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Kab. indragiri hilir,
Riau
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 920 Documents
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Knowledge Acquisition for the Stunting Prevention Expert System (SIPENTING) using Decision Tree and Grid Search Basir, Azhar; Tyas, Fitri Ayuning
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): 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.v14i3.5004

Abstract

Stunting is a condition in which toddlers have a shorter height compared to the normal growth standard for their age. Preventing stunting is crucial, as children with stunting are more vulnerable to illnesses, experience growth failure before the age of 12 months, and tend to have lower intellectual abilities. Stunting can be diagnosed even before birth by assessing the nutritional status of pregnant women. Pregnant women with poor nutritional status are at a higher risk of delivering babies with low birth weight (LBW), which in turn increases the risk of stunting. Diagnosing the nutritional status of pregnant women and the risk of giving birth to stunted children typically requires expert knowledge, such as that of midwives or obstetricians. Expert systems make it possible for pregnant women to receive real-time diagnoses without the need for direct consultations with healthcare professionals. Expert knowledge in identifying the nutritional status of pregnant women and indicators of stunting risk is stored in a knowledge base, which is translated into a computer-readable rule base in the form of IF-THEN statements. This process is known as knowledge acquisition. The accuracy of the rule base plays a crucial role in ensuring reliable diagnostic results. Decision Tree is one of the data mining algorithms used to generate rule bases. In this study, the Decision Tree algorithm is optimized using Grid Search as a knowledge acquisition technique to determine the rule base applied in the Stunting Prevention Expert System (SIPENTING). The system is Android-based and aims to help pregnant women better understand their nutritional needs. Testing and validation results show that the Decision Tree model achieved an accuracy of 86.3%.
User Acceptance Testing to Assess User Receptiveness Toward a Soft Skills Training Information System Hermansah, Lutfi; Murhadi, Murhadi; Saputro, Wahju Tjahjo
Sistemasi: Jurnal Sistem Informasi Vol 14, No 5 (2025): 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.v14i5.5116

Abstract

Soft skills organizations face significant challenges due to manual management practices, leading to scattered participant data, lack of proper documentation, and manual archiving. The main issue is the absence of a dedicated soft skills training information system. This study aims to develop and evaluate a soft skills training information system to address these organizational problems. The Rapid Application Development (RAD) method was chosen for its ability to accommodate changing requirements and enable rapid deployment of the system. System acceptance testing was conducted using the User Acceptance Test (UAT) method with 70 respondents, covering 20 questionnaire items related to system functionality, user interface experience, performance, efficiency, and productivity. The UAT results indicated that the system received an average acceptance rate of 80.4% for functionality, 76.8% for user experience and interface design, 77.3% for performance, and 78.7% for efficiency and productivity. These results show that the soft skills training information system meets user requirements with an overall interpretation score of "Good." The developed system is considered acceptable and capable of supporting soft skills training activities at Universitas Muhammadiyah Purworejo.
A Comparative Study of Machine Learning Algorithms for Intrusion Detection Systems using the NSL-KDD Dataset Putra, Rulyansyah Permata; Amarudin, Amarudin
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): 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.v14i4.5246

Abstract

In today’s digital era, cyberattacks are becoming increasingly complex, rendering traditional rule-based Intrusion Detection Systems (IDS) often ineffective in recognizing new attack patterns. The primary objective of this study is to design and implement a machine learning model for detecting network intrusions efficiently while minimizing latency, through a comparative analysis of several algorithms: Decision Tree, Random Forest, Support Vector Machine (SVM), and Boosting. The research methodology includes the collection of the NSL-KDD dataset, followed by data transformation, cleaning, normalization, and partitioning into training and testing sets. Each algorithm was trained using tuned parameters, and performance was evaluated using metrics such as accuracy, precision, recall, F1-score, and an analysis of training and prediction time. The results indicate that the Boosting algorithm stands out, achieving an accuracy rate of 99.36%. Boosting also demonstrated greater reliability in detecting minority classes, despite requiring longer training times. The application of machine learning methods—particularly Boosting—proves to be an effective approach to enhancing intrusion detection and can serve as a foundation for developing more adaptive and reliable cybersecurity systems.
Risk Analysis of the Information System of the Riau Provincial Plantation Agency Website using ISO 31000 Fernanda, Ustara Dwi; wati, Mega; Rozanda, Nesdi Evrilyan; Salisah, Febi Nur
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): 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.v14i4.5368

