Map can show information needed by map users from various scientific fields, especially in Indonesia. Effective maps can help users understand. One of the factors that influence the effectiveness of map reading is the color symbol scheme used in symbolization. Effectiveness’ study of color symbol scheme applied on choropleth mapping. Choropleth map is using population density data in Special Region of Yogyakarta. The selection of the study area in the Special Province of Yogyakarta is because the Special Region of Yogyakarta is one of the provinces in Indonesia which has a fairly high population density in the area of 3,185.80 km<sup>2</sup> . In 2016, the population density of the Special Province of Yogyakarta ranked 4th in the Indonesian Statistics 2017 by the Central Bureau of Statistics, which amounted to 1,188 population per km2 . The effectiveness of color symbol schemes adapts the capabilities of each user. This study is expected to be able to study the effect of age group differences on maps with the best color symbol scheme. All scientific field that used choropleth map of population density consist of 2 age groups, those are 20-25 years old and >5 years old respondents. The purpose of this study was to observe age group influence for the most effective color symbol scheme for mapping population density in the Special Region of Yogyakarta. The result of this study shows the difference between age group based on the important aspects of conventional-eye tracking. The important aspects to consider are average answering duration, the accuracy of the answer and easiness level of symbolization readings. The first group (20-25 years) shows map 3 (diverging color scheme) as a map with the most effective color symbol scheme. While group 2 (>25 years) shows map 1 (ArcGIS 10.3 color scheme) as a map with the most effective color symbol scheme. This research is expected to be able to show the influence of age in determining the best color symbol scheme on population density maps so that its effectiveness can be adjusted specifically to map users.
Data related to socio-economic activities in Indonesia mostly used statistical data. Statistics for large numbers of socioeconomics will make it difficult to interpret and analyze because it consists of many columns and rows with each value. Geo-visualization is a visualization of data represented in a geographic coordinate system. Socio-economic statistics can be visualized to facilitate the process of spatial analysis data that considers spatial surface of earth. Study area is in Special Region of Yogyakarta. This study aims to (1) Select, test and find out color symbol scheme most effective classification method for choropleth mapping of Demographic Map, (2) Mapping happiness profile of population using small area estimation method, (3) Analyzing tourist trends based on Instagram data using space time cube visualization. Secondary data used are population and happiness, while primary data uses social media data for tourist visualization. Geo-visualization of population and happiness used choropleth method. In social media geo-visualization for tourists using space time cube geo-visualization with hexagonal tessellation cells. The results obtained are population maps with best classification scheme, happiness maps at different scale levels, and tourist map using space time cube in Yogyakarta Special Region.
Indonesia is one of the disaster-prone countries. 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 65 landslides in Purworejo. Landslide is one of the most common disaster that occur in Indonesia. Landslide is caused by meteorological and geomorphological factors. 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. Landslide susceptibility modeling in Purworejo Regency was carried out using three different methods, namely Information Value Model (IVM), Information Value Model-Analytical Hierarchy Process (IVM-AHP) and Information Value Model-Gray Clustering (IVM-GC). Each modeling is conducted using the Natural Breaks (Jenks) method to produce five classes, namely very low, low, medium, high and very high class based on the IVM value of each method. This research’s goal is to visualized 3 maps of modelling results. The visualization used is 3-dimensional mapping. This mapping is intended to make it easier to compare the map results of modeling that have been done before. The expected results of this study are accurate and reliable 3-dimensional visualization to study the advantages and disadvantages of each of the modeling methods used.