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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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ANALISA PENGARUH KUALITAS WEBSITE SHOPEE PADA KEPUASAN PENGGUNA MENGGUNAKAN METODE WEBQUAL 4.0: ANALYSIS OF THE INFLUENCE OF SHOPEE WEBSITE QUALITY ON USER SATISFACTION USING THE WEBQUAL 4.0 METHOD Isaac Julio Herodion
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.v11i1.6819

Abstract

The quality of e-commerce websites has a significant impact on user satisfaction, which in turn influences purchasing behavior and customer loyalty. This study aims to analyze the effect of Shopee’s website quality on user satisfaction using the WebQual 4.0 framework, which includes three dimensions: usability, information quality, and interaction quality. A quantitative approach was employed, involving an online survey distributed to 100 active Shopee users. The collected data were analyzed using multiple linear regression with the assistance of SPSS software. The results indicate that all three WebQual 4.0 dimensions have a positive and significant influence on user satisfaction, with usability being the most dominant factor. These findings highlight the importance of intuitive interface design and efficient navigation in enhancing user experience. The study offers practical implications for website developers and e-commerce managers in formulating strategies to improve platform quality in order to maximize user satisfaction and loyalty.
ANALISIS TINGKAT PELANGGARAN LALU LINTAS DI WILAYAH POLRES GROBOGAN MENGGUNAKAN METODE CLUSTERING K-MEANS Niken Silvia Anggraini; 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.v11i1.6834

Abstract

The increasing number of vehicle users in Grobogan Regency has resulted in a high number of traffic violations that have the potential to cause accidents and traffic congestion. This study aims to analyze the level of traffic violations using the K-Means clustering method. The data used is primary data from the Grobogan Police Traffic Unit for the 2020-2024 period with a total of 38,318 violation cases. The research process consists of data preprocessing which includes number extraction, text transformation, and normalization, determining the number of clusters using the Elbow method, and a clustering evaluation process using the Davies-Bouldin Index (DBI). The results of the analysis show that the data on the level of traffic violations can be grouped into minor violations of more than 3,000 cases, which include violations of not wearing a helmet and violating traffic signs, moderate violations of approximately 5,000 cases, which include violations of not carrying a driver's license or vehicle registration, and severe violations of approximately 1,000 cases, which involve large vehicles. Evaluation of the quality of clustering using the Davies-Bouldin Index (DBI) shows that the arrangement with three groups (k = 3) provides the smallest DBI value, namely 0.486770. This figure indicates that the formation of three groups is the best arrangement, so that the results of the grouping divided into categories of minor, moderate, and severe violations have a fairly good quality of grouping. These results are expected to be a reference for the Regional Police and local governments in developing more effective law enforcement strategies and traffic safety policies.
KLASIFIKASI TINGKAT PELANGGARAN LALU LINTAS DI WILAYAH GROBOGAN DENGAN PERBANDINGAN ANTARA METODE KNN DAN SVM Dea Adwitiya Daffa; 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.v11i1.6854

Abstract

The increasing number of motorized vehicle users in Grobogan Regency has resulted in an increasing number of traffic violations that have the potential to cause accidents. Each violation has a different level of severity, so a classification method is needed to assist in determining the appropriate action. This study aims to compare the performance of the K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) methods in classifying the severity of traffic violations into three categories: minor, moderate, and severe. The research data was obtained from the Grobogan Police Department in 2020–2024 with a total of 38,318 cases. The research stages include data preprocessing, transformation, labeling using the K-Means method, data division, feature selection with Chi-Square, and classification using KNN and SVM. The evaluation results show that the KNN method produces an accuracy of 87.7% with an F1-score of 84.8%, but the AUC (64.3%) and MCC (21.1%) values ​​are still low, making it less than optimal in distinguishing classes. Meanwhile, the SVM method excelled in all evaluation metrics, with accuracy, precision, recall, F1-score, and MCC values ​​each reaching 98.5%. The distribution of classification results showed that KNN tended toward the mild class, while SVM was able to separate the three classes more evenly. Thus, SVM proved more effective in classifying traffic violation severity in Grobogan, producing more accurate results.
ANALISIS SENTIMEN KEBIJAKAN PEMBLOKIRAN REKENING PPATK DI MEDIA SOSIAL X MENGGUNAKAN TF-IDF, SMOTE SERTA PERBANDINGAN SVM DAN DECISION TREE David Wahyu Setyo Aji; Asih Rohmani; 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.v11i1.6877

