Binary Logistic Regression of Student Participation Levels from FMIPA at UNSOED in the 2024 General Elections

Awis Paramita Damayanti; Agung Prabowo; Agus Sugandha; Sukono Sukono

Awis Paramita Damayanti Mathematics Study Program, Mathematics Department, Faculty of Mathematics and Natural Sciences, Universitas Jenderal Soedirman, Purwokerto, Indonesia.
Agung Prabowo Statistics Study Program, Mathematics Department, Faculty of Mathematics and Natural Sciences, Universitas Jenderal Soedirman, Purwokerto, Indonesia.
Agus Sugandha Mathematics Study Program, Mathematics Department, Faculty of Mathematics and Natural Sciences, Universitas Jenderal Soedirman, Purwokerto, Indonesia.
Sukono Sukono Mathematics Department, Faculty of Mathematics and Natural Sciences, Universitas Padjdajaran, Sumedang, Indonesia.

Abstract

Student voter participation is essential for reinforcing democracy, particularly as elections approach. Understanding the factors that drive young people’s decisions to participate is critical for fostering political engagement. This study models the voter participation levels of FMIPA students at UNSOED for the 2024 elections using binary logistic regression. This method was selected for its effectiveness in assessing how independent variables influence a dichotomous dependent variable (participation: yes or no). Data were gathered through an online survey targeting FMIPA students, examining factors such as gender, political interest, parental motivation, the impact of social media, and trust in government. Remarkably, 94.7% of respondents reported exercising their voting rights in the 2024 elections. The analysis reveals that political interest, parental motivation, social media influence, and trust in government significantly affect student voter participation.