Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Sevaka: Hasil Kegiatan Layanan Masyarakat
Nadya Fitriyani
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Education Engineering Health Professions

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

Found 2 Documents
Search

 1 
Penyuluhan Klasifikasi Risiko Infertilitas Pada Pasien Wanita Berdasarkan Data Rekam Medis Menggunakan Algoritma Naive Bayes Fahruzi Sirait; Hafizhah Mardivta; Nailatun Nadrah; Nadya Fitriyani; Baginda Restu Al Ghazali
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 3 No. 3 (2025): Agustus : Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v3i3.555

Abstract

Infertility in women is a reproductive health issue that requires early intervention to prevent long-term effects. With the advancement of technology, electronic medical records data can be utilized to assist in the diagnosis and classification of infertility risks. This study aims to classify the risk of infertility in female patients using the Naive Bayes algorithm based on medical record data, which includes factors such as age, health history, and medical test results. The data used in this study were obtained from hospitals and health clinics focused on managing infertility patients. The methods applied include data preprocessing, applying the Naive Bayes algorithm for classification, and evaluating the model using accuracy, precision, recall, and F1-score metrics. The results of the study show that the Naive Bayes algorithm provides fairly accurate classification in predicting infertility risks. The analysis-generated graph shows the distribution of infertility risks, with 60% of patients having a positive risk (1) and 40% having a negative risk (0). This study also suggests implementing the classification results in the form of counseling for patients to increase awareness and encourage early preventive actions. Thus, the Naive Bayes algorithm can be an effective tool in assisting healthcare providers in data-driven decision-making to address infertility risks in female patients.
Pemberdayaan Pekerja Informal Untuk Kepersetaan Mandiri Dalam Asuransi Kesehatan Nur Indah Nasution; Nadya Fitriyani; Indah Kumala Dewi
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 3 No. 4 (2025): November : Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v3i4.584

Abstract

Informal workers are a group that contributes significantly to the Indonesian economy, but still have a low level of independent participation in the national health insurance program. This low participation is caused by minimal insurance literacy, income instability, and a lack of awareness of the importance of health protection. This activity aims to empower informal workers to have the ability and willingness to become independent participants in health insurance. The method used is a community-based participatory approach through three main stages: education on the benefits of health insurance, microfinance management training for regular premium payments, and assistance with independent registration for participation. The activity results showed a significant increase in participants' knowledge and understanding of the benefits of health insurance. In addition, there was an increase in the number of informal workers registering as independent participants and demonstrating a commitment to sustainable premium payments. This program demonstrates that community empowerment can be an effective strategy to expand Universal Health Coverage (UHC) and improve the welfare of informal workers through sustainable health protection.
Co-Authors Baginda Restu Al Ghazali Fahruzi Sirait Hafizhah Mardivta Indah Kumala Dewi Nailatun Nadrah Nur Indah Nasution