Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Pengabdian pada Masyarakat Ilmu Pengetahuan dan Teknologi Terintegrasi International Journal of Healthcare and Information Technology
Muhammad Ainul Fikri
Politeknik Negeri Jember
Automotive Engineering Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Public Health

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Intelligent System for Early Detection of Heart Disease Using XGBoost Machine Learning Algorithm on Web Application Intan Sulistyaningrum Sakkinah; Puji Hastuti; Muhammad Ainul Fikri; Ulfa Emi Rahmawati; Raditya Arief Pratama; Maulana Akbar Firdausya; Ratna Indah Anggraini
International Journal of Healthcare and Information Technology Vol. 3 No. 2 (2026): January
Publisher : P3M Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/ijhitech.v3i2.6685

Abstract

Heart disease remains a major contributor to global mortality, highlighting the importance of effective early detection systems that can assist both clinicians and general users. This study develops a heart disease prediction model based on the XGBoost algorithm and deploys it within a web-based application to enhance accessibility and practical usability. The research uses a dataset of 918 instances containing 12 demographic and clinical features commonly associated with cardiovascular risk. Pearson correlation analysis was performed to assess feature relevance, revealing that ExerciseAngina, Oldpeak, ST_Slope, Age, and MaxHR exhibit the strongest correlations with the HeartDisease outcome. These findings align with established clinical evidence on exercise-induced angina, ST-segment depression, and cardiac functional capacity. Following preprocessing and feature encoding, the XGBoost model was trained and evaluated. The model achieved strong predictive performance, with 88.26% accuracy, 88.32% precision, 91.66% recall, an F1-score of 89.96%, and an ROC-AUC of 0.93. The results demonstrate that XGBoost effectively discriminates between positive and negative cases and provides a good balance between sensitivity and precision. To enable real-world applicability, the final model was deployed on a Flask backend and integrated into a web application that allows users to input clinical parameters and receive real-time predictions. System testing confirmed that the application accurately delivers outputs and functions reliably across different input conditions. Overall, this study shows the feasibility of combining machine learning with web technologies to support early, accessible heart disease screening. Future work will involve usability testing and validation using real patient data to further strengthen the system’s clinical relevance.
Pengembangan Website dan Konten Karang Taruna Rukun Agawe Santosa Ngijo Bantul sebagai Optimalisasi Media Digital: Development of Web Platforms and Digital Content for Karang Taruna Rukun Agawe Santosa Ngijo Bantul as Digital Media Optimization Inggrid Yanuar Risca Pratiwi; Yudha Riwanto; Ajie Kusuma Wardhana; Fauzia Anis Sekar Ningrum; Muhammad Ainul Fikri
Jurnal Pengabdian pada Masyarakat Ilmu Pengetahuan dan Teknologi Terintegrasi Vol. 10 No. 1 (2025): December
Publisher : Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jindeks.v10i1.9093

Abstract

Kegiatan ini bertujuan untuk mengoptimalkan pemanfaatan media digital sebagai sarana informasi, publikasi, dan komunikasi organisasi kepemudaan melalui pengembangan website serta pelatihan manajemen konten bagi Karang Taruna Rukun Agawe Santosa (RAS) Dusun Ngijo, Kabupaten Bantul, Daerah Istimewa Yogyakarta. Permasalahan utama yang dihadapi Karang Taruna RAS meliputi keterbatasan media publikasi kegiatan dan rendahnya kemampuan pengurus dalam mengelola informasi secara digital. Kegiatan dilaksanakan melalui empat tahapan, yaitu observasi dan pengembangan, sosialisasi dan pelatihan, implementasi teknologi dan evaluasi. Website yang dikembangkan memiliki fitur-fitur utama yaitu Manajemen Agenda, Keuangan, Inventaris Perlengkapan, dan Broadcast WhatsApp. Hasil sosialisasi dan pelatihan ini telah berhasil mengembangkan dan menyerahkan website untuk Karang Taruna yang fungsional dan dapat diakses melalui internet kapan saja dan di mana saja. Dari sisi sumber daya manusia, para pengurus Karang Taruna RAS telah menerima transfer pengetahuan melalui pelatihan manajemen konten dan terbukti mampu mengelola website secara mandiri, termasuk mempublikasikan beberapa konten awal pasca-pelatihan. Berdasarkan hasil pengujian UAT terhadap website oleh pengurus dan anggota Karang Taruna RAS  didapatkan nilai rata-rata 97,8%. Hal ini menunjukkan peningkatan kemampuan digital yang signifikan dalam pengelolaan informasi organisasi. Luaran kegiatan ini mencakup website dan buku panduan penggunaan website (manual book) yang diberikan kepada Karang Taruna RAS.
Co-Authors Ajie Kusuma Wardhana Fauzia Anis Sekar Ningrum Inggrid Yanuar Risca Pratiwi Intan Sulistyaningrum Sakkinah Maulana Akbar Firdausya Puji Hastuti Raditya Arief Pratama Ratna Indah Anggraini Ulfa Emi Rahmawati Yudha Riwanto