Penerapan Metode Principal Component Analysis (PCA) Untuk Identifikasi Faktor-Faktor yang Mempengaruhi Sikap Mahasiswa Memilih Melanjutkan Studi ke Kota Malang

Abstract

The future of a nation depends on how good the quality of education and human resources of the nation is. Higher education is an important part of the world of education that carries the responsibility in an effort to educate the nation's life. This study aims to determine the factors that influence student attitudes in choosing to continue their studies at Islamic Higher Education (PTAI). The background of this research is that there is a significant gap between PTN and PTAI enthusiasts and the lack of student interest in Islamic tertiary institutions is very interesting to be used as research study material to find out things that are considered by students in choosing PTAI. The results of the study indicate that the data used have met the assumption test of validity, reliability, adequacy and feasibility of the data so that it can be continued in the next analysis using factor analysis using PCA. All the variables contained in this study have an extraction value of more than 50%, so it can be concluded that all the variables used can explain these factors. In the "% of variance" column, because the specified eigenvalues ​​is 1, then the value to be taken has eigenvalues ​​greater than 1, there are component 1, component 2, component 3, component 4, and component 5. If you use 5 components then the total factors that can explain the variance are 20.011% + 19.692% + 15.935% + 14.632% + 10.745% = 81.015%

Analisis Principal Component Analysis (PCA) dalam Penentuan Faktor Kepuasan Pengunjung terhadap Layanan Perpustakaan Digilib

“…Pada penelitiannya mereka menggunakan metode untuk mereduksi 4 variabel yang berkorelasi menjadi 2 faktor baru yang tidak terdapat korelasi. Selain itu penelitian yang dilakukan oleh (Badri & Sari, 2021) dengan menggunakan metode yang sama yaitu Principal Compenent Analysis pada penelitiannya dalam penentuan faktor yang mempengaruhi sikap mahasiswa memilih program studi tadris matematika UIN Malang. Pada penelitiannya Badri menggunakan metode PCA untuk mereduksi 20 variabel yang berkorelasi menjadi 5 faktor yang mempengaruhi sikap mahasiswa memilih melanjutkan studi ke PTAI.…”

Application of Principal Component Analysis Method on Tutor Performance Assessment Instruments With Jeffreys's Amazing Statistics Program Formula

“…PCA can reduce data easily to simplify the observed variables by shrinking their dimensions. (Fenyvesi & Horváth, 2022) (Badri & Sari, 2021) (Wangge, 2021) This step is done to eliminate the correlation between variables by forming new sub-variables. CONCLUSION Based on the results of research using factor analysis using the PCA method, it is concluded that the tutor's performance assessment instrument has formed eleven main components with various sub-variables of each component such as seven sub-variables, three sub-variables, two sub-variables, and one sub-variable with a high correlation matrix value so that the tutor's performance assessment instrument can be declared to have a high level of validity and reliability so that it is appropriate to be used to assess the tutor's performance.…”