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Tourism Attraction and Destination Image in Building Interest in Visiting Tourists : A Case Study of Red Lentera Beach Adelia Pratama1.
Anggi Josetio Prayoga 2* 1,2Universitas Muhammadiyah Bengkulu.
Indonesia *corresponding author:
josetioanggi07@gmail.
Received November 26, 2024.
Received in revised form December 19, 2024.
Accepted December 20, 2024 Abstract.
This research aims to find out how tourists' willingness to visit Lentera Merah Beach is influenced by the image of the destination and its tourist attractions.
Questionnaires were distributed to visitors to Lentera Merah Beach as part of the research methodology.
The results of the investigation show that the natural beauty, facilities and uniqueness of a destination's beaches are one of the factors that make the destination attractive to visitors and significantly influence their willingness to come.
In addition, positive opinions about a location, such as its reputation, perceived safety, and high-caliber service, also influence tourists' desire to visit Lentera Merah Beach.
The conclusions of this research have implications for destination managers, who must continue to improve tourist attractions and increase positive opinions of their places to attract more visitors.
Keywords: destination image.
interest in visiting This is an open access article under the Creative Commons Attribution 4.
0 International License INTRODUCTION The tourism industry has a significant impact on the economic prosperity of a region, especially in rich and beautiful countries.
Indonesia has a wealth of natural resources which provide great opportunities for the growth of the tourism industry.
This is very encouraging for the growth of the tourism industry and makes it the main driver of economic growth.
The city of Bengkulu, one of the most popular tourist attractions in Indonesia, is located on Sumatra Island.
Bengkulu, one of the cities in Indonesia with stunning beaches like Lentera Merah Beach, has untapped potential in the travel and tourism industry.
As a result.
Bengkulu City's tourism industry is increasingly developing, which is very important for the regional economy and welfare.
The main objective of this research is to create a marketing plan that effectively advertises Lentera Merah Beach as a tourist destination and increases visitor attraction.
In terms of travel, curiosity basically refers to the desire to visit a place that seems interesting.
Each tourist location must have a thorough understanding of the elements that influence tourists' desire to visit in order to attract visitors.
The image of a location and its tourist attraction are two important elements identified in tourism literature.
Destination image is the overall Journal of Managiere and Business Available at http://ojs.
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picture and reputation of a location in the eyes of tourists, while tourist attraction refers to the distinctive and attractive elements of a place that are able to attract tourists.
A number of studies have examined how tourist attractions influence interest in visiting, in addition to how destinations and tourist attractions influence tourism marketing.
Tourist attractions have a positive impact on visitors' desire to return to Mount Halimun Salak National Park, as shown by Batubara & Putri .
data, which is 11,983.
However, the Tourist Attraction variable runs in the opposite, opposite, or opposite direction to Intention to Revisit, according to research by Saputro et al .
, so this theory cannot be adopted .
According to Hapsara & Ahmadi .
, descriptions of destinations of interest to visit have a path coefficient value of 0.
327, a t-statistic value of 3.
626, and a P value of 0.
Because the P value is less than 5% .
000 < 0.
, it can be stated that the destination image variable has a significant effect on tourists' willingness to visit.
The aim of this research is to better understand how tourists' desire to visit Lentera Merah Beach is influenced by their impression of the location and its tourist attractions.
The results of this research will provide deeper knowledge to stakeholders, including local governments, tourism destination managers, and social media influencers, in order to encourage visitor growth in Bengkulu City and maintain the attractiveness of Lentera Merah Beach.
METHOD
This kind of research uses quantitative methodology to provide explanations.
This research was conducted at Lentera Merah Beach.
Bengkulu.
The main focus of this research is on domestic and international students who are at least eighteen years old.
Using the Cochran formula, the sample size was determined with a 90% confidence level, a 7% .
margin of error, and a p = 0.
4 assumption.
At the 90% confidence level, the Z value from the normal table is around 1.
As a result, 132 responses made up the sample size.
Google Forms is used in this study to distribute questionnaires and gather data.
A survey on a Likert scale of 1 to 5, ranging from strongly disagree to strongly agree, is the method employed.
Validity and reliability are assessed in this work through the use of instrument testing.
assess the hypothesis, multiple linear regression analysis is employed together with a simultaneous test (F tes.
, partial test (T tes.
, and coefficient of determination test (R.
help with calculations, a tool known as SPSS 25 is utilized.
Signs that imply desire For visit (Y): Interest traveler For travel be measured from three factors : .
how much active they look for information product .
how much big possibility they For visit .
how they Finally decide For visit ( Ramadoni & Rumorong , 2.
Apriliyanti .
states the indicators of tourist attraction (X.
as follows: .
Uniqueness of souvenirs.
Natural .
Convenience.
Cool air.
In accordance with Tasci and Konzak .
, the indications for the target image variable (X.
are: .
Cognitive image.
Unique images.
Affective image.
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Daya Tarik (X.
