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
 66   67   68   69   70 
PENGEMBANGAN SISTEM KENDALI OTOMATIS PEMOTONG PISANG BERBASIS ARDUINO MENGGUNAKAN SENSOR LOAD CELL MENINGKATKAN KONSISTENSI PRODUKSI Muhammad dandy
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.v11i2.8485

Abstract

Banana chip production in Micro, Small, and Medium Enterprises (MSMEs) is generally still carried out using manual cutting processes. This method has several drawbacks, including inconsistent slice thickness, relatively long processing time, low productivity, and a high risk of hand injuries due to continuous use of knives. In addition, direct contact with banana sap reduces operator comfort and process hygiene. This study aims to design and develop an Arduino Uno-based automatic banana slicing control system to improve cutting efficiency, produce more consistent slice thickness, and enhance operator safety. The research method includes hardware and software design, system assembly, Arduino Uno microcontroller programming, and performance testing using Kepok bananas as the test material. The developed system consists of an Arduino Uno as the main controller, a stepper motor as the driving mechanism, and two limit switches as motion-limiting sensors. Signals from the limit switches are processed by the Arduino to automatically control the rotation direction of the stepper motor, enabling the pusher mechanism to move forward and backward repeatedly during the cutting process. The experimental results show that the proposed system is capable of producing banana slices with a consistent thickness ranging from 1 to 3 mm, regardless of the operator's hand strength. In addition to improving the uniformity of the slices, the system also reduces the risk of hand injuries and minimizes direct contact with banana sap. Based on the results, the Arduino Uno-based automatic control system effectively improves work efficiency, productivity, cutting quality, and operator safety, making it suitable for implementation in banana chip production processes in MSMEs.
PROTOTIPE SISTEM JEMURAN OTOMATIS BERBASIS IOT (INTERNET OF THINGS) MENGGUNAKAN METODE FUZZY TSUKAMOTO Agus Setiawan; Mukti Qamal; Rini Meyanti
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.v11i2.8488

Abstract

The development of Internet of Things (IoT) technology has provided practical solutions for various aspects of daily life, including smart home applications. One household activity that remains largely manual is clothes drying, which is highly dependent on unpredictable weather conditions. This study aims to develop an IoT-based automatic clothesline system using the Fuzzy Tsukamoto method to respond automatically to changing environmental conditions. The system employs a rain sensor, light sensor (LDR), and DHT22 temperature and humidity sensor to monitor environmental conditions in real time. Sensor data are processed using the Fuzzy Tsukamoto method to determine whether the clothesline should be opened or closed and to control a blower fan inside the drying chamber. The system is also integrated with a mobile application for remote monitoring and control. The test results show that all implemented functions achieved a 100% success rate, with a system response time of 0–5 seconds to changes in sensor conditions. These results demonstrate that the proposed system operates automatically and responsively, improving the efficiency and convenience of clothes drying under changing weather conditions.
ANALISIS TINGKAT USABILITY APLIKASI EDUKASI RUANGGURU MENGGUNAKAN METODE SYSTEM USABILITY SCALE (SUS) Iqbal Sidiq
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.v11i2.8489

Abstract

Ruangguru is one of the most widely used digital tutoring platforms by students in Indonesia; however, dynamic interface updates have the potential to affect system usability. This study aims to evaluate the interface quality and user experience of the Ruangguru application using the System Usability Scale (SUS) method. Primary data collection was conducted online using a purposive sampling technique, involving 30 active respondents in the Purwokerto region dominated by teenage students (96.67%) with varying durations of use. The evaluation focused on two standard industry assessment parameters, namely Acceptability Ranges and Grade Scale. The results of the questionnaire raw data processing showed an accumulated conversion value of 857 with a total score of 2142.5, yielding a global average SUS score of 71.4. This score maps the usability performance of the Ruangguru application into the Acceptable zone and places it in the Grade C category. Based on the item statement analysis, the system's core strengths lie in the high interest for routine use (Q1) and the ease of learning the system quickly (Q7). However, identified barriers were still found in the consistency of visual elements across pages (Q6). This research contributes recommendations for developers to harmonize graphic design and simplify sub-menu navigation in subsequent version updates to mitigate user cognitive load.
IMPLEMENTASI ALGORITMA LEBAH DAN ALGORITMA SEMUT UNTUK MENENTUKAN RUTE TERPENDEK DALAM PROSES MONITORING WAJIB Mohammad Wandy; Yuri Yudhaswana Joefrie; Rizka Ardiansyah; Dwi Shinta Angreni; Nouval Trezandy Lapatta
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.v11i1.7583

