Awareness of the halal concept is followed by awareness of the importance of halal certification. In addition, producers must also understand the stages and procedures for applying for halal certification. The practice of halal certification in its implementation also requires motivation and commitment from the producers.
Among these studies, it is concluded that halal certification has become part of an innovative strategy that leads to improved business performance (Supian et al., 2018;. Studies related to halal certification have been found to be mainly related to the behavior or intention of consumer purchasing Most previous studies regarding halal certification and manufacturers treated halal certification as the independent variable of business or financial performance.
Studies related to halal certification and producers' intention have also been conducted and mostly qualitative studies. Especially for Indonesia, the halal certification recognized by the institution is LPPOM MUI and BPJPH. Previously, halal certification was voluntary, in the Halal Assurance Regulation it is now mandatory.
Method
One of the important statistical analyzes in PLS-SEM modeling is to estimate and evaluate statistics on the resulting model. This phase involves the theoretical specification of the relationship between latent variables and how each latent variable will be measured. The path diagram illustrates the research hypothesis and shows the relationship between the variables to be tested.
In PLS-SEM, Average Variance Extracted (AVE) can be used to determine the convergent validity of the construct being measured. Multicollinearity is a phenomenon in which two or more exogenous constructs (latent variables) are highly correlated, causing the predictive power of the model to decrease. Furthermore, the determination coefficient (R2) measures the accuracy of the model's predictions and is calculated as the squared correlation between the actual value and the predicted specific endogenous constructs.
It is difficult to provide a rule of thumb for an acceptable value of R2 because it depends on the complexity of the model and the research discipline. Apart from evaluating the magnitude of the R2 value as a criterion for predictive accuracy, the Stone-Geisser Q2 value should also be examined (Geisser, 1974; Stone, 1974). In the structural model, a Q2 value greater than zero for a specific reflective endogenous latent variable indicates the predictive relevance of the path model for a specific construct.
The overall model fit test aims to determine whether the predictive value of the model tends to accurately predict the response to other samples. It is therefore possible to assess the average size of the difference between the observed and expected correlations as the absolute measure of the fit criterion (model). The halal status of the product is important to me A1 I know exactly the halal status of all the materials I use (including the . main and supporting materials).
My closest friends suggest that I should confirm the halal status of the products I make/sell. My teacher / Ustadz / Ustadzah suggested that I confirm the halal status of the products I manufacture/sell. My neighbor told me that I need to confirm the halal status of the products I make/sell.
People around me have suggested that I should confirm the halal status of the products I make/sell.
Result and Discussion
External model evaluation is performed to assess the validity and reliability of the manifest variable in measuring each latent variable. Testing an external model that is reflective is generally done using three measures, namely convergent validity and discriminant validity. Convergent validity can be assessed by looking at the results of the factor loading measurement model as well as the average variance extracted (AVE) exceeding 0.5 (Hair et al. 2014).
In Table 4.2 it can be seen that the AVE value of all latent variables used in the model is greater than 0.5. This shows that the average of each latent variable can explain more than 50 percent of the variation in the measurement indicators. Furthermore, the reliability of the measurement model can be assessed using three values, namely the Cronbach alpha coefficient above 0.6, the rho_A coefficient above 0.6, and the composite reliability value above 0.7 or greater (Fornell and Larcker 1981).
In PLS-SEM modeling, structural model evaluation can be performed using three indicators, namely: Variance Inflation Factor (VIF) and Coefficient of Determination (R2). Multicollinearity is a phenomenon where two or more exogenous constructs are highly correlated, causing the predictive ability of the model to decrease. This coefficient is a measure of the predictive accuracy of the model and is calculated as the squared correlation between the actual and predicted values of a particular endogenous construct.
Table 4.6 also shows that the results of the overall fit model test for the manufacturer's model. As with the manufacturer's model, the Standardized Root Mean Square Residual (SRMR) is used here as the appropriate measure for PLS-SEM to avoid model specification errors. This section presents an analysis of the influence of the variables Attitude, Functional Factors, Subjective Norms, Perceived Behavioral Control and Confidence of MSME Producers on Halal Certification Intention based on the estimation results of the PLS-SEM model.
Furthermore, Table 4.7 presents the results of the significance test of the direct effect of each exogenous latent variable on the endogenous latent variable. In addition, using a realistic level of 1% and 5% alpha, it can be seen that out of 8 (eight) available hypotheses, 6 (six) hypotheses are rejected with the conclusion of H0, which means that the hypothesis that endogenous latent variables have a significant effect on endogenous latent variables. In addition, there is a need for a trusted authority to play an important role in issuing halal certificates for suppliers so that consumers can be assured of the halal status of the product (Hanzaee and Ramezani, 2011).
So that companies must implement a halal assurance system to obtain halal certification so that producers and consumers are equally sure of the quality and halal status of the products being marketed (Ghazali and Md.
Conclusion and Recommendation Conclusion
The other six are found to be significant at 1% alpha; belief to intention, subjective norm to belief, subjective norm to intention, perceived behavioral control to attitude and functional factor to belief and functional factor to attitude. interested in similar research topics in an effort to strengthen studies related to the determinants of halal certification by manufacturers. To increase the number of halal certifications, especially for kitchen products in the Bogor Raya area, it is necessary to carry out continuous socialization so that people, especially producers, have good motivation to carry out and renew halal certification. The relevant authorities can educate about the importance of halal certification and that this can also be used as a strategy to increase sales.
This is primarily aimed at increasing the public's trust, especially of producers, in order to adequately maintain the motivation to apply for the halal certificate and the motivation to renew the halal certificate. Further research can use in-depth interview methods and qualitative research methods to better explore the causes and barriers related to efforts to increase halal certification in Indonesia, both from the producer side and the halal certification body side. 2017), “Linking Halal Food Certification and Business Performance”, British Food Journal, Vol. 2008), "SMEs and halal certification", in Thrusting Islam, Knowledge and Professionalism in ECER Development: ECER Regional Conference, Kelantan, Malaysia, 15-17 December 2008, UPENA UiTM, Shah Alam, p. The Mediating Role of Organizational Reputation and Trust in Intention to Use Wearable Health Devices: A Cross-Country Study.
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