The influence of shopping orientation, online trust, and purchase experience on online buying interest : case study on Bukalapak consumers in Tulungagung district

4) The effect of shopping orientation, online trust, and purchase
experience on consumer buying interest online.
Based on data collected from 148 respondents, the results of

multiple linear regression analysis can be presented in table 4.19
as follows:

Table 4.19: Multiple Linear Regression Results

Coefficientsa

Unstandardized Standardized t Sig
Coefficients Coefficients

Model B Std. Error Beta

1 (Constant) 1,815 1.044 .149 1,739 .085
.334 2,384 .019
Shopping Orientation .078 .033 .535 4.488 .000
8,308 .000
Online Trust .307 .068

Purchase Experience .493 .059

Source: Primary Data, Processed, 2021

From the results of the regression analysis, it can be seen
that the multiple regression equation is as follows:
Y = 1.815 + 0.078 X1 + 0.307 X2 + 0.493 X3

Based on this equation, it is known that the regression
coefficients of shopping orientation (b1), online trust (b2), and
purchasing experience (b3) have positive regression coefficients.
This shows that shopping orientation (b1), online trust (b2), and
purchasing experience (b3) have a positive influence on buying
interest (Y). Furthermore, to find out whether the hypothesis
proposed in this study is accepted or rejected, hypothesis testing
will be carried out using the t test and F test. The results of
hypothesis testing are explained as follows:

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b. T Test (Partial)
The t test is a test to show the significance of the individual

influence of the independent variables in the model on the
dependent variable. This is intended to determine how far the
influence of one independent variable explains the variation of the
dependent variable. If the significance value is less than 0.05 (sig t
table 1.976 and the significance level is 0.000 <0.05.
1) The effect of X1 on Y with a tcount of 2,384 >ttable 1,976

and a significance level of 0.019 <0.05.
The results show that the shopping orientation variable
significantly and positively affects buying interest. So the first
hypothesis put forward can be accepted.
2) The effect of X2 on Y with a tcount of 4.488 >ttable 1.976
and a significance level of 0.000 <0.05.
The results show that the online trust variable significantly and
positively affects buying interest. So the second hypothesis put
forward can be accepted.
3) The effect of X3 on Y with a tcount of 8.308 >ttable 1.976
with a significance level of 0.000 <0.05.
The results show that the purchase experience variable
significantly and positively affects buying interest. Then the
third hypothesis put forward can be accepted.

c. F Test
To analyze the influence of the independent variables,

namely shopping orientation, online trust, and purchasing
experience together on the dependent variable, namely buying
interest, the Fcount test was used. If the value of t count is greater

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than t table and the significance value is less than 0.05 (p < 0.05),

then the effect of the independent variables, namely shopping

orientation, online trust, buying experience together on the

dependent variable, namely buying interest is significant. For

more details, it can be seen in the following table: Table 4.20:

Simultaneous ANOVA . Test Results

ANOVAa

Sum of Mean

Model Squares df Square F Sig.

1 Regression 168,720 3 56,240 91.331 .000b

Residual 62.194 101 .616

Total 230,914 104

a. Dependent Variable: Buying Interest
b. Predictors: (Constant), Purchase Experience, Shopping Orientation, Online
Trust

Source: Primary Data. Processed, 2021

Table 4.20 shows that the Fcount value is 17.959 and Ftable
is 2.67 with a significance F of 0.000 with a probability of 2.67),
with a significance value less than 0.05 (0.000 <0.05), it means
that shopping orientation, confidence online, and the buying
experience together affect buying interest. So the fourth
hypothesis put forward can be accepted.
d. Coefficient of Determination The coefficient of

determination can be analyzed through the coefficient
of determination test by calculating adjusted R
The coefficient of determination measures how far the
model's ability to explain the variation of the dependent variable
(Ghozali, 2009). The adjusted R2 value is an overview measure
that shows how well the sample regression line fits the population
data. The value of the coefficient of determination is between 0

46

and 1. The coefficient of determination which is closer to 0 means
the smaller the influence of all dependent variables on the
independent variable. The closer to 1, the greater the influence of
all dependent variables on the independent variables.

Table 4.21 : Coefficient of Determination

Model Summaryb

Change Statistics

Model R Adjusted Std. Error of R Square
R Square R Square the Estimate Change F Change

1 .855a .731 .723 .78472 .731 91.331

Source: Primary Data, Processed, 2021

Table 4.21 shows the results of the adjusted R2 value of
0.731 or 73.10%. The results of this test show that 73.1% of
buying interest variables can be explained by shopping
orientation, online trust, and purchasing experience variables.
While the remaining 26.90% can be explained by other variables
that are not included in the research model.

4.8 Discussion
This study aims to determine the effect of shopping

orientation variables, online trust, and purchase experience on
buying interest.
a. The Effect of Shopping Orientation on Buying Interest

The results showed that the shopping orientation variable
obtained a regression coefficient of 0.078 and a tcount of 2.384
with a significance of 0.000. So it can be concluded that shopping

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orientation has succeeded in proving the first hypothesis which
states that "shopping orientation has a positive and significant
effect on online buying interest".

b. The Effect of Online Trust on Buying Interest
The results showed that the online trust variable obtained a

regression coefficient of 0.307 and a tcount of 4.488 with a
significance of 0.000. So it can be concluded that online trust has
succeeded in proving the second hypothesis which states that
"Online trust has a positive and significant effect on online buying
interest".

