Article Per Year (5 Year)
p-Index From 2021 - 2026
0.702
P-Index
This Author published in this journals
All Journal JISA (Jurnal Informatika dan Sains) JITCoS : Journal of Information Technology and Computer System Proceedings of The International Conference on Computer Science, Engineering, Social Sciences, and Multidisciplinary Studies
Berutu, Asro Hayati
Unknown Affiliation
Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Analysis of Indonesian Netizen Sentiment Towards the Government's Campaign on the Use of Artificial Intelligence Using the Naive Bayes Algorithm Nasution, Salsabila; Berutu, Asro Hayati; Aulia, Fatwa
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.28

Abstract

The development of artificial intelligence (AI) has encouraged the Indonesian government to adopt this technology in various public service sectors. However, the use of AI has received mixed responses from the public, particularly on social media. This study aims to analyze Indonesian netizen sentiment towards the government's AI campaign using the Naive Bayes algorithm. Data was collected from the Twitter platform and analyzed through preprocessing, sentiment classification, and model evaluation. The results show that the majority of netizen sentiment is negative, with concerns related to unfairness for creative workers, a lack of regulation, and the use of AI for political gain. This research is expected to provide input for the government in designing more ethical and inclusive AI adoption policies.
Analysis of User Interaction Association Patterns in E-Learning Systems Using the Apriori Algorithm Rizka; Berutu, Asro Hayati; Nabawy, Putri; Pratama, Haris; Supiyandi
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.30

Abstract

The development of e-learning systems has generated a vast volume of user interaction data. Every activity—such as logging in, viewing materials, taking quizzes, and downloading assignments—contains valuable information that can be leveraged to enhance the effectiveness of online learning systems. This study aims to analyze user interaction association patterns in an e-learning system using the Apriori algorithm. A data mining approach was employed to identify relationships among features frequently accessed together, with a minimum support threshold of 0.4, minimum confidence of 0.6, and lift > 1.0. The dataset used consists of simulated (dummy) data representing seven user transactions and five main e-learning features. The analysis produced eight significant association rules with lift values above 1.0, indicating non-random relationships among features. Feature combinations such as {login} → {view_material} and {take_quiz} → {view_score} exhibited strong relationships, with confidence values reaching 0.75. These findings suggest the existence of dominant user interaction patterns that can be utilized to optimize navigation design, recommendation features, and overall user experience in e-learning systems. This research contributes to the application of the Apriori algorithm for exploring user access patterns in online education contexts, providing an analytical foundation for developing more adaptive and behavior-driven systems.
Implementation of a Website-Based Proposal Seminar Registration System Using the Waterfall Method at Sheikh Abdul Halim Hasan Binjai Institute Rizka, Rizka; Lubis, Fitra Hidayat; Berutu, Asro Hayati; Ritonga, Saprina Putri Utama; Gibran, M Khalil
JISA(Jurnal Informatika dan Sains) Vol 8, No 1 (2025): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v8i1.2200

Abstract

Registration of proposal seminars at the Sheikh Abdul Halim Hasan Binjai Institute is still done manually, which causes problems such as late information, errors in data recording, and lack of efficiency in administrative management. The institute currently has approximately 1,200 active students, with an average of 150–200 students submitting seminar proposals each semester. This increasing number of participants makes the manual system even more burdensome and prone to errors. To overcome these problems, a website-based proposal seminar registration system was implemented. This system is designed to make it easier for students to register, as well as help the administration in managing the data of seminar participants in a more effective and structured manner. The system development uses the PHP programming language with a MySQL database and the waterfall development method as a systematic approach in the implementation process. The results of the implementation show that the system is able to improve the efficiency of the registration process, minimize data errors, and provide real-time information for students and supervisors. With this system, it is expected that the proposal seminar administration process will become more organized and transparent.
Parking Route Modeling Using the A* Algorithm for Density Reduction at the Faculty of Science and Technology, State Islamic University of North Sumatra Berutu, Asro Hayati; Nasution, Salsabila; Rahmadani, Suci
JITCoS : Journal of Information Technology and Computer System Vol. 1 No. 2 (2025): Volume 1 Number 2, December 2025
Publisher : CV. Multimedia Teknologi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65230/jitcos.v1i2.46

Abstract

The increasing number of vehicles on university campuses has led to significant congestion, particularly around parking areas. This study aims to design an intelligent parking route model using the Density-Aware A* algorithm to minimize vehicle congestion within the Faculty of Science and Technology (FST) at UIN North Sumatra. The proposed approach represents the internal campus network as a weighted graph, where each edge integrates both spatial distance and a density penalty that reflects the occupancy-to-capacity ratio of each parking area. The algorithm was implemented and simulated using Python and the NetworkX library within Google Colab. The results show that the system accurately identifies the optimal parking route based on vehicle type and real-time occupancy data. For motorcycles, the optimal path is A > B > F with a total cost of 23.06, while for cars, the most efficient path is A > B > H with a total cost of 18.21. The findings indicate that incorporating density-based cost adjustments effectively balances travel efficiency and vehicle distribution, contributing to overall congestion reduction in the FST–FKM corridor. Future research should focus on integrating live sensor data and adaptive feedback mechanisms to support large-scale deployment across diverse campus environments.
Co-Authors Aulia, Fatwa Gibran, M Khalil Lubis, Fitra Hidayat Nabawy, Putri Nasution, Salsabila Pratama, Haris Ritonga, Saprina Putri Utama Rizka Rizka Rizka, Rizka Suci Rahmadani Supiyandi Supiyandi