Data mining is a method that can classify data into different classes based on the features in the data. With data mining, non-performance loan categories can be classified based on data on lending from cooperatives to their members. This study uses K-Nearest Neighbor to classify non-performance loan categories with various distance metric variations such as Chebyshev, Euclidean, Mahalanobis, and Manhattan. The evaluation results using 10-fold cross-validation show that the Euclidean distance has the highest accuracy, precision, F1, and sensitivity values compared to other distance metrics. Chebyshev distance has the lowest accuracy, precision, sensitivity, while Mahalanobis distance has the lowest F1 value. Euclidean and Manhattan distances have the highest reliability values for true-positive and true-negative class classifications. Mahalanobis distance has the lowest reliability value for false-positive class classification, while Chebyshev distance has the lowest value for false-negative class classification
As one the most famous world-class motorcycle racing competition, MotoGP is an event broadcast live on television with millions of viewers on each race. Indonesia, especially the Pertamina Mandalika Circuit, will hold this prestigious racing event in the 19th series of 2022. This event sparks Indonesian netizens' reactions on social media, especially on Twitter. This research aims to analyze the public sentiment and emotional value regarding this event, with the data collected from Twitter social media. With the features of sentiment and emotion values extracted from the contents of this tweet, we use K-means clustering to generate sentiment clusters as targets for the classification using the Random Forest (RF) algorithm. From the evaluation using the 5-fold and 10-fold cross-validation, we get the highest accuracy of 0.99, the highest precision of 0.990175, and the highest recall of 0.99 from the RF model with ten trees configuration. We also get the lowest accuracy, precision, and recall values of 0.96, 0.960934, and 0.96 from the RF models with 15 and 20 trees configuration, with the 10-fold evaluation.
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