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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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PERANCANGAN SISTEM INFORMASI TPQ BERBASIS WEBSITE DENGAN EVALUASI USABILITY MENGGUNAKAN METODE SUS (STUDI KASUS : TPQ AL-MUWAHHIDIN KOTA BIMA) Fitri Aryani
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.v11i2.8353

Abstract

Because the administrative management of the TPQ at the Al-Muwahhidin Grand Mosque in Bima City is still done manually, there is no way to manage data on students, instructors, class schedules, payments, and the dissemination of information. The objective of this study is to develop a web-based TPQ information system that allows for the evaluation of usability levels using the System Usability Scale (SUS) method. The system development method employed is the Software Development Life Cycle (SDLC), specifically using the Waterfall model. Black Box Testing was used to test the system. The SUS evaluation involved 43 participants, including administrators, instructors, and parents of students. The results of the Black Box testing showed that all system functions operated with a 100 percent success rate. For the SUS evaluation, the average score of 70.58 fell into the “Acceptable,” “Grade C,” and “Good” categories. The research results indicate that the information system can help manage and disseminate information at the TPQ more efficiently and effectively.  
SYSTEMATIC LITERATURE REVIEW KERENTANAN LANSIA TERHADAP SERANGAN PHISHING PADA SISTEM DANA PENSIUN DIGITAL Hanacahyani Widya Asih; Lintang Amarul Fatah; Mukti Diananingsih; Djoko Pitoyo; Eka Ardhianto; Aji Supriyanto
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.v11i2.8356

Abstract

The digital transformation of financial systems has improved efficiency while simultaneously expanding the cybersecurity attack surface, particularly for phishing threats in pension fund distribution. Elderly individuals, as primary beneficiaries, are considered highly vulnerable due to limited digital literacy, cognitive decline, and a strong trust bias toward authority. This study aims to identify phishing attack patterns, risk factors, and effective mitigation strategies targeting elderly populations through a Systematic Literature Review (SLR) approach following the PRISMA framework. Literature was sourced from IEEE Xplore, Scopus, SpringerLink, and Google Scholar (2015–2025). A total of 120 articles were initially identified, with 35 studies meeting the inclusion criteria after rigorous screening. The findings indicate that elderly individuals are particularly susceptible to email phishing, smishing, and vishing, with significantly higher success rates compared to younger populations. Key contributing factors include low cybersecurity literacy, cognitive limitations, trust bias, and non-inclusive interface design. Effective mitigation strategies include user-centered security design, biometric multi-factor authentication (MFA), and simulation-based security training. This study contributes to a comprehensive risk mapping of phishing threats among elderly pension beneficiaries and provides actionable insights for designing more secure and inclusive digital pension systems.
IMPLEMENTASI REGRESI LINIER BERGANDA DALAM PREDIKSI PENDAPATAN PADA SISTEM INFORMASI KEUANGAN PRAKTIK MANDIRI ANAS NASRULLAH; Mundirin; Deden Hedin Purnama Binaefsa
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.v11i2.8365

Abstract

Manual financial record-keeping in Praktik Mandiri results in ineffective financial management and revenue prediction. This study aims to develop a web-based Financial Information System by implementing the Multiple Linear Regression method to predict monthly revenue. The system was developed using the Agile methodology. The research dataset consists of 49 months of historical financial data (June 2022–June 2026). The predictor variables include the number of patient visits, total operational expenses, and the number of practice days, while net revenue is used as the target variable. Functional testing was conducted using Black Box Testing, user evaluation was carried out using a Likert scale, and model validation was performed using RapidMiner Studio. The prediction model achieved a MAPE of 7.88% and an RMSE of IDR 3,969,764, while the RapidMiner validation produced identical results. These findings indicate that the implemented model is consistent with the validation results and is capable of supporting financial management and monthly revenue prediction.
E - CRM E-CRM DALAM MENDUKUNG PROSES BISNIS PENJUALAN BUSANA DI DITA FASHION BATU BARA Mahyumita Sari; William Ramdhan; Elly Rahayu
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.v11i2.8369

