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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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TIKTOK SEBAGAI DISTRAKSI, MEMPENGARUHI PRODUKTIVITAS DAN MANAJEMEN WAKTU PADA GENERASI Z: TIKTOK AS A DISTRACTION, AFFECTING PRODUCTIVITY AND TIME MANAGEMENT IN GENERATION Z Nadya Gracia Saragi; Firman; Sahiruddin
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.v11i1.7462

Abstract

The rapid development of information and communication technology has transformed the behavioral patterns of Generation Z, particularly in their use of social media such as TikTok. While TikTok provides entertainment and creative expression, excessive use can lead to distraction that negatively affects students’ productivity and time management. This study aims to analyze the impact of TikTok as a distraction on productivity and time management among students of the Information Technology Education Study Program at Muhammadiyah University of Education, Sorong, while also examining the social influence of parents and peers. A quantitative descriptive-correlational approach was employed, involving 30 active TikTok users (minimum one hour per day). Data were collected using a closed-ended questionnaire measuring levels of distraction, productivity, time management, and social influence. Results showed that distraction, productivity, and time management were at a moderate level (mean = 2.83). Peer influence (mean = 3.08) was found to be stronger than parental influence (mean = 2.22) in shaping TikTok usage behavior. Pearson’s correlation analysis indicated a significant positive relationship (r = 0.554; p < 0.01) between distraction, time management difficulties, and social factors. These findings highlight the importance of digital literacy programs emphasizing effective time management and healthy social media habits through peer-to-peer learning approaches.
PERBANDINGAN KINERJA NAÏVE BAYES DAN SVM PADA ULASAN KULINER BALI DENGAN SLANG CODE-MIXING Anak Agung Sandatya Widhiyanti; I Gusti Agung Ayu Sekarini
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.v11i1.7473

Abstract

Online reviews have become a primary source for consumers in evaluating the quality of products and services, including in Bali’s culinary sector. However, these reviews are typically written in informal language, containing slang, non-standard expressions, and code-mixing between Indonesian, English, and local languages. Such linguistic characteristics pose challenges for sentiment analysis systems, as language variability can reduce the consistency and reliability of classification results. This study compares the performance of two machine learning methods, namely Naïve Bayes and Support Vector Machine (SVM), in classifying sentiment from unstructured Balinese culinary reviews. The dataset consists of 5,000 Google Reviews, which were processed through text cleaning, slang normalization, and TF-IDF feature representation using a combination of unigram and bigram models. Performance was evaluated using accuracy, precision, recall, F1-score, and 5-fold cross-validation to assess model stability. Naïve Bayes was employed as a baseline to enable a more objective comparison between the two methods. The experimental results indicate that SVM achieves more balanced and consistent performance than Naïve Bayes, particularly for minority classes. Naïve Bayes tends to be biased toward the majority class due to its independence assumption and the imbalanced data distribution. Furthermore, the preprocessing stage, especially slang normalization, contributes to reducing lexical variability and improving the interpretability of sentiment patterns. These findings suggest that appropriate classifier selection and tailored preprocessing strategies play a crucial role in maintaining the reliability of sentiment analysis systems in informal and multilingual contexts.
IMPLEMENTASI USER CENTERED DESIGN DALAM PENGEMBANGAN WEBSITE MANAJEMEN DATA SENTRA HAK KEKAYAAN INTELEKTUAL POLITEKNIK NEGERI SIRIWIJAYA Malahayati; Rika Sadariawati; Ebtaria Nadeak; Sri Rahayu Rezeki; Lenno Nardo; M Irfan Apriansyah
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.v11i1.7474

