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Journal Innovations Computer Science
Published by Yayasan Kawanad
ISSN : 29619718     EISSN : 2961970X     DOI : https://doi.org/10.56347/jics
Core Subject : Science,
Computer Science & IT
Journal Innovations Computer Science (JICS) is a peer-reviewed, twice-annually published international journal that focuses on innovative, original, previously unpublished, experimental or theoretical research concepts. Journal Innovations Computer Science (JICS) covers all areas of computer & information science, applications & systems engineering in computer & information science. JICS core vision is to be an innovation platform in information technology and computer science. Articles of interdisciplinary nature are particularly welcome. All published article URLs will have a digital object identifier (DOI).
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 137 Documents
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AcaraKita: Integrated Digital Platform for Event Organizer Services in Indonesia Tegar Pangestu, Bukhori Debrillianda; Nurfattah, Fu’ad Na’im; Rahman, Haidar; Wido Prasojo, Nanda
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.306

Abstract

This study examines the development and implementation of AcaraKita, a web- and mobile-based digital platform designed to modernize event organizer (EO) services in Indonesia. The system integrates three primary actors—Admin, Admin EO, and Customer—each with distinct yet complementary roles involving vendor management, booking, verification, status tracking, and service reviews. The development process applied the Waterfall model, consisting of requirement analysis, design, implementation, testing, deployment, and maintenance, combined with IT governance evaluation using the COBIT 5 framework to ensure alignment with business objectives. Testing results indicated that all core features operated effectively, with an average response time of less than one second and a user satisfaction score of 4.139 on the Likert scale. The IT governance risk analysis highlighted the need for improvements in documentation, security, and business continuity planning. While the system demonstrates a solid foundation, further enhancements are necessary, including social media API integration, vendor recommendation systems, and analytics dashboards to support decision-making. Overall, AcaraKita strengthens EO digitalization, improves operational efficiency, and fosters service transparency in a sustainable manner.
Security Analysis of Midtrans Payment Gateway API against DDoS Attack and Rate Limiting Technique Using Node.js Widianto Putro, Faris; Matheos Sarimole, Frencis
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.308

Abstract

The development of digital transaction services has led to the widespread use of APIs in payment systems, including payment gateway services such as Midtrans. However, the open access to APIs also increases the risk of cyber attacks, one of which is Distributed Denial of Service (DDoS) which can destabilize the system and reduce user confidence. This research aims to analyze the potential DDoS threats to the Midtrans API and explore the application of rate limiting techniques using Node.js as one of the mitigation measures. The methodology used is a waterfall approach, which includes requirements analysis, system design, implementation, testing, and evaluation. The test design is done through simulating DDoS attacks on API endpoints, both before and after the application of rate limiting, by measuring parameters such as the number of requests, response time, and request success rate. It is hoped that this research can provide a clear picture of the importance of API protection in digital payment systems, and produce a technical approach that can be used as a reference in developing a secure and reliable system. This research is also expected to make practical and theoretical contributions in the field of API security and digital service traffic management.
Decision Tree-Based Predictive Model Development for RumahNet Customer Satisfaction Analysis in West Jakarta Yuliantoro, Dita Tri; Sarimole, Frencis Matheos
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.310

Abstract

The rapid growth of information technology has amplified the demand for fast and reliable internet services, particularly in urban centers such as West Jakarta. This study aims to design a predictive model of customer satisfaction for RumahNet’s Fiber to the Home (FTTH) services by applying the Decision Tree (C4.5) algorithm. A survey of 250 active subscribers was conducted using a Likert-scale questionnaire distributed through Google Forms, capturing perceptions of internet speed, connection stability, pricing, and technical support. The dataset was processed and analyzed using RapidMiner Studio within the Knowledge Discovery in Databases (KDD) framework. Results show that the model achieved an accuracy of 85.33%, precision of 91.93%, recall of 90.47%, and an F1-score of 91.18%. The decision tree revealed that internet speed and connection stability were the most critical determinants of satisfaction, followed by pricing and responsiveness of customer service. These findings suggest that prioritizing technical reliability while maintaining affordability and responsive support is essential for strengthening loyalty and reducing churn. The research demonstrates that Decision Tree modeling not only provides high predictive accuracy but also offers clear interpretability, making it a valuable tool for data-driven decision-making in the ISP sector.
Analysis of the JAKLITERA Website Information System Using the PIECES Method to Enhance Library Services at the Library and Archives Office of DKI Jakarta Province Anandita Putri, Syaharani; Tanti Rahayu, Agus; Aditiya, Arya
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.312

