THE YOUTH UNEMPLOYMENT IN SRAGEN REGENCY: SAKERNAS DATA ANALYSIS

Abstract


INTRODUCTION
Over the past decade, Indonesia has experienced a phenomenon of demographic transition that has led to a long-term explosion in the number of young people.
Changes in the age structure of the Indonesian population, due to the proportion of the productive age population (15-64 years) is far greater than the population under 15 years.It results in a decrease in the dependency ratio in Indonesia, one of which is experienced by Central Java Province, one of the highestpopulation provinces in Indonesia.the government fails to manage the existing workforce, it will give a negative impact, namely disrupting economic growth (Soleh, 2017).If there are productive employment opportunities, then a substantial labor supply will increase future per capita income.
The existence of a demographic bonus and an increase in the productive age population has accentuated the problem of the growth of the workforce to be noticeable (Elfindri & Bachtiar, 2004).Until recently, the problem of unemployment and employment is still a major concern for every country around the globe, particularly developing countries (Soleh, 2017)

RESEARCH METHODS
The data source used in the study

DISCUSSION
The effect of demographic characteristics on youth unemployment can be identified using the logistic regression method.By referring to the results of the logistic regression analysis that has been carried out, simultaneously a very small significance value is attained, the value is much smaller than a 1 percent alpha.

Gender
The gender variable (male) has a One of the factors that make men have higher work participation opportunities than women is the existence of statistical discrimination in the labor market and the conditions of the neighboring community.
People in Central Java, especially Sragen Regency, still think that men are generally positioned as the main breadwinner in the household.In addition, there is still a high level of negligence of the woman's existence in the social sphere and the placement of women as second-class residents whose job is to deal with domestic categorical household chores without pay.This is in line with the statement that women are not obligated to earn a living so young unemployed women are more dominant than men.In addition, this statement is also in accordance with gender theory which states that the existence of sociocultural construction will provide different roles and labels between men and women.These differences make women always be left behind and deserted in their contributions, including their right to obtain a decent job.

Marital Status
The variable of marital status variable (married, widowed, divorced) has a significant negative effect on the probability of unemployment in the young workforce.The marital status variable (married, widowed, divorced) has a negative coefficient value of -

Status in Household
The status variable in the household The results of this study are also consistent with the findings of Pasay and Indrayanti (2012) and Khan and Yousaf (2013).
According to Pasay and Indrayanti (2012) By paying attention to this group, it is expected that unemployment can be reduced.
Source: Statistics Indonesia The significance of the logistic regression model can be seen from the results of concurrent parameter testing.Meanwhile, to identify the significance of each independent variable, a partial test was carried out with the Wald Test statistic or by considering the appropriate p-value.The interpretation of the coefficients in the logistic regression model is done in the form of Odd (risk comparison) or adjusted probability (Nachrowi & Usman, 2002).If the independent variable is considered a categorical variable with two categories (dichotomy), then parameter interpretation is executed by comparing the odd value of one of the values in the variable with the odd value of any other values (reference).For categorical independent variables with more than two categories (polytomies), the parameter interpretation for this variable uses dummy variables.If there are k categories, (k-1) dummy variables with one category will serve as the reference.
significant negative influence on the probability of unemployment in the young workforce.The gender variable (male) has a negative coefficient value of -1.102.It means that the male youth workforce (15-29 years) has a lower risk of becoming young unemployment, compared to the female youth workforce (15-29 years).The gender variable (male) has a tendency ratio value/Odd Ratio of 0.332.It demonstrates that the tendency of the young workforce (15-29 years) who are male to become young unemployed is 0.332 times lower than the female young workforce (15-29 years) if other variables are considered constant.It means that among the young workforce, men have a smaller tendency to become young unemployment.The results of this study are consistent with the findings from Tasci and Tansel (2004), Pasay and Indrayanti (2012), and Khan and Yousaf (2013), who suggested that men have higher opportunities for work participation than women.

2. 151 .
It means that the young workforce (15-29 years) who are married, divorced, or widowed have a lower risk of becoming youth unemployment compared to the young workforce (15-29 years) who have never been married.The marital status variable (married, widowed, divorced) has a propensity ratio value/Odd Ratio of 0.116.It means that the tendency of the young workforce (15-29 years) who are married, divorced, or widowed to become young unemployment is 0.116 times lower than the young workforce (15-29 years) who are single if other variables are considered constant.This result is aligned with the findings of Qayyum and Siddiqui (2008), Yuliatin, et al (2011), Pasay and Indrayanti (2012), and Nganwa, et al (2015) Wardana et., al (2019) which explained that individuals with not-married status do not have a responsibility to work on income, but individuals with a married status will do anything to earn income and their needs.The opportunity for young workers (15-29 years) who are married, divorced, or widowed to become young unemployment is low since they are considered to have a big responsibility to support their families.It is different from the young, unmarried workforce who do not yet have family responsibilities.This was also revealed by Harfina (2009) in research, who suggested that an unmarried person tends to be unemployed since that individual has no responsibilities toward the family.

