanbaru Jl. Riau Ujung No. 73 Pekanbaru Riau - Indonesia
Location
Kota pekanbaru,
Riau
INDONESIA
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
 63   64   65   66   67 
PENERAPAN ALGORITMA K-MEANS DALAM ANALISIS DAN KLASIFIKASI TEKS ULASAN KEPUASAN PENGGUNA PERPUSTAKAAN Maulana Ihsan; Mhd Ikhsan Rifki
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.v11i2.8276

Abstract

This study aims to analyze and classify user satisfaction review texts of the Faculty of Science and Technology (FST) Library into three categories: Dissatisfied, Satisfied, and Very Satisfied. The study used 1,096 library service survey reviews collected between 2023 and 2025 as the dataset for analysis. The research process comprises text preprocessing, such as stemming, stopword removal, tokenizing, case folding, and cleaning, and filtering), The study applied TF-IDF weighting, divided the dataset into 70:30 training and testing sets, and performed clustering with the K-Means algorithm into three clusters. The resulting clusters were assigned to satisfaction categories and evaluated using an accuracy, precision, recall, and F1-score confusion matrix. The model achieved 87.23% accuracy, 86.67% weighted precision, 87.23% weighted recall, and 86.85% weighted F1-score. These results showed that the K-Means algorithm can be used as a foundation for assessing and enhancing the quality of library services and is capable of efficiently classifying user satisfaction reviews.  
RANCANG BANGUN GAME EDUKASI HURUF HIJAIYAH SEBAGAI PEMBELAJARAN ANAK USIA DINI BERBASIS CONSTRUCT 2 zalra; Nurgiyatna
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.v11i2.8277

Abstract

Learning Hijaiyah letters for early childhood education is still commonly carried out using conventional methods, such as books and whiteboards, which are often less effective in attracting children's attention during the learning process. Advances in technology have created opportunities for utilizing games as educational media to support a more engaging and enjoyable learning environment. This study developed an educational game for learning Hijaiyah letters using the Construct 2 game engine. The game is intended to serve as a learning medium to facilitate the educational process for early childhood students at TK IT Taruna Teladan. The development process employed the Waterfall-based Game Development Life Cycle (GDLC) method, which consists of several stages, including requirement analysis and identification, design, implementation, testing, and system maintenance. System testing was conducted using the Black Box Testing method to ensure that all features functioned according to their intended design, while the System Usability Scale (SUS) instrument was used to evaluate user responses and assess the application's usability from the users' perspective. The results of this study produced an educational game equipped with features such as Hijaiyah letter recognition, letter-matching games, pronunciation audio, sound settings, and a scoring system. Based on the evaluation results, the application was able to perform all its functions properly. The average System Usability Scale (SUS) score of 75, categorized as "Good," indicates that the game is suitable for use as a learning medium for teaching Hijaiyah letters to early childhood learners.
IMPLEMENTASI SISTEM INFORMASI DAN PELAYANAN ADMINISTRASI KELURAHAN BERBASIS WEBSITE (STUDI KASUS: KELURAHAN TANJUNG) Nadila Melati Sukma; Syarifuddin; Dahlan
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.v11i2.8279

Abstract

The rapid development of information technology has encouraged government institutions to improve the quality of public services through the implementation of digital information systems. Tanjung Village continues to face various challenges in administrative services because most administrative processes are still performed manually, resulting in service delays, data recording errors, difficulties in document archiving, and limited public access to administrative information. This study aims to implement a website-based Village Information and Administrative Service System to enhance the effectiveness and efficiency of public services. The research employed the Research and Development (R&D) method using the Waterfall software development model, which consists of requirements analysis, system design, implementation, testing, and maintenance. The system was developed using PHP as the programming language and MySQL as the database management system. The developed application provides features for population data management, online administrative letter submission, village information management, and administrative verification by village officers. The results indicate that all major system functions operated successfully based on Black Box Testing, demonstrating that the system effectively improves administrative service processes, simplifies data and document management, and enhances public access to village services. Therefore, the proposed system can support the digital transformation of village administration and serve as a reference for implementing similar systems in other villages.
PERANCANGAN SISTEM INFORMASI TEMPAT WISATA SEBAGAI MEDIA PROMOSI DI KABUPATEN BIMA tyas tyas; Tyas mayang sari; Syarifuddin; Hilyatul Mustafida
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.v11i2.8280

