When compared to K-Mode Algorithm, a Novel K-Means Algorithm Has Improved Accuracy for Corona Crisis Prediction among Small Businesses

Abstract

Aim: The purpose of this study is to Predict the Concussion of  Corona Crisis over Small Businesses using Novel K-Means Algorithm Comparing K-Mode Algorithm. Materials and Methods: Novel K-Means Algorithm with sample size = 110 with G power (value =0.6) and K-Mode Algorithm with sample size = 110 were evaluated many times to predict the efficiency percentage. Results: Novel K-Mean algorithm has better accuracy (66.50%) when compared to K-Mode algorithm accuracy (54.60%). The results achieved with significance value p=0.884 (p>0.05) shows that two groups are statistically insignificant. Conclusion: K-Means algorithm performed significantly better than the K-Mode algorithm.