Many research in economics only focus on the independence of a region while neglecting the effects of space and the interaction that occurs between mutually adjacent areas. The purpose of this study is to measure the multidimensional poverty concept in 15 districts/cities in the province of Lampung in 2015-2019. Spatial analysis such as moran i statistics, LISA clustered map, and lisa signification are used to analyze spatial patterns and spatial autocorrelation. Spatial modeling with spatial autoregressive model, geoda and geographical information systems are used as explanatory spatial data and spatial modeling. The results show that the percentage of poor people between districts/cities in Lampung Province have positive Moran's I values, there is a clustered pattern in 2015-2019, Moran scatter plot depicts 4 quadrants, LISA Cluster map indicates high-high and low-low areas, and LISA map has 4 significant areas. Spatial regression results show that per capita expenditure for nonfood has a negative effect, per capita expenditure for food has a positive effect, population growth rate has a positive effect, household clean water has a positive effect, life expectancy has a negative effect, mean years of schooling has a negative effect, and simultaneously the independent variables have a significant influence on the percentage of poor people. Poverty in Lampung Province is spatially related to each other between regions, the findings suggest that the variables used affect spatially. The implication of this result is one of the basis for inter-regional policies in the interests of multi-dimensional poverty alleviation between regions.Keywords: Poverty, Spatial analysis, Spatial Autoregressive Model (SAR)

This study aims to calculate the relative ratio of the value added contribution of a sector in Sumatra region to the value added contribution of the sector concerned on a provincial or national scale growth patterns in South-Sumateran distinct groups of regions across Sumatera Island from 2014 until 2019. The analysis follows the two steps of quantitative analysis tools; Location Quotation (LQ) and Klassen Tipology.The LQ analysis will show of quantifying how concentrated a particular source of income, geographic, and the demographic group is in a region as compared to the nation. It can reveal what makes a particular region “unique” in comparison to the national average. The results showed that the GDRP business sector which has high potential value and high added value significantly spurs economic growth. This article ends with several policy recommendations for lagging regions. The recommendation and analysis will help to organize the economic growth of each province in a structured manner based on its sector potential.

The regional economy is in space and time, space is an important strength in the activity of an economy. This study examines spatial dependencies in observing economic activity in the form of regions and the convergence hypothesis as a study to see the economic gap between poor and rich regions. The spatial interaction of the economy in this study uses the Moran I statistical method, LISA Signification, and LISA Clustered map, the Convergence Study is analyzed using ordinary least square panel data using the Fixed Effect model approach. This study uses secondary data and panel data with 15 districts and cities and the 2015-2019 time series. Testing Results spatial relationship between the GDP per capita 15 districts and cities in the province of Lampung year 2015-2019, there has been a positive spatial autocorrelation spatial pattern formation has a regional grouping of Economy with the indication of the same characteristics. A process of absolute convergence is marked and significant negative coefficient, an indication of speed- reducing the economic gap of 4.8%, so that the time required in a process of reducing the gap from the initial gap was 14.17 years in 15 districts and cities in the province of Lampung Year 2015-2019.

Hipotesis Konvergensi masih menjadi topik yang menarik dengan melihat apakah antar wilayah sedang mencapai titik konvergen atau divergen dalam aktivitas perekonomian, semakin menjauh atau semakin mengecil gap perekonomian antar wilayah. Alat analisis dengan regresi linier berganda menggunakan pendekatan fixed effect model, penelitian ini menggunakan variabel PDRB Perkapita tahun penelitian dan tahun sebelumnya. Data skunder berbentuk panel data dengan 15 wilayah Kabupaten dan kota serta runtun waktu penelitian tahun 2015-2019. Hasil penelitian menjelaskan telah terjadi proses konvergensi absolut ,ini ditandai koefisien negative dan signifikan, Indikasi kecepatan mengurangi gap perekonomian sebesar 4,8% , waktu yang dibutuhkan dalam suatu proses pengurangan kesenjangan dari kesenjangan awal adalah adalah 14,17 Tahun antar 15 Kabupaten dan Kota di Provinsi Lampung Tahun 2015-2019.

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