Hubungan Faktor Individu dan Pekerjaan sebagai Ojek Online dengan Kelelahan Kerja pada Komunitas Avengers di Kota Medan Tahun 2024

Abstract

Online motorcycle taxis are a type of personal transportation that is widely used by the public, especially in big cities, both for goods and people delivery services. The number of online motorcycle taxi drivers operating in Medan City is around 600 people, some of whom join a community according to where they operate. One of the online motorcycle taxi communities in the city of Medan is the Avengers community. Long driving distances and congested road conditions are factors that can cause work fatigue. The aim of this research is to determine the relationship of individual factors (age, gender, education level, length of service, marital status, nutritional status/BMI) and job factors (work load and length of work) as online motorcycle taxi with work fatigue in the Avengers community in Medan city. The research was conducted using quantitative methods using a cross sectional design. The population in this study were 150 online motorcycle taxi drivers at the base of Jalan Setia Budi, Jalan Pinang Baris, Jalan A.H. Nasution, Jalan Simpang Simpang Selayang and Jalan Ngumban Surbakti. Sampling used a proportional random sampling technique totaling 60 drivers. The data collection method uses the PSQI questionnaire to measure sleep quality and work fatigue measurement using a reaction timer which is then analyzed using the Spearman correlation test. The research results showed that 45% of online motorcycle taxi drivers experienced mild fatigue. In individual factors, there is a significant relationship between sleep quality and work fatigue (p=0.001) and in work factors, there is a significant relationship between workload (p=0.001) and length of work (p=0.042) and work fatigue. It is recommended that online motorcycle taxi drivers should avoid foods high in fat and caffeinated drinks, determine the maximum working hours per day, and ensure that there is rest time after making a maximum of five deliveries.