Determining Factors Affecting Mother's Decisions in Providing and Selecting Infant Formula Using Data Mining - Decision Support System Collaborative
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Abstract
Indonesia is one of the countries with a population of around two hundred million people, ranking fourth after the United States in the list of the most populous countries in the world. According to data from the Central Statistics Agency (BPS), the birth rate is projected to reach 4.45 million people in 2022, an increase of 0.22% from the previous year, which was 4.45 million people. According to the 2007 Indonesian Demographic and Health Survey (IDHS), the rate of exclusive breastfeeding in Indonesia was only 32%. Factors such as maternal health, infant health, and formula milk promotions influence mothers' decisions to use formula milk. The availability of numerous formula brands complicates the decision-making process, with each brand offering different nutritional claims. This study employs the K-Medoids clustering algorithm to analyze factors affecting mothers' choices in formula feeding and the TOPSIS method to determine the most suitable formula for infants aged 0-6 months. The research involves clustering data from a questionnaire distributed to 100 mothers in the Solo Raya region into five categories: maternal health, maternal employment, formula promotion, infant health, and breastfeeding education. Results indicate that maternal health is the most influential factor, followed by infant health, maternal employment, and formula promotion. Lack of breastfeeding education does not significantly influence formula choice. The TOPSIS method, applied to evaluate 10 formula brands against six nutritional criteria, identifies Lactogen 1 as the best formula for infants aged 0-6 months with a highest value of 2.777104826. This data-driven approach provides a clear, systematic method for selecting an appropriate formula based on specific nutritional needs.
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