Biserial Point Correlation to Measure The Relationship Between The Characteristics of Health Workers at Undata Palu Hospital with Antibody Levels - Fadjriyani; Mohammad Fajri; Hartayuni Sain; Gamayanti, Nurul Fiskia; Rais (Program Studi Matematika, Universitas Tadulako, 2024)
Correlation analysis is a term in statistics commonly used to study the relationship between variables. The purpose of this analysis technique is to get a pattern of the closeness or strength of the relationship between two variables expressed by the correlation coefficient. The correlation coefficient is a value that indicates whether or not there is a strong linear relationship between two variables. This study aims to find the relationship between the characteristics of health workers at Undata Hospital Palu and antibody levels. The characteristics of health workers are nominal data with two categories while antibody levels are measured using ratio or interval data. This type of data is suitable to be analyzed using point biserial correlation technique. There are several variables of respondent characteristics that influence immune performance, namely gender, presence or absence of comorbidities, smoking habits, health conditions, exercise habits, close contact with patients and vaccine history. The results of the correlation analysis showed that all respondent characteristic variables had a very weak correlation with antibody levels. This is indicated by the correlation coefficient value of each variable of 0.034; 0.062; 0.063; 0.074; 0.020; 0.079 and 0.119. This means that the characteristics of respondents do not really affect the rise and fall of antibody levels. However, vaccine history has the highest correlation coefficient compared to other variables. This indicates that one of the prevention efforts against infectious diseases is the administration of vaccines.