Analysis of Social Inequality and Education Level in South Sulawesi Province, Indonesia

Besse Qur’ani^1*, Abdul Hadis², Muh. Ashary Anshar³

^1,2State University of Makassar, South Sulawesi, Indonesia

³IBK Nitro, Makassar, South Sulawesi, Indonesia

 ABSTRACT: The purpose of this research is to analyze social inequality and education levels in regencies and cities in South Sulawesi so that the development process can be improved and there is an equitable distribution of development. This type of research is survey research with quantitative data. The factors analyzed and influencing social inequality in this study are population growth, population density, level of education, and the number of workers. The findings show that the average socio-economic inequality in the high category includes Selayar regency, Bulukumba regency, Bantaeng regency, Takallar regency, Pangkep regency, Soppeng regency, Wajo regency, Sidrap regency, Bone regency, Barru regency, Enrekang regency, Tana Toraja regency, North Luwu regency, Luwu regency, East Luwu regency and Makassar city. Meanwhile, the average socio-economic inequality in the moderate category includes Jeneponto regency, Gowa regency, Maros regency, Sinjai regency, Pinrang regency, North Toraja regency, Pare-pare city, and Palopo city. The suggestions to be conveyed are to expand the study by adding several related variables and developing a Green Open Space (RTH) variable to see the environmental quality of each Regency and City in responding to climate change issues.

KEYWORDS: Social inequality, education level, South Sulawesi.

INTRODUCTION

Development is a process in realizing equity, justice, prosperity and welfare for the people without discrimination (Gupta & Vegelin, 2016). Efforts to equalize development are the noble ideals of the Indonesian people which must be realized in eliminating disparities (Firdaus, 2020). The existence of equitable development is expected to accelerate economic growth, create jobs, and eliminate development gaps (Stanef, 2012; Didiharyono et al, 2023). Experts have formulated that economic progress and equitable development are two important things in achieving the goals of justice and prosperity (Hernovianty et al, 2022).

Among the challenges in national development is overcoming the problem of inequality and development gaps (Greig, 2007). Data from the Central Statistics Agency (BPS) show that over the last three decades, the average rate of economic growth in Indonesia has been relatively high, but at the same time the  income  gap  has also  been high.  Poverty  data  for 1970–2017 shows that the average poverty rate in urban areas is 13.9 percent, while in rural areas it reaches 19.0 percent (BPS, 2018). These conditions indicate that rural residents who generally work in the agricultural sector experience poverty most often than urban residents (Sukwika, 2018; Ivanic & Martin, 2018).

Development gaps will become the root of the problem in progress between regions so that justice is needed in order to bring prosperity to the community (Wahyuntari & Pujiati, 2016). Development gaps are sometimes influenced by differences in geographical conditions, education levels, economic growth, and other social conditions of the population (Rosmeli, 2018). If the development gap is not immediately anticipated, it will become an obstacle and a challenge for economic development that will cause losses on a fairly large scale (Hofman, 2014; Mansi et al, 2020). It can even trigger bigger problems such as social conflict in society which takes many victims (Kagan et al, 2019).

The regencies and cities in South Sulawesi Province still have problems of social inequality, including the uneven distribution of the population and tend to be concentrated in urban centers with the availability of fairly complete development facilities (Dini & Fauzan, 2020; Surya et al, 2020). While the population density in rural areas, the distribution is uneven and the area is quite large and depends on agricultural activities. The low level of population density also makes the development process quite difficult (Hu et al, 2013; Hernovianty et al, 2023).

In addition, the factors of education level and number of labor force are also important indicators in supporting sustainable development (Haque et al, 2019; Strelan et al, 2020). Based on this explanation, it is necessary to conduct a study related to the analysis of social inequality and education levels in districts and cities in South Sulawesi so that the development process can be improved and there is an equitable distribution of development.

METHODOLOGY

This type of research is survey research with quantitative data. Data collection techniques apply literature studies, interviews, documentation, and tabulation of secondary data obtained online from the Central Statistics Agency (BPS) and related institutions of South Sulawesi province. The analytical method used is scoring analysis based on the assumption of benchmarks for each aspect of the assessment as shown in Table 1 below.

Table 1. The indicator for determining the score for each aspect of social inequality (Hernovianty et al, 2022).

In this study the number of observations was 3 so that the results obtained for the number of classes were  and rounded up to 3 class intervals. As for determining the range of data using the interval formula with 3 classes. The highest and lowest scores are obtained from the largest and smallest total scores for each indicator of social inequality, namely population growth, population density, education level, and labor force. The equation is,

(1)

Description, I = Interval, Range = Highest Score – Lowest Score, and K = Class.

or 3

Then the class intervals applied to measure the level of social inequality in each district and city in South Sulawesi, among others

> 3 – 6 : Low inequality

> 6 – 9 : Middle inequality

> 9 – 12 : High inequality.