Abstract

This study aims to analyze public sentiment toward the policy of the Pusat Pelaporan dan Analisis Transaksi Keuangan (PPATK) regarding bank account blocking, as expressed on the social media platform X (formerly Twitter), using a machine learning approach. The research data were collected through a web crawling process that gathered 799 tweets using Tweet Harvest during the period of July 28 to August 1, 2025. This time frame was selected because discussions related to account blocking by PPATK experienced a significant surge and became one of the viral topics on social media X. The analytical stages consisted of text preprocessing, data visualization, sentiment labeling using VADER, feature extraction with Term Frequency–Inverse Document Frequency (TF-IDF), data splitting, class balancing using the Synthetic Minority Oversampling Technique (SMOTE), and the development of classification models employing Support Vector Machine (SVM) and Decision Tree (DT) algorithms. The results indicate that the majority of public opinion was negative, accounting for 92.1% of the data, while positive opinions comprised only 7.9%. Both SVM and DT achieved high accuracy levels ranging from 93% to 94%. However, after hyperparameter tuning using GridSearchCV, the Decision Tree model demonstrated more balanced performance in detecting the minority (positive) class, with a precision of 0.73, recall of 0.65, and an F1-score of 0.69. These findings suggest that the integration of comprehensive preprocessing, TF-IDF feature representation, SMOTE-based class balancing, and parameter tuning can significantly enhance sentiment classification performance. Furthermore, this study provides a comprehensive overview of public perceptions of government policy. The results highlight the importance of utilizing machine learning–based sentiment analysis as a strategic consideration in formulating public policies that are more responsive to societal aspirations.
PERBANDINGAN AKURASI MODEL ARIMA DAN PROPHET DALAM MEMPREDIKSI HARGA SAHAM PT INDOFOOD SUKSES MAKMUR Yanuar Anggara Firdaus; 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.v11i1.6878

Abstract

Stock price predictions are an important aspect in supporting investment decision-making, especially for large companies whose stock prices fluctuate dynamically. This study aims to compare the accuracy levels of the AutoRegressive Integrated Moving Average (ARIMA) and Prophet models in predicting the closing price of PT Indofood Sukses Makmur Tbk (INDF.JK) shares. The historical data used covers the period from January 1, 2019, to April 28, 2025, and was obtained from web scraping yahoo.finance.com. The research stages include data preprocessing, stationarity testing, training and testing data division, ARIMA and Prophet modeling, and performance evaluation using the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) metrics. The results show that the Prophet model with the parameter changepoint_prior_scale = 0.01 provides higher accuracy with an RMSE of 499.76, an MAE of 424.41, and an MAPE of 6.46% compared to ARIMA(1,1,0), which produces an RMSE of 907.50, an MAE of 701.36, and an MAPE of 9.98%. This study shows that Prophet produces better prediction performance for INDF.JK stocks, making it an alternative stock price forecasting model with an acceptable level of relative error.  
RANCANG BANGUN E-LEARNING BERBASIS GAMIFIKASI DAN LEARNING STYLE PEMBELAJAR UNTUK OPTIMALISASI HASIL BELAJAR: DESIGN AND DEVELOPMENT E-LEARNING BASED ON GAMIFICATION AND LEARNER LEARNING STYLE TO OPTIMIZE LEARNING OUTCOME Andang Wijanarko; Endina Putri Purwandari; Febrian Solikhin
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.v11i1.6891

Abstract

The adoption of e-learning has been becoming crucial in modern education by offering flexibility, accessibility, and scalability for learners. However, many e-learning platforms still adopt a “one-size-fits-all” approach that ignores the differences in individual learner characteristics, especially learning styles. This lack of personalization often leads to a lack of motivation that ends in suboptimal learning outcomes. This study aims to design and develop an e-learning platform by integrating gamification elements and learning styles to optimize user learning outcomes. The research method uses a Research and Development (R&D) approach and the ADDIE model which includes five stages: analysis, design, development, implementation, and evaluation. This system combines general and specific gamification features according to the VARK learning style model. The system's effectiveness was tested on 67 students in the Computer and Programming course who were divided into experimental and control groups. The evaluation results showed significant differences in learning outcomes in the experimental group compared to the control group. In addition, the results of the independent t-test showed a significant difference (p < 0.05) in learning outcomes between the experimental and control groups. This means that the implementation of a gamification-based e-learning system and learning style features significantly impacts learning outcomes, especially compared to e-learning without learning style features. This study confirms that integrating gamification elements and learning styles positively enhances the learning experience. Furthermore, the integration of these two approaches has been proven to provide a meaningful learning experience and encourage learners to maintain their participation.  
PENGEMBANGAN APLIKASI MARKETPLACE INFLUENCER SEBAGAI MEDIA PROMOSI UMKM Chabelita ananda Putri; Suyud Widiono
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.v11i1.6899

