KLASIFIKASI BINTANG KATAI DAN RAKSASA DENGAN METODE K-NN DAN DECISION TREE
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Abstract
Stars are celestial objects that emit light at night. Stars have several properties such as brightness and temperature based on color. These properties can be used for classification and the most commonly used are the Harvard classification and the Morgan-Keenan classification. Both classifications can be used to classify the size of a star as a dwarf or giant star. With so many stars to classify, manual classification can take a lot of time. Therefore, in this study, the K-NN and Decision Tree algorithms are used to determine the accuracy of the classification of dwarf and giant stars. The dataset used in this study comes from the Gaia DR3 and Hipparcos and Tycho catalogues. A total of 25182 rows or records were used. The composition of experiments performed in this study is 80% training data and 20% test data (80/20) and 60% training data and 20% test data (60/20). Experiments were conducted 10 times by randomizing datasets for training data and test data. The average accuracy value obtained with Decision Tree is 81.5% for 80/20 composition and 60/40 composition. Meanwhile, with K-NN, the average accuracy value is 80.9% for the 80/20 composition and 81.1% for the 60/40 composition.
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