Corresponding Author: Tianna
Kinantasya
E-mail: [email protected]
INTRODUCTION
The benefits
of a growing tourism destination include increasing the number of jobs,
reducing the number of unemployed, and improving community welfare (Novitaningtyas et al., 2022). This is indicated by the number of domestic tourist trips in
2022, growing by 19.82% compared to the previous year (Statistics, 2023). Indonesia is the largest archipelago in the world, with an ocean
area of 5.8 million square km and a coastline length of 81,000 km. It has
extraordinary marine resources. Indonesia, with a potential 3⁄4 of its
territory in the sea, is known as the world's largest archipelago, with around
17,508 islands (Riska et al., 2020). The number of islands in Indonesia provides advantages that can
be developed into marine tourism objects. Marine tourism is a source of
utilization located in coastal and marine areas (Leonard Manaloe et al., 2020).. One of the most popular marine tourism activities is diving
tourism. Indonesia's diving tourism is ranked second in the World's Best Diving
Destinations based on readers' choices in Scuba Diving magazine in 2019.
According to (Malik & Sirait, 2021), diving tourism is a swimming activity to explore the natural
beauty of the sea with a breathing apparatus to survive in the sea for a longer
time. Many areas in Indonesia have been developed into sites for diving
tourism; one of the areas in Indonesia that has great potential for this diving
activity is Weh Island.
Weh Island is one of the regions in the
Province of Nangroe Aceh Darussalam, and it has a geographical location at the
western end of the Republic of Indonesia archipelago. It has diverse natural
potential on land and in the sea and distinctive and beautiful characteristics.
The area of Weh Island is � 39,375, with boundaries to the north with the Bay
of Bengal, south with the Indonesian Ocean, east with the Malacca Strait, and
west with the Indian Ocean. Weh Island has considerable and varied tourism potential
with the characteristics of the area surrounded by the sea (Agus, 2019). The current condition of tourism on Weh Island is still affected
by the COVID-19 pandemic. (Sugihamretha, 2020)This is reflected in the number of tourist visits to the Sabang
City Tourism Office. There was a decrease in the number of tourists, but with
the reduced spread of the COVID-19 virus in 2022, the graph of tourist visits
has begun to show a fairly good increase.
Table 1. Number of Tourist Visits
to Weh Island in 2018-2022
|
Year
|
Total
|
|
2018
|
739.333
|
|
2019
|
620.694
|
|
2020
|
126.290
|
|
2021
|
155.253
|
|
2022
|
254.048
|
Source:
Sabang City Tourism Office 2023
The decline in tourist visits also impacts the
income of tourism sector business actors. This condition also occurs on Weh
Island. Therefore, it is necessary to identify factors that are expected to
influence diving tourism interest. If the number of diving tourist visits
increases, it is hoped that diving tourism destinations on Weh Island can
develop and be sustainable.
One factor that has been shown to influence
interest in diving tourism is attractiveness. If attractiveness increases, tourists' interest in visiting will
also increase (Marpaung, 2019); (Indriastuty et al., 2020). The 3S should be used to measure the attraction of tourist
destinations: something to see, something to do, and something to buy (Purba & Simarmata, 2018). Based on this, tourist attractions are considered factors that
influence diving tourism interest on Weh Island.
A facility is
a service that a tourist destination offers to help or facilitate visitors'
activities there. Tourists will return to a location if it has sufficient
amenities, upholds service standards, and pleases them (Irawan et al., 2021). Previous research explains that facilities affect visitor
interest (Murdani & Martha, 2023); (Aini & Purwanto, 2023). Conversely, based on research (AMINAH, 2020), facilities do not significantly affect visiting interest.
However, there are gaps in some previous
research results. Therefore, the relationship between tourist attractions and
diving tourism interests and the facilities that are related to diving tourism
interests needs further research. The study results can be used as evaluation
material for managers of diving tourism destinations on Weh Island to determine
the factors that can increase diving tourism interest. Suppose the number of
diving tourist visits increases. In that case, it is hoped that the diving tourism
area on Weh Island can continue to develop and be sustainable to provide
benefits for improving the welfare of the surrounding community.
