Huyula participation model and its impact on community behaviour in rehabilitating critical agricultural lands

Abstract

The low application of conservation techniques is in line with the increasing criticality of agricultural land. Weak awareness of sustainable land management also reduces community participation in managing land wisely. This is where the form of local wisdom intervention becomes a synthesis of the downturn in the socio-cultural aspects of agriculture. So the focus of this study is to design a model of the influence of huyula participation and its impact on community behaviour in critical land rehabilitation activities. This study uses an ex post facto approach combined with a literature review. Using a survey method, with various exogenous parameters (X), namely motivation (X1), togetherness (X2), and concern (X3), the endogenous parameters (Y) namely parental participation (Y1) and their impact on abusive behaviour (Y2). The research was conducted from March to August 2022 in Limboto watershed, with a sample size of 166 respondents. In designing a model of the influence of various parameters, SEM analysis was carried out (Structural Equation Model) Partial Least Square-based (PLS). The results showed that: (i) the factors of motivation, togetherness, and caring directly had a positive and significant effect on huyula participation, with R2 of 0.577; (ii) the factors such as motivation, concern, and participation directly have a significant positive effect on huyula behaviour, but not significant on the parameter of togetherness. The value of R2 of 0.786; (iii) all factors indirectly have a significant positive effect on huyula behaviour through the parameters of huyula participation; (iv) the ability of the research parameters to explain the model from the results of the Q2 value by 79.40%. These results indicate that increasing motivation, togetherness, community awareness will be able to increase their participation which has an impact on improving behaviour in managing critical land in Limboto watershed. Thus the model created is able to explain the diversity of research data information.

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