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INDONESIA
Sistemasi: Jurnal Sistem Informasi
Published by Universitas Islam Indragiri
ISSN : 23028149     EISSN : 25409719     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Sistemasi adalah nama terbitan jurnal ilmiah dalam bidang ilmu sains komputer program studi Sistem Informasi Universitas Islam Indragiri, Tembilahan Riau. Jurnal Sistemasi Terbit 3x setahun yaitu bulan Januari, Mei dan September,Focus dan Scope Umum dari Sistemasi yaitu Bidang Sistem Informasi, Teknologi Informasi,Computer Science,Rekayasa Perangkat Lunak,Teknik Informatika
Arjuna Subject : -
Articles 1,011 Documents
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Analysis of Immunization Coverage Among Toddlers in Indonesia using the K-Means Algorithm based on 2025 People’s Welfare Data Makin, Maria Angelina Luisa; Yudhistira, Aditia
Sistemasi: Jurnal Sistem Informasi Vol 15, No 3 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i3.6203

Abstract

Disparities in toddler immunization coverage across different regions of Indonesia indicate the need for an analytical approach capable of capturing regional characteristics in greater depth. This study aims to cluster toddler immunization coverage using the K-Means algorithm based on the 2025 Indonesian People’s Welfare Data published by Statistics Indonesia. The variables analyzed include immunization history, types of immunization, place of immunization, and immunization providers. Data processing was conducted using Python through the Google Colab platform. The determination of the optimal number of clusters using the Elbow Method resulted in three clusters, with a Silhouette Score of 0.5086, indicating a moderately good clustering quality. The results show that the cluster labeled Low surprisingly exhibits the highest immunization coverage (95.68%), suggesting that the cluster labels do not represent coverage levels in a linear manner but instead reflect differences in operational characteristics and the distribution of immunization services across regions. Meanwhile, the Medium cluster shows the lowest coverage (63.82%), and the High cluster falls at an intermediate level (92.23%). Further analysis indicates that the type of immunization and immunization history are the most influential variables in cluster formation. With clustering quality categorized as moderately good, the K-Means method is considered capable of adequately identifying immunization coverage patterns for region-based policy analysis. These findings demonstrate that a clustering approach can reveal immunization coverage patterns that are not captured through conventional statistical analysis and can serve as a basis for more targeted and data-driven immunization policy formulation.
Implementation of Random Forest for Predicting Complaint Handling Priorities at the Minahasa Education Office Tumbo, Sinta; Tinambunan, Medi Hermanto; Santa, Kristofel
Sistemasi: Jurnal Sistem Informasi Vol 15, No 3 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i3.6060

Abstract

Public service delivery in the education sector requires government institutions to handle public complaints promptly and accurately. However, the Minahasa Regency Education Office still faces challenges in determining complaint handling priorities, which are often subjective and manually assigned. This condition may lead to delays in addressing urgent complaints. This study aims to implement the Random Forest algorithm to objectively predict complaint handling priorities based on data. The research methodology includes collecting a dataset of 500 public complaints with six attributes: complaint type, violation level, work unit, follow-up action, outcome, and priority. The process involves data preprocessing, splitting the dataset into training and testing sets, building the Random Forest model, and evaluating its performance. Data processing and modeling were conducted using Jupyter Notebook within the Anaconda environment. Model performance was evaluated using accuracy, confusion matrix, precision, recall, and F1-score metrics. The results show that the Random Forest algorithm achieved an accuracy of 100%, with precision, recall, and F1-score values of 1.00 across all priority classes. These findings indicate that the model demonstrates excellent and stable classification performance. Therefore, it can serve as a foundation for developing a decision support system to improve the effectiveness and quality of public service delivery at the Minahasa Regency Education Office.
Implementation of the K-Means Algorithm for Clustering Zoning of Natural Disaster-Prone Areas in Pati Regency Arifin, Arifin; Herlambang, Bambang Agus; Harjanto, Aris Tri Joko
Sistemasi: Jurnal Sistem Informasi Vol 15, No 3 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i3.5970

Abstract

Based on data from the Central Bureau of Statistics (BPS) of Pati Regency, during the 2018–2022 period the region frequently experienced natural disasters, particularly floods and landslides, across many areas.The high frequency of these disasters and the lack of proper mapping of affected areas present challenges that need to be addressed effectively. By utilizing technology and the K-Means clustering method, this study proposes an alternative solution to identify and map areas that are vulnerable to natural disasters. The results of the analysis indicate that Pati Regency can be divided into three clusters: Cluster 1 represents highly disaster-prone areas, accounting for 42.86% (9 regions); Cluster 2 represents disaster-prone areas, accounting for 19.04% (4 regions); and Cluster 3 represents areas with low disaster vulnerability, accounting for 38.1% (8 regions). The visualization results are presented as a classification map of regions based on their disaster vulnerability levels. This map can serve as a reference for local governments and relevant institutions in formulating more targeted and effective disaster mitigation policies.
Evaluation of a Furniture Product Testing Process and Results Reporting Application using the Extended Technology Acceptance Model (TAM) at XYZ Company Pasaribu, Faizal Asrul; Simangunsong, Jumadi; Arianty, Kiki Puspo
Sistemasi: Jurnal Sistem Informasi Vol 15, No 3 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i3.6198

