Effect of Marketing Mix on Decisions to Add Customer Electricity (Case Study in Pt Pln (Persero) Tolitoli Customer Service Implementation Unit)

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dc.creatorRajavalens, Muhammad
dc.creatorLapian, SLHV Joyce
dc.creatorJan, Arrazi Hasan
dc.date2022-10-13
dc.date.accessioned2023-08-20T06:05:11Z
dc.date.available2023-08-20T06:05:11Z
dc.descriptionThe purpose of this study was to determine the effect of Product Marketing Mix (X1), Price (X2), Place (X3), and Promotion (X4) on the Decision to Add Electricity to Customers (Y) at PT PLN (Persero) UP3 Tolitoli. The test results conclude that the Product Factor has a positive effect on Purchase Decisions but is not significant. The probability of this variable is 0.373, which is greater than the 0.05 significance level, so the effect of Product Factor on Purchase Decision is not significant. The test results show that the Price Factor has a positive and significant effect on Purchase Decision. This is obtained from the p-value which is less than a significance level of 0.05, which is 0.001. Place has a positive and significant effect on purchasing decisions. This is because the probability value of 0.002 is smaller than the significance level of 0.05. Promotion has a positive and significant effect on purchasing decisions. This is because the probability value is less than the 0.05 significance level, which is 0.012. Consumers have a positive effect on purchasing decisions but not significant. The probability of this variable is 0.469 which is greater than the 0.05 significance level so that the influence of consumers on purchasing decisions is not significant. The process has a positive and significant effect on purchasing decisions. This is because the probability value is less than the 0.05 significance level, which is 0.025. The resulting R-Square value is 0.571. This means that the product factors, place factors, price factors, promotion factors, people factors and process factors contribute 57.1 percent in explaining their relationship to the purchasing decision variables. While the remaining 42.9 percent are influenced by other variables outside the model. The probability of this variable is 0.469 which is greater than the 0.05 significance level so that the influence of consumers on purchasing decisions is not significant. The process has a positive and significant effect on purchasing decisions. This is because the probability value is less than the 0.05 significance level, which is 0.025. The resulting R-Square value is 0.571. This means that the product factors, place factors, price factors, promotion factors, people factors and process factors contribute 57.1 percent in explaining their relationship to the purchasing decision variables. While the remaining 42.9 percent are influenced by other variables outside the model. The probability of this variable is 0.469 which is greater than the 0.05 significance level so that the influence of consumers on purchasing decisions is not significant. The process has a positive and significant effect on purchasing decisions. This is because the probability value is less than the 0.05 significance level, which is 0.025. The resulting R-Square value is 0.571. This means that the product factors, place factors, price factors, promotion factors, people factors and process factors contribute 57.1 percent in explaining their relationship to the purchasing decision variables. While the remaining 42.9 percent are influenced by other variables outside the model. The process has a positive and significant effect on purchasing decisions. This is because the probability value is less than the 0.05 significance level, which is 0.025. The resulting R-Square value is 0.571. This means that the product factors, place factors, price factors, promotion factors, people factors and process factors contribute 57.1 percent in explaining their relationship to the purchasing decision variables. While the remaining 42.9 percent are influenced by other variables outside the model. The process has a positive and significant effect on purchasing decisions. This is because the probability value is less than the 0.05 significance level, which is 0.025. The resulting R-Square value is 0.571. This means that the product factors, place factors, price factors, promotion factors, people factors and process factors contribute 57.1 percent in explaining their relationship to the purchasing decision variables. While the remaining 42.9 percent are influenced by other variables outside the model. People Factors and Process Factors contributed 57.1 percent in explaining their relationship to the Purchasing Decision variable. While the remaining 42.9 percent are influenced by other variables outside the model. People Factors and Process Factors contributed 57.1 percent in explaining their relationship to the Purchasing Decision variable. While the remaining 42.9 percent are influenced by other variables outside the model.en-US
dc.formatapplication/pdf
dc.identifierhttps://economics.academicjournal.io/index.php/economics/article/view/582
dc.identifier.urihttp://dspace.umsida.ac.id/handle/123456789/6547
dc.languageeng
dc.publisherAcademic Journal Incorporationsen-US
dc.relationhttps://economics.academicjournal.io/index.php/economics/article/view/582/589
dc.rightshttps://creativecommons.org/licenses/by/4.0en-US
dc.sourceAcademic Journal of Digital Economics and Stability; Vol. 22 (2022): Academic Journal of Digital Economics and Stability; 70-82en-US
dc.source2697-2212
dc.subjectMarketing Mixen-US
dc.subjectDecisionen-US
dc.subjectCustomer Serviceen-US
dc.titleEffect of Marketing Mix on Decisions to Add Customer Electricity (Case Study in Pt Pln (Persero) Tolitoli Customer Service Implementation Unit)en-US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typePeer-reviewed Articleen-US
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