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INDONESIA
Instal : Jurnal Komputer
Published by Cattleya Darmaya Fortuna
ISSN : 20855702     EISSN : 2808683X     DOI : https://doi.org/10.54209/jurnalkomputer.v12i02.22
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Focus And Scope Instal : Jurnal Komputer is a peer-reviewed scientific journal published by CV. Cattleya Darmaya Fortuna which has been published since 2009. The aim of this journal is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of computer science. Instal : Jurnal Komputer is consistently published two times a year in June and December. This journal covers original article in computer science that has not been published. The article can be research papers, research findings, review articles, analysis and recent applications in computer science. The scope of Instal : Jurnal Komputer covers, but is not limited to the following areas: 1. Data Mining 2. Image Processing 3. Artificial Neural Networks 4. software engineering.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 279 Documents
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IMPLEMENTATION OF LBPH ALGORITHM IN AUTOMATIC DOOR OPENING SYSTEM WITH FACIAL RECOGNITION Stepanus.S, Ronaldo; Satria, Beni; Dani, Ahmad
Bahasa Indonesia Vol 16 No 06 (2025): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v16i06.349

Abstract

Automatic door opening system with facial recognition is an application that is widely used to improve security and comfort in various fields, such as offices, homes, and other limited areas. This study implements the Local Binary Pattern Histogram (LBPH) algorithm in an ESP32-based automatic door opening system integrated with an OV2640 camera. LBPH was chosen because of its superiority in recognizing faces even with varying lighting conditions and imperfect image quality. This system works by capturing facial images through an OV2640 camera, then processing the image using the LBPH algorithm to extract facial features. The results of facial recognition are then sent to the ESP32 which controls the automatic door locking system. In this implementation, the ESP32 is used as a microcontroller to connect the camera, data processing, and control the door actuator. Tests were conducted to measure the accuracy of facial recognition and system performance in opening the door. The test results show that the system can recognize faces with a high level of accuracy and open the door automatically in a short time, thereby increasing the efficiency and security of the system.
Development of IoT Based Smart Grid System for Monitoring And Management of Electrical Energy Distribution Sianturi, Barata Mandala; Satria, Beni; Tarigan, Amani Darma
Bahasa Indonesia Vol 16 No 06 (2025): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v16i06.350

Abstract

This study aims to develop a smart grid system based on the Internet of Things (IoT) to improve efficiency and sustainability in monitoring and managing electrical energy distribution. Smart grid is a modern electrical network that utilizes communication and information technology to integrate various components in the energy distribution system. IoT technology allows real-time data collection from sensors spread across various points, thus providing accurate information regarding energy consumption, network conditions, and potential disruptions. The research methodology includes designing the IoT system architecture, developing software for data analysis, and testing system performance through simulation and implementation on a limited scale. The data obtained is analyzed using an artificial intelligence (AI)-based predictive algorithm to detect anomalies and provide recommendations for energy distribution management. The results of the study show that the developed system is able to increase energy distribution efficiency by up to 25% and reduce the duration of disruptions by up to 40%. In addition, this system allows for faster and data-based decision making in energy management. In conclusion, the development of an IoT-based smart grid system can be an innovative solution to face the challenges of electricity distribution in the modern era, while supporting the implementation of sustainable energy.
EFFICIENCY AND RELIABILITY ANALYSIS OF SOLAR POWER GENERATING SYSTEM FOR 450 VA APPLICATION IN SIRUAR VILLAGE, TOBA REGENCY Nugraha, Satria; Wibowo, Pristisal; Siagian, Parlin
Bahasa Indonesia Vol 16 No 06 (2025): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v16i06.352

Abstract

This study aims to analyze the efficiency and reliability of a solar power generation system (PLTS) for household applications with a power of 450 VA in Siruar Village, Toba Regency. PLTS is a potential solution to meet electricity needs in remote areas that are difficult to reach by conventional electricity networks. This study includes evaluation of solar panel performance, energy conversion efficiency, and analysis of system reliability in providing a stable electricity supply. The research method involves collecting technical data from the installed PLTS system, analyzing energy efficiency using input and output power parameters, and measuring reliability indices such as duration of interruption and frequency of blackouts. The results of the study show that the PLTS system is able to produce sufficient electrical energy for basic household needs, with energy conversion efficiency reaching 89.74% to 97.22% and a level of reliability that meets operational standards. This study contributes to supporting the development of renewable energy in rural areas and becomes a reference in planning and optimizing similar PLTS systems in the future.
A COMPARATIVE ANALYSIS OF PREPAID AND POSTPAID KWH METERS IN IMPROVING ACCURACY OF ELECTRICITY USAGE MEASUREMENTS TO CUSTOMER SERVICE UNIT (ULP) CUSTOMERS PT PLN IN PEUREULAK, EAST ACEH Sarita, Rahma; Tarigan, Adisastra Pengalaman; Anisah, Siti
Bahasa Indonesia Vol 16 No 06 (2025): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v16i06.353