Abstract

Intellectual Property Rights (IPR) play a strategic role in supporting innovation and productivity in higher education institutions. However, IPR management at Politeknik Negeri Sriwijaya (POLSRI) is still conducted manually, leading to various issues such as delays in the submission process, low data accuracy, and difficulties in tracking and reporting. This study aims to design and develop an integrated web-based IPR management information system by applying the User-Centered Design (UCD) approach. The research employs a prototype development method combined with UCD principles, encompassing literature review, observation, interviews, requirements analysis, interface design using Figma, system development using the Laravel framework, and usability evaluation through the System Usability Scale (SUS). The results indicate that the developed Sentral HKI (SHKI) system effectively facilitates digital submission, validation, status tracking, archiving, and reporting of IPR data in accordance with the needs of users, including lecturers, students, and administrative staff. Usability evaluation demonstrates that the system achieves a good level of ease of use and meets user requirements. Therefore, the SHKI system is considered effective in improving efficiency, accuracy, and transparency in IPR data management at POLSRI and has the potential to support sustainable institutional IPR governance.
EFEKTIVITAS MENINGKATKAN PENJUALAN PRODUK PENYANDANG DISABILITAS MENGGUNAKAN MEDIA FACEBOOK: EFFECTIVENESS OF INCREASING SALES OF PRODUCTS FOR PEOPLE WITH DISABILITIES USING FACEBOOK MEDIA ST Hajar Munawarah; Indri Anugrah Ramadhani; Matahari
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.v11i1.7483

Abstract

People with disabilities in Indonesia continue to face significant challenges in developing their businesses, particularly in product marketing. This study aims to examine the effectiveness of Facebook utilization training and mentoring in improving the sales performance of micro, small, and medium enterprises (MSMEs) operated by people with disabilities in Sorong Regency. The study employed a quantitative approach using a quasi experimental design with a one-group pretest–posttest design, involving 20 MSME entrepreneurs with disabilities. Data were collected through a closed-ended questionnaire using a four-point Likert scale, measuring six indicators: promotion intensity, market reach, transaction convenience, income, independence, and self confidence. The results of the paired sample t-test revealed a statistically significant difference between pretest and posttest scores (t = −3.525, p = 0.002). The highest improvements were observed in transaction convenience (0.90 points), income (0.65 points), and self-confidence (0.50 points). The normalized gain value of 0.35 indicates a moderate level of program effectiveness, with 42.1% of participants achieving a high effectiveness category. This study concludes that Facebook utilization training and mentoring are effective in enhancing the business performance of MSMEs operated by people with disabilities; however, continuous post-training mentoring is necessary to optimize outcomes for all participants. The findings highlight the importance of practical, measurable training programs supported by sustained mentoring to promote inclusive and sustainable digital entrepreneurship
ANALISIS PERFORMA HOLT-WINTERS DAN SARIMA DALAM PERAMALAN MULTIVARIABEL IKLIM BULANAN DI WILAYAH PESISIR KOTA SEMARANG Dzakiyya Nur Fadhilahrizka; Kenya Ditha Tania; 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.v11i1.7487

Abstract

This study aims to analyze and compare the performance of two conventional time series forecasting models, Holt–Winters and Seasonal Autoregressive Integrated Moving Average (SARIMA), in predicting monthly climate variables in Semarang City, including air temperature, rainfall, and humidity. A head-to-head multivariable comparison was conducted within a single experimental framework in a tropical coastal climate context. Daily climate data from February 2017 to December 2023 were obtained from Kaggle and preprocessed through data completeness checks, date format conversion, and aggregation into monthly series. The dataset was divided into 80% training data and 20% testing data. In addition to static data splitting, a time series validation approach was applied to assess the stability of model performance across different training windows. Forecasting accuracy was evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). The results indicate that Holt–Winters and SARIMA achieve comparable performance for temperature and humidity variables, with MAPE values of approximately 2.12% and 7.76%, respectively. In contrast, both models exhibit substantially higher errors when applied to rainfall data due to strong fluctuations and the presence of extreme values, indicating serious and shared limitations in accurately forecasting rainfall. This study concludes that conventional time series methods are effective for climate variables with relatively stable seasonal patterns but have inherent limitations in modeling highly volatile variables such as rainfall in tropical coastal regions.
EVALUASI PERFORMA ALGORITMA HILL CIPHER DAN AFFINE CIPHER PADA PENGAMANAN DATA PENGGUNA WEBSITE E-COMMERCE : PERFORMANCE EVALUATION OF HILL CIPHER AND AFFINE CIPHER ALGORITHMS IN SECURING E-COMMERCE WEBSITE USER DATA Ona Mazura; 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.v11i1.7490

