Machine Learning for Indonesian Education Challenges

Abstraksi

To be the major country for economic and social development, human capital development has critical role to drive the system. However, the education challenges remain including the risk of dropping out, not complete the education on time, quality of education, and expanding enrolment in secondary and tertiary education. The government of Indonesia has implemented 12-year for compulsory education that is successfully viewed to support the children to achieve the higher education level. However, the 12-year compulsory education has not been applied yet in all schools. Along with the advance of technology, the existence of Artificial Intelligence (AI) and machine learning are seen the solution that potentially able to tackle the problems from society. Machine learning can be an approach to target early and do an intervention at students that face challenges such as graduate on time, continue to pursue the next education level, and the risk of dropping out. This research use qualitative method, elaborating Lakkaraju, et.al and Aulck, et.al methodology for Indonesia case, who use machine learning to predict the number of dropout and complete the education level and enrolment number. The paper will be structured: (1) education challenge in Indonesia, (2) the methodology on how machine learning can contribute to education, especially to understand the risk of dropping out, complete the education on time, and the enrolment number of the next education level. This paper shall contribute on how using technology for Indonesia education especially in different provinces that showing the high inequality number.