Abstract

This study aims to analyze the comparison of prepaid and postpaid KWH meters in improving the accuracy of electricity usage measurements for customers of PT PLN's Customer Service Unit (ULP) in Peureulak, East Aceh. The prepaid system allows customers to control electricity usage based on previously purchased power, while the postpaid system records electricity consumption that will be billed after a certain period. This study was conducted through collecting primary and secondary data from customers and comparative analysis of the level of measurement accuracy, efficiency, and customer satisfaction. The results of the study indicate that the prepaid KWH meter system has a better level of accuracy compared to the postpaid system, especially in reducing the risk of incorrect manual recording and increasing transparency of electricity usage. These findings are expected to be a consideration for PT PLN in improving services to customers and encouraging the implementation of the prepaid system more widely.
Architectural Design of an Executive Information System (EIS) to Support Strategic Decision-Making in the Government Sector Setiadi, Farisya; Rubhasy, Albaar; Muhaemin
Bahasa Indonesia Vol 17 No 09 (2025): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v17i09.423

Abstract

Indonesia is a country with great potential to play a significant role in globalization. Indonesia's potential lies in its highly strategic territory, cultural and biological diversity, and abundant human resources. However, this enormous potential requires sound management to achieve prosperity for the Indonesian people. The government is the most important component in the state administration that runs the wheels of government. However, to date, the government is considered slow and ineffective in making strategic decisions. To make strategic decisions, tools are needed to assist leaders in carrying out their duties. This paper presents an EIS architectural design containing techniques and technologies divided into layers: collection, processing, analysis, presentation, and management. These layers are mutually supportive and integrated, serving as a guideline for the development of an Executive Information System (EIS) that functions to support strategic decision-making within the government sector.
Quantum-Safe Evaluation of TLS 1.3 Hybrid with ML-DSA Jaya, Dery Yuswanto; Jakaria
Bahasa Indonesia Vol 17 No 09 (2025): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v17i09.428

Abstract

Quantum computing poses a significant threat to classical cryptographic schemes widely used in modern networks, particularly RSA and ECC, which are vulnerable to Shor’s algorithm. To address this challenge, this study conducts a post-quantum security evaluation of TLS 1.3 by implementing hybrid X25519+Kyber key exchange and ML-DSA digital signatures. The objective is to assess the performance, overhead, and effectiveness of hybrid TLS in ensuring long-term data confidentiality within enterprise environments. The research method involves building a server–client testbed using OpenSSL with the oqs-provider, applying network load simulations under various latencies, and measuring key metrics including handshake latency, CPU utilization, certificate size, and client compatibility. The results indicate that hybrid TLS 1.3 with X25519+Kyber introduces only moderate handshake latency, while ML-DSA increases certificate size but remains manageable for deployment in modern enterprise systems. The conclusion of this study is that combining X25519+Kyber with ML-DSA offers an effective transition path towards quantum-safe networks without significantly sacrificing system performance..  
Analysis and Implementation of an EMC-Based Radio Frequency Emission Measurement System Ariyanto, Endro; Yudo, Yogi Anggun Saloko; Sailellah, Hassan Rizky Putra
Bahasa Indonesia Vol 17 No 10 (2025): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v17i10.433