Abstract

The furniture manufacturing industry demands efficient internal processes and reliable reporting quality; however, the adoption of digital reporting applications is often hindered by user acceptance factors. This study evaluates user acceptance of a Furniture Product Testing Process and Results Reporting Application at PT XYZ using the Extended Technology Acceptance Model (ETAM), which integrates constructs from the Technology Acceptance Model (TAM) and variables from the Information System Success Model (ISSM), including system quality, information quality, service quality, and user satisfaction. A survey of employees across operational units was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The measurement model met the criteria for validity and reliability (AVE = 0.598–0.875; composite reliability = 0.869–0.954). The coefficient of determination (R²) indicates a strong to very strong model across key variables (R² for intention to use = 0.883; attitude toward use = 0.738; perceived ease of use = 0.737; perceived usefulness = 0.788; actual use = 0.698). The main results reveal significant paths: system quality → perceived ease of use (β = 0.563; p < 0.007), perceived ease of use → attitude toward use (β = 0.735; p < 0.001), attitude toward use → behavioral intention (β = 0.940; p < 0.001), and behavioral intention → actual use (β = 0.828; p < 0.001). In contrast, information quality and service quality do not have a significant effect on perceived usefulness, perceived ease of use, or user satisfaction; additionally, perceived usefulness and user satisfaction do not significantly drive actual use. These findings highlight the central role of system performance and usability in shaping sustained adoption. They also suggest the need for enhanced training strategies and clearer communication of system benefits to strengthen perceived usefulness and to ensure that service support contributes more effectively to user satisfaction and system usage.
Analysis of User Experience in the WEVERSE Application using the ITIL V3 Service Design Domain : An ENGENE Perspective in Indonesia Saudale, Emmanuela Adtrisel; Tanaem, Penidas Fiodinggo
Sistemasi: Jurnal Sistem Informasi Vol 15, No 3 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i3.6172

Abstract

The rapid development of digital technology has changed the way artists and fans interact through community applications such as Weverse. This study aims to evaluate the user experience of Weverse from the perspective of ENGENE (ENHYPEN fans) in Indonesia using the ITIL V3 Domain Service Design approach, as well as to analyze the service quality of the application and provide recommendations for improvement. The research employed a quantitative approach through a survey using a questionnaire instrument developed based on the ITIL V3 Service Design Framework, which consists of six subdomains : Service Catalogue Management, Service Level Management, Capacity Management, Availability Management, Information Security Management,and Supplier Management. The sample consisted of 100 respondents selected using the Slovin formula with a 10% margin of error from an estimated population of 29,937 ENGENE members in Indonesia. Data were analyzed using maturity level analysis and gap analysis. The results show that all subdomains are at Maturity Level 4 (Managed and Measurable), with an average current maturity score of 4.07 and Expected Maturity score of 4.50, resulting in an average gap of 0.43. Among the subdomains, Service Catalogue Management demonstrates the best performance with a current maturity score of 4.21 and the smallest gap of 0.29, while Service Level Management shows the lowest score of 3.89 with the largest gap of 0.61, making it the primary priority for improvement. The findings suggest that the Weverse application has reached the managed stage, where IT service design processes can be systematically measured and monitored. However, continuous improvements are still required to achieve the optimal target of Maturity Level 5 (Optimized).
Hyperparameter Optimization of Ensemble Learning for Heart Disease Prediction using Patient Data Wicaksono, Nikko Listio; Kusrini, Kusrini
Sistemasi: Jurnal Sistem Informasi Vol 15, No 3 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i3.6006

Abstract

This study evaluates the impact of hyperparameter optimization on the performance of four machine learning algorithms—Extra Trees, XGBoost, Random Forest, and AdaBoost—in heart disease prediction. The results show that hyperparameter tuning significantly improves model performance for three out of the four algorithms, with varying effects across models. Extra Trees demonstrates the most consistent improvement, achieving the highest Area Under the Curve (AUC) of 0.9107 and a recall of 80.93%, which is particularly crucial in medical contexts for accurately identifying disease cases. XGBoost exhibits the largest increase in accuracy, rising from 78.11% to 81.49%, while Random Forest shows improvements in both recall and F1-score. In contrast, AdaBoost experiences a slight decline in performance, suggesting that the model was already near optimal prior to tuning. Overall, Extra Trees with hyperparameter optimization emerges as the best-performing algorithm for heart disease prediction, offering high reliability in identifying at-risk patients.
Literature Review: Comparison of Machine Learning Algorithms for Sentiment Analysis of Free Nutritious Meals Mukhlisin, Mukhlisin; Berlilana, Berlilana; Saputro, Rujiyanto Eko
Sistemasi: Jurnal Sistem Informasi Vol 15, No 3 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i3.6201