Abstract

Abstrak Perkembangan teknologi internet yang semakin pesat, didukung oleh kemudahan akses melalui berbagai perangkat komunikasi, telah mengubah pola dan perilaku konsumen dalam berbelanja menjadi lebih efektif dan efisien. Selain itu, melalui pokok pembahasan yang dilakukan pada penelitian kali ini bertujuan dapat meningkatkan efektivitas aktivitas pemasaran yang sebelumnya hanya mengandalkan media sosial, diperlukan penerapan sistem yang lebih terintegrasi agar seluruh proses pemasaran dapat berjalan secara lebih optimal dan terarah. Dan selain itu juga untuk bagian Metode Penelitian yang digunakan dalam penelitian kali ini adalah metode kualitatif, karena penelitian ini ditujuhkan untuk dapat memperoleh pemahaman yang mendalam mengenai fenomena yang terjadi melalui pengumpulan dan analisis data. Berdasarkan keseluruhan penjabaran dalam penelitian ini maka penulis dapat menyimpulkan bahwa penerapan Electronic Customer Relationship Management (E-CRM) pada Dita Fashion terbukti mampu meningkatkan efektivitas proses bisnis, terutama dalam pemasaran, pelayanan dan pengelolaan hubungan dengan pelanggan. Sistem ini mengintegrasikan aktivitas promosi serta komunikasi pelanggan ke dalam satu platform sehingga lebih terstruktur, cepat dan mudah dikendalikan. Selain meningkatkan kualitas pelayanan melalui respons yang lebih efisien, E-CRM juga memusatkan data pelanggan, termasuk riwayat transaksi pelanggan. Ketersediaan informasi yang terorganisasi tersebut membantu Dita Fashion memahami kebutuhan pelanggan dengan lebih baik serta mendukung penyusunan strategi bisnis yang lebih tepat, efektif dan berorientasi pada kepuasan pelanggan. Abstract The rapid development of internet technology, supported by easy access via various communication devices, has transformed consumer shopping patterns and behaviors, making them more effective and efficient. Furthermore, the focus of this study aims to enhance the effectiveness of marketing activities—which previously relied solely on social media by implementing a more integrated system so that the entire marketing process can run more optimally and in a targeted manner. Furthermore, the research method employed in this study is a qualitative approach, as this research is intended to gain a deep understanding of the phenomena observed through data collection and analysis. Based on the overall findings of this study, the author concludes that the implementation of Electronic Customer Relationship Management (E-CRM) at Dita Fashion has proven effective in enhancing business process efficiency, particularly in marketing, customer service, and customer relationship management. This system integrates promotional activities and customer communications into a single platform, making them more structured, faster, and easier to manage. In addition to improving service quality through more efficient responses, E-CRM also centralizes customer data, including customer transaction histories. The availability of this organized information helps Dita Fashion better understand customer needs and supports the development of business strategies that are more precise, effective, and focused on customer satisfaction.
SEGMENTASI PROBABILISTIK CALON MAHASISWA BERBASIS INDOBERT, GAUSSIAN MIXTURE MODEL, DAN LLM DI ITSNU PEKALONGAN Mujibul Hakim; Eri Zuliarso
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.v11i2.8370

Abstract

Private higher education institutions face challenges in understanding shifting prospective-student characteristics driven by socio-economic dynamics, including the COVID-19 pandemic. ITSNU Pekalongan recorded a non-linear enrollment pattern in 2019–2024 (from 146 to a peak of 680; N = 2,362). This study aims to analyze probabilistic segmentation, measure cross-period structural breaks, build an LLM-based analysis automation system, and validate it through expert judgement. A Research and Development approach follows a ten-stage CRISP-DM framework: IndoBERT (768 dimensions), PCA, Gaussian Mixture Model (GMM) with diag covariance and k-means++ init, Adjusted Rand Index (ARI), and a Hybrid Cognitive Pipeline (local Llama 3.2 and OpenRouter cloud). The results show that 4 of 5 inter-period transitions are structural breaks (ARI < 0.30), identical-entity cosine similarity of IndoBERT embeddings averages 0.9234 (range 0.8932–0.9426), and expert validation reaches 4.0/5.0 for a 2025 projection of 592 applicants. The IndoBERT–GMM–LLM integration yields a replicable recruitment decision-support system.
ANALISIS FAKTOR-FAKTOR PENERIMAAN TEKNOLOGI TERHADAP PENGGUNAAN APLIKASI BSGTOUCH MENGGUNAKAN MODEL UTAUT2 Miskiyah Nur Wahidah Balu; Irving Vitra Paputungan
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.v11i2.8373

