International Journal of Information System and Innovation Management Volume 1 Issue 1 June 2023 Page : 32-45 Unravelling Factors Shaping Purchase Intention for AuTriAy Cellular Card Dewi Karina1.
Andi Oh2.
Zulfadli Hamzah3 School of Business.
Institut Bisnis dan Teknologi Pelita Indonesia.
Indonesia1,2 Universitas Islam Riau3 Dewikarina1688hui@gmail.
Submitted: 29 May 2023.
Accepted: 20 June 2023.
Published: 30 June 2023
ABSTRACT
This study aims to investigate the factors that affecting purchase intention of Three products at Qmotion Shop in Pekanbaru .
Factors examined in this study is the quality of the product, brand awareness, and promotion as an independent variable on purchase intentions as the dependent The method used in sampling is a non probability method with accidental sampling techniques and the population is people who had bought and consumed Three products at Qmotion shop Pekanbaru.
A total of 80 questionnaires, 80 questionnaires that can be used for statistical analysis using SPSS 16.
0 program.
The results of this study indicate that the variable of quality of the product, brand awareness, and promotion have positive significantly influence purchase intention.
Keywords: Product quality, brand awareness, promotion, purchase decision.
Introduction In the era of globalization, mobile telecommunications are no stranger to us.
Especially in Indonesia.
Indonesia is one of the largest countries that uses cellular telecommunications The entry of cellular telecommunications into Indonesia in 1984 but with various developments continuously, it has caused the emergence of public buying intentions on a product, brand, and quality is very high.
in intense competition between companies, especially in companies engaged in telecommunications.
One of the companies PT Hutchison Indonesia is experiencing quite rapid development by issuing 3 card products in various variants of telephone packages and internet packages.
(Tr.
from English for the number three: "Three" is the brand name used for nine mobile telecommunications networks in Europe.
Asia and Australia.
The network is present in Australia.
Austria.
United Kingdom.
Denmark.
Hong Kong.
Indonesia.
Ireland.
Italy and Sweden.
Tri was founded in 2002 and entered Indonesia in 2009.
In making a purchase decision, consumers must consider the product to be purchased, one of which is Product Quality.
Brand Awareness, and Promotion.
These considerations are very important in making consumer purchasing decisions.
Tri cards provide several variant services including SIM cards, quota cards, credit, and vouchers to attract consumer buying Qmotion stores sell and provide many variant offers, especially on Tri card products in order to be of buying interest to consumers.
Based on the data, from January to December 2016 the total sales of the four variants of Tri card products amounted to Rp86,430,000 with the highest sales figure being the Tri Quota Card with RP48,600,000 or 56.
Next in second place is Tri Credit with sales of Rp23,025,000 or 26.
Next in third place is Tri Credit Voucher with sales of Rp13,770,000 or 18.
Furthermore, the fourth rank is Tri SIM Card Karina et al.
, .
Sales with sales of Rp1,035,000 or 1.
However, the data that has been processed can be seen from the ranking and percentage of Tri products.
Tri has the opportunity to become a superior product that is difficult to compete with.
The following are the promotions offered by Tri cards in 2016, among others, as follows:
Data Pack For Tablet and Mifi/Modem users.
For only Rp.
75k/month get 3GB bonus data per month that can be used for any internet .
ncluding streaming and downloadin.
with a maximum speed of 14.
4 Mbps for 24 hours.
Tri's Talk to Each Other Bonus Promo For those of you who are in Aceh.
Mataram.
Balikpapan.
Padang.
Pekanbaru.
Banjarmasin.
Surabaya Inner.
Batam.
Surabaya Outner.
Denpasar.
Yogjakarta- Solo.
Jambi.
Palembang.
Jamber.
Madium-Malang.
Congratulations, you can immediately get a bonus promo to talk to sesame tri after topping up a minimum credit of Rp 1,000 this bonus is for all Tri users.
You can freely call each other without any credit deduction, with a reasonable usage limit of 100 minutes.
The findings from previous studies serve as essential considerations to gain an overview within the framework of thought.
