Maukar, Anastasya Lidya
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Expert System Application for Determining Toddler Nutrition Status Using the Mamdani Fuzzy Method Kacung, Slamet; Vitianingsih, Anik Vega; Sufianto, Dani; Maukar, Anastasya Lidya; Marisa, Fitri
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 12, No 3 (2024)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v12i3.75976

Abstract

Malnutrition is still a national issue that affects many regions in Indonesia. The use of the Kartu Menuju Sehat (KMS) is considered less than optimal because of frequent recording errors due to the loss of the card, making it impossible to properly monitor the nutritional status of toddlers. In addition, people, especially parents, want to know whether their toddler's diet is adequate or not. Based on these problems, an application is needed to determine the nutritional status of toddlers. This research is important to assist medical personnel in assessing the nutritional status of toddlers and can be relied upon for accuracy through an expert system application. This research aims to develop an expert system application that utilizes the Fuzzy Mamdani method to identify the nutritional status of toddlers based on weight, age, height, and arm circumference parameters. The stages in this research include identifying parameters that affect nutritional status through sources of expertise from doctors, determining sets and rules in the fuzzy method, system implementation, system evaluation, and optimization. The results stated that the Fuzzy Mamdani method has an accuracy value of 90.2% in detecting the nutritional status of toddlers. The acceptance test of the application display assessment resulted in 92.5%, the ease of use of the application was 85.83%, and system analysis resulted in 90.83%.