Abstract

The endorsement strategy is an effective digital marketing method for expanding reach and increasing consumer trust. However, this practice is still dominated by large brands collaborating with well-known influencers, thus limiting access to affordable promotions for Micro, Small, and Medium Enterprises (MSMEs). On the other hand, micro-influencers with smaller audiences lack a structured, professional platform for collaborating with MSMEs. This study aims to develop a mobile-based influencer marketplace application that facilitates integrated collaboration between MSMEs and influencers. The development method used is the Waterfall method, which includes needs analysis, system design, implementation, testing, and maintenance. The mobile application was developed to support MSMEs in delivering products, receiving influencer offers, and placing endorsement orders through a digital transaction system. The development results show that the developed marketplace application provides paid endorsement features as well as additional free endorsement features (product barter), enabling more flexible, transparent, and mutually beneficial collaborations. Therefore, this application has the potential to be an initial solution in expanding digital promotion opportunities for MSMEs and supporting more inclusive collaboration with micro-influencers.
PEMANTAUAN KEKERUHAN DAN SUHU AIR KOLAM IKTIOTERAPI BERBASIS MIKROKONTROLER PADA MITRA RULE ATHALLAH BANYUASIN Franklin Khobir; Muhammad Agus Triawan; Arif Prambayun; Yulian Mirza; M. Aidil Fikka S
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.v11i1.6900

Abstract

Water quality in fish farming plays an essential role in maintaining the health and survival of the fish. The same applies to ichthyotherapy ponds, where water quality not only affects the survival of therapy fish but also influences the effectiveness of the therapy for users. This study analyzes real-time variations in water turbidity and temperature as physical parameters using a microcontroller-based monitoring system implemented at Rule Athallah, Banyuasin. The turbidity and temperature sensor data from ichthyotherapy pool water sample were continuously collected every 0.6-second intervals for approximately 4.57 hours. The turbidity sensor recorded a value of 0.0 NTU, indicating that the ichthyotherapy pond water was relatively clear with minimal suspended particles during the observation period. This NTU value remains within the optimal range for ichthyotherapy activities. Meanwhile, the water temperature remained stable, ranging between approximately 23.9°C and 24.2°C. These findings suggest that the developed system can serve as a reliable tool for automatic and measurable monitoring of ichthyotherapy pond water quality.
PENERAPAN METODE AHP DAN SMART DALAM PEMILIHAN PROVIDER WIFI DI KOTA PALEMBANG Michael Darwin; M. Rudi Sanjaya; Dedy Kurniawan; Rizka Dhini Kurnia
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.v11i1.6910

Abstract

The demand for fast and stable internet services continues to grow in line with the advancement of digital technology in Palembang City. The wide range of Wi-Fi service providers (Internet Service Providers) with varying characteristics makes it difficult for users to objectively determine the best option. This study aims to apply the Analytic Hierarchy Process (AHP) and Simple Multi Attribute Rating Technique (SMART) methods to support decision-making in selecting the best Wi-Fi provider in Palembang City. The AHP method is used to determine the priority weights of each criterion, including price, internet speed, connection stability, and after-sales service. Meanwhile, the SMART method is used to calculate the preference value of each provider alternative based on the obtained weights. The results indicate that internet speed is the most influential criterion in users’ decision-making, followed by stability, price, and after-sales service. Based on the calculation results, Biznet Home ranked highest with a score of 0.966 (on a maximum scale of 1.0) and is therefore recommended as the best Wi-Fi provider in Palembang City. The integration of AHP and SMART methods proves effective in producing systematic, objective, and easily interpretable decision outcomes for users.
TOWARDS AN IT-ENABLED FRAMEWORK FOR REMOTE WORK IMPLEMENTATION: MENUJU KERANGKA KERJA TEKNOLOGI INFORMASI UNTUK KERJA JARAK JAUH Alfa Yohannis; Glenny Chudra; Julian Yang
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.v11i1.6914

Abstract

This study identifies the essential components of an IT-enabled socio-technical framework to support effective remote work implementation. It draws on employees’ experiences and perceptions during the shift from office-based to remote arrangements, examining four dimensions: perceived advantages, perceived disadvantages, technological requirements, and ethical considerations in distributed work settings. Data were collected through an online questionnaire across multiple sectors, yielding 97 valid responses, predominantly from knowledge-intensive and digitally enabled organisational contexts. Qualitative thematic analysis revealed flexibility, time efficiency, and reduced commuting costs as key benefits, while communication difficulties, work–life imbalance, and technical limitations were cited as major challenges. Respondents also emphasised the importance of integrated digital tools, reliable infrastructure, and ethical guidelines related to privacy, trust, and fairness. These findings informed the proposal of six interrelated components forming a preliminary IT-enabled framework intended to support sustainable remote work practices. The anonymised dataset is openly available to encourage further research and contextual validation.  

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