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All Journal JURNAL SAINS DAN TEKNOLOGI INDONESIA QALAMUNA: Jurnal Pendidikan, Sosial, dan Agama UNM Geographic Journal JURNAL MUQODDIMAH : Jurnal Ilmu Sosial, Politik dan Hummaniora Journal of Advanced English Studies MALLOMO: Journal of Community Service SCIENCE : Jurnal Inovasi Pendidikan Matematika dan IPA MANAJERIAL: Jurnal Inovasi Manajemen dan Supervisi Pendidikan Moestopo Journal of International Relations (MJIR) Edukasiana: Jurnal Inovasi Pendidikan La Ogi : English Language Journal Journal of Community Health Provision Sahabat Sosial: Jurnal Pengabdian Masyarakat Jurnal Pustaka Dianmas International Journal of Sustainable Applied Sciences (IJSAS) Visioner : Jurnal Manajemen dan Bisnis Indonesian Journal of Applied Technology and Innovation Science
Nadirah, Nadirah
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Comparison of Machine Learning Algorithm Performance for Toddler Stunting Prediction Anjani, Sophia; Nadirah, Nadirah; Iskandar, Nur Qistina Binti Mohamad; Zinky, Mujahid; Atmanagara, Ramzy Hammad; Syahbani, Rayhan; Marzuq, Muhammad; Fitri, Muhammad Anis; Khalis, Nur; Khairullah, Fajar Abiyyu; Alfarizy, Fawwaz Zanuar; Kalam, Ahmad Fahiq Zauqol; Aldi Setiawan
IJATIS: Indonesian Journal of Applied Technology and Innovation Science Vol. 3 No. 1 (2026): IJATIS February 2026
Publisher : Institut Riset dan Publikasi Indonesia (IRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/ijatis.v3i1.2503

Abstract

Stunting is a chronic nutritional issue in toddlers that has long-term effects on children's physical growth and cognitive development. This study aims to compare the performance of four machine learning algorithms, namely Support Vector Machine (SVM), Random Forest (RF), Multilayer Perceptron (MLP), and Logistic Regression (LR), in classifying the nutritional status of toddlers. The research stages included data preprocessing, data division into training and test sets, model training, and evaluation using accuracy, precision, recall, F1-Score, a confusion matrix, and Area Under the Curve (AUC). The evaluation results showed that Random Forest achieved the best performance, with an accuracy of 94%, as well as precision, recall, and F1-score values above 90%, and an AUC value close to 1.00 across all nutritional status classes. This was followed by the MLP algorithm in second place, with an accuracy of 93.29%. The main contribution of this study is the identification of a high-performing, stable model for large-scale stunting detection, providing a strong foundation for developing decision-support systems for early detection in the public health sector.
Edukasi Perawatan Luka Diabetes Kepada Masyarakat Dalam Upaya Pencegahan Komplikasi Adiaksa, Baso Witman; Sriyanti, Febri; Hartati, Hartati; Nadirah, Nadirah; Pannyiwi, Rahmat
Sahabat Sosial: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2026): Sahabat Sosial: Jurnal Pengabdian Masyarakat (Maret)
Publisher : Asosiasi Guru dan Dosen Seluruh Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59585/sosisabdimas.v4i2.1021

Abstract

Diabetes mellitus is a chronic disease that often leads to complications, one of which is diabetic wounds, which carry a high risk of infection and amputation if not properly cared for. Poor public knowledge and skills regarding diabetic wound care are major factors contributing to further complications. This Community Service activity aims to improve the community's knowledge, attitudes, and skills in diabetic wound care as an effort to prevent complications. Implementation methods included health education, diabetic wound care demonstrations, hands-on practice, and evaluation through pre- and post-tests. The results of the activity indicated an increase in community knowledge and skills regarding diabetic wound care and infection prevention. Education on diabetic wound care is expected to reduce the risk of complications and improve the quality of life of people with diabetes.
Co-Authors Adiaksa, Baso Witman Alaydrus, Anwar Aldi Setiawan Alfarizy, Fawwaz Zanuar Amalia Amalia Andi Nafisah, Andi Andi Sadapotto Anjani, Sophia Aprillia, Sabila Asri asri Asrifan, Andi Aswani, Irma Atmanagara, Ramzy Hammad Azizah, Shela Nurul Bada, Sitti Sastriana Bangun Muljosukojo Broto, Mani Festati Buhari Buhari Ecca, Suleha Evri, M Fitri, Muhammad Anis Haedar Haedar, Haedar Hartati Hartati Heriyati, Heriyati Hernaeny, Ulfah Indrawati Indrawati Iskandar, Nur Qistina Binti Mohamad Kalam, Ahmad Fahiq Zauqol Khairullah, Fajar Abiyyu Khalik, Suhartini Khalis, Nur Kurniana Bektiningsih L, Syahrir Lanta, Jumiati M., Usman Manda, Ibrahim Marzuq, Muhammad Muhammad Hanafi mulyono, Sidik Muslimin Muslimin Naza, Kasyifatun Naza, Kasyifatun Naza Oracle, Yusuf Nirendra Pannyiwi, Rahmat Prabandari, Sherlly Merisa Tri Pramasti, Aliza Prasetyo , Ridho Jun Prasetyo Prasetyo Ramadhani, Salwah Musti Rasyid, Rustam Efendy Ridwan, Ridwan Rina Hidayati Pratiwi Sadly, M Sagit Hartono Santoso, Sagit Hartono Sam Hermansyah Sari, Valentina Permata Sartika Sartika Simanjuntak, Parulian Siregar, Julinda Sri Fitri Ramadhani Sriyanti, Febri Suardi Zain, Suardi Suhartono Suhendra Suhendra Sultan, Salim Surya, Jimmy Syahbani, Rayhan T Syamsu Tahir, M. Hijaz Tang, Syamsu Teguh Hariyanto, Teguh Vargheese, K. J. WIJAYANTI, EVA Yulini Rinantanti Zinky, Mujahid