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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 1,127 Documents
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Smart Budikdamber Sistem Budidaya Ikan Terintegrasi Berbasis IoT Blynk Dengan Pemantauan dan Pengendalian Real-Time Davin Andika Dhananjaya
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4344

Abstract

Budikdamber (budidaya ikan dalam ember) adalah metode budidaya ikan yang efisien dan ramah lingkungan. Namun, pemantauan dan pengendalian kondisi air dan ikan sering kali terhambat oleh keterbatasan waktu dan akses, mengakibatkan kualitas air yang buruk dan pertumbuhan ikan yang suboptimal. Untuk mengatasi tantangan ini, penelitian ini mengembangkan sistem Budikdamber berbasis Internet of Things (IoT) yang terintegrasi, memungkinkan pemantauan dan pengendalian secara real-time. Sistem ini dirancang dan diimplementasikan menggunakan sensor suhu air, sensor ketinggian air, sensor pH, pompa air, lampu, kipas, dan alat pemberi makan otomatis. Seluruh sistem terhubung ke internet melalui mikrokontroler ESP32 dan aplikasi seluler Blynk untuk pemantauan dan pengendalian. Hasil pengujian menunjukkan bahwa sistem ini berhasil memantau suhu dan ketinggian air secara real-time serta secara otomatis mengendalikan pompa air, lampu, kipas, dan alat pemberi makan. Sistem ini secara signifikan meningkatkan kualitas air dan pertumbuhan ikan, sehingga meningkatkan efisiensi dan efektivitas budidaya ikan. Penelitian ini berkontribusi pada pengembangan teknologi budidaya ikan yang lebih cerdas dan berkelanjutan, serta memberikan solusi praktis bagi petani ikan dalam mengelola kolam budidaya mereka
Klasifikasi Serangan Jaringan menggunakan Teknik Imputasi Berbasis Jaringan Syaraf Tiruan Safrizal Ardana Ardiyansa; Eric Julianto; Natasha Clarissa Maharani; Haidar Ahmad Fajri
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4349

Abstract

Rapid technological developments have changed access to information significantly, especially in telecommunications. This growth creates new threats, such as network attacks, so detection becomes critical for network security. Leveraging machine learning algorithms to detect threats is promising, with effectiveness largely dependent on selecting relevant features optimized by the bat algorithm. Data imputation is critical in preparing data sets, and neural network-based imputation techniques demonstrate outstanding performance, achieving accuracy rates of 99.4% on validation data and 99.3% on test data. This method consistently maintains precision, recall, and scores around 98%. Models using this method also approach perfection in classifying normal and neptune labels. This imputation method can also be applied to other model architectures using autoML. Alternative models such as Light GBM, XGBoost, Random Forest, Extra Trees, and Weighted Ensemble L2 also exhibit exceptional accuracy, exceeding 99.8%.
Implementasi metode SDLC pada aplikasi media interaktif “EcoWatt” berbasis WebGL Adiguna, Yogatama; Purwanto, Agus; Laksmita, Nadea Cipta
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4352

Abstract

Electrical energy is derived from the movement of electric charges due to a potential difference. Beyond housing, clothing, and food, electricity is a fundamental necessity, providing not only illumination but also powering various daily activities. Indonesia is rich in both fossil and renewable energy sources. However, the focus has predominantly been on fossil fuels, despite the fact that the electricity sector contributes 31% to global greenhouse gas emissions. Renewable energy, such as biomass, wind, water, and solar, offers sustainable alternatives. To foster early understanding and innovation in alternative energy, the author has developed "Ecowatt," a web-based educational application created using Unity and WebGL. This application aims to introduce children to the concept of alternative energy, inspiring them to develop eco-friendly energy solutions in the future. The author distributes the EcoWatt application through the website ecowatt.fun to achieve more efficient distribution, thereby fulfilling the purpose of this application's research.
Akurasi Metode Mesin Pembelajaran dalam Analisis Variabel Penting Faktor Risiko Sindrom Down Palit, Oscar Oleta; Dhenanta, Rafi Prayoga; Susanto, Agnes Indarwati; Syawly, Adzky Matla; Ivansyah, Atthar Luqman; Santika, Aditya Purwa; Arifyanto, Mochamad Ikbal; Muttaqien, Fahdzi
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4354

