Prediksi Kanker Payudara di Indonesia menggunakan Algoritma Support Vector Machine dan Regresi Logistik

Abstract

Breast cancer is one of the leading causes of death among women worldwide, including in Indonesia. Early detection and risk factor analysis are crucial in the efforts toward more effective prevention and treatment. This study aims to identify risk patterns of breast cancer through the analysis of clinical patient data. The dataset includes several clinical variables such as age, menopausal status, tumor size, cancer grade, the number of affected lymph nodes, and hormone status (progesterone and estrogen). The analytical method used is descriptive and exploratory to uncover common patterns within the data. The results indicate that age, menopausal status, and tumor size show a significant correlation with the level of breast cancer risk. These findings are expected to contribute to the development of decision support systems in breast cancer diagnosis and promote greater public awareness of the importance of early detection and regular breast health monitoring.