The Influence of Social Media Marketing Instagram and Word of Mouth On D3.Kitch Consumer Purchasing Decisions in Makassar City

Abstract

This research aims: (i) to determine the influence of social media marketing Instagram decisions on purchasing (ii) to determine the influence of words of mouth on purchasing decisions (iii) to determine the influence of social media Instagram marketing and word of mouth simultaneously influence decisions D3.Kitch consumer purchases in Makassar city. This type of research is quantitative associative. The population in this study were followers of Instagram accounts @d3.kitch totaling 804 accounts and using sampling techniques deliberate sampling. With the sampling method contained, the sample size was 90 respondents. The data collection technique used is observation, online questionnaires and documentation. Then the analysis techniques used are research instrument tests (validity and reliability), multiple linear regression analysis, hypothesis testing (partial and simultaneous). The results obtained in this research are (i) Instagram social media marketing has a significance level of 0.001 i.e. smaller than 0.05. The coefficient value of 0.313 shows the influence given is positive for the dependent variable. This means that H1 is accepted and Ho is rejected so it can be said that social media marketing is Instagram positive and significant effect on purchasing decisions (ii) word of mouth has a significance level of 0.000, which is smaller than 0.05. The coefficient value a value of 0.716 indicates that the influence given is positive on the variable depending. This means that H2 is accepted and Ho is rejected so it can be said that Word of mouth has a positive and significant effect on purchasing decisions (iii) Instagram social media marketing and word of mouth variables have levels of significance is smaller than 0.05. This means that H3 is accepted so it can be said that social media marketing Instagram and word of mouth simultaneously (together) have an influence on purchasing decisions, with a probability of 0.000. Because the probability is much smaller than the significant value of 0.05, the regression model can be used to predict purchasing decisions.