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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 40 Documents
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Search results for , issue "Vol 14, No 6 (2025): Sistemasi: Jurnal Sistem Informasi" : 40 Documents clear
Multi-Platform System Development for Violence Complaint Services using the CodeIgniter Framework Rohmah, Putri Anjilis; Setiaji, Pratomo; Muzid, Syafiul
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5528

Abstract

Violence against women and children remains a prevalent social issue in Indonesia, including in Kudus Regency. The lack of fast, secure, and easily accessible reporting facilities is one of the factors contributing to the low reporting rate, leaving many cases unaddressed. This study aims to design and develop a web-based violence complaint information system using the CodeIgniter framework with a Model-View-Controller (MVC) architecture to ensure a more structured, secure, and efficient system. The development method follows the waterfall model, consisting of requirements analysis, design, implementation, integration, and system testing. The system provides key features such as an online reporting form, automated notifications to officers, real-time report status tracking, and case progress recording by authorized personnel. Black-box testing conducted by one reporter and three staff members of the Kudus Social Service (Dinas Sosial P3AP2KB) on six main features across four different scenarios resulted in a total of 96 test cases, achieving a functional success rate of 98.9%. One failure was identified in file upload validation, where the system still allowed unsupported file formats. Nevertheless, all other features functioned properly, and the system was proven responsive across devices. This reliability supports faster reporting and case handling, enabling victims to report more easily while allowing relevant institutions to respond quickly, accurately, and transparently.
User Review Automation: Detecting Actionable Complaints on Gojek in the Play Store using the LSTM Method Ramadhani, Indira Nailah; Sari, Winda Kurnia; Tania, Ken Ditha
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5708

Abstract

This study aims to develop an automatic complaint detector for Gojek app reviews using Long Short Term Memory (LSTM). The dataset consists of 225,002 user reviews on the Google Play Store. The purpose of this study itself is to facilitate the service team in understanding the shortcomings of the application complained by users. Automatic complaint detection will facilitate the service team to take action to resolve the problems experienced by users. Therefore, the review data provided by users is properly processed using LSTM to create an effective and efficient detection system. Processing is carried out using three different data sharing ratios, namely 90:10, 80:20, and 70:30 to ensure that the system is stable and effective. The accuracy results of the three data sharing ratios reached above 90%, thus proving that the system is able to detect complaints well. A pre-built dashboard is used to visualize the results of the system built using LSTM to facilitate monitoring the classification results. This system is expected to facilitate companies in detecting all user complaints and finding solutions to improve services to provide comfort for users.
Decision Support System for Porang Land Selection based on Multi Attribute Utility Theory (MAUT) Umar, Najirah; Idris, Muhammad; Rahmat, Agus
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.4297

Abstract

This study aims to develop a web-based decision support system using the Multi-Attribute Utility Theory (MAUT) algorithm to assess land suitability for porang cultivation. The system is designed to assist farmers and land developers in selecting optimal planting sites. The research methodology includes problem identification, primary data collection through field surveys, determination of criteria and weights based on land characteristics, and the implementation of the MAUT algorithm to generate land recommendations. The five main criteria considered are soil texture, altitude, temperature, soil pH, and shading level. The results indicate that the three tested land alternatives achieved suitability levels of 86.67%, 75.57%, and 73.33%, respectively. Based on the suitability threshold of ≥70%, all land alternatives are deemed suitable for porang cultivation. These findings demonstrate the effectiveness of MAUT in supporting data-driven decision-making in the agricultural sector. Furthermore, this approach can be replicated for other commodities and further enhanced through the integration of spatial mapping and financial benefit analysis.
Proposing a Model of Technology Acceptance and use in Digital Banking: A Systematic Review and Meta-Analysis Approach Suwito, Justin Hadinata; Panjaitan, Erwin Setiawan
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5670

