The relationship between infrastructure development, economic growth, and income inequality has always been debated. Those debates raised the question of "is there a role for infrastructure development in economic growth which in turn encourages a decline in income inequality?". This study aims to analyze the direct effect of infrastructure development on economic growth and the indirect effect-on income inequality. The present study used the Gini Ratio, Gross Regional Domestic Product (GRDP) data at constant market prices, investment, number of workforces, percentage of poor population, distribution of clean water, electricity distribution, and road length as of 2010-2016. The analytical methods applied here include descriptive method along with a twostep regression analysis method. The results reveal that infrastructure had a positive effect on economic growth, whereas direct economic growth harmed income inequality. These findings demonstrate that infrastructure indirectly reduces income inequality. Thus, infrastructure development, especially basic infrastructure and transportation, could reduce income inequality in Indonesia. Based on these findings, the government and related parties should encourage investment in basic infrastructure and transportation to improve economic performance sustainably.

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Land-use change in Pandaan District was identified as the fourth-highest in East Java Province. This change is due to the population increase caused by the strategic location of the Pandaan Sub-district, which is passed by the Surabaya-Malang City connecting road, creating a rapid development of built-up land. The spread of built-up land development with low density becomes the initial identification of the sprawl phenomenon. Changes in land-use due to push factors caused inconsistencies in the development of existing land as stipulated in spatial planning documents. This study aims to determine land-use change and land-use prediction in Pandaan Sub-district to be used for future planning. Research methods incorporated spatial analysis of land-use change and the land-use planning process in ArcMap and SELVA IDRISI. The land use forecasts for modeling are based on the use of the Cellular Automata (CA) -Markov method and the ANN / MLP method. Land-use changes were identified through land-use comparisons in recent years. The land-use prediction was determined through the land-use change transition by including the motivating and inhibiting variables of land-use changes. The results of the study stated that the most significant land-use change occurred in rural/urban villages passed by arterial and collector road connecting Surabaya-Malang City. CA-Markov results showed that the results of land-use prediction have a linear development pattern in the spreading road networks and residential settlements. The prediction results show that settlement increase13,62% and industry increase 20,7%..