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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 364 Documents
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Design of a Web-Based E-Correspondence System for the Secretariat Division of BPBD Binjai City Dwi Azzahra Siregar; Rio Septian Hardinata; Barany Fachri
Bahasa Indonesia Vol 18 No 06 (2026): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v18i06.531

Abstract

The development of information technology has encouraged various government agencies to implement digital transformation in their administrative processes, including letter management. The Secretariat Department of the Regional Disaster Management Agency (BPBD) of Binjai City currently manages incoming and outgoing letters manually using agenda books and physical document storage. This condition has led to several problems, such as difficulties in retrieving archives, the risk of document loss, and delays in letter distribution. This study aims to design a Web-Based E-Correspondence System that can support the processes of recording, storing, searching, and managing letters within the Secretariat Department of BPBD Binjai City. To develop the proposed system, this research adopts the Design Thinking approach, which consists of five stages: empathize, define, ideate, prototype, and test. The system is designed using the Laravel Framework based on PHP with a MySQL database. The result of this research is a Web-Based E-Correspondence System design that supports letters administration processes to become more effective, structured, and user-friendly for employees.
Analysis and Classification of Emergency Conditions Endangering Humans Based on Operational Data Using Random Forest and Support Vector Machine Methods (Case Study: UPT Basarnas Medan) Dwika Ardya; Muhammad Iqbal; Muhammad Irfan Syarif
Bahasa Indonesia Vol 18 No 06 (2026): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v18i06.532

Abstract

Operation Search and Rescue (SAR) in phase DETRESFA demands fast and accurate decision-making because it involves real, life-threatening situations. The Medan Basarnas UPT faces challenges in classifying four main categories of incidents: ship accidents (Y1), accidents requiring special handling (Y2), natural disasters (Y3), and conditions endangering humans (Y4), which have so far been done manually and subjectively. This study aims to build a decision support system based on data collection. machine learning to improve the efficiency of resource deployment through objective classification of emergency conditions. Performance comparisons were conducted between the algorithms Random ForestAnd Support Vector Machine(SVM) based on operational features such asresponse time, number of victims, number of personnel, and distance of the incident. The test results show thatRandom Forestprovides superior performance compared to SVM across all evaluation metrics, with accuracy 86.4%, AUC value 93.9%, F1-score 85.5%, And Matthews Correlation Coefficient (MCC) 0.759. AnalysisConfusion Matrixconfirm that Random Foresthas better stability in recognizing operational feature patterns for most target categories, including its more consistent ability in handling less dominant classes than SVM. Although the Y2 category is still a challenge for both models, Random Forestproven to be much more robust with an accuracy of 49.6% compared to SVM which only achieved 16.5%. This research proves that Random Forestis a more reliable and consistent model to support SAR practitioners in improving the accuracy of field responses, efficiency of resource deployment, and minimizing the risk of loss of life.
Design of a Cloud-Based Monitoring System for Household Energy Consumption Analysis Using Datasets on CV Atta Network Galih Wisnu Nugroho; Hafni; Muhammad Zen
Bahasa Indonesia Vol 18 No 06 (2026): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v18i06.533

Abstract

Advances in information technology have driven a digital transformation in household energy management through cloud-based monitoring systems that enable real-time, centralized consumption monitoring (Rahman & Sari, 2023). However, implementation remains challenging because most households rely solely on monthly bills without detailed knowledge of consumption patterns, potentially leading to electricity waste. CV Atta Network possesses a household energy consumption dataset that has not been optimized into an integrated system. This research aims to design a cloud-based monitoring system to analyze household energy consumption using this dataset. This system is expected to help users understand energy consumption patterns and support efficient electricity use.
Analysis of Artificial Neural Network and Support Vector Machine Algorithms in Predicting General or Vocational School Choices for Panca Budi Middle School Students in Medan Hindra Syahputra; Muhammad Iqbal; Khairul
Bahasa Indonesia Vol 18 No 06 (2026): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v18i06.534