Abstract

The advancement of information technology has driven a significant transformation in the banking sector through digital banking, which has now become the backbone of modern financial services. Digital banking offers efficiency, ease of transactions, and reduced operational costs. Despite these benefits, challenges remain, particularly the high initial investment costs and the complexity of customer adoption. Without a well-designed user acceptance strategy, substantial investments risk being underutilized. Therefore, a deep understanding of the factors influencing digital banking adoption is crucial to ensure the effectiveness of digital transformation initiatives. Previous studies have examined the acceptance and use of digital banking using popular models such as TAM, UTAUT, and UTAUT2. However, fragmented findings—caused by variations in results and the inclusion of additional variables—pose challenges for generalization. This study aims to develop a more comprehensive model of digital banking acceptance through a systematic review and meta-analysis. The results indicate that most core constructs of UTAUT2—such as Performance Expectancy, Effort Expectancy, Facilitating Conditions, Social Influence, Habit, Price Value, and Hedonic Motivation—are significant. Furthermore, external variables such as Trust, Perceived Security, Enterprise Image, Promotions, and Perceived Risk also play a role, thereby extending the model beyond the generic framework. The proposed model is expected to enrich the development of technology acceptance theory by introducing a context-specific framework for digital banking. It also provides strategic guidance for the banking industry to enhance adoption through targeted interventions on the most influential variables. Consequently, this model can serve as a stronger foundation for both institutional practices and future research in the field.
Bitcoin Price Forecasting using Seasonal Log-Differenced XGBoost with 2014–2025 Data Akbar, Muhammmad
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5547

Abstract

Bitcoin, as a decentralized digital currency, experiences significant price fluctuations, making accurate price forecasting a complex yet valuable challenge. Price forecasting is essential in economic decision-making, serving as the foundation for portfolio construction, risk analysis, and investment strategy development. Bitcoin's high volatility makes it an attractive asset for investors but also poses significant risks, necessitating sophisticated forecasting tools and models to mitigate uncertainty. The XGBoost model in regression is widely known and effectively applied to handle time series data. This model can capture complex nonlinear relationships in Bitcoin price data, providing more accurate forecasts than traditional statistical models. The research methodology includes data collection, data preprocessing, stationarity checking, differencing, feature engineering, data division into training and testing sets, XGBoost model training, prediction and evaluation, and result visualization. The research results show that the XGBoost model achieves a Mean Absolute Error of 8.26% and an RMSE of 9.87%, indicating excellent forecasting accuracy. The implications of this research could potentially assist investors and traders in improving their strategies and risk management.
Integrating Agile and Business Metrics into Backlog Prioritization: A Case Study at PT. XYZ Purba, Susi Eva Maria; Tambunan, Katrina Arlyanti
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5244

Abstract

Backlog prioritization is an essential component of Agile development because it makes sure that resources are used in the best way possible and that business value is maximized. The Effort-influence Matrix gives you a way to prioritize items in your backlog based on how much effort they will take and how much influence they might have. However, just prioritizing them doesn't mean you'll be successful in the long term. Integrating Agile Metrics—such as velocity, cycle time, and lead time—with Business Metrics—such as customer satisfaction, retention, and market adoption—offers a more comprehensive approach to guiding decision-making. This study examines how Product Owners at PT. XYZ applies the Effort-Impact Matrix while incorporating Agile and Business Metrics to align development priorities with organizational objectives. This study employed qualitative research design, drawing on structured interviews, project documentation, and literature review. The findings show that combining prioritizing frameworks with performance indicators improves decision-making, increases alignment with company goals, and leads to more predictable delivery outcomes. This study contributes to the literature by being among the few to empirically demonstrate how Agile and Business Metrics can be systematically integrated into backlog prioritization using the Effort-Impact Matrix.
Implementation of a Network Security System using an Intrusion Prevention System with Machine Learning Lumban, Andre Pardamean; Tedyyana, Agus; Hidayasari, Nurmi
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5460

Abstract

This research develops a machine learning-based Intrusion Prevention System (IPS) to automatically detect and prevent network attacks. The system was designed using the Random Forest algorithm, trained on the CICIDS2017 and CICIDS2019 datasets—standard benchmarks developed by the Canadian Institute for Cybersecurity, widely used in cybersecurity research for their realistic network traffic and diverse attack types. The system focuses on three common attacks: SYN Flood, Port Scanning, and SSH Patator. After preprocessing, training, and evaluation, the model was integrated into the IPS, enabling real-time network monitoring, attacker IP blocking, and automated notifications via Telegram. Testing results indicate that the system achieves high detection accuracy while delivering fast and efficient responses. This system simplifies the work of network administrators by detecting and responding to attacks without the need for manual log monitoring. Through its automated and adaptive approach, the IPS makes a significant contribution to enhancing network security and can be directly implemented in organizational or institutional network environments to substantially reduce the risk of cyberattacks.
Website Database Development for Radyakartiyasa using the Directus Headless CMS Irdina, Mutiara; Luthfi, Ahmad
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5512

