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All Journal Jurnal PkM MIFTEK Journal of Intelligent Systems Technology and Informatics
Amelia, Melina
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Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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LITERASI DIGITAL DAN DIGITALISASI KESENIAN DI DESA MEKARMUKTI Elsen, Rickard; Ramadhan, Iwan; Hamzah, Muhamad; Kaulan, Muhammad Denanda; Nurapipah, Nida; Septiyani, Tiara; Amelia, Melina; Indallah, Aghniya Qolbin; Putri, Salsabilah Triana; Romansah, Ubad; Munawar, Deni Wildan; Mubarok, Zam Zam; Abadi, Manza Restu; Hanif, Muhammad; Jaelani, Iqbal Waliyuddin Sidiq; Assholih, Mukhtar; Apriliansah, Rudi; Nurzaman, Ikbal Saputra; Septiana, Yuga; Saputra, Raihan Rafif Syaefudin; Alamsyah, Reza Bachtiar; Rosandi, Ujang Ahmad
Jurnal PkM MIFTEK Vol 6 No 1 (2025): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/miftek/v.6-1.1945

Abstract

This study explores the role of students in the Mekarmukti village community over a period of one month, specifically through real work lecture activities with digital literacy work programs, education, physical development, and collaboration with the village government and other campuses. These activities involve introducing social media to artists, teaching Bebras and Information and Communication Technology Volunteers, teaching in early childhood education (PAUD), and optimizing Micro, Small, and Medium Enterprises through the introduction of Google Maps, rebranding, and employee needs analysis. In addition, students participated in helping prepare for the 79th Anniversary of the Republic of Indonesia, teaching the Koran, cleaning the mosque environment, painting Posyandu and PAUD, and helping with the physical construction of the sports building. This study uses a qualitative method with a case study approach to analyze the impact and contribution of students in these activities.
Classification of Thyroid Disease Risk Using the XGBoost Method Amelia, Melina; Fitriyani, Dila
Journal of Intelligent Systems Technology and Informatics Vol 1 No 3 (2025): JISTICS, November 2025
Publisher : Aliansi Peneliti Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64878/jistics.v1i3.26

Abstract

Thyroid disease is one of the essential health threats and requires early detection to enable more effective medical intervention. This study aims to develop a classification model using the XGBoost algorithm to categorize patient clinical data from the Kaggle platform into three levels of thyroid cancer risk: low, moderate, and high. The data processing process follows the stages of the SEMMA (Sample, Explore, Modify, Model, Assess) methodology, with main techniques such as label coding, stratified 5-fold cross-validation, and hyperparameter tuning being applied. Performance evaluation was conducted using accuracy metrics, including F1-score and AUC-ROC. The results show that the model exhibits excellent performance in detecting low-risk cases (AUC = 1.00), but it still faces challenges in classifying moderate and high-risk categories. After adjusting the hyperparameters, the validation accuracy increased to 96.24%, although the final accuracy on the test data remained at 69.85%. These findings suggest that XGBoost is a promising approach for the early assessment of thyroid disease risk, particularly in detecting low-risk cases. However, further model development is needed to enhance generalizability across risk levels and support informed clinical decision-making.
Co-Authors Abadi, Manza Restu Alamsyah, Reza Bachtiar Apriliansah, Rudi Assholih, Mukhtar Elsen, Rickard Fitriyani, Dila Hamzah, Muhamad Indallah, Aghniya Qolbin Jaelani, Iqbal Waliyuddin Sidiq Kaulan, Muhammad Denanda Mubarok, Zam Zam Muhammad Hanif Munawar, Deni Wildan Nurapipah, Nida Nurzaman, Ikbal Saputra Putri, Salsabilah Triana Romansah, Ubad Rosandi, Ujang Ahmad RR. Ella Evrita Hestiandari Saputra, Raihan Rafif Syaefudin Septiana, Yuga Septiyani, Tiara