File ppt ujian sarjana " Regresi data panel " full INTERPRETASI BAB 1- BAB IV

Summary

In this presentation, Nabila discusses her research on labor absorption in the industrial sector of Maluku province, utilizing panel data regression. She explores the trends of employment, GDP, industrial companies, and workforce in Maluku from 2014 to 2018. Key findings include the significant influence of industrial companies and labor force on workforce absorption, while GDP shows mixed results. Nabila employs various regression models to analyze the data, confirming the fixed-effect model as the most appropriate. Her conclusion suggests that empowering the labor force and improving wage policies could help address unemployment in the region.

Takeaways

• 😀 The study investigates labor absorption in the industrial sector in Maluku Province using panel data regression between 2014 and 2018.
• 😀 The key variables studied include labor force (Y), Gross Regional Domestic Product (PDRB), number of industrial companies (X2), and workforce participation rate (X3).
• 😀 Labor force in the industrial sector showed fluctuations between 2014-2018, with an increase in 2014-2015, a decrease in 2016, and a recovery by 2017 and 2018.
• 😀 PDRB in the industrial sector increased from 2014 to 2015, declined in 2016, and recovered with the highest growth in 2018.
• 😀 The number of industrial companies in Maluku generally increased from 2014 to 2018, although there was a slight decrease in 2017.
• 😀 The workforce participation rate showed an upward trend from 2014 to 2018, with increases in 2014-2015 and 2018 despite a dip in 2016 and 2017.
• 😀 The study applied panel data regression models to analyze the relationship between the variables. Three models were considered: Common Effect (CM), Fixed Effect (FM), and Random Effect (RM).
• 😀 The best model was determined to be the Fixed Effect Model (FM) based on statistical tests, rejecting the Common Effect Model (CM).
• 😀 The statistical tests showed that the relationship between the number of companies and labor absorption was significantly positive, while the relationship between workforce participation and labor absorption was significantly negative.
• 😀 The results of the study indicated that improving workforce participation and enhancing industrial policies could help reduce unemployment and improve labor absorption in Maluku's industrial sector.

Q & A

What is the main objective of Nabila's research?

The main objective of Nabila's research is to analyze the absorption of labor in the industrial sector in Maluku Province using panel data regression.

What are the key variables used in the study?

The key variables in the study include labor (Y), Gross Regional Domestic Product (PDRB), industrial companies (X2), and the workforce (X3). These variables were observed across 11 districts in Maluku Province from 2014 to 2018.

How did the labor sector in the industrial sector perform between 2014 and 2018?

The labor sector in the industrial sector experienced fluctuations, with a peak in 2017 and a significant decline in 2016. The highest labor absorption was recorded in 2017, while the lowest was in 2016.

What was the trend of the industrial sector's PDRB from 2014 to 2018?

The PDRB of the industrial sector showed an increasing trend from 2014 to 2015, followed by a decline in 2016, a recovery in 2017, and a peak in 2018.

What was the trend in the number of industrial companies in Maluku Province during the study period?

The number of industrial companies in Maluku Province generally increased from 2014 to 2018, with a slight decline in 2017 but a recovery in 2018.

How did the workforce in Maluku Province change from 2014 to 2018?

The workforce in Maluku Province increased from 2014 to 2015, experienced a decline in 2016 and 2017, and then saw an increase again in 2018.

Which regression model was chosen for this study and why?

The fixed effects model was chosen based on statistical tests, including the F-test and Chi-square test, which indicated it provided the best fit for the data compared to the other models.

What were the main findings regarding the relationship between the variables?

The study found that the number of industrial companies (X2) has a significant positive relationship with labor absorption, while the workforce (X3) has a negative but significant relationship. The PDRB (X1) was not found to significantly affect labor absorption.

What classical assumption tests were conducted during the analysis?

The study performed several classical assumption tests, including normality, multicollinearity, and heteroskedasticity tests, all of which were satisfied, confirming the validity of the model.

What conclusions and recommendations did the study provide?

The study concluded that the best model for analyzing labor absorption in Maluku Province was the fixed effects model. It recommended that the government focus on empowering the workforce and implementing appropriate wage policies to reduce unemployment in the industrial sector.