PENGEMBANGAN SISTEM MONITORING TUMBUH KEMBANG ANAK BALITA BERBASIS MOBILE DENGAN EXPLAINABLE RISK-BASED PREDIKSI STUNTING DAN UMPAN BALIK GAMIFIKASI ADAPTIF

Annisa Permata Bunda, Syafrijon Syafrijon, Randi Proska Sandra, Erdisna Erdisna

Abstract


Kekurangan nutrisi pada masa balita, khususnya selama 1000 hari pertama kehidupan memicu gangguan pertumbuhan fisik dan kognitif yang dikenal sebagai stunting. Penelitian ini bertujuan mengembangkan sistem monitoring tumbuh kembang balita berbasis mobile "Tumbuh Cerdas" yang interaktif guna memfasilitasi deteksi dini dan pencegahan stunting. Pendekatan yang digunakan mengintegrasikan model klasifikasi Random Forest, transparansi keputusan berbasis Explainable AI (XAI) menggunakan metode SHAP , serta mekanisme umpan balik gamifikasi adaptif rule-based. Hasil evaluasi menunjukkan model Random Forest mencapai akurasi sebesar 99,18% dalam mengklasifikasikan status gizi balita berdasarkan parameter antropometri. Pengujian fungsional dengan Black Box Testing membuktikan seluruh sistem berjalan sesuai skenario dan data tersinkronisasi secara real-time. Dampak dari inovasi ini adalah terciptanya solusi sistem pendukung keputusan kesehatan digital yang transparan, aman, dan edukatif bagi orang tua serta kader posyandu guna menekan prevalensi stunting secara berkelanjutan.

Keywords


Explainable AI, gamifikasi adaptif, monitoring kesehatan mobile, prediksi stunting, random forest.

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References


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DOI: https://doi.org/10.17509/ijdb.v5i4.102819

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