The coastal area has experienced significant changes of waste problems over the past few years. To resolve the waste problems in coastal areas, an understanding of community perception is needed to support government efforts. Therefore, this study aims to review people’s perspectives on the dynamics of waste in the coastal areas. Community perception data were compiled through semi-structured interviews with the surrounding communities in coastal areas. ArcGIS and load count analysis were used to analyze the waste density. Waste was collected from the coastal area in Ambon Bay and analyzed using waste density calculation and spatial analysis. The results show that the total waste density obtained at the coastal area of Ambon Bay is 0.249 kg/m², of which 0.078 kg/m² is the density of plastic waste, and 0.171 kg/m² is the density of non-plastic waste. Communities in coastal areas have made efforts to deal with waste problems, but the efforts made are still ineffective in overcoming these problems. That problem happens because there is a lack of knowledge of the community and lack of infrastructure in coastal areas. The research results have the potential for replication in other coastal areas and are used as the basis of decision making for waste management improvement.

Almost all of landslide in Indonesia, especially in West Java, occurred in area with volcanic sediment. Some of them are occurred in Bogor area. The controlling factors that can affect landslide susceptibility area are rock lithology, slope, and land use. In the circumstance when data is insufficient, contain factors causing the landslides used to obtain landslide susceptibility analysis by using the fuzzy logic approach. Therefore, the aim of this paper is to know the landslide susceptibility condition of the research area. In this study, methods used consist of field method to collect geological structure and lithology data also studio method with fuzzy logic to generate the mapping parameters of landslide susceptibility (lithology, geological structure, slope, and land use). The result shows that research area divided into three landslide susceptibility zones, i.e.: (i) non-susceptiblity zone, (ii) low susceptibility zone, (iii) moderate susceptibility zone. The susceptibility area is an area with more massive geological structure and high angle of slope with lithology consist of tuff. The results of landslide susceptibility are useful for the prevention and mitigation of landslide hazards, and appropriate planning for future land use and construction in research area.

The purpose of this study was to simulate land use change in 1996-2016 and its prediction in 2035 as well as its potential to deforestation. Both of these purposes were obtained through modeling analysis using Markov Chain Cellular Automata. This modeling method was considered important for understanding the causes and impacts. Based on the analysis, the land use change between 1996 to 2007 has caused forest loss (the region and non-region) covering an area of 62,012 ha. While in the period of 2007 to 2016, the change has lead to the east side of the slope grade of 0-15 percent and an altitude between 500-1000 meters above sea level. In this period, plantation area has increased by 50,822 ha, while the forest area has reduced from 80,038 ha. In a period of 20 years, North Bengkulu Regency has lost the forest area of 80,038 ha. The amount of intervention against forest suggested the potential for deforestation in this area. Simulation of land use change in 2035 did not indicate significant deforestation due to the limited land on physical factors such as slope and elevation. However, it should be noted that, in 2035, the area of conservation forest was reduced by 16,793 ha (29 %), while the areas of protected and production forest were reduced by 4,933 ha (19 %) and 2,114 ha (3 %), respectively. Land use change is a serious threat of deforestation, especially in forest areas in North Bengkulu Regency, where any decline in forest area means the addition of plantation area.

The unprecedented growth in population put pressure on urban land suitability. Besides that, the deterioration of infrastructure facilities, traffic jam, and disaster like flood and landslide could be happen more severe in a few years later. This study attempted to find out the projection of population growth and suitability of urban land in order to be carried out sustainably. Land use suitability assessment is a key determinant in any urban planning and decision-making process. The variables taken for the study are slope, altitude, and land cover. This study provided the information not only the existing urban land cover pattern but also the simulation of population growth and land suitability for the establishment in future.

Large-scale mining activity is the major environmental issue, including water pollution caused by Acid Mine Drainage (AMD). Samarinda, which is located in the province of East Kalimantan, Indonesia, has open pits and acid contributing land as a source of AMD pollutants. The potential AMD pollution can be assessed by utilizing Geographic Information System (GIS) and Remote Sensing (RS), which are considered reliable tools for measuring, mapping, monitoring, and model making for an area. The variables used in this research are void distribution, land cover, soil type, rainfall, topography, water body, and groundwater. The integration of these variables is used to analyze the potential of AMD pollution to water bodies by acid contributing land. Meanwhile, the void distribution and groundwater integration data are used to analyze the potential of AMD pollution to groundwater by voids. The overlay method is employed to analyze the potential spatial patterns of AMD pollution in the study area. The results show the high potential of AMD pollution to water bodies, specifically in the districts of Samarinda Utara, Palaran, and Sungai Kunjang. The high potential of AMD pollution to groundwater is found in the south delineation area, namely Palaran, Loa Janan Hilir, and Samarinda Seberang districts, with low and medium groundwater depth categories (20 - 70 and 50 - 150 MBGL). The spatial pattern of AMD pollution was random with the geometric arrangement of AMD pollution in the form of clusters.