Abstract

The advancement of information technology has shifted libraries from traditional physical services to digital platforms. One example is JAKLITERA, a web-based information system developed by the Provincial Library and Archives Office of DKI Jakarta. This study aims to evaluate the performance and service quality of JAKLITERA using the PIECES framework (Performance, Information, Economics, Control, Efficiency, Service). A mixed approach was applied, combining quantitative data from 100 user questionnaires with qualitative insights from observation and administrator interviews. Validity and reliability testing confirmed that all research instruments were appropriate for analysis. Results showed that the Economics dimension achieved the highest mean score (3.95), while Control received the lowest (3.39). Overall, the average score of 3.62 categorized JAKLITERA as “satisfactory,” yet highlighted the need for improvements in security mechanisms and clarity of information. These findings suggest that JAKLITERA functions effectively as a digital literacy platform but requires continuous evaluation, technical optimization, and user-centered enhancements to ensure sustainable service delivery.
Implementation Analysis of Network Core Redundancy Using HSRP and VRRP Protocols for Enterprise Infrastructure Reliability Assurance Firdaus Syah, Tengku; Adriyanto, Sopan
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.314

Abstract

This study examines the role of redundancy protocols in enhancing the reliability of core networks within enterprise infrastructures. The research is motivated by the growing reliance of organizations on network-based services and the increasing risks of financial losses caused by downtime, which are projected to escalate alongside global traffic growth. A simulation-based approach was conducted using Cisco Packet Tracer to compare baseline networks without redundancy against implementations of Hot Standby Router Protocol (HSRP) and Virtual Router Redundancy Protocol (VRRP). The evaluation focused on key performance indicators, including failover time, uptime rate, packet loss, latency, and jitter. The results demonstrate that both protocols successfully provided automatic recovery mechanisms, achieving an average failover time of less than five seconds while maintaining stable connectivity. Further analysis revealed that HSRP excels in failover speed, whereas VRRP offers cross-vendor flexibility with consistent stability. These findings confirm that redundancy protocol selection should align with specific network requirements, yet both HSRP and VRRP have proven effective in minimizing downtime risks and ensuring service continuity in enterprise-scale environments.
Low-Cost DC Motor Design for Embedded Systems in Smart Applications Patel, Arjun
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.273

Abstract

The rapid growth of embedded systems demands reliable, efficient, and affordable actuators for smart applications such as home automation and IoT. This study develops a low-cost DC motor based on fundamental electromagnetic principles, finite element analysis (FEA), and Arduino-based PWM control. The motor is constructed from simple materials like copper wire, iron core, and neodymium magnets, with a production cost under five US dollars per unit. Experimental results demonstrate efficiency up to 35% at 165 RPM with a 100-turn coil configuration and a 0.4 Tesla magnetic field. FEA is used to validate the design and identify optimal configurations, while PWM control enables precise speed and torque regulation. The motor is integrated into a smart curtain prototype using MQTT, which automatically adjusts curtain position based on light sensor input, proving the motor’s compatibility with modern automation systems. Experimental findings reveal that increasing coil turns and magnetic field strength significantly improves torque, speed, and mechanical stability. This motor offers a cost-effective solution suitable for educational, research, and commercial applications in resource-constrained environments. The study also opens avenues for future brushless motor development and AI-based adaptive control to further enhance performance. By combining mechanical simplicity with electronic sophistication, this motor presents an optimal alternative for embedded systems prioritizing efficiency and affordability. This approach supports the democratization of automation technology, especially in developing countries and educational institutions with limited budgets.
IoT-Based Integrated Monitoring System for Household Water Level and Usage Tracking Rivaldi, Muhammad Rizki; Said, Fadillah
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.317

Abstract

Conventional household water management often results in inefficiencies, including tank overflow, unexpected shortages, and a lack of awareness about daily consumption. Most existing solutions address these issues only partially—either by monitoring water levels, automating pump control, or recording usage data—without integrating the three into a unified system. To address this gap, this research developed and validated a low-cost Internet of Things (IoT) prototype that combines real-time water-level monitoring, daily consumption measurement, and automatic pump control within a smartphone-connected platform. The system is built on a NodeMCU ESP8266 microcontroller equipped with an HC-SR04 ultrasonic sensor, a YF-S201 flow sensor, and a relay-controlled pump, with data transmitted via Wi-Fi to the Blynk application. Using a Research and Development (R&D) methodology with a prototyping model, the study conducted functional, accuracy, and usability testing. Results show that the prototype achieved reliable performance, with an average error below 2% for both sensors and stable operation during 24-hour trials. Beyond technical validation, the system demonstrated its potential as an eco-feedback tool by providing clear consumption data that can encourage more sustainable water use at the household level.
Support Vector Machine-Based Sentiment Analysis of Customer Reviews for Android Smartphone Products on Shopee Marketplace Hutauruk, Lucas Namora; Lestari, Sri; Aula, Raisah Fajri
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.321

