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All Journal International Journal of Electrical and Computer Engineering Jurnal Teknoinfo Petir Kilat INTEK: Informatika dan Teknologi Informasi Jurnal Analis Medika Biosains (JAMBS) Journal of Information Systems and Informatics TERANG : Jurnal Pengabdian Pada Masyarakat Menerangi Negeri Jurnal E-Komtek JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Journal Social Science And Technology For Community Service
Rakhmadi Irfansyah Putra
Institut Teknologi PLN
Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Other

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Penguatan Kompetensi Digital Berstandar Microsoft Office Specialist (MOS) bagi Guru MA Annida Al-Islamy Luqman; Hendra Jatnika; Rakhmadi Irfansyah Putra; Yudhi Setyo Purwanto; Ocha Nia Martcya Situmorang; M. Rafif Soniansyah; Fakhri Faros
JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Vol. 7 No. 1 (2026)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/jurpikat.v7i1.3006

Abstract

This Community Service program aims to strengthen the digital competence of teachers at MA Annida Al-Islamy through Microsoft Office Specialist (MOS) certification preparation. The primary issue identified was the basic level of office application mastery, which fell below global standards. The method involved preliminary surveys, needs analysis, material preparation, hands-on technical workshops based on participant interests (Word, Excel, PowerPoint), and evaluation. Results from 15 participants showed significant success, with an average perceived competence improvement of 92.4%. Additionally, over 85% of technical challenges during trivia sessions were answered correctly. Program outputs, including digital modules and video tutorials, were provided to support sustainable self-paced learning. This training effectively enhanced educators' technical readiness and confidence in meeting international competency standards.
Toddler Nutritional Status Classification For Early Detection Of Malnutrition Using Xgboost: A Case Study Of “West Lombok Regency Nazwa, Lalu Muhammad Risgan; Putra, Rakhmadi Irfansyah; Zaetun, Siti
Jurnal Analis Medika Biosains (JAMBS) Vol. 13 No. 01 (2026): JURNAL ANALIS MEDIKA BIOSAINS (JAMBS)
Publisher : Poltekkes Kemenkes Mataram

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Abstract

Malnutrition among toddlers remains a critical challenge in West Lombok Regency, with a stunting prevalence reaching 32.7% in 2022. This study aims to develop a classification system for toddlers' nutritional status using XGBoost, with class imbalance handled through SMOTE. The dataset consists of 788 toddlers aged 24–59 months from 12 villages in West Lombok District. Preprocessing steps include filtering biologically invalid values based on WHO criteria, normalization using MinMaxScaler, and feature engineering through anthropometric ratios such as weight-for-height (WHZ) and height-for-age (HAZ). The data is split using a stratified approach with an 80:20 ratio, and SMOTE is applied exclusively to the training set. Evaluation using macro F1-score and minority class recall shows that XGBoost achieves an F1-score of 94.3% and a recall of 92.1% for severe malnutrition, significantly outperforming Random Forest (89.7%), KNN (84.2%), Naïve Bayes (81.5%), and Decision Tree (83.8%). A Streamlit-based prototype was also developed as a practical interface for community health workers (posyandu cadres), featuring prediction tools, distribution visualizations, and automated referral recommendations. The results demonstrate that XGBoost combined with SMOTE is effective in improving early detection of minority malnutrition cases in imbalanced populations, supporting stunting reduction targets.
Co-Authors Abd. Rasyid Syamsuri Alwi Muhammad Amanda T Supriadi Andi Dahroni Andi Muhammad Fadel Omar Pasha Arfani Lovina Br. Stendel Budi Prayitno Dahroni, Andi Duliades Mirsal Eka Putra Eka Putra Fakhri Faros Firmansyah, Filan Hendra Jatnika luqman M. Rafif Soniansyah Mohamad Tanwirul Akbar Muhammad Fadli Pratama Muhammad fadli Prathama Muhammad Fadli Prathama Muhammad Zaid Al-Khair Nazwa, Lalu Muhammad Risgan Ocha Nia Martcya Situmorang Palupiningsih, Pritasari Purwanto, Yudhi Setyo Rahman, Adith Aulia Rakhmat Arianto Siti Zaetun, Siti Sudirman, M Yoga Distra Tiara Kusuma, Dine Yessy Fitriani Yoga Distira Sudirman Yudhi Setyo Purwanto Yudi Setyo Purwanto