Abstract

The website of the Riau Provincial Plantation Agency plays a vital role in supporting public information and administrative services. However, the use of information technology also introduces various risks that may disrupt system operations. This study aims to analyze information technology risks associated with the website using the ISO 31000:2018 risk management framework. A qualitative descriptive approach was employed, utilizing interviews, observations, and documentation. The risk management process was conducted through the stages of risk identification, analysis, evaluation, treatment, as well as monitoring and review. The findings identified nine main risks. Eight of them were categorized as medium-level risks, including lightning, fire, human error, data corruption, server downtime, hardware damage, overheating, and power outages. One risk—software updates—was classified as low-level. This study is limited to information technology risks identified internally, based on primary data collected from the website management team. The findings provide risk mitigation recommendations that can serve as guidelines to enhance the security and continuity of the information system within the Riau Provincial Plantation Agency.
Liver Disease Classification using the NAIVE BAYES Nurhalisa, Vitra; Fajri, Ika Nur
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): 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.v14i4.5072

Abstract

The advancement of artificial intelligence technology presents new opportunities to support medical professionals in making faster and more accurate clinical decisions. This study introduces a liver disease classification system based on the Naive Bayes algorithm, designed to be easily interpretable by doctors and healthcare personnel. A dataset of 580 patients with 11 clinical attributes—ranging from bilirubin levels to albumin–globulin ratio—was used and processed through data cleaning and normalization stages. The Bernoulli Naive Bayes model was then trained and evaluated using a confusion matrix and ROC-AUC analysis. The results show an accuracy of 67%, with strong performance in identifying patients at risk of liver disease (recall of 0.82), but weaker in classifying healthy individuals (recall of 0.28). The fast training time and transparent probabilistic predictions of the Naive Bayes algorithm make it a practical solution for developing a prototype of a medical decision support system. Future recommendations include incorporating additional relevant clinical features and applying ensemble methods to improve diagnostic sensitivity and specificity.
Bridge Scorekeeping Automation: An iOS Application to Improve Tournament Scoring Accuracy and Efficiency Mahazoya, Aqilla Shahbani; Wiradinata, Trianggoro
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): 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.v14i3.5136

Abstract

Scoring in bridge tournaments is still largely dominated by traditional methods such as manual score sheets and specialized devices like Bridgemate. While widely used, these approaches present significant limitations—manual scorekeeping is prone to human error, and Bridgemate devices are often costly and not accessible to all organizers. To address these challenges, Bridge Team Comparator was developed as an iOS-based application offering a more accurate, efficient, and affordable scoring solution for bridge tournaments. Designed with a user-friendly interface for both novice and experienced players, the application supports real-time score entry, automatic calculation of International Match Points (IMP), and efficient result summaries. The development process adopted the Challenge-Based Learning (CBL) framework through the phases of Engage, Investigate, and Act, focusing on simplifying the bridge scoring process. User testing involved bridge athletes from Universitas Negeri Malang, Universitas Brawijaya, and the Sidoarjo bridge community. Results demonstrated a reduction in scoring errors by 8–36% and increased efficiency compared to conventional methods. In addition to offering a cost-effective alternative to commercial devices, the application contributes to the digital transformation of scoring systems in traditional sports. With potential for cross-platform development, Bridge Team Comparator opens new opportunities for broader adoption within the global bridge community.
Design of an IoT-Based 4-Channel 5V Relay Controller Using WiFi and Smartphone Integration Samsudin, Samsudin; Abdullah, Abdullah; Muni, Abdul; Niansyah, Niko
SISTEMASI Vol 14, No 3 (2025): 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.v14i3.5111

Abstract

The development of remote-controlled electrical device systems has become increasingly essential, particularly in supporting the transition toward a green economy. This IoT-based system, built on the NodeMCU microcontroller, enables real-time monitoring and control of electrical power usage, helping reduce energy waste and minimize carbon emissions caused by inefficient electricity consumption. This study aims to develop an Internet of Things (IoT)-based system for controlling electrical devices using a NodeMCU microcontroller integrated with the Telegram bot platform. The system utilizes a WiFi network to receive and execute user commands in real time. The development process follows the Multimedia Development Life Cycle (MDLC), while the programming is conducted using the Arduino IDE in C++. Testing on various devices—including Samsung Galaxy, iPhone, and Xiaomi Redmi smartphones—demonstrated the system’s ability to respond to commands within 0.45 to 0.82 seconds, with a deviation tolerance of ±0.15 seconds, depending on the specific WiFi network used. No overheating occurred under maximum load conditions. Overall, the system met performance criteria in terms of speed, consistency, and reliability. The primary advantages of the system include its universal chat-based interface, low cost, and simple design, accessible from any geographical location with a stable internet connection. However, the system is limited by its dependence on electricity supply and WiFi stability. Therefore, the implementation of this system in smart homes is recommended with the support of a backup power source to improve reliability. In conclusion, the system not only fulfills technical performance requirements but also contributes to energy efficiency in alignment with green economy principles.
User Behavior Analysis of E-Wallet Usage Among Generation Z using the Theory of Planned Behavior Raditya, Muhammad Zacky; Fronita, Mona; Saputra, Eki; Megawati, Megawati; Anofrizen, Anofrizen
SISTEMASI Vol 14, No 4 (2025): 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.v14i4.5312

