摘要：The annually increasing number of urban populations will have impacts on waste generation. Tembalang Sub-district as a sub-district located on the outskirts of Semarang City has significant developments in the term of population growth in correlation with waste generation. Within four years, waste generation in the Tembalang Sub-district increased from the fifth rank to the third rank. It is possible that this sub-district will become the first rank in Semarang City in waste generation. To be able to identify influential factors and spatial distribution pattern of waste generation in Tembalang Sub-district, it is necessary to apply statistical and spatial approach. This study uses quantitative methods with a statistical spatial analysis approach by using GIS. In addition, this research also intends to model the relationships of Solid Waste Generation by applying socio-economic variables. Based on the results of Ordinary Least Square analysis, social economy variables that affect the amount of waste generation in Tembalang Subdistrict are the number of population and trading activities. The model of formed socio-economic variables has the effect of 25% towards the amount of waste generation. Spatial patterns identified from waste generation shows that what needs to be considered is the waste management in TPS (Temporary Waste Disposal) in Tembalang and Sendangmulyo.
其他摘要：The annually increasing number of urban populations will have impacts on waste generation. Tembalang Sub-district as a sub-district located on the outskirts of Semarang City has significant developments in the term of population growth in correlation with waste generation. Within four years, waste generation in the Tembalang Sub-district increased from the fifth rank to the third rank. It is possible that this sub-district will become the first rank in Semarang City in waste generation. To be able to identify influential factors and spatial distribution pattern of waste generation in Tembalang Sub-district, it is necessary to apply statistical and spatial approach. This study uses quantitative methods with a statistical spatial analysis approach by using GIS. In addition, this research also intends to model the relationships of Solid Waste Generation by applying socio-economic variables. Based on the results of Ordinary Least Square analysis, social economy variables that affect the amount of waste generation in Tembalang Sub-district are the number of population and trading activities. The model of formed socio-economic variables has the effect of 25% towards the amount of waste generation. Spatial patterns identified from waste generation shows that what needs to be considered is the waste management in TPS (Temporary Waste Disposal) in Tembalang and Sendangmulyo.
关键词：Spatial Statistics; Waste
Generation; Ordinary Least
Square
其他关键词：Spatial Statistics;Waste Generation;Ordinary Least Square