Abstract

Determining the educational trajectory following junior high school graduation represents a pivotal decision shaped by students' academic competence, personal interests, and inherent personality inclinations. In practice, this selection process is frequently carried out in a subjective manner, which risks producing a disconnect between students' genuine potential and their eventual educational placement. The present research seeks to examine and compare the predictive performance of the Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms in forecasting students' preference for either senior high school (SMA) or vocational high school (SMK) among learners at SMP Panca Budi Medan. A total of 220 student records were employed as the dataset, incorporating academic performance data alongside RIASEC personality scores as the predictor variables. All data processing was executed within the WEKA application environment utilizing 10-fold cross validation as the evaluation scheme. The ANN model was constructed through the Multilayer Perceptron approach, while SVM relied on the Sequential Minimal Optimization (SMO) technique. Experimental findings revealed that both classifiers attained an identical accuracy rate of 85.45%; however, the ANN model demonstrated a superior ROC Area value of 0.925 relative to the SVM's 0.849, signifying that ANN possesses stronger discriminative capability in distinguishing SMA from SMK selections. The study confirms that integrating academic metrics with RIASEC scores provides a viable foundation for constructing a machine learning-driven school-choice prediction system that is both more objective and better attuned to individual student profiles.
Transaction Fraud Detection in Savings and Loan Cooperatives Using Xgboost with Shap Explanations (Shapley Additive Explanations) Indra Marto Silaban; Muhammad Syahputra Novelan; Muhammad Irfan Sarif
Bahasa Indonesia Vol 18 No 06 (2026): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v18i06.535

Abstract

Savings and loan cooperatives play a crucial role in supporting the community's economy. With the motto "From Members, By Members, and For Members," cooperatives focus on developing member funds and providing returns in the form of dividends. However, cooperative operations are not free from the risk of fraud, especially by internal parties (employees or administrators). This study aims to develop a machine learning-based transaction fraud detection model using the Extreme Gradient Boosting (XGBoost) algorithm and to increase model transparency through an Explainable Artificial Intelligence (XAI) approach with the SHAP (SHapley Additive exPlanations) method. This study uses user activity log data and financial transactions that can be described as operator/employee behavior in the savings and loan cooperative system. The model will be trained to classify whether transactions are fraudulent or non-fraudulent. The results will then be evaluated using accuracy, precision, recall, F1-score, and AUC metrics. The results show that the XGBoost model has good performance with an accuracy value of 0.81 and an AUC of 0.912. SHAP analysis shows that features such as transaction amount, transaction frequency, transaction time, and changes in user and member data are key factors in fraud detection. This study demonstrates that the integration of XGBoost and SHAP can improve fraud detection accuracy and provide transparency in model decision-making. Therefore, the results of this study can support a more effective supervisory system for savings and loan cooperative financial institutions.
Optimization of Indosat's Fiber to the Home (FTTH) Network for Customer Satisfaction Using the Random Method Forest and Naïve Bayes Jelly Rolleys Sitompul; Muhammad Iqbal; Muhammad Irfan Sarif
Bahasa Indonesia Vol 18 No 06 (2026): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v18i06.536

Abstract

Currently, customer satisfaction is a crucial indicator in evaluating the quality of Fiber to the Home (FTTH) services. This study aims to analyze customer satisfaction with Indosat HiFi services and compare the performance of the Random Forest and Gaussian Naive Bayes algorithms in predicting customer satisfaction levels. The research dataset consists of Quality of Service (QoS) parameters and customer operational data, including latency, throughput, packet loss, downtime, response time, and complaint count. The data was processed using a Machine Learning approach through preprocessing, model training, and performance evaluation stages. The research results showed that Random Forest produced the best performance with 98.8% accuracy, 100% recall, 99.4% F1-score, and 95.9% CV Mean. Meanwhile, Gaussian Naïve Bayes obtained 97.6% accuracy, 98.8% F1-score and 95.2% CV Mean. The research findings show that service quality and user experience factors influence the level of customer satisfaction. The resulting model has great potential to support data-based decision making to improve the quality of FTTH services. The research data was processed and then tested with a ratio of 80:20. Model evaluation was carried out using accuracy, recall, F1-score and cross validation.
Web-Based Design of Drug Supply Stock at the Selotong Village Sub-district Health Center, Secanggang District, Langkat Regency Lia Riyanti; Muhammad Donni Lesmana Siahaan; Darmeli Nasution
Bahasa Indonesia Vol 18 No 06 (2026): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v18i06.537

Abstract

The Sub-District Health Center (Pustu) plays a crucial role in supporting public health services, particularly in the provision of medicines. However, drug stock management at the Sub-District Health Center in Selotong Village, Secanggang District, Langkat Regency, is still performed manually, resulting in various problems such as inaccurate stock data, delayed recording, and difficulties in preparing reports. This study aims to design and build a web-based drug stock information system to improve the effectiveness and efficiency of drug data management. The system development method used is the Waterfall Model, which consists of the stages of needs analysis, system design, implementation, testing, and maintenance. The system was developed using the PHP programming language and MySQL database. The system's main features include drug data management, recording incoming and outgoing drugs, real-time stock monitoring, and automatic report generation. The results of the study indicate that the system is able to minimize recording errors, increase data accuracy, and facilitate officers in managing drug stocks. Thus, this system is expected to improve the quality of health services at the Sub-District Health Center in Selotong Village.
Implementation of the ESP-NOW Protocol in a Multi-Sensor-Based Control System Using ESP8266 and ESP32 Marsinta Uli Sinurat; Ahmad Dani; M. Rizky Syahputra
Bahasa Indonesia Vol 18 No 06 (2026): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v18i06.538

