ANALISIS POLA SEBARAN FAKTOR RISIKO LINGKUNGAN DENGAN KEJADIAN MALARIA DI WILAYAH KERJA PUSKESMAS TANJUNG TIRAM KABUPATEN BATUBARA

Malaria is an infectious disease caused by the Plasmodium parasite which lives and reproduces in human red blood cells and is naturally transmitted through the bite of female Anopheles mosquitoes. Based on data from the Simalungun District Health Service, there were 955 cases of malaria in 2021 and the highest cases were in the Tanjung Tiram health center working area with 279 cases in 2021. Malaria transmission is influenced by several factors, including parasites, humans, mosquitoes and the environment. Environmental conditions have a big influence on the incidence of malaria, because a bad environment can increase the breeding and breeding of Anopheles mosquitoes. With spatial analysis, a mapping process can be carried out to determine the geographic distribution of potential disease risks and their relationship with existing environmental risk factors. Seeing the fluctuating incidence of malaria, it is necessary to carry out research to determine the distribution pattern and risk of malaria incidence in the working area of the Tanjung Tiram Community Health Center, Batubara Regency. The aim of this research is to determine environmental risk factors and malaria distribution patterns in the Tanjung Tiram health center working area, Batubara Regency. To find out the distribution of environmental risk factors in relation to malaria incidence so that it can provide input for the health service in the context of malaria control activities. Research sampling was carried out using a non-probability sampling method and the results of bivariate data analysis used Chi square.      The results of this research are that there is a relationship between environmental risk factors such as ceilings, wall types, ventilation, wall density, screens on windows, the presence of puddles, gutters and swamps around the house with a p value of 0.000 and depicted in a distribution pattern map. which is able to optimize reducing the incidence of malaria cases.