Based on the
background that has been described, that is why the researcher is very
interested in researching with a study entitled "Factors That Affect The
Interest in Diving Tourism on Weh Island�
METHOD
This research
was conducted in September - November 2023. The research method was carried out using quantitative research methods.
The quantitative approach is used to examine a specific sample of a population
where data collection uses research instruments, and the data that has been
collected is analyzed statistically or quantitatively (Sugiyono, 2013). The data collection used is divided into
two ways, namely:
Primary Data Collection
Secondary and
primary data collection was carried out by distributing online questionnaires
in the form of perform to respondents to determine their interest in diving
tourism on Weh Island.
Secondary Data Collection
This is one
indirect way of obtaining the necessary data. Surveys in this way are carried
out using literature study techniques published online by the Tourism Office,
scientific journals, and others.
This study
uses a measurement tool, namely the Likert scale. The Likert scale is used to gauge an
individual's or a group's attitudes, beliefs, and perceptions on social issues (Sugiyono, 2013). Researchers created a questionnaire
regarding diving tourism on Weh Island, which was given to participants in the
study. The questionnaire included five levels total on a scale, and the results
were broken down into the following categories:
1)
Strongly
Agree (SS): with a score of 5
2)
Agree (S):
With a score of 4
3)
Neutral (N):
with a score of 3
4)
Disagree(TS)
:with score2
5)
Strongly
Disagree (STS): with a score of 1
The sampling
technique involves distributing type forms through chat applications and groups
such as WhatsApp and Instagram to target people with diving certifications.
From the results of the distribution of the typeform, there were 97
respondents. After the data is collected, it is compiled into a similar table
for further quantitative processing. Ninety-seven respondents were obtained
based on surveys/questionnaires and interviews. The sample respondents are dive
tourists who have special diving certifications. This research uses
non-probability sampling techniques because the population is unknown, and
purposive sampling is a sampling technique that considers reaching respondents
who are easiest to provide information. (Suhartanto et al., 2018). The questionnaire used is a closed question type consisting of
10 question items for the tourist attraction variable, 10 for the facility
variable, and 7 for the tourist interest variable. The following is the
questionnaire used in this study.
Table 2. Operational variables
|
Variables
|
Item
|
Indicator
|
|
Attractiveness
|
DT1
|
The sea
used as a diving tourism spot must have an abundant variety of fish species.
|
|
DT2
|
The sea
used as a diving tourism spot must have extensive coral reefs.
|
|
DT3
|
Seas used
as dive tourism spots must have restrictions on fishing practices.
|
|
DT4
|
People and
divers are not allowed to take marine life or damage the marine environment,
a dive tourism spot.
|
|
DT5
|
The sea
used as a diving tourism spot must have good visibility.
|
|
DT6
|
Dive spots
should protect shipwrecks and historical artifacts in the sea.
|
|
DT7
|
Dive spots
should have strict regulations on the illegal use of dynamite or nets.
|
|
DT8
|
Seas that
are used as dive tourism spots must have strict nature reserves.
|
|
DT9
|
Seas used
as dive tourism spots must be safe for divers.
|
|
DT10
|
Seas that
are used as tourist spots must have development restrictions so that
sustainability is maintained.
|
|
Facilities
|
FAS1
|
Dive
attractions must have a reception desk for check-in and check-out.
|
|
FAS2
|
The dive
site should have a swimming pool used for amateur diver training.
|
|
FAS3
|
Dive tourism sites must have dive centers.
|
|
FAS4
|
Dive sites should
have areas for other sports.
|
|
FAS5
|
Dive
tourism sites should provide a multipurpose room that can be used as a place
to learn theories.
|
|
FAS6
|
Dive sites
should offer indoor and outdoor activities in addition to diving.
|
|
FAS7
|
The dive
site must have sufficient parking space.
|
|
FAS8
|
There
should be lodging/hotels in the dive site area.
|
|
FAS9
|
There
should be a minimarket in the dive site area.
|
|
FAS10
|
Must have a
restaurant in the dive site area
|
|
Interest in visiting
|
MB1
|
I am interested
in doing diving tourism on Weh Island because I want to see the uniqueness,
authenticity, and beauty of the underwater world.
|
|
MB2
|
I am
interested in visiting Weh Island because I want to enjoy the diving tourism
facilities and infrastructure.
