IMPLEMENTASI CRISP-DM MODEL MENGGUNAKAN METODE DECISION TREE DENGAN ALGORITMA CART UNTUK PREDIKSI LILA IBU HAMIL BERPOTENSI GIZI KURANG - Dita Anies Munawwaroh; Arum Handini Primandari (Delta: Jurnal Ilmiah Pendidikan Matematika, 2022)
LILA is measured in pregnant women to monitor nutritional levels during pregnancy. The classifications in the LILA's measurement are the good nutrition category if the LILA measurement is more or equal to 23.5 cm and the undernutrition category if the LILA measurement is less than 23.5 cm. This study aims to classify LILA based on age, height, weight, blood pressure, hemoglobin level, blood sugar, gestational age, and hip circumference by employing the CRISP-DM methodology. The data used is from May till June 2022 at the Sumber Health Center, Sumber District, Rembang Regency. The decision tree method (decision tree) with the CART algorithm is worked to classify LILA in either the good or poor category. The data is divided into training and testing data by a ratio of 80%:20%. The decision tree method can classify all training data correctly. While evaluating the method with data testing produces values of accuracy, precision, recall, and f1-score, respectively, are 90%, 96%, 92%, and 94%.