They also help identify similarities and differences across various researches, thereby forming a foundation for expanding intellectual insights.
Firstly.
Novansa & Ali .
concluded that product quality and price significantly and positively affect purchasing decisions for the Aqua brand.
However, promotion does not significantly impact purchasing decisions.
Secondly.
Darmawan .
found that price, product quality, and location have a positive and significant influence on purchasing decisions.
Lastly is Chi et al.
and Sivaram et al.
concluded that distribution has a positive and significant effect on purchasing decisions alongside promotions and prices.
Literature Review Product Quality There are several opinions regarding the definition of product quality, among others, according to Imaningsih and Rohman .
in providing a definition of quality, namely: "a dynamic condition related to products, services, people and the environment that meet or exceed the standards .
that have been set".
Meanwhile, according to Gulliando and Shihab .
"product quality is the overall characteristics and properties of a product or service that affect its ability to satisfy stated / implied needs.
From the definition of product quality according to the experts above, we can conclude that product quality is a concept that is difficult to express or detect.
Consumers often cannot reveal when there are differences in quality.
Subscriptions cannot say which one is the best.
Mixing differences - differences in product characteristics so that the product must meet or exceed the expected standards.
The dimensions of Product Quality are:
Performance is a quality dimension related to the main characteristics of a product.
For example, a television, the main performance we want is the quality of the picture we can watch and the quality of the sound that can be heard clearly and well.
Features are supporting or complementary characteristics of the main characteristics of a For example, in a four-wheeled vehicle .
product, the supporting features expected by consumers are such as DVD / CD Player.
Sensor or Reverse Camera and Car Remote Control.
Reliability is a dimension of quality that relates to the likelihood that a product can work satisfactorily at certain times and conditions.
Conformance is the conformity of product performance and quality to the desired standard.
Basically, every product has a predetermined standard or specification.
Durability is related to the durability of a product until it must be replaced.
Durability is usually measured by the age or durability time of a product.
Karina et al.
, .
Serviceability is the ease of service or repair if needed.
This is often associated with aftersales services provided by manufacturers such as the availability of spare parts and ease of repair in the event of damage and the existence of a repair service center (Service Cente.
that is easily accessible to consumers.
Aesthetics is a dimension of quality related to the appearance, sound, taste and smell of a For example, the appearance of a cellphone that you want to buy and the melodious sound of the music produced by the cellphone.
Perceived Quality is the impression of the quality of a product as perceived by consumers.
This quality dimension is related to consumer perceptions of the quality of a product or Such as iPhone cellphones.
Toyota cars.
Canon cameras.
Epson printers and Rolex watches which most consumers think are quality products.
Brand Awareness According to Mappesona et al.
, .
, brand awareness is the ability of a prospective buyer to recognize, recall a brand as part of a particular product category.
Consumers tend to buy a brand that is already known, they feel safe, avoiding various risks of use with the assumption that familiar brands are more reliable.
According to Ali .
, brand awareness is the ability of a brand to appear in the minds of consumers when they are thinking about a particular product category and how easily the name is raised.
According to Simbolon et al.
, .
Brand awareness shows the ability of a prospective buyer to recognize or recall that a brand is part of a particular product category.
We can conclude that the definition of brand awareness is the ability of a prospective buyer to recognize, recall a brand and appear in the minds of consumers with ease the name appears.
Ningsih & pradanawai .
Brand awareness consists of 3 levels, which are as Unaware brand .
ot aware of the bran.
Brand recognition .
rand recognitio.
Brand recall.
Top of mind.
Promotion Promotion comes from the English word promote which means "increase" or "develop".
This definition if used in the field of sales means a tool to increase sales turnover.
So in outline, promotion is communication between producers and consumers.
Promotional activities are one way for companies .
oods/service.
to increase the sales volume of their products.
In addition to the above understanding, it is also interesting to listen to the definition of promotion that has been described by several experts, including: According to (Fandy Tjiptono, 2.
Promotion is a marketing activity that seeks to disseminate information, influence or persuade, and or remind the target market of the company and its products to be willing to accept, buy and be loyal to the products offered by the company concerned.