|
|
MB3
|
I am
interested in visiting Weh Island for fun (recreation)
|
|
MB4
|
I am
interested in visiting Weh Island because of its attractiveness.
|
|
MB5
|
I am
interested in conducting diving tourism on Weh Island to learn how it differs
from other dive sites.
|
|
MB6
|
I am
interested in diving tourism on Weh Island because I am bored with routine
activities and want tranquility.
|
|
MB7
|
I am
interested in doing diving tourism on Weh Island to find new experiences and
friends.
|
Partial Least Square (SEM-PLS) is
a structural equation modeling technique for data processing and analysis. An
analytical method used to test theories and identify the link between
independent and dependent variables is called structural equation modeling, or
SEM. In structural equation modeling (SEM), the Smart-Partial Least Square
(SmartPLS) version 3.3.7 software is used for data processing. Two assessment
model evaluations are employed in the implementation: Evaluation of the
Measurement or Outer Model and the Structural or Inner Model. The outer model
consists of convergent validity observed through loading factor> 0.5,
discriminant Validity, which includes (1) AVE (Average Variance Extracted) value, and (2) Fornell
Larcker criterion measurement. Reliability testing includes (1) Composite
Reliability and (2) Cronbach's alpha. Inner model measurement is by using (1)
the coefficient of determination (R2) and (2) VIF (variance inflation factor). In
order to assess the direction of the link between the variables and the degree
of significance of the association, the original sample estimates (O) value,
t-statistics (T), and p-values (P) are examined during the hypothesis testing
process.
RESULTS AND DISCUSSION
Table 3. Characteristics of respondents
|
Gender
|
Frequency
|
Percentage
(%)
|
|
Male
|
77
|
74.76
|
|
Female
|
26
|
25.24
|
|
Age
|
|
|
|
< 20
|
1
|
0.97
|
|
20 - 30
|
27
|
26.21
|
|
31 - 40
|
38
|
36.89
|
|
41 - 50
|
22
|
21.36
|
|
> 50
|
15
|
14.56
|
|
Dive Agency
|
|
|
|
Lunar dive resort
|
1
|
0.97
|
|
PADI
|
64
|
62.14
|
|
POSITION
|
5
|
4.58
|
|
RAID
|
17
|
16.50
|
|
SSI
|
16
|
15.53
|
|
Certification
level
|
|
|
|
Advanced
|
21
|
20.39
|
|
dive master
|
16
|
15.53
|
|
instructor
|
26
|
25.24
|
|
open water
|
25
|
24.27
|
|
rescue
|
15
|
14.56
|
Table 4. Descriptive statistics of latent variable constituent items
|
Variables
|
Item
|
Mean
|
Median
|
Min
|
Max
|
Standard
Deviation
|
|
Attractiveness
|
DT1
|
4.204
|
5
|
1
|
5
|
1.027
|
|
DT2
|
4.155
|
4
|
1
|
5
|
1.031
|
|
DT3
|
4.650
|
5
|
1
|
5
|
0.720
|
|
DT4
|
4.767
|
5
|
1
|
5
|
0.727
|
|
DT5
|
4.320
|
5
|
1
|
5
|
0.895
|
|
DT6
|
4.718
|
5
|
1
|
5
|
0.769
|
|
DT7
|
4.874
|
5
|
1
|
5
|
0.586
|
|
DT8
|
4.359
|
5
|
1
|
5
|
0.923
|
|
DT9
|
4.738
|
5
|
1
|
5
|
0.638
|
|
DT10
|
4.757
|
5
|
1
|
5
|
0.675
|
|
Facilities
|
FAS1
|
3.825
|
4
|
1
|
5
|
1.092
|
|
FAS2
|
3.553
|
4
|
1
|
5
|
1.229
|
|
FAS3
|
4.534
|
5
|
1
|
5
|
0.810
|
|
FAS4
|
3.087
|
3
|
1
|
5
|
1.158
|
|
FAS5
|
3.641
|
4
|
1
|
5
|
1.139
|
|
FAS6
|
3.621
|
4
|
1
|
5
|
1.116
|
|
FAS7
|
3.699
|
4
|
1
|
5
|
1.113
|
|
FAS8
|
4.301
|
5
|
1
|
5
|
0.912
|
|
FAS9
|
3.913
|
4
|
1
|
5
|
0.996
|
|
FAS10
|
4.087
|
4
|
1
|
5
|
1.006
|
|
Interest in
visiting
|
MB1
|
4.563
|
5
|
1
|
5
|
0.784
|
|
MB2
|
4.301
|
5
|
1
|
5
|
0.857
|
|
MB3
|
4.340
|
5