Minat Berkunjung (Y) Citra Destinasi (X.
Figure 1.
Hypothesis framework Description:
= Partial Influence = Simultaneous Influence Figure 1 above illustrates the link between one dependent variable, desire in visiting, and two independent factors, destination image and attractiveness.
Determining whether the independent and dependent variables influence each other partially or simultaneously is the goal of this study.
The ideas proposed in this research are as follows:
H1: Interest in visiting Lentera Merah Beach is significantly influenced by its partial beauty.
H2: Interest in visiting Lentera Merah Beach is significantly influenced by the description of the destination.
H3: Interest in visiting Lentera Merah Beach is significantly influenced by destination image and attractiveness simultaneously.
RESULT AND DISCUSSION
Test the Research Instrument The two instrument tests that the researcher used included validity and reliability tests.
Meanwhile, the questionnaire test consisted of 11 statements which were administered using SPSS 25 software.
The aim of the instrument test was to evaluate the feasibility of the data collection questionnaire.
The instrument test findings listed in Tables 1 and 2.
Table 1.
Validity testing outcomes AuVariableAy Tourist Attraction (X.
Destination Image (X.
Interest in Visiting (Y) Statement Au1Ay Au2Ay Au3Ay Au4Ay Au1Ay Au2Ay Au3Ay Au1Ay Au2Ay Au3Ay AuRcountAy Au0.
759Ay Au0.
654Ay Au0.
604Ay Au0.
814Ay Au0.
715Ay Au0.
731Ay Au0.
811Ay Au0.
737Ay Au0.
756Ay Au0.
747Ay AuInformationAy AuValidAy AuValidAy AuValidAy AuValidAy AuValidAy AuValidAy AuValidAy AuValidAy AuValidAy AuValidAy Source: SPSS Statistics 25 Journal of Managiere and Business Available at http://ojs.
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Table 1 shows that for each indication examined, the value of rcount > rtable .
indicates that each indicator has fulfilled the validity component and makes it possible to continue with the next testing stage.
Table 2.
Reliability Test ResultsAy AuVariableAy Tourist attraction Destination Image Interest in Visiting Source: SPSS Statistics 25 AuCronbach's AlphaAy Au0.
671Ay Au0.
617Ay Au0.
602Ay AuInformationAy AuReliableAy AuReliableAy AuReliableAy According to the researcher, the dependability element has been fulfilled based on the reliability assessment carried out by the researcher.
According to the reliability assessment shown in Table 2, the three variables used have values above 0.
Linear Multiple Regression Analysis Table 3.
AuMultiple Linear Regression AnalysisAy AuCoefficients aAy AuUnstandardized AuStandardized CoefficientsAy CoefficientsAy AuBAy AuStd.
ErrorAy AuBetaAy 3,741 1,020 ,527 ,055 ,660 -,022 ,072 -,021 AuModelAy Au(Constan.
Ay Tourist attraction Destination Image Dependent Variable: Interest in Visiting Source: SPSS Statistics 25 AuSig.
3,669
,000
9,565
,000
-,305
,761
The linear equation obtained from the results of multiple linear regression analysis is as follows: obtained a constant value of 3.
741 with a value of -0.
022 for the destination image variable (X.
527 for the tourist attraction variable (X.
Y = 3.
527 X1 -0.
022 X2 e The equation shows that:
The constant value obtained is 3.
741, which means the Y value is 3.
This is based on the assumption that other components will be constant if the values of the independent variables X1 and X2 are equal to zero.
Based on multiple linear regression research.
X1 has a coefficient value of 0.
This means that if X1 grows then interest in visiting (Y) will increase by 0.
527 provided all other factors remain constant.
The destination image or coefficient X2 in the multiple linear regression calculation produces a value of -0.
022, meaning that if all other factors remain the same then interest in visiting (Y) will increase by -0.
Journal of Managiere and Business Available at http://ojs.
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Hypothesis Testing t Test (Partia.
To determine if each independent variable has an impact on the dependent variable, or interest in visiting, the partial test .
is utilized.
Consequently, when performing the t test, the following principles for making decisions are followed: In the event where either tcount < ttable or the Sig value >0.
Ho is accepted and Ha is denied.
Stated differently, there is no relationship between the independent and dependent variables.
If the Sig value is less than 0.
05 or the tcount is more than the ttable.
Ha is authorized and Ho is refused.
This demonstrates the relationship between the independent and dependent variables.
To find out the results of the partial test .
you need to know the ttable value from the t distribution table.
The ttable value is 1.
979 with a confidence level of 95%, alpha 0.
and ttable limits = (/2 .
= t .
132-2-.
= t .
= 1.
The following results are displayed from partial test results using SPSS 25 for Windows software:
Table 4.
AuPartial Test Results (T Tes.
Ay AuCoefficients aAy AuUnstandardized AuStandardized CoefficientsAy CoefficientsAy Std.