According to Jasmani & Sunarsi .
Promotion is the coordination of all efforts starting from the seller to build various channels of information and persuasion to sell goods and services or introduce an idea.
According to Hatta et al.
Promotion is any form of persuasive communication designed to inform customers about products or services and to influence them to buy these goods or services which include publicity, personal selling and advertising.
There are five types of promotional activities (Husman & Nawari 2.
, including :
Advertising Face-to-Face Sales (Personal Sellin.
Publicity.
Sales promotion.
Direct marketing.
Karina et al.
, .
Purchase Decision A purchase decision is a consumer decision as an action of two or more alternative choices regarding the process, method, decision to buy, taking into account other factors about what to buy, when to buy, where to buy and how to pay.
According to Helmi & Setyadi .
, purchasing decisions are stage actions in the buyer's decision-making process where consumers actually buy.
purchasing decision according to (Nugroho, 2.
is an integration process that combines knowledge attitudes to evaluate two or more alternative behaviors, and choose one of The decision to buy taken by the buyer is actually a collection of a number of decisions.
Every buying decision has a structure of 6 components (Hatta et al.
, 2.
Decisions about product types Decisions about product form Decision about brand Decision about the seller Decision about the quantity of the product Decision about the time of purchase Research Method Population and Sample Population is a combination of all elements in the form of events, things or people who have similar characteristics that are the center of attention of a researcher because it is seen as a research universe.
The population in this study are people who have bought and used Tri products at Qmotion Pekanbaru Store.
A sample is a subset of the population, consisting of several members of the population.
(The sample is part of the number and characteristics of the population.
In determining the data to be studied, the sampling technique that will be used is non-probability sampling, namely sampling techniques that do not provide equal opportunities for each element or member of the population to be sampled, because the population is unknown.
In this study, the sample chosen was a visitor to the Qmotion store in Pekanbaru city who had bought and used Tri products.
The sample collection method was carried out by Accidental sampling, which is a sampling technique based on chance, namely anyone who happens to meet the researcher can be used as a sample, if it is considered that the person who happened to be met is suitable as a data source (Sugiyono, 2.
This research is carried out by selecting a sample from a population based on available information and in accordance with ongoing research, so that its representation of the population can be accounted for.
Determination of the number of respondent samples is based on the statement (Roscoe, 1.
, which states that a feasible sample size in research is 30-500 samples.
a good sample can be determined by means of, the number of questions in the questionnaire 12 questions multiplied by five.
So in determining the number of samples in this study, the calculation is 12 questions multiplied by five so that it becomes 60.
To prevent data invalidity or errors in the questionnaire data, the number of samples to be distributed was added to 80 Operational Definition of Research Variables The variable in this study consists of two types of variables, namely the dependent variable and the independent variable.
The dependent variable is the variable that is the center of attention of the research.
Meanwhile, the independent variable is the variable that affects the dependent variable, either positively or negatively (Ferdinand, 2.
The variables used in this study are as follows:
The dependent variable in this study is the Purchase Decision.
Independent variables in this study (Product quality, brand awareness, and promotio.
Karina et al.
, .
The instrument used in this study is a questionnaire by asking questions to respondents.
Respondents were asked to respond to the statements in the questionnaire, then each qualitative answer was quantified by giving a score measured by the interval scale.
Indicators and measurements in the form of an interval scale consisting of five levels of answers, each weighted with the following answer choices: 1 = Strongly Disagree (STS), 2 = Disagree (TS), 3 = Less Agree (KS), 4 = Agree (S) and 5 = Strongly Agree (SS).
Data Analysis Technique Descriptive Statistics Descriptive statistics is the process of transforming research data in tabulated form so that it is easy to understand and interpret Indriantoro and Supomo .
This method is used by the author to determine the number and percentage of respondents based on the demographic data categories of respondents to be tested, namely gender, age, occupation, and income per month.
Validity Test A questionnaire is declared valid if the questions on the questionnaire are able to reveal something that will be measured by the questionnaire (Ghozali, 2.