|
1
|
5
|
0.876
|
|
MB4
|
4.369
|
5
|
1
|
5
|
0.903
|
|
MB5
|
4.466
|
5
|
1
|
5
|
0.798
|
|
MB6
|
4.165
|
4
|
1
|
5
|
0.966
|
|
MB7
|
4.272
|
5
|
1
|
5
|
0.957
|
Based on the results of frequency statistical analysis,
it shows that 103 respondents consisted of 77 men, or 74.76%, and 26 women, or
25.24%, where the highest age distribution was 31-40 years old, as many as 38
people or 36.89%, while 20-30 years old was 27 people (26.21%), and 41-50 years
old was 22 people (21.36%). While diving agency respondents mostly belong to
PADI, as many as 64 people (61.14%), and most have instructor-level
certification and open water, as many as 26 people (25.24%) and 25 people (24.27%),
respectively. In addition, based on the results of descriptive statistical
analysis show that the attractiveness variable consisting of 10 items has a
mean value ranging from 4.15 - 4.87, the facility variable consisting of 10
items has a mean value of 3.08 - 4.53, and the visiting interest variable
consisting of 7 items has a mean value of 4.16 - 4.56. This shows that the
attraction variable has a higher mean value range than the facility variable
and visiting interest.
Convergent validity
The convergent validity test is used to confirm that the
responses to each latent variable in this study are interpreted by respondents
in the same way as intended by the researcher. The convergent validity value is
used to determine the validity of a construct. Indicators are valid if the
factor loading value exceeds 0.5 (J. Hair et al., 2010).
Table 5. Loading factor value
|
Variables
|
Item
|
Outer loading
|
Description
|
|
Attractiveness
|
DT1
|
0.566
|
Valid
|
|
DT10
|
0.850
|
Valid
|
|
DT2
|
0.593
|
Valid
|
|
DT3
|
0.794
|
Valid
|
|
DT4
|
0.842
|
Valid
|
|
DT5
|
0.703
|
Valid
|
|
DT6
|
0.775
|
Valid
|
|
DT7
|
0.831
|
Valid
|
|
DT8
|
0.749
|
Valid
|
|
DT9
|
0.722
|
Valid
|
|
Facilities
|
FAS1
|
0.689
|
Valid
|
|
FAS10
|
0.705
|
Valid
|
|
FAS2
|
0.740
|
Valid
|
|
FAS3
|
0.742
|
Valid
|
|
FAS4
|
0.539
|
Valid
|
|
FAS5
|
0.793
|
Valid
|
|
FAS6
|
0.721
|
Valid
|
|
FAS7
|
0.765
|
Valid
|
|
FAS8
|
0.704
|
Valid
|
|
FAS9
|
0.771
|
Valid
|
|
Interest in
Visiting
|
MB1
|
0.786
|
Valid
|
|
MB2
|
0.865
|
Valid
|
|
MB3
|
0.846
|
Valid
|
|
MB4
|
0.906
|
Valid
|
|
MB5
|
0.860
|
Valid
|
|
MB6
|
0.749
|
Valid
|
|
MB7
|
0.814
|
Valid
|
Based on the data presentation in the table and figure
above, it is known that the latent variable attractiveness consisting of 10
items has an outer loading value ranging from 0.566 - 0.850, while the facility
variable consisting of 10 items has an outer loading value ranging from 0.689 -
0.765, and the visiting interest variable consisting of 7 items has an outer
loading value ranging from 0.786 - 0.906. This shows that all items that
comprise the latent variable are classified as valid because they have a
loading factor value> 0.50.
Discriminant Validity
Discriminate validity measures how far a construct is
truly different from other constructs. A high discriminant validity value
proves a construct is unique and can capture the measured phenomenon. The AVE
(Average Variance Extracted) value is used to determine the validity value of a
construct. The AVE (Average Variance Extracted) criterion for a variable to be
valid must be above 0.50 (J. Hair et al., 2010).