Error AuBetaAy 3,741 1,020 ,527 ,055 ,660 -,022 ,072 -,021 AuModelAy AuTAy AuSig.
Ay Au(Constan.
Ay 3,669 ,000 Tourist attraction 9,565 ,000 Destination -,305 ,761 Image Aua.
Dependent Variable: Interest in VisitingAy Source: SPSS Statistics 25 Based on partial test calculations .
carried out with SPSS for Windows software, the following findings were obtained:
How tourist destinations (X.
affect travelers' interest (Y).
According to Table 4's partial test computation results .
Tcount for the tourist attraction variable (X.
Not more than 1.
count > ttabl.
, that is the ttable The tourist attraction-related variables have a significance value of 0.
meaning that the value is less than 0.
05 (Sig.
< 0.
Consequently.
Ho is rejected and H1 is accepted.
This demonstrates that, at least in part, variables associated with tourist attractions affect travelers' willingness to travel.
How Visitor Interest (Y) Affects How People See the Destination (X.
T value for the objective image variable (X.
305 based on the partial test calculation results .
displayed in Table 4.
This number is less than the 979 ttable value .
count < ttabl.
The destination image variable is shown to be bigger than 0.
05 (Sig.
> 0.
with a significance value of 0.
Ho is therefore accepted even though H2 is not.
This demonstrates how the visitor interest variable and the destination image variable are independent.
F Test (Simultaneou.
To determine if the impartial vA simultaneous test (F tes.
is performed to ascertain if the independent factors, considered alone or in combination, have an effect on the dependent Journal of Managiere and Business Available at http://ojs.
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Decisions are made based on the following parameters.
The following criteria are used to help decision-making when conducting a simultaneous test (F tes.
where one or more factors have an effect on the dependent variable:
Ho is approved and Ha is rejected if either Fcount < Ftable or the Sig value is > = 0.
This illustrates that the independent variable cannot have an equal impact on the dependent variable.
Conversely, if Fcount exceeds Ftable or Sig is less than 0.
Ho is rejected and Ha is This demonstrates that the independent and dependent variables are influenced at the same time.
The Fcount and Ftable values can be compared, as can the significance value of F and the alpha value of 0.
Therefore, the Ftable results must be looked for by looking at the F distribution table, or the Ftable value must be calculated using the formula: Ftable = F.
= F.
= F.
= 3.
The following findings were obtained from experiments conducted in parallel using the SPSS 25 for Windows software:
AuTable 5.
Simultaneous Test Results (F Tes.
Ay AuANOVA aAy AuSum of AuMean AuModelAy SquaresAy AudfAy SquareAy AuFAy Au1Ay AuRegression 176,947 88,474 48,388 Ay
Residual 235,864 1,828 Total
412,811
Aua.
Dependent Variable: Interest in VisitingAy Aub.
Predictors: (Constan.
Destination Image.
Tourist AttractionAy Source: SPSS Statistics 25 AuSig.
Ay ,000 b An F value of 48.
388 with a significant value of 0.
000 was found, according to Table 5.
The Fcount value of 48.
388 is greater than the Ftable value of 3.
07 because Fcount is greater than Ftable, and the significant value of 0.
000 is lower than the value of 0.
05 because Sig < Therefore.
H3 is accepted and Ho is rejected.
This shows that interest in visiting is influenced by each independent variable .
ourist attraction and destination imag.
Coefficient Determination Test (R.
AuTable 6.
Results from Testing the Coefficient of Determination (R.
Ay AuModel Summary bAy AuModel AuR AuAdjusted R AuStd.
Error of Ay AuRAy SquareAy SquareAy the EstimateAy ,655 ,429 ,420 Predictors: (Constan.
Destination Image.
Tourist Attraction Aub.
Dependent Variable: Interest in VisitingAy Source: SPSS Statistics 25 Table 6 shows that the independent factors in this study tourist attraction and destination image are expected to have a 42.
9% influence on the dependent variable .
nterest in Journal of Managiere and Business Available at http://ojs.
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, with a coefficient of determination R Square of 0.
Extra factors not included in the study account for 57.
1% of the total influence.
CONCLUSION AND SUGGESTION
On the basis of data analysis and discussion of research findings, the following conclusions can be made: A significant effect of partial attractiveness on interest in visiting Lentera Merah Beach has been seen, as indicated by a tcount value of 9.
565, higher than the ttable value of 1.
979, and a significance value of 0.
000, less than 0.
Research indicates that the tcount value of -0.
305, which is less than the ttable value of 1.
979, and the significance value 761, which is less than 0.
05, both point to the lack of a meaningful relationship between perception of Lentera Merah Beach and interest in visiting.
Two factors determine interest in Lentera Merah Beach: the Fcount value of 48.
388 is larger than the Ftable value of 3.
and the significant value of 0.
000 is less than the value of 0.
05 (Sig is more than alph.
The potential contribution of 42.
9% to the dependent variable (Intention to Visi.
is owned by tourist attractions and destination image.
REFERENCE