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Tri A. Sundara
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The Indonesian Journal of Computer Science
Published by STMIK Indonesia Padang
ISSN : 25497286     EISSN : 25497286     DOI : https://doi.org/10.33022
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
The Indonesian Journal of Computer Science (IJCS) is a bimonthly peer-reviewed journal published by AI Society and STMIK Indonesia. IJCS editions will be published at the end of February, April, June, August, October and December. The scope of IJCS includes general computer science, information system, information technology, artificial intelligence, big data, industrial revolution 4.0, and general engineering. The articles will be published in English and Bahasa Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 65 Documents
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Search results for , issue "Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science" : 65 Documents clear
Penerapan TAM dalam Evaluasi Penerimaan Aplikasi P-Care BPJS Pada Puskesmas di Kabupaten Gorontao Utara Gobel, Jimilin; Dai, Roviana; Ahaliki, Budiyanto
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4102

Abstract

P-Care BPJS is a web-based management information system that can be accessed through a web browser with the address https://pcarejkn.bpjs-kesehatan.go.id/eclaim/ which generally functions to check the validity of BPJS membership data. However, in its use, there was an inconvenience when using the P-Care BPJS application where the patient's social data entry failed, causing the P-Care BPJS officer to double-enter the patient's social data. Another problem found in the form of slow application performance when used which results in the length of work time and service response time by P-Care BPJS officers. This research was conducted to find out how far the acceptance of the existing P-Care BPJS application at Puskesmas in North Gorontalo district and what factors can affect user acceptance. This research uses descriptive quantitative methods and uses the TAM Model to measure user acceptance, the results of the analysis show that the P-Care BPJS application has been well received by users with an acceptance of 80.6.
Optimasi Model Algoritma Machine Learning Suppervised menggunakan Algoritma Genetika untuk Prediksi Kebakaran Hutan dan Lahan Utami, Putri; Sucipto; Risli , Andrea; Aurilia Viona, Tiara
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4395

Abstract

Forest and land fires are a common occurrence in Indonesia, particularly in the provinces of Sumatra and Kalimantan. One strategy for mitigating the impact of forest and land fires is to predict areas that are prone to such incidents. In this study, genetic algorithm (GA) optimization was employed to enhance the efficacy of the random tree and hyper-SVM algorithms, with a view to identifying the most optimal test results. The dataset utilized in this study comprises hotspot data and climate data for Ketapang Regency during the 2021-2022 period. The results of the training and testing demonstrate that the Random Tree +GA algorithm optimization with a PC value of 0.6 and Bolzmann selection parameters yields an accuracy of 99.77%, a recall of 94.88%, a precision of 95%, an RMSE of 0.015, and a Kappa of 0.9. In contrast, the Hyper-SVM +GA optimization, with a PC value of 0.6 and Bolzmann selection parameters, yielded an accuracy of 70.48%, a recall of 52.14%, a precision of 50.58%, an RMSE of 0.493, and a Kappa of 0.026. The results demonstrate that the Random Tree +GA algorithm model optimization exhibits superior performance compared to Hyper-SVM +GA optimization. Consequently, it can be inferred that the Random Tree +GA algorithm represents the most effective classification model for predicting the likelihood of forest and land fires in Ketapang Regency
Detecting Distributed Denial of Service Attacks in Mobile Edge Computing using Modified Extreme Machine Learning Mapunya, Sekgoari; Mthulisi Velempini
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4538

Abstract

Mobile Edge Computing (MEC) is a promising technology which enables 5G and reduces latency. By bringing cloud computing capabilities closer to end users, MEC enables latency-sensitive applications to perform more efficiently. However, security attacks pose significant challenges to the objectives of 5G with Distributed Denial of Service (DDoS) attacks being a major threat. These attacks can overwhelm target systems with excessive data preventing access to and disrupting network services. Effective mitigation strategies are required to protect MEC technology. Given the high data volume generated by such attacks, this paper utilizes a modified Firefly Algorithm to select relevant features. These selected features are then used to train a proposed variant of Extreme Learning Machine (ELM), where weights are initialized using Neighbourhood-Based Differential Evolution. MATLAB simulations demonstrate that the proposed modified ELM outperforms traditional approaches, providing an effective solution to DDoS attacks in MEC.
Implementasi Algoritma Priority Scheduling Pada Sistem Informasi Pemesanan Layanan Fotografi dan Videografi Anfaisa, Anfaisa Ibnu Danar Dana; Dedi Gunawan
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4583