Abstract

The Free Nutritious Meal (FNM) program has triggered massive public responses on social media, driving numerous machine learning–based sentiment analysis studies. However, there has been no comprehensive review comparing the effectiveness of these methods. This study adopts a Systematic Literature Review (SLR) approach on 18 studies (2024–2026) to evaluate the performance of computational algorithms and map trends in public sentiment. The main contribution of this research is to provide an empirical guide for selecting Indonesian-language text classification models, while also offering insights into shifts in public perception. Key findings indicate that Support Vector Machine (SVM) is the most frequently used method, whereas the highest accuracy (97%) was achieved by a combination of Logistic Regression, SVM, and Random Forest on large datasets. Temporally, sentiment trends shifted from budget skepticism (2024) to positive acceptance during program implementation (2025–2026). The study’s implications support policymakers in evaluating program effectiveness in real time. The scope and limitations of this research focus on literature within a specific timeframe, with performance evaluation emphasizing quantitative accuracy metrics.
Predicting Impulsive Buying in Tokopedia Flash Sales: A UTAUT2 Approach Riansyah, M. Bintang Naufal; Afrina, Mira; Tania, Ken Ditha; Kurnia, Rizka Dhini
Sistemasi: Jurnal Sistem Informasi Vol 15, No 3 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i3.6137

Abstract

Flash sale events have become a dominant marketing strategy to trigger rapid purchasing decisions. However, despite the massive growth of e-commerce in Indonesia, it remains unclear whether consumer participation in these events is primarily driven by the thrill of the "hunt" (hedonic) or the rational calculation of discounts (price value), particularly in developing digital markets like Palembang City. This study investigates the determinants of impulsive buying behavior during Flash Sale events on the Tokopedia platform. Drawing upon a modified Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, this study investigates how Hedonic Motivation and Price Value affect Behavioral Intention, and in turn, its effect on Impulsive Buying. A quantitative methodology was applied, leveraging survey responses from 144 participants in Palembang City who had engaged in Tokopedia Flash Sales. Analysis was conducted through Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4 software. Findings reveal that both Hedonic Motivation and Price Value positively and significantly impact Behavioral Intention, with Price Value identified as the most influential predictor. Furthermore, a robust positive relationship was found between Behavioral Intention and Impulsive Buying, confirming that the intention to participate in Flash Sales significantly drives unplanned purchasing behavior. These findings suggest that while hedonic enjoyment is important, the perceived economic benefit remains the primary catalyst for consumers. Practically, platforms can optimize flash sale design by emphasizing perceived savings and enjoyable experience to effectively drive conversion.
Evaluation of User Satisfaction in Web-based Library Information Systems: A Systematic Literature Review Faradina, Faradina; Hariguna, Taqwa; Utomo, Fandy Setyo
Sistemasi: Jurnal Sistem Informasi Vol 15, No 3 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i3.6204

Abstract

The transformation of library management today is highly influenced by the acceleration of information and communication technology (ICT), particularly through the adoption of web-based information systems. While these systems can optimize productivity and service accessibility, their effectiveness ultimately depends on the level of user satisfaction. This study evaluates various user satisfaction assessment methodologies through a Systematic Literature Review (SLR) using the PRISMA protocol on 25 selected articles published between 2020 and 2024. The findings indicate a shift in the dominance of evaluation tools toward the Human-Organization-Technology Fit (HOT-Fit) model and the Net Promoter Score (NPS). Key determinants of satisfaction were identified in terms of information quality, system reliability, and responsiveness of technical support.
Digital Image Confidentiality using New Encryption Method Ismaiel, Yaseen Hikmat; Abdullah, Omar Muayad; Mahmood, Yasir Ali
Sistemasi: Jurnal Sistem Informasi Vol 15, No 3 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i3.6057

Abstract

The significant development in mobile phone cameras, in terms of the clarity and high-resolution images captured, the wide utilizing of mobile phones and other communication devices among all segments of society, and the increasing use of social networking sites and the exchange of millions of digital photos daily, all have been pointed with a great importance of digital images and the need to provide adequate security and protection for these images. Digital images contain a large amount of information and recently they have an effective and easy tools of communication without the need for a determined text.Given that digital images contain important, personal, and sensitive information, there is a great need to protect these images and prevent unauthorized persons from applying any changes to the image's contents. There is a great deal of work in this field, most of which uses encryption methods to achieve this protection. As is well known, there are two types of encryption systems (symmetric and asymmetric). Symmetric encryption systems are fast but require a secret key distribution process, while asymmetric encryption systems are relatively slow, involving complex processes. Therefore, they are not suitable for use in social networking applications that require rapid performance and interaction. In this research, a proposed method for digital image encryption is proposed, which includes the use of logical XOR operation to encrypt the digital image based on two proposed levels with scrambling operation to provide a high degree of diffusion and confusion for the resulting encrypted image. The proposed method was evaluated through a set of efficiency measurement metrics (NPCR, UACI, MSE, PSNR, SSIM, Entropy, and Correlation) and it gave results showed a difference between the original image and the image resulting from the first level of encryption. We also noted that the image resulting from the second level had a higher percentage of difference and randomness compared to the original image. Therefore, the proposed encryption method is suitable in terms of speed and confidentiality for use in encrypting digital images and thus maintaining their privacy.

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