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The minimum wage is very effective as a tool to reduce income inequality. Apart from limiting the minimum wage in general, this policy also has an effect on increasing income and plays an important role in overcoming income gaps. Apart from the minimum wage, micro-spending also influences income inequality. This research aims to determine and analyze the influence of minimum wages and micro expenditure on regional income in Indonesia. This research uses multiple linear regression analysis. The data used is secondary data for 1 period, namely 2022, obtained from the Central Statistics Agency. The variables used are Regional Income (Y), Minimum Wage (X1), Micro Expenditures (X2). The classic assumption test uses the SPSS for Windows version 25 program. The estimation results show that the provincial Minimum wages affect poverty in Indonesia, education affects poverty in Indonesia, and health affects poverty in Indonesia. Local minimum wages, education, and health influence poverty in Indonesia.

Companies must struggle to survive and be the best, this encourages companies to use various strategies and innovations to prevent bankruptcy in the laws of law there are gaps that can be utilized by taxpayers to reduce the tax burden that must be paid. One of them is tax avoidance. The purpose of this study is to determine the effect and explain profitability, leverage on tax avoidance with sales growth as moderation variables in consumer goods companies listed on the Indonesia Stock Exchange for 2020-2021. Types of research approaches are quantitative, with a population of 4 companies and 32 data samples The quarterly financial uses using purposive sampling for sample determination. Data analysis techniques conducted with descriptive statistical analysis, testing of panel data regression estimation models, classical assumption tests, multiple linear analysis, t-test, and moderation regression analysis. The results of this study were obtained that the partial profitability variable had a significant effect on tax avoidance and partially leverage had no significant effect on tax avoidance. The results of moderation regression analysis obtained by the results of sales growth instead of the moderation variable between profitability and leverage of tax avoidance.

Analysis of panel data regression is a regression method to determine the relationship between the independent variable and the dependent variable using combined data, namely between cross-section data and time-series data.Analysis of panel data regression can apply to the processing of rice production estimates for an area including the province of North Sumatera. North Sumatera is one of the provinces in Indonesia, at the very of the population focuses on the agricultural sector as the main livelihood in rice being the primary production. Based on data on the development of rice production at the Agriculture Office of North Sumatra Province, the level of rice production in 2019 for North Sumatra Province reached 4,693,563 Ton/Year.Throught Panel Data Regression Analysis with the three approach methods is Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM) , the best approach method is obtained, namely the Fixed Effect Model (FEM) with the best estimation model is . The coefficient of determination  of 0.950890, which means that the independent variable affects the dependent variable by 95.08% on rice production.Based on the estimation model, the development of rice production in the next 3 years, namely 2020, 2021 and 2022, has changes of around 39.88% (decrease), 10.68% (increase), 9.89% (increase).

The Erlang distribution is a special case of the Gamma distribution with the k shape parameter and the λ rate parameter. In this study, the parameter estimation of the Erlang distribution was carried out using the Maximum Likelihood method. In maximizing the function, an implicit and non-linear form is obtained, then it is solved using the Newton Raphson algorithm. Apart from Newton Raphon, the estimation of parameters was also carried out using the Fisher Scoring algorithm. The Fisher Scoring algorithm is similar to the Newton Raphson algorithm, the difference is that Fisher Scoring uses an matrix information. The result of parameter estimation in Erlang distribution using Newton Raphson algorithm which is applied to outgoing telephone call data that generated by Matlab R2010a software cannot be done simultaneously. Therefore, the parameter assessment is carried out on the k parameter first, then followed by the λ parameter estimation and the parameter and  = 0.6886812 are obtained. Meanwhile, the parameter estimation using the Fisher Scoring algorithm produces an equation that is not different from the Newton Raphson algorithm