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All Journal Indonesian Journal of Data and Science
Andi Vania Anastasia
Universitas Muslim Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

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Journal : Indonesian Journal of Data and Science

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Spatial Prediction of Stunting Incidents Prevalence Using Support Vector Regression Method Andi Widya Mufila Gaffar; Sugiarti; Dewi Widyawati; Andi Muhammad Kemai Arief Hidayat Paharuddin; Andi Vania Anastasia
Indonesian Journal of Data and Science Vol. 4 No. 2 (2023): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v4i2.68

Abstract

Stunting in toddlers is a major nutritional problem faced by Indonesia, with a high incidence rate occurring in several provinces across the country. This nutritional issue can occur at any age, starting from the prenatal stage, infancy, childhood, adolescence, adulthood, and even in the elderly. To reduce the prevalence of stunting in affected provinces, prevention efforts are essential, including predicting the spread of stunting incidents in each region. Therefore, this research conducted spatial prediction of the prevalence rate of stunting incidents using Machine Learning, specifically Support Vector Machine based Regression. The results of this study produced a prediction model with an RMSE (Root Mean Square Error) value of 0.008689303 and a multiple correlation coefficient of 0.65912721. Based on these findings, the predictive model utilized demonstrated satisfactory performance in predicting the prevalence rate of stunting incidents in each area
Co-Authors Andi Muhammad Kemai Arief Hidayat Paharuddin Andi Widya Mufila Gaffar Dewi Widyawati Sugiarti, Sugiarti