The questionnaire is declared valid if the factor loading score is above 0.
3 correlated item Reliability Test Reliability test is used to measure the level of reliability of a questionnaire from the consistency of respondents' answers.
A questionnaire is said to be reliable or reliable if a person's answer to a question is consistent or stable over time.
The questionnaire is stable or reliable if it provides a Cronbach's Alpha value greater than 0.
5 (Hair et al.
, 2.
Normality Test The normality test is carried out to determine whether the research data used in the regression model has a normal distribution or not.
The normality test is carried out by analyzing the normality graph .
ormal probability plo.
This normality test is detected by looking at the distribution of data, if the data distribution .
occurs around the diagonal line and follows the diagonal line, the regression model fulfills the assumption of normality.
Conversely, if the data spreads far from the diagonal line and or does not follow the direction of the diagonal line, the regression model does not fulfill the assumption of normality.
Multicollinearity Test The multicollinearity test aims to test whether the regression model found a correlation between the independent variables.
A good regression model should not have a correlation between the independent variables.
The presence or absence of multicollinearity correlation in the regression model can be detected by looking at the tolerance value and variance inflation factor (VIF).
This measure shows which independent variables are explained by other independent The tolerance value measures the variability of the selected independent variables that cannot be explained by other independent variables.
A low tolerance value equals a high VIF value and indicates high collinearity.
The commonly used cut off value is the VIF tolerance value below 10 or the VIF value above 0.
10 so that each researcher must determine the level of collinearity that can still be tolerated.
Heteroscedasticity Test The heteroscedasticity test is used to determine whether or not there is a deviation from the classical assumption of heteroscedasticity, namely the existence of an inequality of variance of the residuals for all observations in the regression model.
The prerequisite that must be met in the regression model is the absence of heteroscedasticity symptoms.
Heteroscedasticity has a condition that the variance of a residual of an observation to another observation is different.
Karina et al.
, .
Heteroscedasticity test can be done empirically with the Glejser test, namely by regressing the absolute value of the residual with the independent variables in the model.
If the significance value between the independent variable and the absolute residual is more than 0.
then there is no heteroscedasticity problem.
While the independent variable with the absolute residual is less than 0.
05, then there is a heteroscedasticity problem.
A good regression model is one with homoscedasticity or one without heteroscedasticity.
Hypothesis Test The data that has been collected is analyzed with computer assistance.
The application package or statistical program used is the SPSS (Statistical Package for the Social Science.
With the SPSS program, several tests of the collected data can be carried out.
The purpose of this study is to test the hypothesis which is a temporary answer to the formulation of research problems.
The statistical method for testing the relationship between one dependent variable and one or more independent variables is the regression method.
F Test (Model Tes.
The F test aims to test the effect of all independent variables included in the regression model on the dependent variable together.
The regression model is said to have a significant effect, meaning that the regression model can be used to predict the dependent variable if it has a probability value of less than 0.
05 and should be said to have no significant effect if the probability value is greater than 0.
05 or the regression model cannot be used to predict the dependent variable.
Test Coefficient of Determination (R.
The coefficient of determination test (Adjusted R.
is used to show how much change in the dependent variable can be explained by the independent variable, while the rest is explained by other factors.
In other words, the coefficient of determination test is used to measure how far the model's ability to explain variations in the dependent variable.
Hypothesis Test The t test is used to test how far a variable can affect the dependent variable with an individual A variable is said to have no significant effect if the probability value <0.
05 and vice versa is said to have no significant effect if the probability value> 0.
Results and Discussion Validity Test Results The validity test was carried out to determine whether the statement items submitted in the questionnaire could be used to measure the actual situation of the respondents.
The validity test in this study was carried out on 4 existing variables, namely product quality, brand awareness, promotion and purchasing decisions.
The validity test in this study was carried out by comparing the Pearson Product Moment correlation value or r count greater than r table declared valid.
The value of r table with a free degree of 80 .
and at a significance level of 3 .
wo-way tes.
