The Use Of Statistical Quality Control Methods In Analyzing District/city Minimum Wages (UMK) In North Sumatra

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The Use of Statistical Quality Control Methods in Analyzing District/City Minimum Wages (UMK) in North Sumatra

Introduction

Employment is a vital foundation in the lives of Indonesian people, and wages are one of the essential factors for workers to meet their needs. The determination of minimum wages (UMK) is a crucial aspect of employment, as it affects the purchasing power of workers and the competitiveness of businesses. In North Sumatra, the UMK has been a topic of discussion, with some districts/cities having higher or lower minimum wages than others. This study aims to analyze the variation of UMK in North Sumatra using the Statistical Quality Control (SQC) method.

Background

The SQC method is a statistical technique used to monitor and control processes to ensure that they are operating within predetermined limits. In the context of UMK, the SQC method can be used to identify districts/cities that are beyond control limits, indicating potential inequality in the determination of minimum wages. The study uses secondary data on UMK from 2015 to 2019, covering 25 districts/cities in North Sumatra.

Methodology

The SQC method used in this study involves the control map X and R, which plots the mean and range of UMK values for each district/city. The control limits are set at 3 standard deviations from the mean, and any district/city with a UMK value outside these limits is considered to be beyond control. The study uses the following steps to analyze the UMK data:

  1. Data collection: Collect secondary data on UMK from 2015 to 2019 for 25 districts/cities in North Sumatra.
  2. Data analysis: Use the SQC method to plot the control map X and R and identify districts/cities that are beyond control limits.
  3. Further analysis: Investigate the reasons for the inequality in UMK determination, including differences in the level of life needs, regional economic conditions, and discrepancies with regulations.

Results

The results of this study show that there are three districts/cities that are outside the control limit, namely Nias Regency South, West Nias Regency, and West Pakpak Regency. These districts/cities have UMK values that are significantly higher or lower than the mean UMK value for North Sumatra.

Discussion

The results of this study indicate that there is an inequality in the determination of UMK in North Sumatra. The three districts/cities that are outside the control limit may be caused by several factors, including:

  • Differences in the level of life needs: The cost of living in each region is different, so the UMK ideally must also reflect the difference.
  • Regional economic conditions: The economic conditions of each district/city can affect the purchasing power of the community and the company's ability to pay MSEs.
  • Discreptions with regulations: There may be a discrepancy in the application of legislation related to the determination of MSEs.

Recommendation

This research provides several recommendations for the government and stakeholders to overcome the problems of UMK gaps in North Sumatra:

  • Increasing transparency and accountability: The government needs to increase transparency in determining MSEs, by involving various parties such as trade unions, employers, and academics.
  • Conducting in-depth studies: Determination of MSEs needs to be done by considering various factors such as the level of living needs, regional economic conditions, and industrial competitiveness in the region.
  • Strengthening the supervision and law enforcement: Law enforcement of companies that violate MSME regulations need to be strengthened to ensure compliance with applicable regulations.

Conclusion

The SQC method has proven to be effective in analyzing UMK variations in North Sumatra. This research provides an overview of the inequality of MSEs in several districts/cities. Determination of fair and balanced MSEs can help improve workers' welfare, encourage economic growth, and create social stability in North Sumatra.

Limitation

This study has several limitations, including:

  • Secondary data: The study uses secondary data on UMK, which may not reflect the current situation.
  • Limited scope: The study only covers 25 districts/cities in North Sumatra, and the results may not be generalizable to other regions.
  • Methodological limitations: The SQC method used in this study may not capture all the factors that affect UMK determination.

Future Research

Future research can build on this study by:

  • Using primary data: Collecting primary data on UMK can provide more accurate and up-to-date information.
  • Expanding the scope: Conducting a study that covers more districts/cities in North Sumatra or other regions can provide a more comprehensive understanding of UMK determination.
  • Using other methods: Using other statistical methods, such as regression analysis, can provide a more nuanced understanding of the factors that affect UMK determination.
    Frequently Asked Questions (FAQs) on The Use of Statistical Quality Control Methods in Analyzing District/City Minimum Wages (UMK) in North Sumatra

Q: What is the purpose of this study?

A: The purpose of this study is to analyze the variation of UMK in North Sumatra using the Statistical Quality Control (SQC) method and to identify districts/cities that are beyond control limits, indicating potential inequality in the determination of minimum wages.

Q: What is the SQC method?

A: The SQC method is a statistical technique used to monitor and control processes to ensure that they are operating within predetermined limits. In the context of UMK, the SQC method can be used to identify districts/cities that are beyond control limits, indicating potential inequality in the determination of minimum wages.

Q: What are the control limits in the SQC method?

A: The control limits in the SQC method are set at 3 standard deviations from the mean. Any district/city with a UMK value outside these limits is considered to be beyond control.

Q: What are the reasons for the inequality in UMK determination?

A: The reasons for the inequality in UMK determination may include differences in the level of life needs, regional economic conditions, and discrepancies with regulations.

Q: What are the recommendations for the government and stakeholders to overcome the problems of UMK gaps in North Sumatra?

A: The recommendations include increasing transparency and accountability in determining MSEs, conducting in-depth studies to consider various factors such as the level of living needs, regional economic conditions, and industrial competitiveness in the region, and strengthening the supervision and law enforcement of companies that violate MSME regulations.

Q: What are the limitations of this study?

A: The limitations of this study include the use of secondary data, limited scope, and methodological limitations.

Q: What are the future research directions?

A: The future research directions include using primary data, expanding the scope to cover more districts/cities in North Sumatra or other regions, and using other statistical methods such as regression analysis.

Q: What are the implications of this study for policy makers and stakeholders?

A: The implications of this study for policy makers and stakeholders are that they need to increase transparency and accountability in determining MSEs, conduct in-depth studies to consider various factors, and strengthen the supervision and law enforcement of companies that violate MSME regulations.

Q: What are the benefits of using the SQC method in analyzing UMK?

A: The benefits of using the SQC method in analyzing UMK include identifying districts/cities that are beyond control limits, indicating potential inequality in the determination of minimum wages, and providing a framework for policy makers and stakeholders to make informed decisions.

Q: Can the SQC method be applied to other regions or industries?

A: Yes, the SQC method can be applied to other regions or industries that have similar characteristics and data availability.

Q: What are the next steps for this research?

A: The next steps for this research include conducting further studies to validate the findings, expanding the scope to cover more districts/cities in North Sumatra or other regions, and using other statistical methods such as regression analysis.

Q: How can the findings of this study be used in practice?

A: The findings of this study can be used in practice by policy makers and stakeholders to make informed decisions about UMK determination, to identify districts/cities that are beyond control limits, and to develop strategies to overcome the problems of UMK gaps in North Sumatra.