Table 6. Indicator Average Variance Extracted
|
Variables
|
Average Variance Extracted (AVE)
|
|
Attractiveness
|
0.560
|
|
Facilities
|
0.518
|
|
Interest in Visiting
|
0.695
|
The latent attractiveness variable has an average
variance extracted value of 0.560. In contrast, the facility variable has an
AVE value of 0.518, and the visiting interest variable is 0.695. Based on the
results of validity analysis through the average variance extracted indicator,
it has an AVE value> 0.5 on all latent variables, so it is classified as
valid.
In addition to using AVE, Fornell-Larcker criteria and
cross-loading can also be employed to determine discriminant validity. The Fornell-Larcker
criterion involves comparing the square root of the AVE for each construct with
the correlations between that construct and other constructs in the research
model. A construct is considered to have good discriminant validity if the
square root of its AVE is greater than the correlation between it and other
constructs. In that case, the discriminant validity is declared good.
Table 7. Discriminant Validity Value (Fornell-Larcker
Criterion)
and the root of the Average Variance Extracted
|
Attractiveness
|
Facilities
|
Interest in Visiting
|
|
Attractiveness
|
0.748
|
|
|
|
Facilities
|
0.634
|
0.720
|
|
|
Interest in Visiting
|
0.648
|
0.622
|
0.834
|
When viewed from the AVE Root value (bold), it has a
greater value in the construct than in other variables. This value indicates
that the variable is classified as valid. The AVE root value on the
attractiveness variable is 0.748, the facility variable is 0.720, and the
interest in visiting is 0.834.
Cross loading
Discriminant validity can be assessed by examining the
cross-loading values of the construct measurements. These values indicate the
strength of the correlation between each construct and its own indicators, as
well as between its indicators and those from other constructs. A measurement
model is considered to have good discriminant validity if the correlation
between a construct and its own indicators is greater than the correlation
between the indicators of different constructs. The following is a test of
discriminant validity using the cross-loading method.
Table 8. Cross loading value
|
Attractiveness
|
Facilities
|
Interest in Visiting
|
|
DT1
|
0.566
|
0.504
|
0.346
|
|
DT10
|
0.850
|
0.454
|
0.569
|
|
DT2
|
0.593
|
0.509
|
0.389
|
|
DT3
|
0.794
|
0.481
|
0.521
|
|
DT4
|
0.842
|
0.429
|
0.510
|
|
DT5
|
0.703
|
0.444
|
0.404
|
|
DT6
|
0.775
|
0.476
|
0.532
|
|
DT7
|
0.831
|
0.481
|
0.529
|
|
DT8
|
0.749
|
0.542
|
0.541
|
|
DT9
|
0.722
|
0.476
|
0.439
|
|
FAS1
|
0.346
|
0.689
|
0.392
|
|
FAS10
|
0.510
|
0.705
|
0.435
|
|
FAS2
|
0.457
|
0.740
|
0.388
|
|
FAS3
|
0.591
|
0.742
|
0.582
|
|
FAS4
|
0.170
|
0.539
|
0.243
|
|
FAS5
|
0.474
|
0.793
|
0.490
|
|
FAS6
|
0.355
|
0.721
|
0.463
|
|
FAS7
|
0.354
|
0.765
|
0.390
|
|
FAS8
|
0.641
|
0.704
|
0.543
|
|
FAS9
|
0.465
|
0.771
|
0.396
|
|
MB1
|
0.518
|
0.433
|
0.786
|
|
MB2
|
0.599
|
0.540
|
0.865
|
|
MB3
|
0.502
|
0.532
|
0.846
|
|
MB4
|
0.530
|
0.575
|
0.906
|
|
MB5
|
0.540
|
0.543
|
0.860
|
|
MB6
|
0.527
|
0.534
|
0.749
|
|
MB7
|
0.556
|
0.457
|
0.814
|
The cross-loading results show that the attraction
variable has the highest correlation value in the DT1-DT10 indicator, while the
facility variable has the highest correlation value in the FAS1-FAS10
indicator, and the visiting interest variable has the highest correlation value
in the MB1-MB7 indicator. Thus, based on cross-loading testing, the latent
variable constituent items are classified as valid.
