LATENT AND MANIFEST VARIABLES OF PLS-SEM MODEL USED IN DECISION MAKING OF ATTRACTOR INNOVATION BASED ON SOUND WAVES “PIKNET” BY FISHERMEN IN BULAK SURABAYA DISTRICT

LATENT AND MANIFEST VARIABLES OF PLS-SEM MODEL USED IN DECISION MAKING OF ATTRACTOR INNOVATION BASED ON SOUND WAVES “PIKNET” BY FISHERMEN IN BULAK SURABAYA DISTRICT 1 Nurul Rosana, 2 Nuddin Harahab, 3 Gatot Ciptadi, 4 Andi Kurniawan 1 Fisheries Program, Engineering and Marine Science Faculty, hang Tuah University and student of Postgraduate Environmental Science Doctoral Program, Brawijaya University 2,3,4 Postgraduate Environmental Science Doctoral Program, Brawijaya University nurul.rosana@hangtuah.ac.id nuddin.harahab@gmail.com ciptadi@ub.ac.id andi_k@ub.ac.id Abstract The success of implementing an innovation is closely related to the process of diffusion of innovation, where it is hoped that a person or group who will adopt it has belief that the innovation is beneficial in terms of various factors. In this paper, the innovation that will be studied is a sound wave-based attractor named "Piknet" which will be tested on a group of fishermen in Bulak District, Surabaya. The purpose of the study was to determine the latent and manifest variables of the PLS-SEM model used in making decisions about "piknet" innovations by fishermen in Bulak District, Surabaya. The SEM PLS method is a data analysis method that can be used to determine the relationship between latent variables and manifest variables, where latent variables are variables that cannot be measured directly, or also called construct variables. While the manifest variable is a variable that can be used to measure or explain latent variables or also called indicator variables or manifest variables. The results of the study using the SEM-PLS approach can be seen that the latent variables/constructs used are 7 variables and the manifest/indicator variables used consist of 24 variables. Keywords: innovation, piknet, latent, manifest