<![CDATA[This study was conducted to determine (1) the influence of forms of interpersonal communication, group communication and mass communication carried out by agricultural extension services on the adoption rate of postharvest rice field technology innovations. (2) To find out the right form of agricultural extension communication in order to achieve the adoption of pascpapanen technological innovations. This research was conducted in Gapoktan Mulya Jaya in Babakanmulya Village, Jalaksana District, Kuningan Regency. The study was conducted from September to October 2022. This method and type of research uses descriptive quantitative methods with survey techniques and a sample of 75 members of the Association. Technical data collection is primary data obtained from interviews and questionnaires, and secondary data obtained from data obtained from literature studies and data from agencies or institutions related to research. Data Analysis techniques performed include: descriptive analysis, multiple linear regression analysis, and F test. The results of multiple linear regression analysis (1) Interpersonal Communication Variables have a real effect on the adoption rate of postharvest technology innovations in rice fields, with the results of multiple linear regression tests that have a sig value = 0.001 which means 0.001 < 0.05 and have a B value = 0.791. (2) Group communication variables have a significant effect on the adoption rate of postharvest technology innovations in rice fields, with multiple linear regression test results that have a sig value = 0.038 which means 0.038 < 0.05 and have a value of B – 0.510. (3) Mass Communication Variables have a real effect on the adoption rate of postharvest technology innovations in rice fields, with regression test results that have a GIS value = 0.002 which means 0.002 < 0.05 and has a value of 0.977. (4) The variables of interpersonal communication, group communication, and mass communication have a significant effect on the adoption rate of rice postharvest technology innovations with the results of multiple linear regression equation analysis, namely: Y = (-1.031) + 0.791 + 0.510 + 0.977 X_1 X_2 X_3.]]>
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