Abstract

The rapid advancement of electronic technology brings many benefits, but it also introduces risks of interference in the form of electromagnetic wave emissions that may affect the performance of nearby electronic devices. To ensure that devices maintain proper electromagnetic compatibility (EMC), precise and standardized methods for measuring radio-frequency emissions are required. This study focuses on developing radio-frequency emission measurement techniques and creating software capable of controlling a spectrum analyzer, displaying measurement results, storing data, and performing further analysis. The methods used follow the RTCA/DO-160C standard, covering both conducted and radiated emission measurements through voltage conversion and the application of device correction factors. Testing was carried out using a functional (black-box) approach on each main feature of the SpectrumAnalyzer object. The results demonstrate that all software functions operate correctly, from device initialization, data retrieval and storage, to spectrum normalization. Overall, the development and testing results confirm that the RFESW software is capable of performing radio-frequency emission measurements effectively and complies with the requirements of the RTCA/DO-160C standard.
Creating Running Text as a Digital Information Board Based on an Android Application Using the HD-WF2 Controller Subekti, Eko Prasetyo; Eno, Muhammad; Iswahyudi
Bahasa Indonesia Vol 17 No 10 (2025): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v17i10.435

Abstract

Running text is a form of digital media that can display moving text and animations. Until now, many users still update and change text data manually using USB connections, flash drives, and computer keyboards. This means they must interact directly with the running text. This research aims to create a running text that utilizes wireless technology and Android phones using applications connected via a Wi-Fi network. By utilizing an Android application and a Wi-Fi-based HD-WF2 microcontroller as an operational control on the running text, the test results show that the created moving text can be an alternative solution to facilitate the delivery of information and can function at a distance of 20 meters without obstacles and 10 meters with obstacles.
Development of Multimodal Generative AI Models for Adaptive Education Personalization in the Era of Quantum Machine Learning Amin, Muhammad; Rizal, Chairul; Muslem R, Imam
Bahasa Indonesia Vol 17 No 09 (2025): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v17i09.437

Abstract

The rapid advancement of Artificial Intelligence (AI) has transformed the educational landscape, making it increasingly crucial to develop adaptive and personalized learning systems. This study explores the development of a multimodal Generative AI model designed for adaptive educational personalization, enhanced by Quantum Machine Learning (QML). The model integrates various data types, including text, images, and voice, to create customized learning content tailored to individual student needs and learning styles. By combining the power of generative AI with quantum-inspired optimization techniques, this model aims to offer a more responsive and efficient learning experience. The research employs a mixed-methods approach, combining both quantitative and qualitative data to evaluate the effectiveness of the model in improving learning outcomes. The findings suggest that this hybrid approach holds significant potential for revolutionizing adaptive education, especially in resource-limited environments, and aligns with current educational trends such as the Merdeka Curriculum in Indonesia. The study concludes by highlighting the impact of quantum machine learning in enhancing personalization and overcoming the challenges posed by traditional educational models.
Classification of Student Activity Status Using Machine Learning Algorithms at Royal University Iqbal, Muhammad; Hermawan, Rudi
Bahasa Indonesia Vol 17 No 09 (2025): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v17i09.439

Abstract

Inactivity is a significant challenge that impacts academic performance, retention rates, and the operational effectiveness of higher education institutions. Royal University faces an urgent need to identify students at risk of becoming inactive early, so that academic interventions can be carried out appropriately and effectively. This study aims to develop a classification model for student inactivity status (Active or Passive) using a machine learning approach, by testing three main algorithms: Decision Tree (DT), Support Vector Machine (SVM), and Random Forest (RF). The dataset used consists of 642 student entries, including academic information such as Grade Point Average (GPA), total credits taken, attendance percentage, number of courses per semester, and semester level. The methodology steps include data cleaning and transformation, splitting the dataset into 80% training data and 20% testing data using a random sampling method ( train_test_split with random_state = 42), model training, and performance evaluation using accuracy, precision, recall, and F1-score metrics. The experimental results show that DT and SVM achieve the highest accuracy of 98.44%, with maximum precision in predicting active students, while RF excels in recall (0.96), making it more effective in detecting active students at risk of being missed. Feature importance analysis reveals that GPA and attendance are the most determining factors in predicting student active status, while the number of courses, credits taken, and semester level have a lower additional influence. The primary contribution of this research is the provision of an accurate and practically applicable classification model, enabling universities to conduct automated student monitoring, proactive academic interventions, and data-driven decision-making. Implementing this model in academic information systems can improve the effectiveness of advising programs, reduce the risk of student inactivity , and support efforts to improve retention and graduate quality. This research also emphasizes the importance of contextual features in improving prediction accuracy and provides insights that can be leveraged for the development of data-driven academic strategies.

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