5th INTERNATIONAL CONGRESS ON KHAZAR SCIENTIFIC RESEARCH AND INNOVATION
THE STATISTICAL ANALYSIS OF COMPLIANCE WITH WORKING HOURS AMONG PUBLIC PERSONNEL
The 657 Civil Servants Law clearly defines the duties, responsibilities, fundamental rights, and obligations of public personnel, as well as the rules they must follow. Regarding working hours for public personnel, the law specifies that the standard weekly working duration is 40 hours, with Saturdays and Sundays designated as rest days. It also states that the start and end times of daily work, along with lunch breaks, will be determined by the Council of Ministers upon the recommendation of the State Personnel Department at the central level, and by governors at the provincial level. In Diyarbakır, these working hours have been set by the governorate as 08:00-12:00 and 13:00-17:00. Since factors affecting adherence to working hours are frequently brought up by employees in public institutions, there has arisen a need to investigate these factors. In this study, a survey was conducted among employees of a public institution in Diyarbakır province to examine factors influencing tardiness or early departures over the past year. Data were compiled and analyzed using statistical methods to determine the significance of these factors on late arrivals and early departures. Factors often cited by employees, such as having children, distance from home to the workplace, and reliance on public transportation, were considered. Additionally, demographic characteristics like employment status, years of service, age, gender, and job title were examined for their influence on compliance with working hours. The study used t-tests to analyze whether there were statistically significant differences between binary categorical variables and the number of days employees arrived late or left early. For variables with more than two categories, Analysis of Variance (ANOVA) was employed to determine if differences in mean tardiness or early departure days were statistically significant. Quantitative variables were converted into categorical variables, and their relationships with tardiness or early departures were examined using Chi-Square analysis.
