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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 1,170 Documents
 103   104   105   106   107 
Vision-based Obstacle Detection and Motor Speed Control for Autonomous Driving Systems Aye Nilar Win; Zin Mar Lwin; Tin Tin Hla
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.v14i2.4849

Abstract

Autonomous driving systems rely on robust perception and control mechanisms to navigate safely in dynamic environments. This study presents a vision-based approach for obstacle detection and motor speed control using MobileNet SSD object detection model. The system utilizes a camera module to capture real-time video frames, which are processed to detect and classify obstacles. Based on the detected objects' position and distance, an adaptive motor speed control algorithm adjusts the vehicle's velocity to ensure collision avoidance and smooth navigation. The implementation is tested on a Raspberry Pi-based platform with an integrated motor control system, utilizing PWM signals for speed regulation. MobileNet SSD offers a lightweight, faster alternative for real time inference. Experimental results demonstrate the system’s effectiveness in detecting obstacles and dynamically adjusting speed in response to environmental conditions. This approaches enhance autonomous vehicle safety and efficiency, making it suitable for real-world applications in self-driving technologies.
Drone Detection and Identification Using SDR: Analysis of DJI Mini 2 Drone ID Signals Thi Thi Khaine; May Su Hlaing; Tin Tin Hla
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.v14i2.4850

Abstract

The increasing adoption of Unmanned Aerial Vehicles (UAVs) for both commercial and recreational purposes has raised significant security and privacy concerns. DJI OcuSync 2.0, a proprietary communication protocol used in DJI drones, enables high-definition video transmission and telemetry over dual-frequency bands (2.4 GHz and 5.8 GHz). Detecting and identifying OcuSync signals in a crowded RF environment is crucial for effective drone monitoring and threat mitigation. This study presents an SDR-based detection system utilizing the USRP B210 with a 50 MHz sampling rate to capture OcuSync signals. Signal analysis is performed using Short-Time Fourier Transform (STFT) and Welch’s method for estimating Power Spectral Density (PSD). A Non-Parametric Amplitude Quantization Method (NPAQM) is implemented for dynamic threshold estimation to improve detection sensitivity. The system is tested under varying Signal-to-Noise Ratio (SNR) conditions, demonstrating high detection accuracy and robustness against interference. The proposed system provides a reliable framework for real-time OcuSync signal identification and can be adapted for broader UAV detection applications.
Machine Learning-Based Security Algorithms for Detecting and Preventing DDoS Attacks on the IoT: State-of-the-Art, Challenges, and Future Directions Baloyi, Coster; Mathonsi, Topside; Du Plessis, Deon; Muchenje, Tonderai; Tshilongamulenzhe, Tshimangadzo
The Indonesian Journal of Computer Science Vol. 14 No. 3 (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.v14i3.4853

Abstract

Abstract - The Internet of Things (IoT) represents a vast network of interconnected devices equipped with software, sensors, and other technologies that enable data exchange and autonomous operation with other devices and systems without human intervention over the internet. IoT applications span across various sectors, including agriculture, education, healthcare, and communication. However, Distributed Denial of Service (DDoS) attacks continue to pose significant risks to the IoT network due to current challenges of classification efficiency and response times by the existing algorithms, such as Decision Tree (DT), Linear Regression (LR), and K-means. This paper provides a comprehensive review of DDoS attack types within the IoT networks. Secondly, the paper critically examines and analyses the challenges and opportunities inherent in leveraging Machine Learning (ML) algorithms for detecting, preventing, and mitigating these attacks. Finally, it presents the categories of IoT performance metrics, and their statistics found in the Literature over the Past decade.
Perancangan dan Evaluasi Keamanan Modul IAM pada Arsitektur Microservice Menggunakan Keycloak Ruhur, Winayaka
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.v14i2.4854

