Analisis Terhadap Hasil Survei Persepsi Risiko Covid-19 Menggunakan Generalized Structured Component Analysis

Abstract

Ibu kota Indonesia, DKI Jakarta, menjadi provinsi dengan jumlah Covid-19 tertinggi. Merespon hal ini, LaporCovid-19 bekerja sama dengan Social resilience Lab, Nanyang Technological University melakukan survei untuk mengukur bagaimana persepsi warga Jakarta terhadap risiko Covid-19 mulai 29 Mei hingga 20 Juni 2020. Peubah yang memengaruhi persepsi risiko merupakan peubah yang tidak dapat diukur. secara langsung sehingga dianalisis menggunakan pendekatan Structural Equation Modeling (SEM), yaitu Generalized Structured Component Analysis (GSCA). Skala likert bersifat ordinal tetapi ada beberapa penelitian menggunakan skala likert sebagai interval. Oleh karena itu, penelitian ini akan membandingkan metode GSCA dengan nonlinear GSCA dan mengevaluasi enam peubah, yaitu persepsi risiko, pengetahuan, informasi, peilaku kesehatan, modal sosial, dan ekonomi. Evaluasi model secara keseluruhan menunjukkan bahwa nonlinear GSCA dapat menjelaskan keragaman data kualitatif lebih baik daripada GSCA dengan FIT > 0.9. Nonlinear GSCA menghasilkan peubah informasi berpengaruh terhadap pengetahuan, ekonomi dan modal sosial memiliki hubungan timbal balik, sedangkan pengetahuan dan persepsi risiko berpengaruh terhadap perilaku kesehatan.

The capital city of Indonesia, Jakarta, became the province with the highest number of Covid-19. Response this situation, LaporCovid-19 collaborate with the Social Resilience Lab, Nanyang Technological University conducted a survey to measure how Jakarta residents perceive the risk of Covid-19 from May 29 to June 20 2020. Factors of risk perception are variables that cannot be measured directly, so they are analyzed used a Structural Equation Modeling (SEM) approach, namely Generalized Structured Component Analysis (GSCA). The Likert scale used can be considered as interval or ordinal depending on the point of view of the theory built. Therefore, this study will compare the GSCA method with the nonlinear GSCA and evaluate six variables, namely risk perception, knowledge, information, health behavior , social capital, and economy. Evaluation of the overall model showed that the nonlinear GSCA model can explain the diversity of qualitative data better than the GSCA model with FIT > 0.9. Based on GSCA nonlinear model, information has significantly influence of knowledge, economy and social capital have a real reciprocal relationship, along knowledge and risk perception have significantly influence of health behavior.