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All Journal JEECS (Journal of Electrical Engineering and Computer Sciences) Jurnal Kecerdasan Buatan dan Teknologi Informasi
Irfan Saputra
Universitas Indo Global Mandiri
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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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

Abstract

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

Abstract

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.
AN ANALYSIS OF FEAR OF MISSING OUT (FOMO) AS A DRIVER OF HOAX DISSEMINATION IN THE PRABOWO ERA USING MLP Irfan Saputra; Agustina Heryati; Hendra Di Kesuma
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 2 (2026): May 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i2.444

Abstract

The development of social media over the past decade has accelerated the spread of information, including hoaxes, which impact public perception and political stability. One psychological factor contributing to the impulsive spread of information is Fear of Missing Out (FOMO), defined as the feeling of anxiety experienced when individuals believe they are missing important information or events. This study aims to analyze the relationship between the FOMO phenomenon and the tendency to spread political hoaxes related to the Prabowo administration on social media. The research data was obtained through comment crawling techniques on the TikTok platform and then processed using the following stages: preprocessing text (e.g., cleaning, case folding, tokenizing, filtering, stemming) and labeling of FOMO, Non-FOMO, Hoax, and Non-Hoax classes. The Multi-Layer Perceptron (MLP) model is used to classify user behavior patterns. FOMO plays a role in increasing the spread of fake news in the political sphere, and this demonstrates that a combination of psychological factors and machine learning techniques can help understand the dynamics of disinformation on social media.
Co-Authors Agustina Heryati Febri Pratama Kesuma, Hendra Di Melinda Kurnia Putri Nining Ariati Sultan Imam Fajri Terttia avini