Treffer: Analysis of the Classification of Data on the Launch of Apple Mobile Phone Prices in China and Pakistan Using the Decision Tree Algorithm in Python Programming.

This study aims to explain the analysis of data by employing data classification and applying the concept of the Decision Tree Algorithm and programming tools developed using Python programming. This approach serves as a flexible and objective method for data analysis and visualization. In today's world of machine learning, data requires high performance and accurate results when addressing data cases. The data used consists of NoSQL data or datasets in CSV format. These CSV documents contain tables, and the resulting output will be the latest datasets. The process involves data analysis, classification, and categorization of Apple mobile phone products in China and Pakistan to determine whether the quality is high or low based on the launch price of Apple mobile phones. Subsequently, decision tree modeling is built to explain the factors affecting classification and to aid analysis of the launch prices of Apple mobile phone products in China and Pakistan. The results are executed in Python programming, a language distinguished by excellent characteristics for data processing and visualization. The datasets will undergo testing alongside supporting factors in Python programming data modeling, which provides flexibility in modeling, execution, and analysis, thereby enabling problems to be solved effectively and objectively. [ABSTRACT FROM AUTHOR]

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