Abstract

User data security is a crucial aspect in e-commerce systems, especially to protect sensitive data stored in databases (data at rest). One approach that can be used to maintain the confidentiality of this data is the application of cryptographic algorithms. This study aims to evaluate the performance of the classic cryptographic algorithms Hill Cipher and Affine Cipher in securing user data on web-based e-commerce websites. The research method is carried out by implementing both algorithms in an e-commerce system and conducting tests on the encryption and decryption processes of user data. The evaluation focused on two main aspects, namely the efficiency of the processing time and the quality of the resulting ciphertext. Security testing was carried out using the Ciphertext Only Attack approach and measuring the level of ciphertext randomness using Shannon Entropy. The test results show that the Affine Cipher algorithm has a faster encryption and decryption processing time than the Hill Cipher, making it more efficient in terms of performance. Conversely, the Hill Cipher produces ciphertext with a slightly higher level of randomness, as indicated by a larger Shannon Entropy value. This finding indicates a trade-off between processing speed and the quality of ciphertext randomness in both classic cryptographic algorithms. This research contributes by conducting a head-to-head comparative evaluation between Hill Cipher and Affine Cipher in the context of securing stored data in web-based e-commerce systems. The results are expected to be used as considerations in selecting classical cryptographic algorithms for learning, simulation, or small-scale systems with limited computational requirements.
PENGEMBANGAN APLIKASI MOBILE FEEDEZ SEBAGAI SISTEM KENDALI JARAK JAUH AUTOMATIC FISH FEEDER BERBASIS IOT: DEVELOPMENT OF THE FEEDEZ MOBILE APPLICATION AS AN IOT-BASED AUTOMATIC FISH FEEDER REMOTE CONTROL SYSTEM Moh Fauzan Fakhira Nasihin; Nuur Wachid Abdul Majid
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.v11i1.7495

Abstract

The application of Internet of Things (IoT) technology in the aquaculture sector continues to grow as an effort to improve the efficiency and precision of fish feeding. However, most of the automatic fish feeder systems that have been developed still rely on physical interfaces or third-party IoT platforms that have limitations in terms of customization and responsiveness. This study aims to develop an Android-based mobile application as a controller for automatic fish feeders, with a focus on improving the flexibility of mechanical settings and real-time control responsiveness. The research method used is the Prototyping software development model. The FeedEZ application was developed using React Native with the WebSocket communication protocol and integrated with Arduino Uno R3-based hardware and the ESP8266 module. Black box functional testing demonstrated the validity of all application features, while performance testing recorded an average end-to-end response time of 0.92 seconds with a standard deviation in the stable phase of 0.11. This response value is below the real-time interaction threshold (1 second), proving the system's effectiveness in providing instant control. This research demonstrates the paradigm of developing a full-stack custom IoT solution as a more flexible, standalone, and responsive alternative to the popular but limited platform-based approach.
PROTOTIPE SISTEM KONTROL PAKAN IKAN REAL-TIME BERBASIS IOT DALAM BUDIDAYA IKAN LELE: IOT-BASED REAL-TIME FISH FEED CONTROL SYSTEM PROTOTYPE IN CATFISH FARMING Mohamad Fikri; Dian Permata Sari
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.v11i1.7504