Abstract

The rapid expansion of e-commerce in Indonesia has resulted in a surge of unstructured online reviews, especially on platforms such as Shopee. These reviews offer valuable insights into customer satisfaction, product complaints, and purchasing behavior but remain largely underutilized due to their volume and informal language style. This study applies Support Vector Machine (SVM) with Term Frequency–Inverse Document Frequency (TF-IDF) feature extraction to classify reviews of Android smartphones into positive, negative, and neutral categories. Using a dataset of 300 manually annotated reviews from Samsung, Xiaomi, and Oppo official stores, the model achieved an accuracy of 76.67% and demonstrated stable results through 5-fold cross-validation. The negative class showed the highest performance (F1 = 0.86), while the neutral class performed weakest (F1 = 0.62), reflecting challenges posed by mixed opinions and underrepresented samples. Compared with Naïve Bayes and Logistic Regression, the SVM model consistently outperformed both baselines, confirming its suitability for high-dimensional text data and informal Indonesian expressions. The findings highlight SVM’s potential to support automated sentiment monitoring in e-commerce, enabling businesses to identify emerging issues, improve customer service strategies, and leverage positive reviews for marketing. Future research should consider larger and more balanced datasets, techniques for handling imbalanced classes, and integration with deep learning models such as LSTM or BERT to improve performance and generalization.
Real-Time Face Recognition System with Enhanced Security Using Cryptographic Hash-Based Encrypted Embedding Matching Zaidan, Rodhi Shafia; Kastum; Mulyana, Dadang Iskandar
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.322

Abstract

This study presents the development and evaluation of a secure and efficient real-time face recognition system for school attendance, integrating cancelable biometrics with cryptographic hashing. A total of 115 face samples were collected from students and teachers under diverse lighting, pose, and expression conditions. Images were pre-processed using Contrast Limited Adaptive Histogram Equalization (CLAHE) and Gamma Correction, followed by feature extraction with ResNet-128D, key-based random projection, binarization into 128-bit templates, and SHA-256 hashing. Evaluation results demonstrated an accuracy of 86.09%, precision of 100%, recall of 86.09%, and F1-score of 92.52%, with an average latency of 281.71 ms, remaining well below the operational threshold of 500 ms. Offline pre-processing improved the F1-Score by 7.50% on large datasets and 7.28% on smaller datasets without sacrificing processing speed. From a security perspective, the system achieved zero false acceptances (FAR = 0%) and allowed template regeneration when compromised, reinforcing privacy preservation. These findings validate the feasibility of combining cancelable biometrics with cryptographic hashing to balance accuracy, speed, and security in practical attendance systems. The research underscores its broader applicability to access control and public security, while future work should emphasize adaptive pre-processing, diverse hardware validation, and hardware acceleration for robust real-time deployment.
Support Vector Machine and Histogram of Oriented Gradients-Based Classification System for Waste Type Identification Notonegoro, Danendra Satriyohadi; Mulyana, Dadang Iskandar
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.315

Abstract

This study examines the effectiveness of classical computer vision methods for modern waste classification by combining Histogram of Oriented Gradients (HOG) for feature extraction with Support Vector Machine (SVM) for classification. The TrashNet dataset, consisting of five categories—cardboard, glass, metal, paper, and plastic—was used as the primary benchmark. To address data limitations and improve generalization, augmentation techniques such as random rotations, horizontal flipping, and brightness adjustments were applied. Hyperparameter optimization was further conducted using GridSearchCV with the RBF kernel to determine the most effective configuration. The optimized model achieved an accuracy of 84.36%, representing a substantial improvement from the 60% baseline. These findings confirm that non-deep learning approaches remain relevant and can serve as computationally efficient alternatives to CNNs, which typically require GPUs and extensive training time. Challenges persist in classifying reflective materials such as glass and metal, where HOG descriptors are less effective. Future work should integrate complementary descriptors, including color and texture-based features, to enhance robustness and scalability. Overall, the study demonstrates that an optimized HOG-SVM pipeline offers a practical, resource-efficient solution for automated waste classification, with strong potential to support sustainable waste management in real-world applications.

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