Abstract

This study aims to identify risk factors for Down syndrome using machine learning methods. Data were obtained from an epidemiological case-control study conducted at Special Needs Schools in the cities and regencies of Tangerang. Methods used include Random Forest, K-Nearest Neighbors, Support Vector Machine (SVM), Naive Bayes, K-Means, Artificial Neural Network (ANN), and Multi-Layer Perceptron (MLP). The results indicate that maternal age, paternal age, and the time interval of parents' work before the child's birth are the most influential factors in the incidence of Down syndrome. The SVM method achieved the highest accuracy of 76% with data categorized into two groups and using important variables. In addition to SVM, Naive Bayes and Random Forest methods also demonstrated good performance for analyzing epidemiological data with case-control types.
Perancangan Dan Implementasi Aplikasi Monitoring Perkembangan Studi Mahasiswa Alfis Salam; Taufik Nur Adi; Dita Pramesti
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4360

Abstract

Universitas Telkom merupakan salah satu perguruan tinggi swasta terkemuka di Indonesia yang berlokasi di Bandung dan memiliki cabang di Jakarta dan Surabaya. Salah satu program studinya yaitu S1 Sistem Informasi telah terakreditasi unggul oleh BAN-PT. Program studi ini mengukur kinerjanya menggunakan empat indikator yaitu jumlah lulusan tepat waktu, tingkat kelulusan mahasiswa, jumlah mahasiswa yang melampaui masa studi normal, dan jumlah mahasiswa kritis. Saat ini, pemantauan indikator kinerja utama masih dilakukan secara manual yang rawan terjadi kesalahan dan tidak efisien. Penelitian ini bertujuan untuk merancang dan mengimplementasikan aplikasi monitoring untuk memudahkan pemantauan indikator kinerja utama. Aplikasi ini dikembangkan menggunakan framework PHP dan Laravel, dan diuji dengan Black Box Testing. Metodologi pengembangan yang digunakan adalah Iterative Incremental sebanyak dua iterasi. Hasil dari penelitian ini adalah sebuah aplikasi yang membantu program studi S1 ​​Sistem Informasi dalam melakukan monitoring kinerja berdasarkan empat indikator utama.
Perancangan dan Implementasi User Interface dan User Experience Aplikasi Monitoring Perkembangan Studi Mahasiswa Sabila, Alifia
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4367

Abstract

The Bachelor of Information Systems program at Telkom University faces challenges in monitoring four key performance indicators: on-time graduation rates, student withdrawals, students exceeding the normal study period, and critical students. These indicators are crucial for evaluating academic effectiveness and maintaining accreditation. Currently, monitoring is performed semi-manually, which is ineffective and error-prone. This study aims to design and implement a monitoring application using the Design Thinking method, involving empathize, define, ideate, prototype, and testing stages. The application was tested using Maze tools and the System Usability Scale (SUS). Results showed MAUS scores of 91 for students, 88 for guardian lecturers, and 88 for heads of study programs. SUS average scores were 85.8 for students, 84 for guardian lecturers, and 65 for heads of study programs. The application was well-received by students and lecturers but needs improvement for heads of study programs.
Implementasi Algoritma Deep Q-Network (DQN) pada Lampu Lalu Lintas Adaptif Berdasarkan Waktu Tunggu dan Arus Kendaraan Putra, Ridho Amanda; Syahbana, Yoanda Alim; Ananda
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4372

