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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Pengabdian Pada Masyarakat METHABDI
Muhammad Taufiq Rustam
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Religion Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Immunology & microbiology Languange, Linguistic, Communication & Media Medicine & Pharmacology Physics Public Health

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Penerapan Internet of Things (IoT) Dasar dalam Sistem Monitoring Lingkungan Sekolah Serta Smart Classroom di SMK PAB 8 Sampali Medan Alfina, Ommi; Syahputri, Nita; Ananda Pratama; Muhammad Taufiq Rustam; M. Safii; Jamaluddin, Jamaluddin
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 5 No 2 (2025): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methabdi.Vol5No2.pp259-265

Abstract

The development of Internet of Things (IoT) technology has opened up significant opportunities for improving the efficiency and effectiveness of learning systems as well as school environmental management. This community service activity aims to provide basic IoT training and implement an environmental monitoring system and smart classroom at SMK PAB 8 Sampali Medan. The implementation method includes three main stages: (1) socialization of basic IoT concepts and their application in the educational field, (2) practical training for creating simple IoT devices based on temperature, humidity, and light sensors, and (3) implementation of a school environmental monitoring system integrated with a web-based platform and a real-time dashboard. In addition, participants were also introduced to the concept of a smart classroom, where classroom conditions can be monitored and controlled automatically through the developed IoT system. The results of the activity showed an 85% increase in participants' understanding of basic IoT concepts and their ability to independently design environmental monitoring system prototypes. This program has had a positive impact on enhancing digital literacy, technical skills, and school readiness for IoT-based educational digital transformation.
Hybrid Feature Selection dan Ensemble Learning untuk Klasifikasi Risiko Stunting Anak di Indonesia Alfina, Ommi; Nita Syahputri; M. Safii; Muhammad Taufiq Rustam
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp107-111

Abstract

Stunting is a chronic nutritional problem that remains a major public health issue in Indonesia. This study aims to develop a classification model for stunting risk in children using a combination of hybrid feature selection and ensemble learning methods. The dataset used is derived from socio-economic and health data obtained from the Central Statistics Agency and open datasets. The research method includes data preprocessing, feature selection, model development using Random Forest and Gradient Boosting combined with a Voting Classifier, and evaluation using accuracy, precision, recall, F1-score, and ROC-AUC metrics. The results show that the proposed model achieves high performance with accuracy reaching 98% and ROC-AUC close to 1. The hybrid feature selection successfully improves model efficiency by selecting relevant features. This study demonstrates that the integration of feature selection and ensemble learning can produce an accurate and interpretable model for early detection of stunting risk.
Co-Authors Alfina, Ommi Ananda Pratama Jamaluddin M. Safii Nita Syahputri Syahputri, Nita