(
schemes and educational services(Lundvall, 1992).In addition to training, developmentbased skills are also required for qualified human resources to broaden employment opportunities.
, the workforce that has attended job training will have a higher probability of job participation compared to people who have never attended job training.Meanwhile,Khan and Yousaf (2013) argued that a person or young workforce has attended any training or program to improve skills, so he or she is likely to experience a relatively shorter duration of unemployment.high school will increase the tendency to be unemployed by 1.433 times.While the young workforce (15-29 years) who have completed senior high school/equivalent education will increase their chances of being unemployed by 0.968 times.Meanwhile, the young workforce (15-29 years) who complete their education at university will have a lesser risk, compared to the workforce who did not graduate from university.The young workforce who complete their education up to university will increase the tendency to be unemployed by 0.298 times.The young workforce who have graduated from university have greater employment opportunities than workers with lower levels of education since the access to jobs for university graduates is greater than others.These results are in line with Human Capital Theory, which stated that education is a long-term future investment for a better future.The higher the level of education, the better jobs are expected to be obtained with relatively high wages.A higher level of education indicates an increased value in selfesteem and great productivity abilities.Better education encourages people to be more productive in building their own quality(Suhar, et al. 2010).According toLam, et.al (2008), there is a very strong correlation between the level of education and chances of being employed especially in the early years after graduation.Because the level of education has a major influence on the ability to succeed in the labor market, particularly in the direct transition from school to work.Individuals who graduate with a bachelor's degree or higher are about four to five times more likely to find a job than those with a high school certificate or less.It is clear that the benefits of educational investments or employability opportunities will vary to the level of investment and skills acquired through employment prospects.The reason for the high risk of youth unemployment among senior high school graduates/equivalent or below is due to the incompatibility of the curriculum with the realm of work.According to Dalimunthe (2015) and Ahmad and Azim (2010), the learning methods and curriculum provided in schools are theoretical but are not balanced with the provision of skills relevant to the world of work such as entrepreneurship.So that a fairly high youth unemployment rate emerged from the senior high school/equivalent group and below, as a result of skill mismatch between the education and labor market.It is aligned with the opinion of Ningrum (2013) who stated that the low quality and curriculum relevancy as well as the number of schools that are unable to meet the competencies needed by the job market, makes the workforce incapable to compete in the world of work.CONCLUSIONSBased on the National Labor Force Survey (Sakernas) of Sragen Regency in 2021, unemployment is high at a young age.This study succeeded in showing that age, gender, marital status, status in the household, training, junior high school, high school, and university have an effect on youth unemployment in Sragen Regency.The young workforce with the most risk of becoming unemployed is the young workforce with a junior high school level of education and the workforce that is classified in the older age group.Therefore, these groups need special attention due to the potential unemployment risk that may arise.

Table 1 .
Provinces with the Highest Population Density in 2021

Table 2 .
Number of Population in Central Java by Age Group 2021 in Central Java, Sragen Regency is one area that is currently enjoying the era of demographic bonuses.Sragen Regency is one of the areas with a relatively high population density in 2021, reaching up to 1,044.65 people/ Sragen Regency with an area of 941.6 km 2 .The population density in Sragen Regency is higher than the national scale, which is only 142 people/km 2 , but lower than in Central Java Province.

Table 3 .
Number of Population in Sragen Regency Based on Age Group 2021of Population in Central Java by Age Group 2021Based on Table3., it can be seen that =  ̂0 +  ̂1 +  ̂2 +  ̂3 +  ̂4ℎ +  ̂5 +  ̂6 +  ̂7 +  ̂8  .. (1) preparation is derived from Statistics Indonesia, as the result of data collection of the National Labor Force Survey (Sakernas) 2021 conducted by the Statistics Indonesia of Sragen Regency.Sakernas is a survey that is specifically designed to collect data that provide the general condition of employment in Indonesia.Young age refers to research by Qayyum and Siddiqui (2008) which defined a young age in the range of 15-29 years.This study involved a 1989 young workforce as the sample.)

Table 4 .
Research Variables

Table 5 .
The Estimation Result on Coefficient of