Abstract

The application of optimization algorithms to determine the shortest route is one effective approach to improving operational efficiency in various fields, including taxpayer monitoring. This study aims to implement two metaheuristic algorithms, namely the Ant Colony Optimization (ACO) algorithm and the Bee Algorithm, to identify the shortest routes for tax officers who are required to visit multiple taxpayer locations. In this study, both algorithms were tested using a dataset containing the locations of taxpayers that need to be monitored, with the objective of optimizing travel routes in order to reduce the total travel distance. The results show that both algorithms are capable of finding optimal or near-optimal solutions to the shortest path problem in the context of taxpayer monitoring. Although ACO is more effective in producing higher-quality solutions, the Bee Algorithm is faster in finding solutions, albeit with slightly less optimal results. This study also emphasizes the importance of algorithm parameter settings, such as the number of ants, the size of the bee colony, and the pheromone evaporation rate, which significantly affect solution quality and computation time.
IMPLEMENTASI YOLOv8 DAN DEEPSORT DALAM MENGANALISIS KECEPATAN PEMAIN PADA VIDEO REKAMAN SEPAK BOLA: IMPLEMENTATION OF YOLOv8 AND DEEPSORT IN ANALYZING PLAYER SPEED IN FOOTBALL VIDEO RECORDINGS Muhammad Naufal Hadi Silam; Defry Hamdhana Hamdhana; Lidya Rosnita Rosnita
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.v11i2.8474

Abstract

This research develops a computer vision‑based football player speed analysis system integrating YOLOv8 for object detection, DeepSORT for multi‑object tracking, and K‑Means clustering for team identification based on jersey color in the HSV color space. The system processes match videos through preprocessing stages (resizing, color space conversion, and filtering), camera motion compensation using Lucas‑Kanade Optical Flow, and speed calculation with filtering and smoothing mechanisms. Testing on a 30‑second match video demonstrates that HSV‑based K‑Means clustering effectively distinguishes players into two teams with a Silhouette Score of 0.62 and a centroid distance of 5.71°, despite highly similar jersey colors. Speed estimation yields average speeds of 19.7–23.47 km/h, which fall within the high‑speed running category (19.8–25.1 km/h) based on literature, with a maximum speed of 36.2 km/h aligning with professional sprint performance. Comparative analysis proves that HSV is more robust to lighting changes compared to RGB, which fluctuates up to 23 points. The system is implemented as a Flask‑based web application enabling video upload, automated analysis, and annotated video download. Therefore, the system is feasible as an objective and measurable tool for player performance analysis.  
DETEKSI SENTIMEN MULTIBAHASA: INDOBERT VS ROBERTA BERBASIS TERJEMAHAN NLLB-200 Fendi Elyon Ramadhan; Giat Karyono; Purwadi
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.v11i2.8498

Abstract

Sentiment classification in Indonesian-language social media text remains a challenge because informal spelling, code-mixing, culture-specific expressions, and class imbalance can reduce model reliability. Using a dataset containing 1,336 labeled X posts related to the 2024 Indonesian Presidential Election, this research compares two transformer workflows for three-class sentiment classification, which are fine-tuning IndoBERT on Indonesian text and a translation-based workflow, where NLLB-200 translates the same text into English before the RoBERTa training process. The dataset was divided via stratified sampling into 1,069 training examples, 133 validation examples, and 134 test examples. Both models were trained for five epochs with identical optimization settings and evaluated using accuracy, weighted precision, weighted recall, weighted F1, classwise scores, and confusion matrices. IndoBERT achieved 82.09% accuracy and 80.31% weighted F1, compared with 80.60% and 75.69% for the NLLB-200 plus RoBERTa pipeline. The largest difference occurred in the neutral class, for which IndoBERT obtained 0.26 recall and RoBERTa only 0.05. Error analysis indicates that translation artifacts and majority-class bias jointly reduced sensitivity to neutral and context-dependent expressions. Direct monolingual fine-tuning was more reliable for this dataset, although translation-based transfer remained competitive for the dominant positive class. Future work should use larger independently annotated datasets, repeated runs, translation-quality analysis, and class-aware training objectives.

Page 70 of 70 | Total Record : 696

 66   67   68   69   70 

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