Abstract
Cases of leptospirosis in Indonesia mainly occur in areas that often experience floods and areas where the majority of its citizens work as farmers. Special Region of Yogyakarta (DIY) was the province with the most leptospirosis cases in Indonesia in 2011. In 2010-2011 an extraordinary event (KLB) of leptospirosis occurred in Bantul district and in 2014 the number of leptospirosis cases in Bantul district increased by 76 cases.. Based on Kementerian Kesehatan report, data shows that there has been an outbreak of leptospirosis in Bantul , so in addition to epidemiological data necessary case information is also needed to determine the geographic case risk factors and mitigation efforts.In the processing of digital maps for GIS , often found important objects that are not appropriate in its processing can not even be excluded because of uncertainty owned. Applications are made in this study was built and designed by the architectural Tsukamoto fuzzy inference method for handling uncertainty. The results of the application is the visualization of the spread of the disease leptospirosis vulnerability maps based determinants that also involves uncertainty factors that will be resolved with the Tsukamoto fuzzy inference method for use as detection and prevention against the spread of disease leptospirosis in the future
Highlights
Abstrack–Cases of leptospirosis in Indonesia mainly occur in areas that often experience floods and areas where the majority of its citizens work as farmers
In 2010-2011 an extraordinary event (KLB) of leptospirosis occurred in Bantul district and in 2014 the number of leptospirosis cases in Bantul district increased by 76 cases
Based on Kementerian Kesehatan report, data shows that there has been an outbreak of leptospirosis in Bantul, so in addition to epidemiological data necessary case information is needed to determine the geographic case risk factors and mitigation efforts.In the processing of digital maps for GIS, often found important objects that are not appropriate in its processing can not even be excluded because of uncertainty owned
Summary
Leptospirosis merupakan penyakit zoonosis yang berkembang luas di seluruh dunia, baik di negara maju maupun berkembang, dan menyerang lebih dari 160 spesies mamalia. Pentingnya informasi wilayah geografi pada saat terjadi KLB leptospirosis tersebut menuntut adanya suatu sistem yang dibangun untuk memberikan informasi yang akurat terhadap penyebaran kasus tersebut berdasarkan data atribut dan data spasial yang mendukung. Suatu daerah dinyatakan rawan penyebaran penyakit leptospirosis ditentukan oleh beberapa faktor, diantaranya adalah faktor lingkungan fisik meliputi : keberadaan genangan air, curah hujan, jarak rumah dengan selokan dan kondisi selokan yang buruk. Berdasarkan faktor-faktor penentu tersebut, keberadaan genangan air, curah hujan, jarak rumah dengan selokan serta kondisi selokan yang buruk merupakan contoh objek yang memiliki ketidakpastian, yaitu objek yang tidak dapat ditentukan secara diskrit tingkat kuantifikasinya [6]. Dari hasil penggunanan metode inferensi fuzzy tersebut dibangun implementasi pemetaan untuk informasi penyebaran leptospirosis, serta penggunaannya sebagai deteksi dini dan penanggulangan KLB penyakit leptospirosis di Kabupaten Bantul. Keunggulan lainnya adalah dengan implementasi sistem yang berbasis web masyarakat dan pihak-pihak yang terkait akan lebih mudah mengakses informasi tersebut
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