Abstract

Bima Regency has substantial natural, cultural, and culinary tourism potential, but the dissemination of tourism information remains limited because promotion by the Bima Regency Tourism Office still relies on social media and printed brochures with limited reach and infrequent updates. This study aimed to design and implement a website-based tourism information system as a digital promotion medium for Bima Regency and to measure its user experience using the System Usability Scale (SUS) method. The system was developed using the prototyping method, comprising the communication, quick plan, modeling quick design, and construction of prototyping stages, and was built with the Laravel framework and a MySQL database. It provides two access levels: an administrator who manages destination data, categories, and photo galleries, and visitors who can browse destination information through public pages. Black Box Testing on fourteen main function scenarios showed that all functions performed as expected. SUS testing yielded an average score of 92.5 (Grade A, Excellent) for administrators and 62.27 (Grade D, OK/Fair) for visitors. These results indicate that the system is acceptable and operates well, although the visitor-side user experience still needs improvement through better display consistency and clearer navigation.
ANALISIS SENTIMEN PENGGUNA TWITTER TERHADAP KEBIJAKAN PENCAMPURAN ETANOL PADA BBM MENGGUNAKAN METODE NAIVE BAYES Indah Ati; Siti Mujilahwati
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.v11i2.8283

Abstract

The Indonesian government's policy on ethanol blending in fuel has triggered public reactions on Twitter (X), particularly complaints about engine sputtering. This study analyzes public sentiment toward the ethanol fuel policy using the Naïve Bayes algorithm with TF-IDF feature extraction. Data were scraped using Apify with five keywords from October 2025 to May 2026, yielding 3,268 raw tweets reduced to 2,137 clean data points. Preprocessing comprised six stages: cleaning, case folding, slangword normalization, tokenizing, stopword filtering, and stemming using the Sastrawi library. Sentiment labeling used an Indonesian Lexicon method, and data were split 80:20 via Stratified Sampling into 1,709 training and 428 testing samples. Labeling showed a dominance of negative sentiment at 59.1% (1,262 data), followed by positive sentiment at 33.8% (723 data) and neutral sentiment at 7.1% (152 data). The Naïve Bayes model achieved an overall accuracy of 75.5%, with the best performance on the negative class (recall 91.3%, F1-Score 82.4%), moderate performance on the positive class (F1-Score 69.2%), but very poor performance on the neutral class (recall 3.3%, F1-Score 6.2%) due to extreme class imbalance. The study concludes that public opinion is predominantly negative, and that handling imbalanced data remains the primary priority for future model development.
DETEKSI ANOMALI PADA AUDIT BARANG MILIK DAERAH MENGGUNAKAN EXTREME GRADIENT BOOSTING TEROPTIMASI BAYESIAN Sulman Edi S; Giat Karyono; Imam Tahyudin
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.v11i2.8285