The results of the validity test in this study for variable X1 or product quality can be seen in Table 12 below:
Table 1.
Product Quality Validity Test Results (X.
Variabel Statement r count r table Conclusion Product Quality X1_1 0,813 0,2199 Valid (X.
X1_2
0,718
0,2199
Valid
X1_3
0,786
0,2199
Valid Source: Primary data processed .
Based on Table 1, it is known that the Pearson Product Moment correlation value or r count X1_1 is 0.
X1_2 is 0.
718, and X1_3 is 0.
Thus it can be concluded that all Karina et al.
, .
statement items in the product quality variable are valid because r count is greater than r table (> Table 2.
Brand Awareness Validity Test Results (X.
Variabel Statement r count r table Conclusion Awareness X2_1 0,813 0,2199 Valid Brand(X.
X2_2 0,792 0,2199 Valid
X2_3
0,671
0,2199
Valid Source: Primary data processed .
Based on Table 2, it is known that the Pearson Product Moment correlation value or r count X2_1 is 0.
X2_2 is 0.
792, and X2_3 is 0.
Thus it can be concluded that all statement items in the brand awareness variable are valid because r count is greater than r table (> 0.
Table 3.
Promotion Validity Test Results (X.
Variabel Statement r count r table Conclusion Promotion (X.
X3_1 0,693 0,2199 Valid
X3_2
0,660
0,2199
Valid
X3_3
0,786
0,2199
Valid Source: Primary data processed .
Based on Table 3, it is known that the Pearson Product Moment correlation value or r count X3_1 is 0.
X3_2 is 0.
660 and X3_3 is 0.
Thus it can be concluded that all statement items in the promotion variable are valid because r count is greater than r table (> Table 4.
Purchasing Decision Validity Test Results (Y) Variabel
Statement
r count
r table Conclusion Purchase Y_1 0,661 0,2199 Valid
decision (Y) Y_2 0,742 0,2199 Valid
Y_3
0,737
0,2199
Valid Source: Primary data processed .
Based on Table 4, it is known that the Pearson Product Moment correlation value or r count Y_1 is 0.
Y_2 is 0.
742 and Y_3 is 0.
Thus it can be concluded that all statement items in the purchasing decision variable are valid because r count is greater than r table (> Reliability Test The reliability test is carried out to determine the extent to which a measurement result is relatively consistent if the measurement is repeated two or more times.
The reliability test in this study uses Cronbach's Alpha, which if the reliability coefficient value is greater than 0.
5, the research instrument is considered reliable.
The reliability coefficient index criteria table is as Table 5.
Reliability Coefficient Index
Interval Value Criteria
< 0,20
Very low 0,20 Ae 0,40 Low 0,40 Ae 0,60 Simply 0,60 Ae 0,80 High 0,80 Ae 1,00 Very high Source: Wibowo .
Karina et al.
, .
The reliability test results for each variable can be seen in Table 6 below:
Table 6.
Reliability Test Results Variable Alpha Cronbach
Description Criteria
Product Quality 0,664 Reliabel
High
Kesadaran Merek
0,663
Reliabel High Promotion 0,512 Reliabel Simply Purchase Decision 0,513 Reliabel Simply Source: Primary data processed .
Based on Table 6 above, it is known that the result of the Cronbach's Alpha value for the Product Quality variable is 0.
664, the Brand Awareness variable is 0.
663, the Promotion variable is 0.
512, and the Purchasing Decision variable is 0.
So it can be concluded that this research instrument is reliable because the Cronbach's Alpha value of each variable is greater Normality Test The normality test is carried out to determine whether the research data used in the regression model has a normal distribution or not.
The normality test is carried out by analyzing the normality graph .
ormal probability plo.
This normality test is detected by looking at the distribution of data, if the data distribution .
occurs around the diagonal line and follows the diagonal line, the regression model fulfills the assumption of normality.
Conversely, if the data spreads far from the diagonal line and or does not follow the direction of the diagonal line, the regression model does not fulfill the assumption of normality (Ghozali, 2.
Figure 1.
