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The purpose of this research is to analyze the effectiveness and efficiency of the municipal tax revenues and their contribution towards original local government revenue in Sidenreng Rappang district. The study applied the descriptive quantitative method. The data obtained from the municipal tax revenues district and the budget realization report of Sidenreng Rappang district from the period between 2014 and 2019. This research uses the method of effectiveness and efficiency ratio to calculate local tax, local tax realization, local tax fees, local tax target, and local tax contribution. The result in this research indicates that local tax revenues in Sidenreng Rappang district during the period of 2014 are already effective. The annual local tax revenues are very effective. Interestingly, the contribution of local taxes towards original local government revenue in Sidenreng Rappang district is found still very low.

The purpose of this research is to analyze and find out the sectors that include the base sector, changes and shifts in the economic sector and the classification of growth in the economic sector in the Mamminasata region, South Sulawesi. Data analysis methods are Location Quotient (LQ), Shift Share, and Klassen Typology analysis from secondary data which is time series data for the last 4 years (2018-2021) of the Central Bureau of Statistics of South Sulawesi. 1). The results of the Location Quotient index analysis (LQ>1), the sector which was the base sector before (2018-2019) and during the Covid-19 pandemic (2020-2021), namely: manufacturing industry; water supply, waste management, waste and recycling; construction; wholesale and retail trade, repair of cars and motorcycles; transportation and warehousing; provision of accommodation and food and drink; information and communication; financial and insurance services; real estate; company services; educational services; health services and social activities; and other services. 2). The results of the Shift Share analysis show that the specialized sectors grew rapidly (positive proportional shift) prior to the Covid-19 pandemic (2018-2019), namely: the manufacturing industry; construction; wholesale and retail trade, repair of cars and motorcycles; information and communication; company services; government administration, defense, and compulsory social security; educational services; health services and social activities; and other services. Meanwhile, when the Covid-19 pandemic occurred (2020-201), namely: agriculture, forestry, and fisheries; procurement of electricity and gas; wholesale and retail trade, repair of cars and motorcycles; transportation and warehousing; information and communication; company services; health services and social activities; and other services. The sectors that had high competitiveness or competitive (differential shift) before the Covid-19 pandemic (2018-2019), namely: agriculture, forestry, and fisheries; mining and excavation; procurement of electricity and gas; construction; wholesale and retail trade, repair of cars and motorcycles; provision of accommodation and food and drink; real estate; company services; health services and social activities; and other services. Meanwhile, during the Covid-19 pandemic (2020-2021), namely: agriculture, forestry, and fisheries; mining and excavation; processing industry; construction; real estate; government administration, defense, and compulsory social security; and other services. 3) The results of the Klassen Typology analysis, sectors that were classified as developed and growing fast (quadrant I) before the Covid-19 pandemic (2018-2019), namely: construction; wholesale and retail trade, repair of cars and motorcycles; provision of accommodation and food and drink; real estate; company services; educational services; health services and social activities; and other services. Meanwhile, when the Covid-19 pandemic occurred (2020-201), namely: the processing industry; construction; and health services and social activities.

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