III.  RESULTS AND DISCUSSION

Population growth

Population growth is interpreted as a description of the rate of population growth in a certain period by considering death, birth, immigration and emigration rates. The population growth rate (LPP) for each district in South Sulawesi is different, so a different score is also obtained. Comparing the LPP of the province with the LPP of the Regency is a way to see regional disparities from the aspect of population growth as shown in Table 1. The calculation of the population growth score for the regencies and cities of South Sulawesi can be seen in Table 2.

Table 2. Population growth scores in the regencies and cities of South Sulawesi.

Based on the Table 2, the highest LPP is owned by Tana Toraja Regency, which is equal to 1.57% where the LPP of the Regency is higher than the LPP of the Province of 0.72%, so that the level of inequality in Tana Toraja Regency is classified as low inequality. The lowest LPP is owned by Soppeng Regency at 0.17% where the Regency LPP is lower than the LPP of the Province at 0.72%, so that the level of inequality in Soppeng Regency is classified as high inequality. It can be seen that in general the level of social inequality in the South Sulawesi province in terms of population growth is classified as low inequality. This is indicated by the proportion of low inequality level owned by 13 out of 24 regencies or 54.17% and 11 out of 24 regencies or 45.83% have high inequality level.

Population density

The conce ntration of development and population density in the downtown is caused by the uneven population density of an area. This affects the development process only to occur in the downtown, thereby increasing social inequality between densely populated and sparsely populated areas. The basic assumptions for measuring the level of social inequality for the aspect of population density are as shown in Table 1. The calculation of population density scores in the regencies and cities of South Sulawesi province can be seen in Table 3.

Table 3. Population density score in the regencies and cities of South Sulawesi province.

Education level

The education level consists of several categories, namely elementary school with an age range of 7-12 years, junior high school with an age range of 13-15 years, high school with an age range of 16-18 years and education in university with an age range of 19-45 years. Comparing the population according to education level with the population according to school age (see Table 4) is the method used in this study to see regional social inequality scores according to educational level aspects as shown in Table 1. Calculation of education level scores in regencies and cities of South Sulawesi province can be seen in Table 5.

Table 4. Comparison of education level with school age in the regencies and cities of South Sulawesi.

Table 5. The educational level scores in the regencies and cities of South Sulawesi

Based on Table 5, after determining the score, it was found that the level of disparity between districts and cities in South Sulawesi province based on education level is high inequality. For the elementary education level, the number of people attending school exceeds the number of school-age residents in each district. This means that regional social inequality according to the aspect of education level for the elementary level is low inequality. Meanwhile, the number of people who have graduated from junior high school, high school and tertiary education is less than the number of people at the higher education level, so it is classified as high inequality.

Labor force

Labor force is an influential factor in regional development. The more people who work, the faster the development of a region. Regional disparities from the labour force aspect can be seen by comparing the number of working population and the working age population according to the criteria in Table 1. Calculation of the labor force scores in regencies and cities can be seen in Table 6.

Table 6. Labor force score in the regencies and cities of South Sulawesi province.

Based on the results of the analysis in table 6, the number of working people in regencies and cities of South Sulawesi province tends to be lower when compared to the working age population. So, the score results obtained show that the level of social inequality according to the aspect of labour force for each district in South Sulawesi is high. It can be seen in the following table that the ratio of the working population to the working age population is 2:1.

The average level of social inequality in the South Sulawesi province

After obtaining the social inequality scoring results for each aspect of the assessment in 24 regencies and cities, then the score results are accumulated to see the average value of the level of social inequality in the South Sulawesi province as shown Table 7.

Table 7. Social Inequality in the regencies and cities of South Sulawesi province

CONCLUSION

Socio-economic disparities in regencies and cities of South Sulawesi province are in the moderate and high inequality categories. The factors analyzed and influencing social inequality in this study are population growth, population density, level of education, and the number of workers. The average socio-economic inequality in the high category includes Selayar regency, Bulukumba regency, Bantaeng regency, Takallar regency, Pangkep regency, Soppeng regency, Wajo regency, Sidrap regency, Bone regency, Barru regency, Enrekang regency, Tana Toraja regency, North Luwu regency, Luwu regency, East Luwu regency and Makassar City. Meanwhile, the average socio-economic inequality in the moderate category includes Jeneponto regency, Gowa regency, Maros regency, Sinjai regency, Pinrang regency, North Toraja regency, Pare-pare city, and Palopo city. The recommendations to be conveyed are to expand the study by adding several related variables and developing a Green Open Space (RTH) variable to see the environmental quality of regencies and cities in responding to climate change issues.

ACKNOWLEDGMENTS

Thank you to all university leaders and all parties involved in this research.

DISCLOSURE

The author reports no conflicts of interest in this work. All authors contributed and were actively involved in the research.

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