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Deny Zainal Arifin
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matics@uin-malang.ac.id
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+6285646744340
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matics@uin-malang.ac.id
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Jurusan Teknik Informatika Fakultas Sains dan Teknologi Universitas Islam Negeri Maulana Malik Ibrahim Malang Jalan Gajayana 50 Malang, Jawa Timur, Indonesia 65144
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MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology)
Published by Universitas Islam Negeri Maulana Malik Ibrahim Malang
ISSN : 1978161X     EISSN : 24772550     DOI : https://doi.org/10.18860/mat
Core Subject : Science,
Computer Science & IT
MATICS is a scientific publication for widespread research and criticism topics in Computer Science and Information Technology. The journal is published twice a year, in March and September by Department of Informatics Engineering, Faculty of Science and Technology, Universitas Islam Negeri Maulana Malik Ibrahim Malang, Indonesia. The journal publishes two regular issues per year in the following areas : Algorithms and Complexity; Architecture and Organization; Computational Science; Discrete Structures; Graphics and Visualization; Human-Computer Interaction; Information Assurance and Security; Information Management; Intelligent Systems; Networking and Communication; Operating Systems; Platform-Based Development; Parallel and Distributed Computing; Programming Languages; Software Development Fundamentals; Software Engineering; Systems Fundamentals; Social Issues and Professional Practice.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 7 Documents
 1 
Search results for , issue "Vol 17, No 1 (2025): MATICS" : 7 Documents clear
Marketing Optimization: Purchase Data-Based Customer Segmentation Decision Support System Wong, Vinncent Alexander; Fadhiilah, Muhammad Althaaf; Santoso, Dzikry Aji; Setyorini, Luthfia Rahmi; Amrani, Andi Ahyar Almuhajir; Mursityo, Yusi Tyroni
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 17, No 1 (2025): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v17i1.24274

Abstract

Abstract—In the era of technological development and changes in shopping culture, e-commerce is increasingly dominating the market, and customer purchase data is becoming a valuable source of information for companies. To address the challenges of inappropriate targeting, customer retention, customer satisfaction, and measuring the effectiveness of marketing campaigns, this research aims to design a decision support system for customer segmentation based on purchase data, identify the optimal parameters of clustering algorithms, and develop appropriate marketing strategies for each group of customers generated from clustering. By using tools such as Matplotlib, Numpy, and Pandas, this research is expected to provide valuable guidance for companies in optimizing their marketing strategies in the competitive e-commerce market.
Evaluating User Experience (UX) on Universitas Terbuka’s Website: A Combined Survey and GTMetrix Performance Analysis Putri, Mayang Anglingsari; Trihapningsari, Denisha; Nurdiana, Dian
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 17, No 1 (2025): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v17i1.32094

Abstract

The Universitas Terbuka (UT) website serves as the primary platform for providing academic services and information to students, lecturers, and the general public. However, as the number of users and the complexity of digital services increase, User Experience (UX) becomes a crucial aspect that influences the effectiveness and user satisfaction in accessing information and utilizing available features. This study aims to evaluate and analyze the user experience of the Universitas Terbuka website using a combined approach, incorporating survey questionnaires and web performance analysis. The urgency of this research lies in the need to ensure that the UT website delivers an optimal experience for its users, particularly in terms of ease of navigation, access speed, information clarity, and responsiveness across different devices. With the growing reliance on digital systems in distance learning, UX evaluation becomes a strategic step in identifying challenges and opportunities for improvement. The novelty of this study lies in its holistic approach, which integrates subjective user feedback from surveys with objective web performance analysis. The findings of this research are expected to provide concrete recommendations for enhancing the UX quality of the Universitas Terbuka website, thereby supporting the effectiveness of distance learning and improving access to academic services.
Gated Recurrent Unit (GRU) for Sentiment Classification on Imbalanced Data: The COVID-19 Vaccine Program in Twitter Hadi, Mukhlis; Agustian, Surya
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 17, No 1 (2025): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v17i1.27995

Abstract

Abstract— The initial implementation of the COVID-19 vaccination by the Indonesian government sparked mixed reactions from the public, ranging from strong support to fierce opposition. These differing opinions influenced individuals' decisions to either accept or refuse the vaccination program for themselves or their families. Public sentiment, expressed through posts, comments, or status updates, provides valuable insights into vaccine acceptance or rejection. This study conducts sentiment analysis using deep learning techniques, specifically employing the Gated Recurrent Unit (GRU) method on Twitter data. The dataset consists of three sentiment classes: positive, negative, and neutral. The Word2Vec word embedding model was used as input and trained on a COVID-19 vaccination sentiment dataset collected from Twitter. Since the classes in the existing data tweets are imbalanced, some other steps are required to improve the classification. The best-performing model achieved an F1-score of 66% and an accuracy of 69%. This classification model effectively addresses the class imbalance problem, delivering competitive results compared to other methods.
Analysis and Design of the Web Base Guesthouse Reservation Information System at Universitas Terbuka Using The Prototype Method Kusyadi, Irpan; Junianto, Mochamad Bagoes Satria; Basri, Hasan
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 17, No 1 (2025): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v17i1.32380