Normal P-P Plot of Regression Standardized Residual Diagram Source: Primary data processed .
Based on Figure 3 above, it can be seen that the data in this study are normally Data is said to be normally distributed if the dots are around the line and follow the diagonal line.
Multicollinearity Test This measure shows which independent variables are explained by other independent The tolerance value measures the variability of the selected independent variables that cannot be explained by other independent variables.
A low tolerance value equals a high VIF value and indicates high multicollinearity.
The commonly used cut off value is a tolerance value greater than 0.
1 and a VIF value of less than 10 so that each researcher must determine the level of multicollinearity that can still be tolerated (Ghozali, 2.
Table 7.
Multicollinearity Test Results Coefficientsa Collinearity Statistics Model Tolerance VIF (Constan.
Product Quality Brand Awareness Karina et al.
, .
Promotion Dependent Variable: Purchase Decision Source: Primary data processed .
From the multicolonierity test results in Table 7 above, it can be seen that each independent variable has a tolerance value greater than 0.
1 and a variance inflation factor (VIF) value of less than 10 so it can be concluded that there are no multicollinearity symptoms between the independent variables.
Heteroscedasticity Test Heteroscedasticity has a condition that the variance of a residual of an observation to another observation is different (Ghozali, 2.
Gujarati .
states that the heteroscedasticity test can be done empirically with the Glejser test, namely by regressing the absolute value of the residual with the independent variables in the model.
If the significance value between the independent variable and the absolute residual is more than 0.
05, then there is no heteroscedasticity problem.
While the independent variable with the absolute residual is less 05, then there is a heteroscedasticity problem.
A good regression model is that heteroscedasticity does not occur.
Table 8.
Heteroscedasticity Test Results Coefficientsa Model (Constan.
Product Quality Brand Awareness Promotion Dependent Variable: RES2 Unstandardized Coefficients Std.
Error Standardized Coefficients Beta Sig.
Source: Primary data processed .
A model is said not to experience symptoms of heteroscedasticity if the probability or significance value is greater than 0.
Based on Table 8 above, it can be seen that the significance value for the Product Quality variable is 0.
715, the Brand awareness variable is 294 and the promotion variable is 0.
So it can be concluded that there are no symptoms of Hypothesis Test With the SPSS program, several tests of the collected data can be carried out.
The purpose of this study is to test the hypothesis which is a temporary answer to the formulation of research problems.
The statistical method for testing the relationship between one dependent variable and one or more independent variables is the regression method (Ghozali, 2.
The results of data processing using the complete SPSS program are in the attachment and are further explained in Table 9.
Table 9.
Multiple Linear Regression Coefficientsa Model Unstandardized Coefficients Std.
Error 1 (Constan.
Product Quality Brand Awareness Promotion Standardized Coefficients Beta Sig.
Source: Primary data processed .
Karina et al.
, .
The regression equation model that can be written from these results in the form of a regression equation is as follows:
Y = C X1 X2 X3 E
Y = 3.
268 X1 0.
158 X2 0.
285 X3
The regression equation can be explained as follows:
The constant is = 3.
meaning that if the regression coefficient value of the other variables is zero .
, the coefficient of purchase satisfaction (Y) is equal to 3.
Regression coefficient .
= 0.
268, if the product quality variable (X.
is increased by 1 unit, the purchase decision (Y) will increase by 0.
268 assuming the other independent variables are constant.
Regression coefficient .
= 0.
158, if the brand awareness variable (X.
is increased by 1 unit, the purchase decision (Y) will increase by 0.
158 assuming other independent variables are constant.
Regression coefficient .
= 0.
285, if the promotion variable (X.
is increased by 1 unit, the purchase decision (Y) will increase by 0.
285 assuming other independent variables are F Test The F test aims to test the effect of all independent variables included in the regression model on the dependent variable together.
The regression model is said to have a significant effect, meaning that the regression model can be used to predict the dependent variable if it has a probability value of less than 0.
05 and should be said to have no significant effect if the probability value is greater than 0.