Abstract

Creative industries in Indonesia are growing rapidly, including photography and videography services. The need for people to capture important moments drives the demand for these services. Agratha Studio, a production house in Surakarta, specializes in photography and videography. However, the ordering process is still done manually, which creates obstacles for customers and studios. This research aims to help Agratha Studio improve services to customers by designing a website-based videography service booking information system. The system is designed with features such as user login and registration, service data management, online ordering, and order management by the admin. This system implements priority scheduling algorithm. The priority scheduling algorithm is a priority-based scheduling algorithm where each scheduling process has a priority number. The development of a website-based videography service ordering information system can help Agratha Studio improve services to customers and increase the efficiency and effectiveness of the ordering process.Regular monitoring of the information system is also conducted to ensure the fulfillment of the objectives underlying the development of this complaint reporting and information system.
Towards a Cashless Transactional Society Through the Adoption of Digital Banking Services Ngandu, Matipa Ricky; Mwansa, Gardner; Ntoyabo, Siwongiwe Queenest
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4612

Abstract

This study explores the adoption of digital banking services in a rural South African town in the Eastern Cape, emphasizing its contribution to a cashless society. Employing a quantitative method, it examines digital banking usage, adoption challenges, and information security awareness. Data were collected through surveys and analyzed using descriptive statistics. Findings show that mobile and online banking are widely used for convenience and accessibility, with most users engaging in money transfers, credit payments, and online shopping. However, challenges such as poor digital literacy, infrastructure issues like internet access, cost of access, and cybersecurity concerns persist. Users face risks like phishing, hacking, and social engineering, revealing gaps in security awareness and trust. These issues particularly affect older users and those with limited technological experience. While digital banking improves financial inclusion and economic engagement in rural areas, its full potential is hindered by these barriers. The study underscores the need for digital literacy programmes, infrastructure improvements, and robust cybersecurity measures to build trust and ensure secure adoption. Future research should evaluate interventions, explore emerging technologies like blockchain and AI, and compare regional strategies for inclusive digital financial systems.
C vs Rust: Manual vs Automatic Spatial and Temporal Memory Safety Syalim, Amril; Sheradhien, Dewangga Putra
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4640

Abstract

The C programming language is commonly used for creating high-performance and low-level applications such as device drivers and operating systems due to its efficiency. However, despite its performance capabilities, C is known for its vulnerabilities and unsafe coding practices. Rust is presented as an alternative to C, with a focus on improved safety without compromising performance. Rust employs ownership and borrowing concepts to manage memory usage, ensuring that the memory cannot be manipulated freely without adhering to specific rules designed to prevent security attacks. The memory restrictions are implemented either at compile time or runtime without requiring the programmer's direct involvement; however, the programmer must adhere to a strict coding standard. In contrast, C programs can be secured by manually implementing similar restrictions on memory access and adding checks for unpredictable runtime behavior. While this approach offers some protection against attacks, it requires the developer to have detailed knowledge of memory management and programming best practices. This research focuses on evaluating memory safety issues in terms of spatial and temporal safety, comparing Rust's security mechanisms (or lack thereof) to C. Spatial safety involves securing vulnerable memory locations, while temporal safety ensures safe access to memory at different times. These concepts are frequently exploited by attackers to access data or inject attack payload. Our analysis demonstrates that Rust offers stronger guarantees for memory safety compared to manual security implementations in C. However, C remains a viable option for performance-critical applications, as it can still be secured through careful coding practices.
Understanding the Adoption of Healthy Mobile Diet Applications Among Adults Rima Zakiah Putri; Betty Purwandari; Ni Wayan Trisnawaty
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4644

