Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Sains Informatika Terapan (JSIT) TOFEDU: The Future of Education Journal
Yumai Wendra
Universitas Nahdlatul Ulama Sumatera Barat
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Languange, Linguistic, Communication & Media Mathematics Public Health Other

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Penerapan Data Mining Memprediksi Penjualan Obat Menggunakan Metode K-Nearest Neighbor (Studi Kasus : Apotek Difana) Raecky Meyzal Febrialdo; Yumai Wendra
Jurnal Sains Informatika Terapan Vol. 4 No. 3 (2025): Jurnal Sains Informatika Terapan (Oktober, 2025)
Publisher : Riset Sinergi Indonesia (RISINDO)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62357/jsit.v4i3.804

Abstract

The development of information technology in the digital era has provided opportunities for various sectors, including the pharmaceutical industry, to improve operational efficiency and service quality. One of the main challenges faced by pharmacies is inventory management, where both stockouts and overstocks often occur due to the limitations of conventional prediction methods. This study aims to apply data mining techniques using the K-Nearest Neighbor (KNN) algorithm to predict drug sales at Apotik Difana. KNN is chosen because it is simple yet effective in recognizing sales patterns from historical data. A web-based prediction system was developed to facilitate accessibility and usability for the pharmacy. The scope of this study focuses on historical sales data without considering external factors, and only KNN is used without comparison to other algorithms. The results are expected to assist the pharmacy in determining the right type and quantity of drugs, optimizing inventory management, reducing losses from expired drugs, and improving customer service quality. Furthermore, this research provides a theoretical contribution to the development of data mining in sales prediction and offers a practical, technology-based solution for pharmaceutical inventory management.
The Implementation of the K-Means Clustering Algorithm Based on the Severity Level of Diabetes in Patients Using a Website Platform Syaputri Maharani; Yumai Wendra; Melladia Melladia; Radiyan Rahim
The Future of Education Journal Vol 4 No 7 (2025): Continued
Publisher : Lembaga Penerbitan dan Publikasi Ilmiah Yayasan Pendidikan Tumpuan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61445/tofedu.v4i7.933

Abstract

Diabetes mellitus is a chronic non-communicable disease with a steadily increasing prevalence worldwide, posing a significant public health challenge due to its potential for severe complications if not managed properly. In many healthcare facilities, including RSUD Pariaman, there is still no structured system to classify patients according to the severity of their condition, which hampers timely intervention and optimal resource allocation. This study aims to develop and implement a web-based system for clustering the severity levels of type 2 diabetes mellitus using the K-Means Clustering algorithm as a decision support tool for medical staff. A quantitative system development research design was applied, utilizing secondary medical records from January 2023 to December 2024, with five clinical variables: Hemoglobin A1c (HbA1c), Fasting Blood Glucose (GDP), Systolic Blood Pressure (TDS), Diastolic Blood Pressure (TDD), and Body Mass Index (BMI). The system was built using the CodeIgniter PHP framework, MySQL database, and Bootstrap-based interface, following the Knowledge Discovery in Database (KDD) process for data preprocessing. K-Means clustering was configured into three categories (mild, moderate, and severe). Validation using RapidMiner confirmed that the clustering results from the web-based system were consistent with the benchmark model, ensuring the correctness of the algorithm’s implementation. The developed system enables real-time data processing, displays results in both tabular and graphical forms, and provides an intuitive interface for medical personnel, thus supporting clinical decision-making and improving healthcare service quality.
MEMBANGUN LITERASI KECERDASAN BUATAN PADA REMAJA MASJID MELALUI PELATIHAN PENGENALAN DAN PEMANFAATAN AI Tika Christy; Yusli Yenni; Yumai Wendra; Nadia Astri Wulandari; Sayendra Safaria; Indira Karina
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 7 No. 4 (2026): Inpress Vol. 7 No. 4 (2026)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v7i4.60002

Abstract

Penggunaan aplikasi Artificial Intelligence (AI) mengalami peningkatan yang sangat pesat dalam beberapa tahun terakhir. Kehadiran berbagai platform AI seperti ChatGPT, Google Gemini, Microsoft Copilot, dan Meta AI telah mengubah pola masyarakat dalam mencari informasi dan menyelesaikan berbagai pekerjaan. Namun, penggunaan AI yang tidak disertai pemahaman yang memadai berpotensi menimbulkan ketergantungan, kecenderungan menerima informasi secara instan, serta menurunkan kemampuan berpikir kritis pada generasi muda. Oleh karena itu, diperlukan upaya untuk meningkatkan literasi kecerdasan buatan, khususnya pada remaja masjid sebagai generasi penerus yang memiliki peran strategis dalam masyarakat. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk membangun literasi kecerdasan buatan pada remaja masjid melalui pelatihan pengenalan dan pemanfaatan AI. Kegiatan dilaksanakan di Masjid Al Khair Kota Padang dengan melibatkan 35 remaja masjid dari jenjang SD, SMP, dan SMA. Metode yang digunakan meliputi sosialisasi, demonstrasi, praktik langsung, dan diskusi interaktif. Materi yang diberikan mencakup pengenalan konsep dasar AI, penggunaan berbagai platform AI, manfaat dan keterbatasan AI, serta etika penggunaannya. Hasil kegiatan menunjukkan adanya peningkatan pemahaman peserta mengenai konsep, fungsi, manfaat, dan risiko penggunaan AI. Selain itu, peserta menunjukkan kemampuan yang lebih baik dalam memanfaatkan AI secara produktif, kritis, dan bertanggung jawab. Kegiatan ini berkontribusi dalam meningkatkan literasi AI dan kesiapan generasi muda menghadapi perkembangan teknologi digital.
Co-Authors Indira Karina Melladia, Melladia Nadia Astri Wulandari Radiyan Rahim Raecky Meyzal Febrialdo Sayendra Safaria Syaputri Maharani Tika Christy Yusli Yenni