Abstract

Efficient guesthouse reservation management is crucial to supporting the accommodation services provided by Universitas Terbuka. Currently, the existing system faces limitations in data management and time efficiency, particularly in the reservation, recording, and reporting processes. This study aims to analyze and design a web-based guesthouse reservation information system that is expected to facilitate the reservation process more effectively and transparently. The design approach used is the prototype method, which allows system development based on early user feedback. The research begins with identifying requirements through the stages of communication, planning, modeling, prototyping, and feedback collection. The results of this analysis are then used as the basis for designing the system model and the initial user interface (UI/UX). The system prototype is then developed and iteratively evaluated by involving potential users, including guesthouse managers and prospective guests, to ensure that the final design meets user needs
Market Basket Analysis Using FP-Growth and Apriori on Distro Store Sales Transaction Wulandari, Umi Meganinditya; Suseno, Akrim Teguh; Kholilurrahman, Muhammad
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 17, No 1 (2025): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v17i1.28820

Abstract

Market Basket Analysis analyzes consumer buying habits by finding relationships between items in the consumer's shopping basket. This Market Basket Analysis can provide success to the retail industry with the ability to understand consumer behavior and the speed of response to information obtained by retail business owners. This understanding is the result of an analysis that can help business owners improve marketing and sales strategies while utilizing transaction data. Sales transaction data that has been accumulated so far has only become data warehouses, while large amounts of transaction data can bring major changes to the level of competition in business and business actors in order to survive in the business world. In addition, after the COVID-19 outbreak, Indonesia experienced a slowdown in economic growth of 5.31%. This can be overcome by utilizing Market Basket Analysis to increase sales from their businesses. MBA with the methods used are FP-Growth and Apriori to analyze store transaction data in order to obtain association rules that can be used in improving marketing strategies. This analysis was carried out with 3 scenarios for 3 different minimum support values (1%, 2% and 3%) but the same minimum confidence value of 0.6 (60%). The comparison of the two methods is that 2 out of 3 scenarios produce the same association rule, namely 1 final association rule result with a lift value of 1.42. The three scenario results from both methods can be used by business owners as a consideration in determining sales strategies.
Comparison of the SAW (Simple Additive Weighting), AHP (Analytic Hierarchy Process) and Wieghted Product (WP) Methods in Catering Vendor Selection Sufandi, Unggul Utan; Putri, Mayang Anglingsari; Satria Junianto, Mochamad Bagoes; Minrohayati, Minrohayati
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 17, No 1 (2025): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v17i1.31854

Abstract

This study aims to develop a Decision Support System (DSS) for selecting the most suitable catering vendor for the UT Business Center by employing three decision-making methods: Simple Additive Weighting (SAW), Analytic Hierarchy Process (AHP), and Weighted Product (WP), alongside expert evaluation. Selecting an appropriate catering vendor is crucial to supporting university operations and events; therefore, the decision-making process must be based on objective and efficient criteria. Given the differences in the working principles of these three methods, it is essential to conduct a comparative analysis between AHP, SAW, and WP to determine the most suitable approach for catering vendor selection at the UT Business Center. The results of the study indicate varying levels of accuracy depending on the weighting scenario: Scenario 1 (Uniform Criterion Weights): Accuracy levels were AHP (83.33%), SAW (100%), and WP (100%). Scenario 2 (Expert-Determined Criterion Weights): Accuracy levels were AHP (58.83%), SAW (66.67%), and WP (66.67%).
Development of a Prototype Room Security Monitoring System for Early Fire Detection Using a Prototyping Method Based on Sensors and IoT Alfonsius, Eric
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 17, No 1 (2025): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v17i1.29521

Abstract

Many public spaces have implemented monitoring systems to detect fires. Traditional fire monitoring systems typically involve manual supervision of each room, requiring personnel to physically visit locations daily, which is time-consuming and inefficient. This study aims to develop a prototype room security monitoring system designed for early fire detection. The system utilizes IoT technology and a web-based platform, allowing operators to monitor all rooms remotely. The prototype is equipped with fire detection sensors and an alarm system for real-time alerts. Each room is outfitted with a flame detector sensor operated by a microcontroller (Arduino Nano), which serves as the central control for all connected devices. To transmit data from the sensors to the web-based system, the prototype uses the ESP8266 Wi-Fi module, enabling seamless communication between the sensors and the monitoring platform. The system development was carried out using the prototyping method, which involved iterative design, construction, and testing. In addition, blackbox testing was conducted to evaluate the system's functionality without examining the internal code. The results indicate that the system successfully detects fires early and sends real-time notifications to the web platform with high accuracy. The system also allows for rapid operator response through the alarm system. Based on the blackbox testing results, all key features, such as fire detection, web notifications, and alarms, functioned as specified. Thus, this prototype is deemed effective in enhancing the efficiency of room security monitoring.

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