Abstract

With the rapid advancement of digital technology and the growing demand for fast and practical transaction systems, the use of digital wallets (E-Wallets) among the younger generation—particularly Generation Z—has significantly increased. This study aims to identify the behavioral factors influencing E-Wallet usage among Gen Z by applying the Theory of Planned Behavior (TPB). This theoretical framework includes three main constructs believed to influence Behavioral Intention (BI) and actual user behavior: Attitude Toward the Behavior (ATB), Subjective Norm (SN), and Perceived Behavioral Control (PBC). The study involved 100 Gen Z university students in Pekanbaru, selected through purposive sampling. A quantitative research method was employed, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Instrument validity was tested through discriminant validity, while reliability was assessed using Cronbach’s Alpha and Composite Reliability. The findings reveal that all three variables—Attitude Toward the Behavior, Subjective Norm, and Perceived Behavioral Control—have a significant influence on Behavioral Intention to use E-Wallets among Gen Z in Pekanbaru. Furthermore, both Behavioral Intention and Perceived Behavioral Control significantly affect the actual usage behavior of E-Wallets. Theoretically, these results support the applicability of the TPB framework in the context of digital payment systems. Practically, E-Wallet providers are advised to focus on enhancing users’ positive attitudes, leveraging social influence, and improving ease of use for Gen Z. However, this study is limited by its exclusion of external factors beyond the TPB model that may also influence E-Wallet usage behavior.
Strategic Information System Planning using Anita Cassidy Method and Design Thinking Sambadagni, Sabella Yasmin; Fibriani (SCOPUS ID=57192643331), Charitas
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): 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.v14i3.5143

Abstract

The rapid development of information technology in recent decades has significantly impacted various sectors, including education. The D3 Informatics Engineering Study Program at the Faculty of Information Technology, Satya Wacana Christian University, needs to formulate a strategic plan to leverage technology in addressing educational challenges. This study identifies the lack of documentation for student assignments and projects as a key issue, which hampers accessibility and evaluation processes. The Anita Cassidy method and the Design Thinking approach are employed to develop an information system strategy that aligns with academic objectives and supports business processes. The Anita Cassidy method—through the stages of visioning, analysis, direction, and recommendation—facilitates the alignment of information system strategies with academic goals, resulting in recommended system features for development. Meanwhile, Design Thinking is applied to interface design development, focusing on user interaction to enhance the likelihood of system adoption and user satisfaction. This study aims to produce information system recommendations and user interface designs for the archiving of assignments in the D3 Informatics Engineering Study Program, with the goal of improving efficiency and effectiveness in managing student assignments.
Business Process Reengineering based on Information Economics annastasia, syifa; Suakanto, Sinung; Lubis, Muharman
Sistemasi: Jurnal Sistem Informasi Vol 14, No 5 (2025): 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.v14i5.5240

Abstract

Business Process Reengineering (BPR) is a strategic initiative to achieve fundamental improvements in organizational performance. However, research shows that up to 70% of BPR initiatives fail, often due to unclear value delivery and ineffective process redesign. This study aims to address that gap by redesigning the recruitment and selection process using an information economics approach evaluating the value of information to drive better decision making and resource allocation. The research applied process mapping, identification of non-value-adding activities, and value-based analysis at each stage, followed by the integration of digital tools to streamline workflows and improve data accuracy. A case study in a large organization was conducted to test the effectiveness of the redesigned model. The key findings of this study are its greatest strength and must be explicitly highlighted to convey its impact: the redesigned process resulted in a 67.3% reduction in processing time and a Return on Investment (ROI) of 1,085.17% demonstrating not only operational efficiency but also clear financial gain. These outcomes validate the role of information economics in successful BPR and offer a replicable framework for other organizations. By combining BPR with the discipline of information economics, this study offers a replicable, outcome-oriented framework that addresses one of the most common reasons BPR initiatives fail unclear value delivery. This contribution is particularly critical in HR contexts, where decisions are often qualitative and under digitized. The findings provide actionable guidance for organizations seeking to future-proof their HR processes while avoiding the pitfalls that undermine most BPR efforts.

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