Abstract

Traffic congestion often occurs due to the alternating road closure system during repairs on one side of the road, forcing vehicles to take turns passing the unrepaired side. The use of temporary traffic lights with fixed timing is often ineffective because it does not account for the imbalance in traffic flow from both sides of the road. To address this issue, this study implements the Deep Q-Network (DQN) algorithm to optimize traffic light duration based on vehicle wait times and traffic flow. Testing was conducted using the SUMO simulator, focusing on the parameters of epoch, exploration rate, and discount factor that affect the performance of the DQN agent. The results show that DQN achieves optimal performance when configured with an exploration rate of 1 and a discount factor of 0.9, after training for 50 epochs and testing for 10 epochs. In this configuration, DQN proves to be more adaptive in managing traffic lights compared to conventional methods that use fixed timing for green and red lights. Although the fairness value of DQN is lower, it successfully reduces congestion and improves overall traffic efficiency.
Implementation and Performance Analysis of Non-Blockchain-based and Blockchain-based Business Licensing Systems Using Hyperledger Fabric Al Muzaffar, Moza Sajidah Putri; Farah Afianti; Edouardo Bintang Rokatenda
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4378

Abstract

The inefficiency of traditional administrative processes highlights the need for innovative digital solutions. This study aims to evaluate and compare the performance of blockchain-based and non-blockchain-based business licensing systems to determine which approach offers better efficiency and security. The blockchain system was developed using Hyperledger Fabric with IPFS for data storage, while the non-blockchain system utilized Node.js with the Express.JS framework and MinIO for storage. Testing involved document upload and retrieval operations based on User ID and Document ID. Results indicate that while the blockchain system offers enhanced data integrity and security, it suffers from significantly slower performance, especially in document upload operations. The non-blockchain system demonstrated faster and more consistent response times, suggesting that in contexts where speed is crucial, a non-blockchain approach may be more suitable, despite the security trade-offs.
BEoF: An Approach to Protecting Encrypted Messages Within Digital Images Anto; Muhammad Amrizal Arripai; Muhammad Fadlan
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4379

Abstract

This research develops and implements a combined technique of steganography and cryptography to enhance the security of messages within digital media. This research introduces BeoF, a novel technique combining End of File (EOF) steganography with Beaufort Cipher cryptography to secure text messages within digital images. The study demonstrates that EOF effectively hides text messages without significantly degrading image quality. Beaufort Cipher adds a security layer by encrypting messages before embedding, enhancing data confidentiality. The application of BeoF was validated through case studies, proving its efficacy in practical scenarios for both message embedding and extraction. Despite positive results, further optimization is suggested, including comparative studies with other steganographic and cryptographic methods to assess their relative advantages and limitations. This research affirms that BeoF is a robust and efficient solution for protecting sensitive information in the digital era.
From Generative AI to Objective-Driven Systems: A Paradigm Shift in Artificial Intelligence Omar, Marwan
The Indonesian Journal of Computer Science Vol. 14 No. 5 (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.v13i5.4381

Abstract

The rapid advancement of Artificial Intelligence (AI), particularly in the domain of generative models, has led to impressive achievements in content creation and natural language processing. However, these models are inherently limited by their reliance on pattern recognition and lack of true understanding. In contrast, Objective-Driven AI offers a promising alternative by focusing on goal-oriented behavior, causal reasoning, and the development of world models. This paper explores the limitations of generative AI, highlighting its inability to grasp context, causality, and ethical considerations. It then presents the concept of Objective-Driven AI, emphasizing its potential to operate effectively in complex, real-world environments where understanding and reasoning are critical. The paper concludes with a discussion of future research directions, including advanced world modeling techniques, ethical AI, and robustness against adversarial attacks, which are essential for the further development of Objective-Driven AI systems. Keywords Objective-Driven AI, Generative AI, Causal Reasoning, World Modeling, Ethical AI, Artificial Intelligence, Adversarial Attacks, Machine Learning, Autonomous Systems

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