Abstract

The development of information technology has driven the transformation of banking services toward digital platforms, including BSGTouch, a mobile banking application developed by Bank SulutGo. Despite offering various banking services, BSGTouch still faces challenges such as limited features, an impractical account reactivation process, and user complaints that may affect technology acceptance and application usage. This study analyzes factors influencing the acceptance and use of BSGTouch using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model. A quantitative survey was conducted with 183 active BSGTouch users in Gorontalo Province selected through purposive sampling. Data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS) with SmartPLS 4. The results indicate that Social Influence, Price Value, and Habit positively and significantly affect Behavioral Intention. Facilitating Conditions, Habit, and Behavioral Intention also positively and significantly affect Use Behavior. In contrast, Performance Expectancy, Facilitating Conditions, and Hedonic Motivation do not significantly affect Behavioral Intention, while Effort Expectancy has a significant negative effect. Habit is the most influential factor affecting Behavioral Intention. These findings provide insights for Bank SulutGo to improve service quality, enhance application features, and increase user acceptance and continued use of BSGTouch.  
EVALUASI MULTI-SEED L1 DAN L2 REGULARIZATION PADA RESNET-50 UNTUK DETEKSI DEEPFAKE WAJAH Nurayuni Kirana Muti; MUHAMMAD NAUFAL; Novita Kurnia Ningrum
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.v11i2.8401

Abstract

Facial biometric authentication systems are increasingly vulnerable to sophisticated digital manipulations, particularly deepfakes. Conventional single Convolutional Neural Network (CNN) models often encounter overfitting issues, especially when trained on high-resolution datasets containing subtle manipulation artifacts. To address this issue, this study evaluates and compares the effectiveness of applying L1 Regularization and L2 Regularization parameters to the final classification layer of a fine-tuned ResNet-50 architecture. The models were comparatively evaluated using the public CIPLAB Real and Fake Face Detection dataset. To ensure an objective stability measurement, a multi-seed evaluation method was applied using three random initializations. Experimental results indicate that the baseline model without regularization exhibited a high level of prediction fluctuation, with an accuracy standard deviation of 0.0387. The application of L1 Regularization achieved an average testing accuracy of 68.78%, but failed to resolve the stability issue, as it still recorded a high standard deviation of 0.0380. Conversely, L2 Regularization was proven to significantly mitigate the risk of overfitting, emerging as the most superior approach. This is evidenced by a sharp decrease in the accuracy standard deviation to 0.0105, while securing a consistent average testing accuracy of 68.78%. These findings emphasize that applying an L2 Regularization penalty to a single CNN model offers a far more stable, effective, and consistent solution for detecting facial image manipulations compared to both L1 Regularization and conventional models.
ANALISIS EFEKTIVITAS VIDEO MOTION GRAPHIC SEBAGAI MEDIA PROMOSI UMKM DI KABUPATEN PEMALANG Muhamad Topan Dinar; 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.v11i2.8416

