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This study aims to determine the workload of rice harvesters in different harvesting technologies and find ways to reduce the physical workload. The physical workload is shown by the magnitude of a worker's heart rate at work. The linear regression model is used to identify the independent variables that affect the workload dependent-variable. Heart rate and body temperature as the dependent variable are thought to be influenced by independent variables such as age, Body Mass Index, ambient temperature and humidity, and noise. Statistically the workload of workers in the manual harvest method is at the medium level, while the semi-mechanical and mechanical methods are at a low workload level. Factor that play a role in the physical workload of all harvesters is environmental temperature. To reduce the physical workload of manual workers by combining four alternative solutions, wearing red or blue clothes, using harvest tents, drink a lot, and using ergonomic tools.A post-publication change was made to this article on 11 Mar 2020 to correct the conference title in the PDF header.