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Sirait, Reni Aprinawaty
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Humanities Dentistry Education Environmental Science Health Professions Immunology & microbiology Medicine & Pharmacology Neuroscience Nursing Public Health Veterinary Other

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Machine Learning Models Prediction Medication Nonadherence Risk in Type 2 Diabetes: A Systematic Review Hulu, Victor Trismanjaya; Hulu, Yusuf Panserito; Telaumbanua, Kharis Meiwan K; Sirait, Reni Aprinawaty; Zebua, Arianus; Simatupang, Rumiris
Jurnal Keperawatan Priority Vol. 9 No. 1 (2026)
Publisher : Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jukep.v9i1.7859

Abstract

The prediction of medication nonadherence among patients with T2DM can be improved in accuracy and speed using machine learning (ML). This study aimed to develop an ML model to predict the risk of medication nonadherence among patients with T2DM. Methods, inclusion criteria comprised English-language, open-access journal articles published between 2020 and 2025 that developed and validated ML–based prediction models, including ensemble methods, gradient-boosting models, SVMs, and neural networks. Exclusion criteria included review articles, non-English papers, studies published before 2020, studies lacking prediction model development or validation, and studies using only traditional statistical methods, such as logistic regression. The article search was conducted in PubMed, Scopus, ScienceDirect, and Google Scholar. Prediction Model Risk of Bias Assessment Tool (PROBAST) to assess the methodological quality and usefulness of the qualified studies. This narrative synthesis examines the characteristics of ML-based prediction models, their performance, and the factors that predict adherence among patients with T2DM. The papers were sourced from various scientific journal databases. The results show that cross-sectional and cohort studies were among the research designs used in the five papers reviewed. The AUROC of the internal test was 0.782, and the AUROC of the external test was 0.771. The learned-feature classification model achieved an average accuracy of 79.7%. Among these algorithms, the AUC of the best-performing algorithm was 0.866 ± 0.082. The SVM classifier outperformed the others, achieving a recall of 0.9979 and an AUC of 0.9998. The conclusion indicates that predictive capacity is influenced by clinical metrics and the number of prescribed medications.
Persepsi dan Hambatan Orang Tua dalam Mengikuti Program Pendidikan Pengelolaan DA di Fasilitas Primer: Studi Fenomenologi di Puskesmas Secanggang Afriyanti, Dhewi Sri; Wasliati, Balqis; Karo–karo, Tati Murni; Herlina, Herlina; Sirait, Reni Aprinawaty
PubHealth Jurnal Kesehatan Masyarakat Vol. 4 No. 3 (2026): Edisi Januari
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/pubhealth.v4i3.1580

Abstract

Dermatitis atopik (DA) merupakan penyakit kulit kronis pada anak yang memerlukan pengelolaan jangka panjang dan keterlibatan aktif orang tua. Program pendidikan orang tua di fasilitas kesehatan primer menjadi strategi penting dalam meningkatkan kemampuan keluarga mengelola DA. Penelitian ini bertujuan untuk mengeksplorasi persepsi dan hambatan orang tua dalam mengikuti Program Pendidikan Pengelolaan DA di Puskesmas Secanggang. Penelitian menggunakan pendekatan kualitatif dengan desain fenomenologi. Data dikumpulkan melalui wawancara mendalam terhadap 10 orang tua yang memiliki anak usia 0–5 tahun dengan diagnosis DA dan dianalisis menggunakan analisis tematik. Hasil penelitian menunjukkan bahwa orang tua memiliki motivasi tinggi untuk mengikuti program, pengalaman positif selama proses edukasi, serta memaknai program sebagai, meskipun motivai tinggi dan sarana pemberdayaan dalam pengelolaan DA anak banyak hambatan berupa keterbatasan waktu kerja, jarak ke Puskesmas dan kurangnya dukungan keluarga. Program pendidikan berkontribusi terhadap peningkatan pengetahuan, perubahan perilaku perawatan, dan penurunan kecemasan orang tua.
Co-Authors Abdul Wahab Afriyanti, Dhewi Sri Agus Romendra Anita Gandaria Purba Anita Gandaria Purba Anita Oktaviana Siregar Anita Sri Gandaria Purba Arfah May Syara Arum Puspita Sari Bambang Sumantri Binarwan Halim Br Ginting, Luci Riani Defacto Firmawati Zega Dewi Susanti Dewi Susanti Dian Anggriyanti Elda Yusefni Felix Kasim Ginting, Desi Deria Yosepha Handayani, Sri Hariati Hariati Herlina H Herlina Herlina Holan Dianju Melva Meinaria Sitanggang Hulu, Victor Trisman Jaya Hulu, Yusuf Panserito Hutapea, Rismawati Imelda J Verawati Lubis Inka Ardiany Ginting Irma Nurianti Judika Silaban Julianto Julianto Kardina Hayati Karokaro, Tati Murni Kuat Sitepu Kurnia, Anggia Luci Riani Br Ginting Meria Turnip Meria Turnip Muhammad Akhyar Nuary Munthe, Novita Br Ginting Murti Sri Dewi Nining Setiawati Novrika Silalahi Nurhamidah Pohan Nursaputri, Ika Plorita Situmorang Rahmi Andrita Yuda Rahmi, Nurfadhilah Rambey, Harris Reh Malem br Karo Riady Suranta Sinuhaji Riri Safitri Romendra, Agus Rotua Sumihar Sitorus Silaban, Maria Silalahi, Novrika Silvia Indriani Simatupang Simatupang, Rumiris Sinaga, Suharni Pintamas Sinambela, Megawati Singarimbun, Nurbaiti Br Sinurat, Jhon Patar Sitanggang, Loym Ristumerry Sri Dalianti Telaumbanua, Kharis Meiwan K Victor Trismanjaya Hulu Vina Novianti , Wasliati, Balqis Widya Putri Lubis Yanti, Dian Anggri Yohanna Adelina Pasaribu Zebua, Arianus Zul Asdar Putra Samura