Abstract

Non-communicable diseases (NCDs) account for 53% of premature deaths globally, posing significant challenges to healthcare systems. In Indonesia, the rising prevalence of obesity and overweight among adults highlights the urgent need for innovative interventions to promote healthier lifestyles. Mobile diet applications have emerged as a promising solution, offering accessible tools for health monitoring and behaviour change. However, adoption rates in Indonesia remain low due to a limited understanding of the factors influencing user acceptance. This study aims to analyze the determinants of mobile diet application adoption among Indonesian adults using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, extended with five external factors: trust, perceived health threat, health consciousness, health conditions, and body image. Data were collected through an online survey with 218 respondents who had used diet applications such as Cronometer, FastEasy, and MyFitnessPal within the past six months. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed for analysis. The findings reveal that effort expectancy, social influence, price value, health conditions, and body image significantly influence adoption. In contrast, performance expectancy, hedonic motivation, trust, perceived health threat, and health consciousness were not significant predictors. These results underscore the importance of intuitive interface design, community-driven features, and personalization based on health data to enhance user engagement and adoption. This study contributes to understanding user behaviour in health technology adoption in a developing country. It offers practical recommendations for application developers and policymakers to optimize the use of mobile diet applications as part of broader efforts to address NCD challenges in Indonesia.
A Determination of Sample Size for Plant Leaves in Deep Learning Models for Predicting Late Blight in Irish Potatoes: An experimentation methodology in Kigezi –Uganda Turihohabwe, Jack
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4647

Abstract

Determining the sample size of Deep learning models still remains a challenges in the Artificial Intelligence world. This is because most of the developers of deep learning models utilize available data collected from public datasets sites such PlantVillage or Kaggle. This study proposes using the acreage method putting into consideration of the machine learning dataset condition. The main objective of this research is to experiment the methods that can be used to determine the appropriate sample size for a Deep learning model. This study used the experimental and statistical methodologies and incorporated the boundaries of the Machine learning condition. The average sample estimation of the measurements in the piece of land (plot) was (1x4X10) cm. The measurement of the leaves was 3.5-5cm in length and 1.5-3 cm in width. The experiments were done between (2:00-4:00) am to have a good lighting condition. The optimal leaning rate of the deep learning architectures involved in the study used a learning rate of 0.0001. The study covered an acreage of 28000.25 acres and the Dataset 2145 Irish potato leaves was obtained and got 9,660 images after augmentation. This was purposively collected from ten sub-counties due to time and financial constraints in this study. This study proposed a methodology for obtaining the sample size using the acreage methodology and purposive sampling and there use the Machine learning condition for  sample sizes  for creation of deep learning models from potato leaf images targeted at preventing late blight based on leaf images. Future research may extend this study to further more validate the acreage methodology putting into account the Machine learning condition and also developing the Deep learning condition. 
Analisis Sentimen Publik Terhadap Penangkapan Ikan Ilegal oleh Kapal Vietnam di Twitter Menggunakan Metode GRAFT Ardiansyah, Rama; Inayah, Nur; Liebenlito, Muhaza
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4650

Abstract

Penangkapan ikan ilegal oleh kapal asing, khususnya dari Vietnam, telah menjadi masalah yang cukup serius di Indonesia. Kegiatan ini tidak hanya merugikan perekonomian nasional, tetapi juga mengancam sumber daya laut. Di era digital, media sosial, khususnya Twitter, telah menjadi wadah penting bagi masyarakat untuk menyuarakan pendapat dan reaksi terhadap berbagai isu terkini. Penelitian ini menggunakan metode GRAFT untuk menganalisis sentimen publik di Twitter terkait penangkapan ikan ilegal oleh Vietnam. Analisis ini bertujuan untuk menggali pandangan masyarakat dan mendapatkan wawasan yang lebih mendalam mengenai isu-isu tersebut. Temuan penelitian ini diharapkan dapat menjadi dasar untuk merumuskan kebijakan yang lebih efektif dalam menanggulangi IUU Fishing di perairan Indonesia.
APT Winnti Panda as a Power-Gathering Tool in International Cyberspace Septiasari, Rycka; Kurniawan, Yandry; Arifandy, Mohamad; Putri, Erika Husna Nabila
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4687

Abstract

This study provides an analysis of the Advanced Persistent Threat (APT) Winnti Panda impact on Indonesian infrastructure in 2022, which is a tool for gathering power in international cyberspace. The cybersecurity dilemma concept is utilized to explain the phenomena that occur using a deductive qualitative method. This study highlights how Indonesia perceives the cyber threats posed by the APT Winnti Panda. The data used in this study are primary data sourced from the Indonesian Cyber Security Agency (BSSN), which was taken through interviews. In addition, secondary data is also used using the archival and desk research methods from various online and offline sources. The main argument of this study is that the APT Winnti Panda, which attacked Indonesia in 2022, is a tool used to gather power in international cyberspace.

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