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All Journal LEBAH JKM: Jurnal Kemitraan Masyarakat
Ananda, Muthia
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Implementasi Sistem Informasi Berbasis Web dengan Fitur Chatbot untuk Meningkatkan Layanan Konsultasi Mardiyah, Ainil; Kariman, Delsi; Fadhli, Irfan; Ananda, Muthia; Jasril, Jasril
JKM: Jurnal Kemitraan Masyarakat Volume 4 Number 2 Desember 2025 artikel in press
Publisher : Program Studi Pendidikan IPA Fakultas MIPA Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jkm.v4i2.78783

Abstract

The purpose of this community service activity is to help schools improve their consultation services by utilizing a web-based information system equipped with a chatbot feature. Furthermore, it also digitizes consultation data management. The program implementation consists of several stages: outreach, training, system implementation, mentoring, and evaluation. After the activity was completed, there was a significant improvement in the ability of teachers and staff to manage the digital system, increased ease of consultation for parents, and improved structured data documentation. The system used also expanded the reach of consultation services without the constraints of space and time. Furthermore, it reduced the administrative burden on teachers. This system can be applied to other schools to encourage the digital transformation of educational services.
Analisis Komparatif Algoritma Machine Learning untuk Prediksi Dini Tuberkulosis di Puskesmas X Koto I Tanah Datar Junaidi, Satrio; Febriyani, Nia; Putri, Melani Septina; Ananda, Muthia
Lebah Vol. 19 No. 4 (2026): Maret: Pengabdian
Publisher : IHSA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/lebah.v19i4.493

Abstract

Tuberkulosis (TB) masih menjadi masalah kesehatan serius di Indonesia, terutama di daerah dengan akses terbatas seperti Kabupaten Tanah Datar. Deteksi dini yang lambat sering kali terjadi karena gejala awal yang tidak spesifik dan sistem pencatatan yang masih manual. Penelitian ini bertujuan mengembangkan sistem prediksi pasien TB berbasis machine learning dengan algoritma Support Vector Machine (SVM) untuk membantu tenaga kesehatan di Puskesmas X Koto I dalam melakukan skrining awal. Metode yang digunakan meliputi pengumpulan data rekam medis sebanyak 1.000 pasien, pengembangan model prediktif, pelatihan bagi tenaga kesehatan, serta implementasi dan evaluasi sistem. Hasil uji coba menunjukkan bahwa sistem mampu memprediksi risiko TB dengan akurasi mencapai 98% dengan precision, recall dan fi-score 93%.  Sistem ini telah diimplementasikan dalam bentuk aplikasi web interaktif yang mudah digunakan oleh petugas kesehatan. Selain meningkatkan akurasi diagnosis, sistem ini juga mempercepat proses skrining dan mendukung upaya pencegahan penularan TB di masyarakat. Program ini diharapkan dapat menjadi model inovatif yang berkelanjutan dan dapat diadopsi oleh puskesmas lainnya
Co-Authors Ainil Mardiyah Delsi K Delsi K Fadhli, Irfan Jasril Jasril Nia Febriyani Putri, Melani Septina Satrio Junaidi