Pemetaan Penyebaran Tingkat Kepatuhan Masyarakat dalam Menggunakan Masker di Pasar Tradisional Kota Surabaya dengan Metode Hot Spot Analysis (Getis-Ord Gi*)

Stefanus Benhard(1*), Silvia Rostianingsih(2), Resmana Lim(3),


(1) Program Studi Informatika
(2) Program Studi Informatika
(3) Program Studi Teknik Elektro
(*) Corresponding Author

Abstract


According to a study conducted to see the level of effectiveness for using masks in case study by [1]), explains that if the use of masks has a positive impact on resulting transmission. Research conducted invloving cloth masks, surgical masks and Filtering Face Piece 2 (FFFP2) masks, with output results that the three types of masks show stable resuts to protect all the time and doesn’t depend on persons activities. At this moment, CoronaVirus Disease 2019 (COVID-19) is one of the disease that causes global pandemic and creates several new clusters, especially traditional market clusters. Traditional market is one of the driving wheels that can pursue society economy. In that case, there needs to be serious attention in taking self care by using protective equipment at least a mask. This mapping of the distribution level people for using masks combines many aspect such as map visualization, website information system and image processing for masks detection. The use of image processing plays an important role in the mapping system, that’s because the processing of manually counting people who are not using masks will take a lot of labor in its implementation. Image processing used is face mask detector and people counter with 82% average accuracy at the implementation process. The hot spot analysis mapping method cannot be used in static data types such as traditional market, because it will gave the same result in the same density of market location from day to day. The most exact method for the data type that compares the values of not using mask to the entire traditional market is Inverse Distance Weighted (IDW) Interpolated Method. Testing results using the new method show that there is a change for highest or lowest not using masks by people at the traditional market. This method only calculates the value and not calculate distance between each market.

Keywords


Hotspot Analysis; Inverse Distance Weighted; Geographic Information System; Traditional Market; face mask

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