Abstract

Identity and security management are relevant concerns in microservice-based systems. The aim of this research is to model and examine a secure and unified Identity and Access Management (IAM) module founded on Keycloak and the NIST SP 800-53 security standard. A case study was conducted in organization that is undergoing digital transformation to a microservice architecture. The system offers authentication and authorization based on roles, attributes, and permissions. Identity federation is achieved via CAS, OIDC, and REST API protocols with custom Service Provider Interfaces (SPI). Testing includes unit testing, integration testing, and security testing. Results show the system functions as designed without show-stopping security vulnerabilities. This study contributes to secure and flexible IAM practices for microservice ecosystems.
Komparatif Studi Model Deep Learning Untuk Deteksi Karies Gigi Tanuwijaya, Yefta; Rochadiani, Theresia Herlina
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.v14i2.4857

Abstract

Dental caries is a dental disease that is considered a global public health problem and requires detection that is friendly to remote areas. This study presents a comparison of the evaluation results of deep learning models for detecting dental caries from early to extensive levels using YOLOv11, Faster R-CNN and RetinaNet models. The dataset contains 1,036 images divided into 4 classes (healthy teeth, early caries, moderate caries and extensive caries). As a result, YOLOv11 produced the highest mean average precision (mAP) of 79.2%. In addition, balanced precision (70.9%), recall (76.6%) and f1 score (73.6%), high average precision (AP) per class (healthy teeth: 85.5%, early caries: 66.9%, extensive caries: 91.6% and moderate caries: 72.6%), a 5.6 ms inference time and 5 MB model size are featured by YOLOv11 which is suitable to be implemented into various devices to support medical personnel in detecting dental caries in remote areas.
Evaluasi Kualitas Data Pada Daftar Produk Tayang Di Katalog Elektronik Versi 6.0 Pratiwi, Aprilia; Mahsa Elvina Rahmawyanet; Amanda Ghaisani; Tri Broto Siswoyo; Yova Ruldeviyani; Yudho Giri Sucahyo
The Indonesian Journal of Computer Science Vol. 14 No. 3 (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.v14i3.4858

Abstract

Data quality is important aspect in supporting transparency, accountability, and efficiency of the government procurement process. Electronic Catalog data acts as a source of information on products, services, and providers of goods/services. The transition from Electronic Catalog v5 to v6 is form of digital transformation in the government procurement of goods/services as form of improving public services. Measuring the quality of Electronic Catalog v6 data has significant role in providing effective, efficient and accountable information. This study aims to evaluate the quality of data on Electronic Catalog v6 product data using the Total Data Quality Management (TDQM) framework. There are 6 dimensions used in evaluating data quality, completeness, accuracy, data integrity, fairness, consistency, and precision. The results of the study show that the dimensions of consistency, accuracy, completeness, fairness and precision reach above 90% while data integrity reaches below 50% and requires improvement on product data quality.
A Model to Amplify Transmission Quality of Satellite Television Lebogang Maja; Deon du Plessis; Mathonsi, Topside; Tshilongamulenzhe, Tshimangadzo
The Indonesian Journal of Computer Science Vol. 14 No. 3 (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.v14i3.4861

Abstract

One of the various applications of communication satellite technologies is broadcasting satellite television (TV). In TV broadcasting, satellite communication is the easiest way to transmit many services and offers a variety of choices across a varied region, thereby overcoming the need for the complex infrastructure of terrestrial transmitters that a terrestrial network needs to broadcast its signals throughout a wide range area like countries or continents and providing quality digital TV viewing. However, Satellite TV broadcasting has a deficiency of outage effect caused by rain fade that instigate due to bad raining weather which at once will cuts signal transmission from the transmitter satellite to the receiver dish. this study was undertaken to explore the challenges that satellite TV broadcasting faces, which is caused by the rain fade effect. Thereafter, a model to amplify the transmission quality of satellite television is designed. The proposed Gau-satcomm algorithm, ITU-R model, and SAM model had an average BER of 5%, 8%, and 10%, respectively. Additionally, the Gau-Satcomm algorithm, SAM model, and ITU-R model experienced 4%, 9%, and 11% attenuation, respectively.  Furthermore, the study compared outage probability across three algorithms at frequencies over 10 GHz, the proposed Gau-satcomm algorithm, the ITU-R algorithm, and the SAM algorithm minimized outages by 10%, 7%, and 5%, respectively. Therefore, the proposed Gau-Satcomm outperforms these traditional algorithms in regard to average BER, a reduced average attenuation, and outage probability.
Improving Wireless Communication OFDM systems based on image processing Jaber, Ali
The Indonesian Journal of Computer Science Vol. 14 No. 3 (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.v14i3.4863

