Purworejo is one of the potential area that could be experiencing landslides, because the geomorphological conditions which are included in Menoreh Hills are geographically sloping to very steep. Based on the Indonesian Disaster Information Data (DIBI) and the National Disaster Management Agency (BNPB) in the last five years from 2014 to April 2019 there have been 64 landslides in Purworejo. The research on landslide vulnerability mapping has been done with various spatial modeling methods, one of them is using Information Value Model (IVM). There are four landslide factors arranging the model, such as elevation, slope, slope direction and vegetation index (NDVI). The purpose of this research is to determine the most influence factors towards landslide vulnerability levels thorugh remote sensing data. Multiple regression analysis is used to determine the most influential factors. In this research, dependent variable represented by eight landslide factors, and the independent variable is vurnerability level of landslide in Purworejo. The results of this study explain that the predictor variables that most influence the occurrence of landslides in Purworejo are elevations with regression values that are quite dominant among other variables.
Abstract. The need for presenting information in maps is increasingly high in various scientific fields. All scientific fields need to present effective data for decision making. Good decision making based on maps requires good understanding but not all scientific fields are familiar with using maps. Supporting factors for easy maps to understand are classification method and color symbol scheme. The purpose of this study was to select and test the classification method and the most effective color symbol scheme for mapping population density in the Special Region of Yogyakarta. The classification methods used in this study are constant interval, arithmetic progression, geometric progression, quantile, standard deviation and dispersal graph. The effectiveness test method for the most effective classification method is the proportion assessment. The color symbol scheme used in this study is a sequential color scheme, diverging color schemes, Corel Draw color schemes and color symbol schemes provided in ArcMap 10.3 software. The effectiveness test method for the most effective color symbol scheme is conventional eye tracking. The results showed that according to the proportion test the most effective classification method was the arithmetic interval classification method with results of 0.26. The most effective color symbol scheme in accordance with the effectiveness test using the conventional eye tracking method shows that the most effective color symbol scheme is a diverging color scheme. The important aspects to consider are average answering duration of 8.15 seconds, the accuracy of the answer is 98.9%, and easiness level of symbolization readings is 341. This research can be one of the references on the most effective classification method and reference regarding the selection of the most effective color symbol scheme on Choropleth Map of Population Density in Special Region of Yogyakarta, so that further research can continue the analysis of appropriate classification methods for demographic data. The method discussed in this study is also expected to be applicable to other data.
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