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Title: The book Optimization performance results in combination of algorithm C4.5 and Naive Bayes use Particle Swarm Optimization for early detection of nutritional Status determination on toddlers Author: Jon Indrison Molina & Soetanto Day Page: xvi, 120 pgs, Uk: 14x20 cm Mold: June 2021 Synopsis: Nutritional status assessment plays great role in children's nutritional monitoring. When the assessment of nutritional status is conducted precisely and accurately, the existence of sign or symptoms of growth disorders and child development can be prematurely known so that it can be taken a stage and prevention in the effort to improve nutritional status in toddlers. As well as nutritional problems occurring can be minimized. For that., Then the nutritional status determination in toddlers should be done quickly and accurately. To get an accurate method then it needs to be made a comparison between existing methods to obtain a method that has high accuracy, so that in this research author compares the algorithm C4.5 and Na.ve Bayes. From the comparison of this algorithm is obtained, the C4.5 algorithm has higher accuracy than Na Swarm Bayes algorithm so that the selected C4.5 algorithm to optimize again its accuracy level using algorithm Particle Swarm Optimization (PSO). C4.5 Algorithm is the highest accuracy value algorithm on C4.5 classification model with accuracy rate 72.13%, after optimizing with the accuracy level Optimization increased to 80.04%.

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LanguageBahasa Indonesia

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