Abstract

Kawadenan Radyakartiyasa, under the auspices of the Karaton Ngayogyakarta Hadiningrat, plays a vital role in cultural preservation and the management of historical tourism destinations. To broaden the reach of information and enhance the promotion of cultural events and Kagungan Dalem heritage sites, a website database was developed as the core foundation of the digital information system. The development process adopted the Agile methodology with the Scrum framework, involving sprint planning to prioritize collections, daily scrums to synchronize progress, sprint reviews to evaluate outcomes, and sprint retrospectives to improve processes. The system was built using the Directus Headless CMS, which decouples the backend and frontend, enabling non-technical teams to manage content efficiently while supporting cross-platform integration. The resulting system includes core collections such as Navigation, Destination Index, Event Index, Hero Banner, FAQ, and other supporting collections, all designed to systematically accommodate information and support multilingual display. These features significantly improve content management efficiency by accelerating information updates, reducing data redundancy, and simplifying content organization in multiple languages. Inter-collection integration ensures consistent information across all website pages, enabling users to quickly and systematically access the data they need. Collection endpoint testing was conducted using Postman to verify that all functions operate according to design specifications and support more organized content management.
The use of iTCLab Kit as a Learning Media for Dynamic Systems and Control Fachrezi, Ahriyad; Rahmat, Basuki; Risal, Muhammad
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5616

Abstract

The Internet-Based Temperature Control Lab (iTCLab) kit is an instructional tool designed to facilitate the understanding of fundamental concepts in dynamic systems and control, particularly Proportional-Integral-Derivative (PID) controllers. The background of this study lies in the gap between students’ theoretical knowledge and its application in real-world systems, which often poses a challenge in learning Dynamic Systems and Control courses. This research aims to evaluate the effectiveness of using iTCLab in improving students’ understanding of both PID control theory and its practical applications. The study was conducted in three stages: development of learning modules, implementation, and evaluation involving 30 Informatics students. Assessment was carried out through knowledge tests (pre-test and post-test) and perception surveys. The results indicated an increase in the average score from 52.30 to 76.48 (+46.26%, p < 0.001, Cohen’s d = 1.86), along with positive evaluations in terms of theory–practice integration (4.30), ease of use (4.10), content relevance (4.40), and learning satisfaction (4.20) on a 1–5 scale. These findings suggest that iTCLab is effective in strengthening students’ conceptual understanding and technical skills. From a practical standpoint, iTCLab is suitable for integration into Semester Learning Plans (RPS) and further development to support Internet of Things (IoT)-based distance learning.
The Best Nurse Performance Recommendation Model with Integration of AHP and Weighted Product Methods Fatkhurrochman, Fatkhurrochman; Kanafi, Kanafi
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (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.v14i6.5529

Abstract

This study aims to develop a recommendation model for identifying the best nurse performance by integrating the Analytical Hierarchy Process (AHP) and Weighted Product (WP) methods. Nurse performance plays a vital role in determining the quality of healthcare services; however, existing performance evaluations are often subjective and lack transparency. This situation leads to dissatisfaction among nurses and reduces work motivation. Therefore, a system that provides objective and fair evaluation is needed. The AHP method is employed to determine the priority weights of nurse performance criteria through pairwise comparisons, while the WP method is applied to rank nurses based on the assigned weights. The criteria used include Technical Competence, Professional Attitude, Teamwork, and Patient Satisfaction. This research adopts a Research and Development (R&D) approach, which involves data collection, criteria identification, AHP weighting, web-based system development, and model validation and evaluation. The results indicate that integrating the AHP and WP algorithms can produce a comprehensive and practical nurse performance recommendation model that enhances decision-making efficiency and accuracy in hospitals. The best nurse performance recommendation resulted in Wulandari achieving the highest score of 0.3251.

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