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Design of an Intelligent Computing-based Information System for Automated Decision Making Febri Pratama; Terttia Avini; Irfan Saputra; Melinda Kurnia Putri; Sultan Imam Fajri
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 9 No. 2 (2024): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v9i2.2

The rapid growth of information technology has increased the need for intelligent computing-based information systems across sectors, such as business, education, and government, to facilitate quick and accurate decision-making. Previous research primarily focused on data analysis without a seamless integration for automated decision support. This study aims to bridge this gap by designing an information system that leverages machine learning algorithms for automated decision-making. The system incorporates artificial intelligence and big data processing to provide accurate recommendations based on historical and real-time data patterns. Key processes include identifying user needs, selecting suitable algorithms, developing predictive models, and integrating them into a user-friendly, web-based platform. Results indicate that the intelligent system significantly enhances decision-making speed and accuracy, particularly in scenarios demanding real-time analysis. Tests with decision trees and neural network algorithms demonstrate the system's reliability and adaptability to various data types, supporting consistent, data-driven outcomes. This research concludes by highlighting the system's potential to address complex data challenges, enabling efficient decision-making in dynamic environments.

Strategy to Improve Operational Performance Efficiency through the Implementation of Management Information System Nining Ariati; Febri Pratama; Irfan Saputra; Melinda Kurnia Putri; Sultan Imam Fajri
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 10 No. 1 (2025): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v10i1.1

The rapid advancement of information technology has encouraged many companies to adopt Management Information Systems (MIS) to enhance operational performance. However, a significant number of organizations continue to experience suboptimal results due to inadequate employee training, inconsistent system maintenance, and weak managerial support. This indicates a critical gap between MIS implementation and its expected benefits, particularly in improving operational efficiency. This study aims to bridge that gap by investigating the impact of MIS implementation on operational performance and identifying key success factors that influence its effectiveness. Using a quantitative approach, the research involved a case study in a medium-sized manufacturing company, with data collected from 100 respondents across operational-related depart-ments through a structured questionnaire. The findings show that effective MIS implementation contributes substantially to operational efficiency by streamlining workflows, minimizing processing time, and enhancing resource allocation. Furthermore, success is strongly associated with comprehensive user training, consistent system maintenance, and committed managerial support. These findings offer practical insights for organizations seeking to maximize the benefits of MIS and can serve as strategic references for improving operational performance through targeted system implementation efforts.

Design of an Intelligent Computing-based Information System for Automated Decision Making Febri Pratama; Terttia Avini; Irfan Saputra; Melinda Kurnia Putri; Sultan Imam Fajri
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 9 No. 2 (2024): December
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v9i2.2

The rapid growth of information technology has increased the need for intelligent computing-based information systems across sectors, such as business, education, and government, to facilitate quick and accurate decision-making. Previous research primarily focused on data analysis without a seamless integration for automated decision support. This study aims to bridge this gap by designing an information system that leverages machine learning algorithms for automated decision-making. The system incorporates artificial intelligence and big data processing to provide accurate recommendations based on historical and real-time data patterns. Key processes include identifying user needs, selecting suitable algorithms, developing predictive models, and integrating them into a user-friendly, web-based platform. Results indicate that the intelligent system significantly enhances decision-making speed and accuracy, particularly in scenarios demanding real-time analysis. Tests with decision trees and neural network algorithms demonstrate the system's reliability and adaptability to various data types, supporting consistent, data-driven outcomes. This research concludes by highlighting the system's potential to address complex data challenges, enabling efficient decision-making in dynamic environments.

Strategy to Improve Operational Performance Efficiency through the Implementation of Management Information System Nining Ariati; Febri Pratama; Irfan Saputra; Melinda Kurnia Putri; Sultan Imam Fajri
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 10 No. 1 (2025): June
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v10i1.1

The rapid advancement of information technology has encouraged many companies to adopt Management Information Systems (MIS) to enhance operational performance. However, a significant number of organizations continue to experience suboptimal results due to inadequate employee training, inconsistent system maintenance, and weak managerial support. This indicates a critical gap between MIS implementation and its expected benefits, particularly in improving operational efficiency. This study aims to bridge that gap by investigating the impact of MIS implementation on operational performance and identifying key success factors that influence its effectiveness. Using a quantitative approach, the research involved a case study in a medium-sized manufacturing company, with data collected from 100 respondents across operational-related depart-ments through a structured questionnaire. The findings show that effective MIS implementation contributes substantially to operational efficiency by streamlining workflows, minimizing processing time, and enhancing resource allocation. Furthermore, success is strongly associated with comprehensive user training, consistent system maintenance, and committed managerial support. These findings offer practical insights for organizations seeking to maximize the benefits of MIS and can serve as strategic references for improving operational performance through targeted system implementation efforts.

Analysis of the Task Technology Fit Suitability of the SiNonA Application and its Impact on Improving the Performance of Non-ASN Employees Melinda Kurnia Putri; Nining Ariati; Dhamayanti Dhamayanti
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 11 No. 1 (2026): June
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v11i1.9

The implementation of the Electronic-Based Government System (SPBE) encourages government institutions to utilize information technology to improve employee effectiveness and administrative efficiency. One implementation in Ogan Ilir Regency is the SiNonA application, which is used as a digital attendance system for Non-ASN employees. However, several problems are still encountered in its implementation, such as limited application features, difficulties in system usage, and the mismatch between system capabilities and employee work requirements. Previous studies on digital attendance systems mostly focused on usability, system quality, and technology acceptance, while studies examining the suitability between technology characteristics and employee task requirements using the Task Technology Fit (TTF) approach are still limited, especially in the government sector for Non-ASN employees. Therefore, this study aims to analyze the influence of Task Characteristics and Technology Characteristics on Task Technology Fit and its impact on employee performance improvement in using the SiNonA application. This study used a quantitative approach with a survey method involving 353 respondents selected using the Slovin formula. Data were collected through Likert-scale questionnaires and analyzed using the PLS-SEM method with SmartPLS software. The results showed that Task Characteristics and Technology Characteristics had a positive and significant effect on Task Technology Fit, while Task Technology Fit also had a positive and significant effect on employee performance improvement. These findings indicate that the suitability between technology and work tasks plays an important role in improving the effectiveness, efficiency, and productivity of Non-ASN employees in using the SiNonA application.

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