Abstract

The rapid development of the Internet of Things (IoT) has increased the demand for wireless communication systems that are fast, efficient, and independent of internet network infrastructure. This study aims to implement the ESP-NOW protocol in a multi-sensor monitoring system using ESP32 as the data transmitter and ESP8266 as the data receiver. The system was designed to acquire temperature and humidity data using a DHT11 sensor and distance data using an HC-SR04 sensor, which were then transmitted in real time through ESP-NOW communication. On the receiver side, the data were displayed on a 16×2 LCD and Serial Monitor, while packet loss was calculated using the sequence number method. An experimental approach was employed to evaluate communication performance based on temperature, humidity, distance, received packets, lost packets, and packet loss percentage. The results showed that the DHT11 sensor produced an average temperature of 29.82°C and an average humidity of 75.1%, while the HC-SR04 sensor achieved a measurement error of less than 2%. Communication testing was conducted over five cycles with 100 samples per cycle. The first three cycles recorded 0% packet loss, whereas the fourth and fifth cycles experienced packet losses of 32.34% and 62.12%, respectively. The average packet loss obtained was 18.89%. The findings indicate that ESP-NOW is capable of supporting real-time multi-sensor data communication without requiring an access point or internet connection, although communication quality is influenced by distance, physical obstacles, and signal interference. The developed system demonstrates potential for deployment in various IoT-based monitoring and automation applications.
Local Network Security Analysis Using Intrusion Detection System (IDS) on Public Hotspot Network at Moonlight Café Mhd Rizky Ananda Pratama Nasution; Leni Marlina; Hanna Willa Dhany
Bahasa Indonesia Vol 18 No 06 (2026): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v18i06.539

Abstract

The development of computer network technology and the increasing use of public hotspot services in various public places, such as cafes, have made network security threats increasingly complex. Public hotspot networks have a high level of vulnerability to various types of cyberattacks, such as port scanning, sniffing, spoofing, brute force, and Distributed Denial of Service (DDoS). An Intrusion Detection System (IDS) is a network security solution used to detect suspicious activities and attacks on computer networks in real-time. This study aims to analyze the implementation of an Intrusion Detection System (IDS) on public hotspot networks in Moonlight Cafe to improve local network security. The research method used is an experimental method by implementing an IDS using Snort on a public hotspot network. Testing was conducted using several types of attack simulations, such as port scanning, brute force login, ping flood, and sniffing attacks. The testing parameters included the attack detection rate, response time, packet detection accuracy, false positive rate, and server resource utilization. The results showed that the IDS was able to detect various types of network attacks with an accuracy rate of 96.8%. The IDS system was also able to provide real-time notifications for suspicious activities on the public hotspot network. Based on the research results, the implementation of an IDS is proven to be effective in improving local network security within a public hotspot environment in cafes.
Design of a Web-Based Point of Sale (POS) System with Stock Management and Sales Reports at Zeals Sport Store Muhammad Andre Wahyudi; Ruly Dwi Arista; Juliandri
Bahasa Indonesia Vol 18 No 06 (2026): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v18i06.540

Abstract

The rapid development of information technology has transformed the way retail businesses manage sales transactions and inventory. However, many retail stores still rely on manual methods, such as notebooks and spreadsheets, to record sales and stock data. These conventional practices often lead to recording errors, inaccurate inventory information, delayed report generation, and inefficiencies in daily operations. As a result, business owners face difficulties in monitoring stock availability and making informed managerial decisions. Similar issues have been identified in previous studies, which suggest that web-based Point of Sale (POS) systems can improve transaction management by providing automated and integrated data processing. A POS system not only facilitates the sales transaction process but also supports inventory control, reduces human errors, and generates accurate sales reports in a timely manner. Therefore, Zeals Sport requires a web-based POS system equipped with inventory management and sales reporting features. The implementation of this system is expected to enhance operational efficiency, improve data accuracy, accelerate the payment process, and provide reliable information to support business decision-making.  

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