Abstract

Digital transformation has become a primary determinant in business communication effectiveness, yet MSMEs in the DM Kuliner area of Pemalang Regency still rely on static, conventional promotional formats. This study aims to examine the effectiveness of using motion graphics videos as a multimedia tool to improve usability perceptions and information acceptance among MSME operators. Using a One-Group Pretest-Posttest design, data were collected from 21 respondents using the System Usability Scale (SUS) instrument, which had been rigorously tested for validity and reliability. Data analysis was comprehensively conducted through descriptive statistics, the Shapiro-Wilk normality test, and hypothesis testing using the Paired Sample T-Test via SPSS. The results showed a significant increase in the overall mean SUS score from 62.26 in the pre-test phase to 69.64 in the post-test phase. Based on Acceptability Ranges mapping, this promotional medium successfully transitioned from the "Marginal Passive" category to "Acceptable" with a practical magnitude effect size (Cohen's d) of 0.66 (Medium Effect). Statistical analysis supports this finding, showing a calculated -value of -3.014 with a significance coefficient (Sig. 2-tailed) of 0.007 (), proving the increase is scientifically valid. The practical implication confirms that interactive motion graphics integration is highly effective in minimizing the digital divide and expanding market penetration for local culinary MSMEs in alignment with local government development policies.  
KOMBINASI REGRESI LINEAR DAN K-MEANS UNTUK ANALISIS TREN PROYEKSI PESERTA KB PADA DINAS DPPKB KABUPATEN LABUHAN BATU Hasyim Ar Rasyid Hasyim; Aninda Muliani Harahap Aninda
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.v11i2.8431

Abstract

The rapid development of information technology requires public institutions to transform their data management to enhance efficiency and objectivity in decision-making. The Department of Population Control and Family Planning (DPPKB) of Labuhanbatu Regency faces challenges in managing dynamic and growing Family Planning (KB) participant data. Conventional data processing triggers issues such as reporting delays, difficulties in mapping regional characteristics, and inaccurate future service projections. This study aims to develop a web-based information system capable of analyzing trends and projecting the number of KB participants by combining K-Means Clustering and Linear Regression methods. The K-Means method is utilized to group KB participant data based on similarities in regional characteristics, status, and age into three growth rate clusters (low, medium, high). Subsequently, Linear Regression is applied to each cluster to predict the participant trend volume for the next period based on historical data from December 2024 to December 2025. The system is designed using Unified Modeling Language (UML) and built utilizing the Laravel 10 framework, PHP, and MySQL database. The system provides two main access roles: Administrator for data management and algorithm execution, and Leader (Head of Department) for real-time dashboard trend visualization monitoring. The results of this study are expected to serve as an objective, accurate, and data-driven strategic decision-making tool for DPPKB Labuhanbatu Regency in determining service strategies and resource allocation.
KLASIFIKASI MODA TRANSPORTASI BERBASIS TRAJEKTORI GPS UNTUK ANALITIK TRANSPORTASI PUBLIK Johanes Harindrias Kurniawan; Raviez P Putra; Dwi Pebrianti
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.v11i2.8444

Abstract

Transportation mode information automatically derived from Global Positioning System (GPS) trajectories can help operators and planners understand public, individual, and walking mobility patterns. This study compared Logistic Regression, Linear Support Vector Machine, Decision Tree, Random Forest, and Light Gradient Boosting Machine to classify walk, bike, bus, car/taxi, and train/subway. The Microsoft GeoLife dataset was processed from 5.3 million labeled GPS points into 172,105 segments with a maximum duration of 120 seconds from 55 users. Validation used Stratified Group 5-Fold Cross-Validation based on user_id. Sensitivity analysis was conducted on one main hyperparameter of each algorithm, while ablation testing was used to select feature groups. The results showed that 20 kinematic and motion-dynamics features produced the best performance. Random Forest achieved the highest macro F1 of 0.722±0.114, accuracy of 0.764±0.085, and macro AUROC of 0.903±0.058, followed by LightGBM with a macro F1 of 0.703±0.085. In out-of-fold aggregation, grouping bus and train/subway as public transport produced an F1 of 0.724 and a public-segment proportion difference of 3.14 percentage points compared with actual labels. The Friedman test showed an overall ranking difference, but pairwise comparisons after Holm correction were not significant. The results confirmed that tree-based ensembles are effective for nonlinear GPS patterns, although bus and car/taxi errors must be controlled before operational decision-making.

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