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Face recognition is a highly active research topic in pattern recognition and computer vision, with numerous practical applications. Face recognition can provide the most natural interaction experience similar to the way humans can recognize others. This paper presents a performance comparison of various machine learning approaches and feature extr...
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... workings of data validation assigned to the k-fold cross-validation method are as follows: For data that has passed the feature recognition and classification stage, k-fold cross-validation divides the data into k folds of the same size and does not overlap for the training and testing process. Figure 3 is an example of how data is divided by applying 5-fold cross-validation ...
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Addressing the problems of manual dependence and low accuracy of traditional building electrical system fault diagnosis, this paper proposes a novel method, which is based on random forest optimized by improved sparrow search algorithm (ISSA-RF). Firstly, the method utilizes a fault collection platform to acquire raw signals of various faults. Seco...
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... This is due to problems in studying the relationship of interest between feature variables and target variables [7]. Classification is one part of the data mining method to find functions and models that distinguish the class of an object whose label is not known [8] [9]. In fulfiling this goal, the classification forms a model that can distinguish a set of data into different classes based on certain functions and rules. ...
Utilization of historical data into new knowledge can increase added value for its users, including Mitra Setia Cooperative (KMS) which has debtor data that is not utilized. “Not Paid Off” potentioal of debtors cannot be detected as early as possible. In this study using the Naive Bayes algorithm in classifying the feasibility of prospective debtors based on the classification of "Paid Off" and "Not Paid Off" based on parameter of Age, Sex, Amount of Loan, Occupation, Income, and Repayment Period. The research stages consist of (1) Research Initiation, (2) Data Selection, (3) Data Preprocessing, (4) System Design, (5) Program Implementation and (6) Program Testing. The purpose of this study is to minimize the increase in bad loans by implementing the Naive Bayes method in the application of the assessment of prospective debtors. The final result is a debtors prospective assessment application at Mitra Sejahtera Cooperative with an accuracy rate of 86%