05 or the regression model cannot be used to predict the dependent variable (Ghozali, 2.
Table 10.
ANOVA F Test Results Model Sum of Squares Mean Square Sig.
Regression Residual Total Source: Primary data processed .
The results of the F test in this study indicate that the independent variables have a significant effect together on the dependent variable.
Table 10 shows that the calculation of the F test which has a significant value of 0.
000 or less than 0.
05 (F.
Sig 0.
000 < 0.
with F 512> F table 2.
72, meaning that all independent variables have a significant influence on the dependent variable.
In this case, the variables of product quality, brand awareness, and promotion have a significant influence on the purchasing decision variable.
Test Coefficient of Determination (R.
The adjusted R square (R.
coefficient of determination test is used to show the relationship between the dependent variable and the independent variable.
In testing the coefficient of determination, it is seen how much the independent variable provides information on the dependent variable.
Table 11.
Results of the Analysis of the Coefficient of Determination (R.
Model Summaryb Model R Square Adjusted R Square Std.
Error of the Estimate Predictors: (Constan.
Promotion.
Product Quality.
Brand Awareness Dependent Variable: Purchase Decision Source: Primary data processed .
Karina et al.
, .
Based on the number of variables of more than 2, the adjusted R2 determinant coefficient has a value of 0.
265 or 26.
5%, so it can be concluded that the variables of product quality, brand awareness, and promotion affect purchasing decisions by 26.
5%, while the 5% is influenced by other factors outside this research model.
T Test The t test is used to test how far a variable can affect the dependent variable with an individual A variable is said to have no significant effect if the probability value <0.
05 and vice versa is said to have no significant effect if the probability value> 0.
05 (Ghozali, 2.
Table 12.
t Test Results Coefficientsa Unstandardized Standardized Coefficients Coefficients Model Std.
Error Beta Sig.
1 (Constan.
Product Quality Brand Awareness Promotion Dependent Variable: Purchase Decision Source: Primary data processed .
Based on Table 12 above, the hypothesis test for each independent variable on the dependent variable can be explained as follows:
For hypothesis 1, it is said to have a positive effect because the t value for the product quality variable is positive at 2.
It is said to be significant because the significance value of the product awareness variable of 0.
006 is smaller than the value of 0.
05 and the t value of 840 is greater than the t table value of 1.
So it can be concluded that the first hypothesis is accepted.
For hypothesis 2, it is said to have a positive effect because the t value for the brand awareness variable is positive at 2.
It is said to be significant because the significance value of the brand awareness variable of 0.
048 is smaller than the value of 0.
05 and the t value of 2.
012 is greater than the t table value of 1.
So it can be concluded that the second hypothesis is accepted.
For hypothesis 3, it is said to have a positive effect because the t value for the promotion variable is positive at 2.
It is said to be significant because the significance value of the promotion variable is 0.
004 less than the value of 0.
05 and the t value of 2.
931 is greater than the t table value of 1.
So it can be concluded that the third hypothesis is accepted.
previously described that this research is to determine the effect of purchasing decisions at the Qmotion Pekanbaru store.
Thus the discussion is to see the significance of the influence (X.
Product Quality (X.
, brand awareness (X.
and promotion on purchasing decisions at the Qmotion Pekanbaru store.
Effect of Product Quality on Purchasing Decisions The regression coefficient .
268, indicating that if the product quality variable (X.
increases by one unit, the purchasing decision (Y) will increase by 0.
268, assuming other independent variables remain constant.
The t-test results for product quality (X.
yield a tcount value of 2.
840 and a significance value of 0.
Given that the tcount of 2.
840 is greater than 992 and the significance value of 0.
006 is less than 0.
05, it can be concluded that product quality (X.
has a significant positive effect on purchasing decisions.
Descriptive statistical analysis results suggest that respondents' perceptions of product quality are good to very good, with an average score of 4.
Respondents' responses to product quality (X.
indicate that an increase in features provided by the complete Tri cardAiincluding SMS.
GPRS.
MMS, 3G, and NSPAiwill also enhance purchasing decisions.