Abstract

The management of feed is a pivotal element in the success of catfish farming. However, in practice, the management of feed is predominantly conducted manually, which can result in feed wastage and inconsistency in feeding times. The objective of this study is to develop and evaluate a prototype of a real-time fish feed control system based on the Internet of Things (IoT) called Feedez. This system is designed to support the automation of feeding in catfish farming. The method employed is evolutionary prototyping, which encompasses a systematic sequence of steps including needs analysis, architecture design, prototype implementation, functional testing, and evaluation and iteration of improvements. The primary contribution of this research is the development of a system that exhibits high operational resilience through a dual data persistence mechanism. In addition to synchronization on the database server, the feeding schedule configuration is stored locally in the Arduino EEPROM memory to ensure security even in the event of network failure or power outage. Additionally, Feedez is equipped with multi-level (5-level) feed discharge speed control using pulse-width modulation (PWM) signals to ensure even feed distribution in large ponds. The experimental results indicate that the system possesses the capacity to execute feed scheduling in a timely manner, with an average output of 110 grams per minute for a feed with a diameter of 3 millimeters. The system's capacity to function autonomously in the event of an internet connection loss is ensured by the synchronization of the RTC module and local memory. This ensures the production of an even distribution of feed in a 4-meter diameter biofloc pond. These findings demonstrate that the Feedez prototype exhibits excellent operational reliability as an effective feed automation solution, particularly within the context of intensive catfish farming.
SISTEM REKOMENDASI MUSIK PSYCHEDELIC ROCK BERBASIS KONTEN DENGAN EKSTRAKSI FITUR AUDIO DAN COSINE SIMILARITY Iqbal Nurhidayat; 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.v11i1.7512

Abstract

The exponential growth of music libraries on streaming services has led to information overload, making it difficult for listeners to find works that match their preferences. The main issue faced is the cold-start problem, which is the failure of the system to recommend new tracks or specific genres such as Psychedelic Rock due to a lack of historical interaction data. This study aims to build a content-based filtering recommendation system architecture to overcome this problem. The technical procedure begins with the conversion of analog audio signals into digital spectral representations using the Librosa module. Feature extraction focuses on the parameters of Mel-Frequency Cepstral Coefficients (MFCC), Spectral Centroid, and Zero Crossing Rate (ZCR). Next, the similarity level between music entities is calculated using the Cosine Similarity metric. Testing on a data corpus consisting of 100 song samples shows satisfactory system performance with 88% accuracy and 86% precision. These results validate that the combination of audio feature extraction and the cosine similarity algorithm is effective in providing accurate recommendations without relying on user history.
DATA MINING MENGANALISA POLA PENJUALAN PERABOTAN PADA TOKO PRABOT KUKUH DI ACEH TENGGARA MENGGUNAKAN ALGORITMA FREQUENT PATTERN GROWTH (FP-GROWTH) musthofa fahrurrozi musthofa; Raissa Amanda Putri Raissa
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.v11i1.7514

Abstract

Household furniture sales at Prabot Kukuh Store in Aceh Tenggara exhibit significant monthly fluctuations, while the manual transaction analysis conducted by the store makes it difficult to accurately identify customer purchasing patterns. This limitation affects strategic decision-making related to stock management, product placement, and promotional planning. Therefore, this study aims to analyze sales patterns using data mining techniques, specifically the Frequent Pattern Growth (FP-Growth) algorithm, to provide strategic recommendations for the store. The dataset consists of 1,830 sales transactions collected through observation, interviews, and documentation from June to December 2024. The research stages include data selection, data cleaning, data transformation, construction of the FP-Tree, and generation of association rules. The FP-Growth algorithm was implemented using the Python programming language on the Google Colab platform. The results indicate that FP-Growth successfully identified 33 valid association rules representing product combinations frequently purchased together, such as strong relationships between Broom and Mop, Detergent and Toilet Brush, as well as bedding items like Pillows, Bedsheets, and Bolsters. These patterns can be utilized to develop product bundling strategies, optimize stock availability, and improve product placement. Thus, the application of the FP-Growth algorithm effectively supports data-driven decision-making to enhance operational efficiency and business competitiveness.

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