Abstract

The audit and reconciliation of Local Government-Owned Assets (BMD) constitute a critical governance process that remains heavily reliant on manual verification, rendering it susceptible to inefficiency and human error, particularly within datasets exhibiting extreme heterogeneity in acquisition values. This study proposes an intelligent analytical framework for asset depreciation anomaly detection using the Extreme Gradient Boosting (XGBoost) algorithm, optimized via a Bayesian Optimization approach through the Optuna framework. From an initial raw population of 98,526 records, the data underwent preprocessing to yield 42,241 clean records with unique profiles. To address the disparity in price ranges, the dataset was divided into three strata using the Equal Frequency quantile method, with the prediction target transformed into a depreciation ratio. The evaluation demonstrated highly precise performance, consistently achieving a coefficient of determination (R²) above 0.99. Bayesian optimization reduced the Weighted Average Percentage Error (WAPE) to a range of 0.54% to 1.32%. Using a 10% deviation threshold, the system automatically extracted 101 anomalous records (1.20%) from 8,450 test samples as red flags. The results confirm that this framework is highly viable as a decision-support instrument for public asset audits, in compliance with regional regulations.
ANALISIS METRIK INTERAKSI TERHADAP PERTUMBUHAN PENGIKUT AKUN INSTAGRAM ITBSS MELALUI MEDIASI JANGKAUAN: PENDEKATAN SEM PLS: ANALYSIS OF ENGAGEMENT METRICS ON ITBSS INSTAGRAM ACCOUNT FOLLOWER GROWTH THROUGH REACH MEDIATION: AN SEM-PLS APPROACH Melyanto Melyanto
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.v11i2.8294

Abstract

Marketing in the era of digital transformation has shifted conventional marketing strategies toward digital marketing, particularly within the education sector. A primary objective in digital marketing is increasing brand awareness. Educational institutions could implement digital marketing strategies by leveraging Instagram analytical data as a data driven decision-making. Interaction is one of the key metrics used by Instagram to determine content ranking and reach. Interaction comprises several actions which are likes, comments, saves, and shares. High post reach can drive visibility and potentially attract new followers. Consequently, this study aims to analyze the influence of these interaction metrics on follower growth for the ITBSS Instagram account as the dependent variable, with reach acting as the mediating variable. The findings indicate that shares have a significant influence on both reach (p-value= 0.000) and follow (p-values= 0.014). Furthermore, likes also significantly influence reach  (p-value= 0.000). Comments and saves showed less significant results toward both reach and follow (p-value < 0,05). Reach has no significant in relation to follow (p-value = 0,357). These results provide valuable insights regarding interaction metrics, likes and shares. Instagram content creation should focus on encouraging likes and shares to effectively expand content reach and acquire new followers.
PERAMALAN PERSENTASE PENDUDUK MISKIN DI INDONESIA MENGGUNAKAN METODE HOLT Rizky Maryam Shinta Mutiara; Khoiriya Latifah; Ramadhan Renaldy
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.v11i2.8303

Abstract

Forecasting provincial poverty indicators is important for understanding poverty dynamics across Indonesian provinces. This study aims to forecast the Percentage of Poor Population (P0) at the provincial level for the 2026–2030 period using the Holt method with numerical parameter optimization. Secondary data were obtained from Statistics Indonesia for 2013–2025 and covered five poverty indicators, namely P0, the number of poor people, the poverty line, the Poverty Gap Index (P1), and the Poverty Severity Index (P2). P0 was used as the main forecasting indicator, while the other indicators supported the descriptive analysis. The preprocessing stage included data format standardization, province-name harmonization, selection of Semester I/March observations, removal of national aggregate data, and data completeness checking. Model accuracy was evaluated using MAE and MAPE by comparing the initial Holt model, optimized Holt model, optimized Neural Network, optimized Prophet, and optimized ARIMA. The results show that the optimized Holt model produced the best accuracy, with an MAE of 0.497 and a MAPE of 5.763% on the 2025 test data. The average predicted P0 across provinces decreased from 8.79% in 2026 to 7.56% in 2030. However, forecasts for newly established provinces, particularly in the Papua region, should be interpreted cautiously due to shorter historical time series.
ANALISIS PERBANDINGAN KETANGGUHAN RESNET50 DAN EFFICIENTNETB0 TERHADAP DEGRADASI GAUSSIAN BLUR PADA ATRIBUSI PROVENANCE DEEPFAKE Ronaldus Morgan James
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.v11i2.8306