Similarly, improvements in voice network Karina et al.
, .
quality and clarity during calls will boost purchasing decisions furtherAias will expanded signal coverage across remote regions in Indonesia.
Conversely, reductions in Tri card features or declines in voice network quality and call clarity would lead to decreased purchasing decisionsAias would any decrease in wide signal coverage across remote Indonesia.
This study aligns with previous research conducted by Hafidz & Mahaputra .
, which found a positive and significant effect of product quality on purchasing decisionsAiindicating strong influences from these variables across both past and present studies.
The Effect of Brand Awareness on Purchasing Decisions.
The regression coefficient .
158, suggesting that if the brand awareness variable (X.
increases by one unit, the purchasing decision (Y) will increase by 0.
158, assuming other independent variables remain constant.
The t-test results for brand awareness (X.
yield a tcount value of 2.
012 and a significance value of 0.
Since the tcount of 2.
012 is greater than 1.
and the significance value of 0.
048 is less than 0.
05, it can be concluded that brand awareness (X.
has a significant positive effect on purchasing decisions.
Descriptive statistical analysis results indicate that respondents' perceptions of product quality are good, with an average score Respondents' responses to brand awareness (X.
suggest that quick recall of the brand leads to increased purchasing decisionsAiso does heightened recognition of Tri products and faster recall of the Tri brand.
Conversely, slower recall or lower recognition levels for Tri products would lead to decreased purchasing decisionsAias would any decrease in quick recall for the Tri brand.
This study aligns with previous research conducted by Putra et al.
, .
which found a significant and positive influence from brand equity on purchasing decisionsAi indicating strong influences from these variables across both past and present studies.
The Effect of Promotion on Purchasing Decisions The regression coefficient .
285, suggesting that if the promotion variable (X.
increases by one unit, the purchasing decision (Y) will increase by 0.
285, assuming other independent variables remain constant.
The t-test results for promotion (X.
yield a tcount value of 2.
and a significance value of 0.
Since the tcount of 2.
931 is greater than 1.
992 and the significance value of 0.
004 is less than 0.
05, it can be concluded that promotion (X.
has a significant positive effect on purchasing decisions.
Descriptive statistical analysis results indicate that respondents' perceptions of product quality are good, with an average score of 3.
Respondents' responses to promotions (X.
suggest that increased notifications about latest information lead to higher purchasing decisionsAias does an increase in new bonus offers for Tri products and increased Tri advertising media.
Conversely, fewer notifications about latest information or decreased bonus offers would lead to reduced purchasing decisionsAias would any decrease in Tri advertising media.
This study contrasts with previous research conducted by Aeni .
, which found that promotion has a positive but non-significant effect on purchasing decisionsAiindicating discrepancies between past studies and current research regarding the strength of influence from these variables.
Conclusions Based on the results of data analysis research and discussion in the previous chapter, the conclusions that can be written are as follows:
There is a positive and significant influence between product quality on purchasing decisions, meaning that if product quality meets or exceeds predetermined or expected standards, purchasing decisions will increase.
There is a positive and significant influence between brand awareness on purchasing If the buyer's ability to recognize and recall a known brand increases, purchasing decisions will increase.
There is a positive and significant influence between promotion on buyer decisions, which means that if the promotion increases, the purchasing decision increases.
Karina et al.
, .
Based on the results of the discussion of conclusions, the authors propose the following By looking at the above conclusions that product quality, brand awareness and promotion have a positive and significant effect on purchasing decisions, it is advisable for management to pay more attention to customer needs in order to increase purchasing decisions.
For Qmotion stores, because this study found that product quality, brand awareness and promotion have a positive and significant effect on purchasing decisions at Qmotion stores.
For this reason, it is hoped that the Qmotion store will maintain and increase the promotions given to customers / consumers in order to increase customer purchasing power and establish good relationships with customers.
For the store must continue to consider the quality of the products offered.
In this study using product quality variables, brand awareness and promotion of purchasing decisions, it is hoped that further research can use other variables not used in this study, such as price, location, service quality and so on.
References: