Wates Regional Public Hospital (RSUD Wates) was built in order to give health service for the people in Kulonprogo Regency. Hospital is one of the functions of land use that results in trip generation and attraction trip generation and attraction is because there are many people that go to hospital to get treatment, to make out health care security (BPJS), to visit inpatient, or only to have routine health care. The research was conducted to find out the trip generation and attraction in hospital land use so that transportation plan could be done appropriately. The method used was by writing the license plate and the time vehicles got in and came out of RSUD Wates as the primary data, while the secondary data used was the number of vehicles that got in and came out of parking lot of RSUD Sleman, and Panti Rapih Hospital, as well as the number of the bed of the patients, the number of polyclinic, the width of the building, and the number of paramedic of RSUD Wates, RSUD Sleman, and Panti Rapih Hospital. The survey was conducted for 2 days, i.e. Sunday, August 6, 2017 and Monday, August 14, 2017 started from 08.00 – 14.00. The data were then analyzed using software of Statistical Product and Service Solutions (SPSS) with vehicle coming out of parking lot as dependent variable of trip generation and vehicles getting in as dependent variable of trip attraction. Independent variables from both models were number of bed, number of polyclinic, width of the building, and number of paramedic. From the analysis, then there were the results of classical assumption test for trip generation. They were the fulfillment of the normality test with the variables of vehicles coming out, number of bed, number of polyclinic, building width, and number of paramedic consecutively i.e. 0.911, 0.835, 0.766, 0.916, 0.999, the fulfillment of multicollinearity test with Value Inflation Factor (VIF) value of number of polyclinic variable and number of paramedic variable consecutively i.e. 1.008 and 1.008, and the autocorrelation test and heteroscedasticity test which were fulfilled. The research obtained the result of trip generation regression model i.e. Y = -1,444.931 + 115.939 X2 – 0.390 X4 with independent variable of number of bed as X1, number of polyclinic as X2, building width as X3, number of paramedic as X4, and dependent variable of number of vehicles coming out as Y. the model had coefficient of determination (R2) of 1. Based on the analysis conducted, the research also obtained classical assumption test results for trip attraction. They were the fulfillment of normality test with variable of vehicles coming out, number of bed, number of polyclinic, building width, and number of paramedic, consecutively i.e. 0.873, 0.835, 0.766, 0.916, 0.999, the fulfillment of multicollinearity test with Value Inflation Factor (VIF) value of number of polyclinic variable and number of paramedic variable consecutively i.e. 1.008 and 1.008, and the autocorrelation test and heteroscedasticity test which were not fulfilled. The regression model produced for trip attraction was Y = -906.420 + 82.891 X2 + -0.488 X4 with independent variable of number of bed as X1, number of polyclinic as X2, building width as X3, number of paramedic as X4 and dependent variable of number of vehicles coming out as Y. The model had coefficient of determination (R2) of 1.