When trust is higher, it will certainly be used as a measure
to grow consumer buying interest to transact online, so the higher
the trust, the higher the buying interest. Positive trust certainly
affects consumer interest in shopping online because they believe
that sellers are able to carry out their business activities properly
and can be trusted by sending purchased products to consumers.

c. The Influence of Purchase Experience on Purchase
Intention
The results showed that the purchase experience variable

obtained a regression coefficient of 0.493 and a t count of 8.308
with a significance of 0.000. So it can be concluded that online
trust has succeeded in proving the third hypothesis which states
that "The buying experience has a positive and significant effect
on online buying interest". Therefore, customers or consumers
will only buy products from the internet if they have experienced

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what buying on the internet looks like. In addition, experienced
customers or consumers are more likely to buy online than those
with no experience at all.

d. The Influence of Shopping Orientation, Online Trust,
and Purchase Experience on Purchase Intention
Based on the results of the simultaneous test, it shows that

the Fcount value is 91.331 >Ftable is 2.67, this means that
shopping orientation, online trust, and purchase experience have
a positive effect on buying interest. Based on a significance value
of 0.000 (0.000 < 0.05), this means that shopping orientation,
online trust, and purchasing experience simultaneously have a
positive and significant effect on buying interest, so it can be
concluded that shopping orientation, online trust, and purchasing
experience have successfully proven the hypothesis. fourth which
states that "shopping orientation, online trust, and previous
purchase experience have a positive and significant effect on
online buying interest".

Based on the results of this study, the value of R Square (R2)
was 0.731 or 73.1%. The results of this test show that 73.1% of
buying interest variables can be explained by shopping
orientation, online trust, and purchasing experience variables.
While the remaining 26.9% can be explained by other variables
that are not included in the research model.

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CHAPTER V
CONCLUSIONS AND SUGGESTIONS

5.3 Conclusion
Based on the results of research and discussion, some

conclusions can be drawn as follows:
a) There is a positive influence of the shopping orientation

variable on online buying interest (a case study on the online
store Bukalapak). Based on the results of the partial test
(tcount) obtained a positive regression coefficient of 0.078 and
tcount of 2.384 with a significance of 0.000. This shows that the
better the shopping orientation, the higher the buying interest
felt by respondents at Bukalapak.
b) There is a positive influence of online trust variables on online
buying interest (a case study on the online shop Bukalapak).
Based on the results of the partial test (tcount) obtained a
positive regression coefficient of 0.307 and tcount of 4.488
with a significance of 0.000. This shows that the higher the
trust, the higher the buying interest felt by respondents at
Bukalapak.
c) There is a positive influence of the purchasing experience
variable on online buying interest (a case study on the online
shop Bukalapak). Based on the results of the partial test
(tcount) obtained a positive regression coefficient of 0.493 and
tcount of 8.308 with a significance of 0.000. This shows that the

50

better the buying experience, the higher the buying interest felt
by respondents at Bukalapak.
d) Based on the results of the simultaneous test shows that the
Fcount is 91.331 >Ftable is 2.67 with a significance value of
0.000 (0.000 <0.05). When compared with the expected
significance level of 5%, it means that the significance of
Fcount is smaller than the expected significance level (0% <
5%). Thus, shopping orientation, online trust, and purchasing
experience simultaneously have a positive and significant
effect on buying interest (a case study on the online shop
Bukalapak). This shows that the better and higher the
shopping orientation, online trust, and purchasing experience,
the higher the buying interest felt by Bukalapak respondents.
e) Based on the results of the coefficient of determination, the
value of R Square (R2) is 0.731 or 73.1%. The results of this
test show that 73.1% of buying interest variables can be
explained by shopping orientation, online trust, and purchasing
experience variables. While the remaining 26.90% can be
explained by other variables that are not included in the
research model.

5.4 Suggestion
Based on the discussion and conclusions in this study, it can

be seen that the variables of trust, perceived benefits and
perceived convenience have a positive and significant effect on
buying interest, either partially or simultaneously, so the
following suggestions can be given:

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a. For Companies
1) The Bukalapak party should intensify promotions so that
everyone prefers to shop online and improve the quality of
the goods sold by verifying the pelapak who will sell the
goods whether the goods are genuine or fake. This is
because if the consumer's shopping lifestyle needs are met,
they will be interested in making a purchase.
2) Bukalapak should further improve product advertisement
moderation services and privacy security which can reduce
fraudulent actions. This is because the trust of consumers is
the basis for whether the consumer will make a purchase,
especially in online shopping.
3) Bukalapak should follow up on fraud that has harmed
consumers and made it easier for consumers to return
purchases. With a positive consumer experience, in the
future consumers will be interested in making repeat
purchases.

b. For Further Researchers
1) Further research can improve the limitations that exist in
this study and increase the number of samples and data
collection methods to obtain comprehensive results.
2) Other research is expected to expand the variables
regarding buying interest and develop research by including
other variables such as promotion, price perception,
perceived benefits, ease of use that can affect buying
interest.

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