Pemodelan Regresi Data Panel Angka Partisipasi Murni Jenjang SMA/sederajat di Provinsi NTT Periode Tahun 2015-2019

Verlita, Tita (2021) Pemodelan Regresi Data Panel Angka Partisipasi Murni Jenjang SMA/sederajat di Provinsi NTT Periode Tahun 2015-2019. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

Text 06211740000032_Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 October 2023. Download (1MB) | Request a copy

Abstract

Angka Partisipasi Murni (APM) merupakan salah satu indikator yang berguna untuk melihat tingkat keberhasilan yang dicapai pemerintah dalam upaya peningkatan mutu pendidikan. APM SMA/sederajat di Indonesia tahun 2015-2019 tergolong paling rendah yaitu masih berkisar 60%, jika dibandingkan dengan APM SD/sederajat yang berkisar 97% dan APM SMP/sederajat yang berkisar 78%, hal ini menunjukkan bahwa semakin tinggi tingkatan pendidikan maka semakin rendah partisipasi penduduk dalam melanjutkan pendidikan. Provinsi NTT merupakan salah satu provinsi yang capaian nilai APM SMA/sederajat selama periode tahun 2015-2019 selalu di bawah nilai APM jenjang SMA/sederajat nasional dan selalu berada di posisi ketiga dan keempat terendah. Sehingga, peneliti ingin mengetahui faktor apa saja yang mengakibatkan rendahnya capaian nilai APM SMA/sederajat di Provinsi NTT periode tahun 2015-2019 dengan menggunakan metode regresi data panel. Penggunaan metode ini berguna untuk mengetahui pengaruh variabel independen terhadap variabel dependen yang modelnya merupakan kombinasi dari data cross section dan data time series. Pada penelitian ini, estimasi model terbaik untuk menganalisis APM jenjang SMA/sederajat di Provinsi NTT yaitu Fixed Effect Model (FEM) individu waktu dengan variabel yang berpengaruh signifikan yaitu rasio murid terhadap sekolah jenjang SMA/sederajat dan kepadatan penduduk serta dihasilkan kebaikan model (R^2) sebesar 87,61%.
=================================================================================================
The Net Enrollment Rate (NER) is one useful indicator to see the level of success achieved by the government in efforts to improve the quality of education. The NER for SHS (Senior High School)/equivalent in Indonesia in 2015-2019 is the lowest, which is still around 60%, when compared to the NER for Elementary School/equivalent which is around 97% and the NER for JHS (Junior High School)/equivalent which is around 78%, this shows that the higher the level of education, low population participation in continuing education. NTT Province is one of the provinces where the achievement of the NER for SHS/equivalent during the 2015-2019 period is always below the NER for the national SHS/equivalent level and is always in the lowest third and fourth positions. Thus, the researcher wants to know what factors cause the low achievement of the NER for SHS/equivalent in NTT Province for the 2015-2019 period by using the panel data regression method. The use of this method is useful to determine the effect of the independent variable on the dependent variable whose model is a combination of cross section data and time series data. In this study, the best estimation model for analyzing the NER for SHS/equivalent in NTT Province is the Fixed Effect Model (FEM) individual time with variables that have a significant effect, namely the ratio of students to high school/equivalent levels and population density and the resulting goodness of the model (R2) by 87,61%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Education, Fixed Effect Model of Individual Time, NER for SHS/equivalent level, Panel Data Regression, APM jenjang SMA/sederajat, Fixed Effect Model Individu Waktu, Pendidikan, Regresi Data Panel.
Subjects:	H Social Sciences > HA Statistics > HA29 Theory and method of social science statistics
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Tita Verlita
Date Deposited:	27 Aug 2021 07:07
Last Modified:	27 Aug 2021 07:07
URI:	http://repository.its.ac.id/id/eprint/90468

Actions (login required)

View Item