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All Journal JOIV : International Journal on Informatics Visualization JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Riset Informatika Jurnal Informatika Global Journal of Information Systems and Informatics Jurnal Pengabdian UNDIKMA Community Empowerment International Journal of Community Service Dharma Sevanam : Jurnal Pengabdian Masyarakat Jurnal Informatika Ekonomi Bisnis IJISCS (International Journal of Information System and Computer Science)
Fianty, Melissa Indah
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Journal : Journal of Information Systems and Informatics

 1 
Empowering Pregnancy Risk Assessment: A Web-Based Classification Framework with K-Means Clustering Enhanced Models Wongso, Bernard Pratama; Johan, Monika Evelin; Fianty, Melissa Indah
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.568

Abstract

This study aims to determine whether there is an increase in accuracy results for predicting pregnancy risk with a classification algorithm that goes through and without going through the clustering stage. After that, compare which classification algorithm gets the best improvement. This study uses the K-Means clustering approach, as well as the SVM, Naive Bayes, and K-Nearest Neighbor (KNN) classification algorithms. The pregnancy risk dataset used comes from the UCI Machine Learning Repository. Evaluation metrics used include accuracy, precision, recall, and F1-score. The results of the study revealed that the K-Means model with KNN provided the highest performance compared to the other two, with an accuracy of 79.53% and an average F1-score of 0.8. The implementation of K-Means resulted in an increase in accuracy of 0.4%, 1.57%, and 2.76% on KNN, SVM, and Naive Bayes respectively, which confirms the impact of clustering in improving classification performance. The resulting model can be used in real-time via a website built using the Flask API, and offers tools that can help health practitioners to plan treatments effectively and minimize the risk of pregnancy.
Application of Clustering-Based Data Mining for the Assessment of Nutritional Status in Toddlers at Community Health Centers Fianty, Melissa Indah; Johan, Monika Evelin; Aulia, Azka; Veronica, Mella Margareta
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.586

Abstract

Nutritional status is a crucial foundation for human health and development. Global facts indicate serious challenges in ensuring adequate nutrition, and the situation is no different in Indonesia. This research collected data from the Kelapa Dua Tangerang community health center and utilized data mining techniques with the k-means clustering algorithm to delve deeper into the nutritional status of toddlers. The research findings revealed that nearly 37.3% of toddlers experience issues with abnormal height or weight, as well as poor nutritional conditions, highlighting the importance of careful and timely intervention. With regular health monitoring by community health centers and active parental involvement, actions can be taken to support the optimal growth and development of these children. The results of this research provide a strong understanding to address malnutrition issues, which will ultimately support the formation of a healthier and more promising future generation in Indonesia.
COBIT 2019 Framework: Evaluating Knowledge and Quality Management Capabilities in a Printing Machine Distributor Beato, Jonathan; Fianty, Melissa Indah
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.638

Abstract

Within the realm of printing machine distribution, information technology assumes a critical role in streamlining business operations. This study addresses persistent challenges related to inaccurate inventory data and insufficient knowledge management in IT applications. Utilizing the COBIT 2019 framework to assess IT governance capability, qualitative data was collected through interviews to uncover prevailing issues. The findings underscore specific process objectives—APO11 (Managed Quality), BAI08 (Managed Knowledge), and DSS06 (Managed Business Process Controls)—highlighting the need for improved capability levels. For example, APO11 currently resides at level 3 while aiming for level 4, indicating a one-level discrepancy. Similarly, BAI08 and DSS06 are at level 2, signaling a collective two-level gap. Proposed enhancements center on bolstering IT knowledge management and procedural training to meet quality standards in future IT applications. These measures aim to strengthen organizations, aligning IT practices with business processes to ensure heightened quality and efficiency. Notably, this abstract intentionally omits explicit mention of the evaluated IT process, adhering to the specified guideline.
Enhancing Organizational Performance through COBIT 2019-Based IT Governance Audit: A Case Study of a Digital Technology Company Setiadi, Laurentinus Heriyanto; Fianty, Melissa Indah
Journal of Information System and Informatics Vol 6 No 2 (2024): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i2.715

Abstract

This study investigates the pivotal role of information technology (IT) governance in contemporary business landscapes, particularly emphasizing the digital technology sector. Through an examination of a digital technology company specializing in software development and fleet management platforms, the study utilizes the COBIT 2019 framework to conduct an IT governance audit. The research workflow, comprising planning, fieldwork, reporting, and result analysis stages, facilitates a comprehensive evaluation of the company's IT governance capabilities. Findings indicate proficiency in managed solutions identification and project management, alongside gaps in managing IT changes effectively. Recommendations are provided to address these gaps, emphasizing enhanced collaboration, documentation, and protocol establishment. By shedding light on IT governance practices within the digital technology sector, this study contributes to advancing organizational performance and competitiveness in an evolving landscape. Specifically, the recommendations align with the following domains: BAI03 (Managed Solutions Identification & Build), BAI06 (Managed IT Changes), and BAI11 (Managed Projects).
Optimizing Motorcycle Sales: Enhancing Customer Segmentation with K-Means Clustering and Data Mining Techniques Fernando, Luis; Fianty, Melissa Indah
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.799

Abstract

Information plays a crucial role in the sustainability of company operations. The development of information technology, especially in the industry 4.0 era, affects various fields including economics, social, and education. The company faces challenges in declining motorcycle sales due to intense competition and ineffective customer segmentation. To address these issues, this study proposes the use of the K-Means algorithm with Python tools for better customer segmentation. The study aims to identify diverse customer groups and tailor marketing strategies accordingly. By utilizing the Elbow method and Silhouette score, the analysis of customer data is simplified. This study also employs data mining techniques to uncover hidden patterns in motorcycle sales data, aiding companies in improving operational efficiency and decision-making.
Co-Authors Aulia, Azka Basuki, Sucipto Beato, Jonathan Cynthia Sari Dewi Dina Fitria Murad Erick Fernando B311087192 Faza, Ahmad Fernando, Luis Johan, Monika Evelin Laurenzia, Kezia Aprila Leandro, Jose Octavian Marojahan Tampubolon Mashur, Tsabitah Ramadhani Pratama, Kenny Riyanto Riyanto Saputri, Fahmy Rinanda Setiadi, Laurentinus Heriyanto Setiawan, Johan sherly sherly Sulaiman, Agus Susanto, Meitio Tandrio, Felix Valentina, Alessandra Veronica, Mella Margareta WINANTI, WINANTI Wongso, Bernard Pratama Yusuf Yusuf