Abstract

The rapid advancement of generative artificial intelligence models has escalated the risks of deepfake image dissemination, necessitating a paradigm shift from binary detection to provenance attribution, i.e., identifying the specific AI source model. Although various Convolutional Neural Network (CNN) architectures have proven highly accurate in classifying image sources under ideal conditions, real-world implementations frequently encounter spatial degradations, such as blurring effects, which destroy AI-generated high-frequency artifacts. This study presents a comparative analysis of the robustness of ResNet50 and EfficientNetB0 architectures in attributing multi-class deepfake images (DALL-E, Midjourney, Stable Diffusion, and Real Images) distorted by Gaussian Blur attacks, using a transfer learning approach to evaluate the degradation rate of both models. Experimental results indicate that while EfficientNetB0 achieved an accuracy of 93.89% under ideal conditions, its performance dropped significantly by 6.56% to 87.33% when images were blurred, due to the sensitivity of its depthwise convolution layers. In contrast, ResNet50, which achieved 95.70% accuracy under ideal conditions, demonstrated far superior robustness with only a 1.58% accuracy degradation, retaining 94.12% accuracy after the Gaussian Blur attack. This advantage is empirically validated as the effect of skip connections in the residual network, which preserve the spatial integrity of semantic feature representations. This study recommends the use of residual-based architectures for digital forensic systems operating in real-world environments that are susceptible to compression and degradation.
ANALISIS SENTIMEN PUBLIK TERHADAP INFRASTRUKTUR DAN AMENITAS KOTA PEKANBARU MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) BERBASIS DATA TWITTER Muhammad Yusri; Elvi Rahmi; Gunawan
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.v11i2.8313

Abstract

Infrastructure development and the provision of urban amenities are important elements in supporting the quality of life of communities in Pekanbaru City. Twitter has become an alternative platform for measuring public opinion in real time. This study aims to analyze public sentiment toward the infrastructure and amenities of Pekanbaru City using the Support Vector Machine (SVM) algorithm. The dataset consists of  3,743 tweets  collected through a scraping technique using the Instant Data Scraper plugin. The analysis process includes text preprocessing, namely data cleaning, case folding, tokenization, normalization, stopword removal, and stemming. The data are then transformed using the Term Frequency–Inverse Document Frequency (TF-IDF) method for term weighting. In addition, this study implements a rule-based Named Entity Recognition (NER) approach to extract location entities from textual data. The proposed SVM model is expected to classify public sentiment effectively into positive, negative, and neutral categories and identify sentiment based on the locations mentioned in the tweets.

Page 65 of 70 | Total Record : 696

 63   64   65   66   67 

Filter by Year

2016 2026


Reset
Filter By Issues
All Issue Vol 11 No 2 (2026): Juli Vol 11 No 1 (2026): Januari Vol 10 No 2 (2025): Juli Vol 10 No 1 (2025): Januari Vol 9 No 2 (2024): Juli Vol 9 No 1 (2024): Januari Vol 8 No 2 (2023): Juli Vol 8 No 1 (2023): Januari Vol 7 No 2 (2022): Juli Vol 7 No 1 (2022): Januari Vol 6 No 2 (2021): Juli Vol 6 No 1 (2021): Januari Vol 5 No 2 (2020): Juli Vol 5 No 1 (2020): Januari Vol 4 No 2 (2019): Juli Vol 4 No 1 (2019): Januari Vol 3 No 2 (2018): Juli Vol 3 No 2 (2018): Juli Vol 3 No 1 (2018): Januari Vol 3 No 1 (2018): Januari Vol 2 No 2 (2017): Terbitan Ke-4 Bulan Juli 2017 Vol 2 No 2 (2017): Juli 2017 Vol 2 No 1 (2017): Januari 2017 Vol 1 No 2 (2016): Juli 2016 Vol 1 No 1 (2016): Januari 2016 More Issue