Interventions to Improve Education Indicators Based on the Dynamic System Scenario Model

Interventions to Improve Education Indicators Based on the Dynamic System Scenario Model

DOI: 10.4018/978-1-6684-8646-7.ch015
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Abstract

Equal education is one option that requires more attention in efforts to improve RLS. Equality is a policy for workers who do not have a certain education certificate. The most effective efforts to improve RLS are interventions at the tertiary level as well as equalization education. This research is a mix-method study with two respondents, stakeholder respondents or policymakers and expert respondents. The methods used are descriptive analysis, linear and non-linear quadratic trend analysis, system dynamics analysis, and interpretative structural modeling analysis. Considering that access to education is very far away and the low economic capacity of the community, it can be considered to carry out learning for this equivalence education online. Therefore, a strategy is needed for interventions to increase education by increasing public awareness, increasing and optimizing scholarship programs, optimizing education funding, increasing coordination between institutions, optimizing educational institutions, and evaluating the adequacy and feasibility of equalizing institutions.
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Method

Acceleration and improvement of the human development index in South Kalimantan need to consider the interconnections among the variables that form the index, which is multidimensional in nature. The three dimensions in the human development index are units that can influence each other. This research strategy for accelerating the improvement of the human development index focuses on the educational dimension. Based on the theory of human capital by Theodore Schultz in 1960, it was stated that education is a form of investment in human resources that can provide economic and non-economic benefits. Increasing the education index is expected to accelerate the increase in the human development index and can improve the other two dimensions in the future.

The types of data used are secondary data and primary data. Secondary data was obtained through literature studies, such as the results of studies, reports, documents, and other related data from various agencies related to the human development index. Primary data is obtained directly from the results of interviews, questionnaires, and the analysis of the results of the human development index in South Kalimantan.

There are two types of respondents in this study: stakeholder respondents, or policymakers, and expert respondents. Stakeholder respondents were determined by policymakers related to the human development index in districts, cities, and provinces. Expert respondents were determined by six experts, namely academics, the Central Statistics Agency, researchers, and three provincial-level policymakers. The determination of the number of expert respondents is based on the fact that the number of expert respondents who have a high level of precision is between five and six (Hora, 2004).

The method of analysis in this study is divided into three parts, namely the first analysis of the achievement of the human development index with descriptive analysis by presenting data on the achievements of the human development index and its component indexes, the analysis of growth, and the analysis of linear and non-linear quadratic trends. The second analysis used to construct the model in this study uses the System Dynamics Analysis method. The system dynamics methodology based on the concept of feedback from control theory developed by Forrester (1968) is the most appropriate technique for dealing with such complex systems to improve systems thinking (Bala et al., 2016).

The third analysis is the interpretative structural modeling analysis. Interpretative structural modeling is a technique developed for strategic policy planning.

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