Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal KREATIF: Jurnal Pengabdian Masyarakat Nusantara International Journal of Electrical and Intelligent Engineering
Andrik Sunyoto
Universitas Panca Marga
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Law, Crime, Criminology & Criminal Justice

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

Found 2 Documents
Search

 1 
Pemberdayaan Posyandu Melalui Digitalisasi dan Penguatan Kapasitas Kader dalam Pencegahan Stunting di Desa Jabung Sisir Ahmad Izzuddin; Nuzul Hikmah; Agustina Widayati; Yustina Suhandini Tj; Ira Aprilia; Andrik Sunyoto; Dyah Ariyanti; Faridahtul Jannah; Noer Fika Dita; Muhammad Hasan Fathul Arifin; Ali Masykur Ibrahim
KREATIF: Jurnal Pengabdian Masyarakat Nusantara Vol. 5 No. 1 (2025): Jurnal Pengabdian Masyarakat Nusantara
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/kreatif.v5i1.9272

Abstract

Stunting is a serious health issue in Indonesia, with a national prevalence of 21.6 percent. Probolinggo Regency in East Java also records a high prevalence rate, reaching 17.3 percent. The main factors contributing to stunting are limited access to health services and nutrition. The Posyandu (Integrated Health Post) plays a crucial role in prevention efforts but faces challenges in management and cadre skills, particularly in data recording and nutritional status measurement. Jabung Sisir Village in Probolinggo Regency was selected as the community partner for empowerment through a program of Posyandu digitalization and cadre capacity building. The aim of this activity is to improve cadre literacy on stunting and to provide an effective digital reporting system to support prevention and control efforts. The implementation method consisted of cadre training on stunting literacy, anthropometric techniques, effective communication, and the use of a web- and Android-based Posyandu Information System. The program was followed by cadre mentoring as well as evaluation through pre-tests, post-tests, and periodic monitoring. The results showed an increase in cadre knowledge, anthropometric measurement skills, and the ability to use digital systems for data recording and reporting. These findings highlight that Posyandu digitalization can strengthen cadre capacity in stunting prevention while serving as an innovative model for enhancing community-based health services.
Android-Based Weed Identification and Herbicide Recommendation Using Convolutional Neural Networks Ahmad Izzuddin; Ryan Prayuga Ardiansyah; Andrik Sunyoto; Dyah Ariyanti; Ira Aprilia
International Journal of Electrical and Intelligent Engineering Vol 1, No 2 (2025)
Publisher : Department of Electrical Engineering Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ijeie.v1i2.40594

Abstract

Weed infestation reduces crop yield and quality, while inappropriate herbicide selection often limits effective control. This paper presents the design and implementation of an Android-based decision-support application for weed identification and herbicide recommendation using a smartphone camera. Weed images are classified using a lightweight Convolutional Neural Network with a MobileNetV2 architecture optimized for mobile deployment. Herbicide recommendations are generated using the Cosine Similarity method to associate identified weed characteristics with suitable control agents. The system is modeled using the Unified Modeling Language (UML) to ensure modularity and scalability. Experimental results show that the proposed CNN model achieves a classification accuracy of 96%. The integrated on-device image acquisition and intelligent recommendation enable practical field deployment, providing an efficient tool to support weed management decisions.
Co-Authors Agustina Widayati Ahmad Izzuddin Ali Masykur Ibrahim Dyah Ariyanti Faridahtul Jannah Ira Aprilia Muhammad Hasan Fathul Arifin Noer Fika Dita Nuzul Hikmah Ryan Prayuga Ardiansyah Yustina Suhandini Tj