CLUSTERING HIV/AIDS DISEASE USING K-MEANS CLUSTERING ALGORITHM - Sari, Indah Purnama; Hariani MD, Pipit Putri; Al-Khowarizmi, Al-Khowarizmi; Ramadhani, Fanny; Sulaiman, Oris Krianto; Satria, Andy; Manurung, Asrar Aspia (Proceeding International Seminar of Islamic Studies, 2024)
The HIV (Human Immunodeficiency Virus) is an infection-causing virus that targets the immune system, making it more vulnerable to illness and infection. East Java (33,043), Papua (25,586), West Java (24,650), and Central Java (18,038 persons) all had more HIV/AIDS infections in 2017 than DKI Jakarta (46,378), which was followed by East Java (33,043), West Java (24,650), and a smaller number—25,586—in Papua. Nationally, West Java is still among the four provinces with the highest HIV/AIDS cases. This shows that HIV/AIDS has become a threat to the wider community because in addition to threatening the lives of sufferers, this disease is at risk of transmission that will increase. The increase in HIV/AIDS cases can be a problem in the psychology of the sufferer, because this disease can have a negative impact in the form of physical, psychological, social and spiritual problems that cause PLWHA (People with HIV AIDS) to live a stressful life. In this study, calculations were carried out using the K-Means algorithm with the Optimize Parameters Grid on data on the spread of HIV / AIDS cases in 2019-2021 sourced from the West Java Provincial Health Office. K-Means is one of the algorithms in data mining that can be used for grouping / clustering of data. The data used in this study were 971 records. The purpose of this study was conducted to determine the cluster of t h e spread of HIV/ AIDS as an effort to assist the government in reducing the number of HIV / AIDS cases in West Java province. The results o f this study are comparing DBI with the K-Means method from k-2 to k-20 contained in the table above, it can be seen that the cluster that is close to 0 is k-2, with a DBI value of 0.414. Because the value of k-2 is the smallest value compared to other k, it can be concluded that k-2 with a value of 0.414 which is closest to 0 is the best cluster result.