Abstract

One of the most common methods used in modern communication systems is orthogonal frequency division multiplexing (OFDM) to reduce the resistance to selective frequency fading. Another important reason is the possibility of reducing interference between symbols. However, there are also drawbacks, including the high peak-to-average power ratio (PAPR), which affects the power loss, increasing the complexity of transmitters. In the proposed study, we reduce PAPR in OFDM-based systems by hiding information in the image to maintain data security. In this steganography method, we insert digital text into the image and hide it, thus providing greater reliability while simultaneously reducing the PAPR required in OFDM. Text steganography is a method for hiding a large amount of information, which is helpful in OFDM. This also helps keep the system free from noise. Therefore, sending hidden data over communication channels is a good way to avoid interference, as image transmission is less affected by interference, and upon receipt, the main structure can be reconstructed to extract the hidden data and the original image. This is a way to preserve communication channels, which is the main objective of this study. The proposed method was evaluated by comparing the results with other methods, and it was found that the amount of data loss is reduced to 50% compared to the conventional method, which is the most important part. Also, the transmitted signal power has improved PAPR to 5.9 dB compared to the conventional method, which helps improve the quality of wireless transmission of the OFDM signal
Mengeksplorasi Faktor-Faktor Penentu Berbagi Pengetahuan di Sektor Publik: Tinjaun Sistematis-PRISMA Rizky, Fajar; Altino, Iqbal Caraka; Sensuse, Dana Indra; Lusa, Sofian; Safitri, Nadya; Elisabeth, Damayanti
The Indonesian Journal of Computer Science Vol. 14 No. 3 (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.v14i3.4864

Abstract

Knowledge sharing (KS) plays is essential for improving organizational performance and innovation, enabling faster problem-solving and collaboration. However, in the public sector, participation in KS remains low, hindering organizational learning and development. As Indonesia adopts knowledge management systems in its public sector, challenges emerge in fostering knowledge-sharing behaviors. This study uses the systematic review method, following PRISMA 2020 guidelines, to identify key factors influencing knowledge-sharing intention (KSI) and propose solutions. Through a rigorous selection process, 20 relevant studies were analyzed, categorizing factors into individual, organizational, and technological groups. The results indicate that attitudes, perceived behavioral control, subjective norms, reward systems, and the perceived usefulness of technology have a significant impact on KSI. This study offers a comprehensive reference for future research on KS in the public sector and provides insights for policymakers to design initiatives that enhance organizational learning.
High-Precision GPS Tracker for Monitoring Agricultural Sprayer Drone Operations Haryono
The Indonesian Journal of Computer Science Vol. 14 No. 3 (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.v14i3.4871

Abstract

Efficient and precise pesticide application is critical in modern agriculture, especially when using drone technology. To ensure that spraying operations are carried out accurately in the intended locations, a reliable tracking system is essential. This newly developed Agriculture Sprayer Drone Tracker addresses this need through several key improvements over traditional methods. Previously, monitoring was performed using wired connections to check the tank, but the new system employs a wireless LoRa solution housed in a robust IP67-rated enclosure for better durability and flexibility.The tracker features a custom-designed GPS board based on the u-blox F9P module, providing high-precision location data. The GPS antenna has been optimized for a more compact form factor, resulting in a smaller, more portable device. Data is logged directly to an SD card and can be quickly accessed via a USB connection. This method offers a significant improvement over previous systems that relied on web APIs, which were often slow and dependent on internet speed. With dedicated software, users can now efficiently retrieve and save tracker data to a PC. Overall, these advancements make the tracker more versatile, reliable, and user-friendly, enhancing the effectiveness of agricultural drone spraying operations.

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