Reliability
The reliability test is carried out to know the research
instrument items, in this case, the research questionnaire used for tools in
this study. Suppose the research instrument item is used twice to measure the
same symptoms. In that case, the research instrument item will provide
consistent measurement results.� The
research instrument's reliability in this study was assessed using both
composite reliability and the Cronbach's Alpha coefficient. Composite
Reliability is an index that shows how much a measuring device can be trusted
to be reliable. Data that has composite reliability> 0.7 has high
reliability. Meanwhile, a variable can be declared reliable or meet Cronbach's
alpha if it has a Cronbach's alpha value> 0.7. The classification of reliability
categories using Cronbach's alpha indicator is as follows: (1) a scale of 0 -
0.2 is categorized as very unreliable, (2) 0.21-0.41 is categorized as
unreliable, (3) 0.42-0.60 is moderately reliable, (4) 0.61-0.80 is categorized
as reliable, and 0.81-1.00 is categorized as very reliable (Viorentina, 2023).
Table 9. Composite reliability and Cronbach's alpha
values
|
Variables
|
Cronbach's Alpha
|
Composite Reliability
|
|
Attractiveness
|
0.911
|
0.926
|
|
Facilities
|
0.896
|
0.914
|
|
Interest in Visiting
|
0.926
|
0.941
|
Based on the data presented in the table above, Cronbach's alpha value
of each research variable ranges from 0.896 to 0.926, which is classified as
very reliable. Meanwhile, the composite reliability value is 0.914 to 0.926,
which is classified as reliable.
Inner
model measurement model
The structural model (or inner model) represents the pattern of
relationships among research variables. This model is assessed by examining the
coefficients between variables and the coefficient of determination (R�). The
R� value essentially gauges the extent to which the model can account for
variations in the dependent variable. A value nearing 1 indicates that the
independent variables almost fully account for the variations observed in the
dependent variable. According to Chin's classification, the R� value is
considered strong if it exceeds 0.67, moderate if it falls between 0.33 and
0.67, weak if it is between 0.19 and 0.33, and very low if it is below 0.19. (J. F. Hair et al., 2021). The R-square value can be
seen in the following table:
Table 10. R-square value
|
R Square
|
|
Interest in Visiting
|
0.494
|
Based on this table, it can be seen that the R-square value of the
endogenous variable of visiting interest is 49.40%. This shows that the effect
of attractiveness and facilities on visiting interest is 49.40%.
In addition, in VIF (Variance Inflation Factor) measurement, according
to (J. et al. et al., 2021), VIF values above 5 indicate
the presence of collinearity symptoms in the research model. The table shows
that all variables in this study have a VIF value <5, which means that this
study is free from collinearity symptoms.
Table 11. Collinearity Statistics (Inner VIF Values)
|
Attractiveness
|
Interest in Visiting
|
|
Facilities
|
1.672
|
|
Interest in Visiting
|
1.672
|
The analysis results show that the latent variables of attraction and
facilities have a VIF value on visiting interest of 1,672 and 1,672,
respectively.� All exogenous variables
have a VIF value < 10, which shows that the latent variable is free from
collinearity symptoms.
Q SQUARE
𝑄� (predictive relevance) is
performed using the blindfolding analysis method. Q-square can explain the
predictive relevance of the dependent variable to the independent variable. The
threshold value in testing 𝑄� (predictive relevance) is 0.02
for small influence, 0.15 for medium influence, and 0.35 for large influence.
The following are the results of the Q-Square in the study.
Table 12. Q square test
|
S
|
SSE
|
Q� (=1-SSE/SSO)
|
|
Attractiveness
|
1030.00
|
1030.00
|
|
|
Facilities
|
1030.00
|
1030.00
|
|
|
Interest in Visiting
|
721.00
|
493.42
|
0.316
|
Based on the table above, it is known that the QSquare value on the
endogenous variable of visiting interest is 0.316. These results mean that the
amount of data diversity explained by this research model is 31.6%. When
classified, the Qsquare value of visiting interest is classified as having a
moderate influence because the resulting value is> 0.17.
Hypothesis Test
Table 4. Hypothesis Test Results of Direct Effect
|
Original Sample (O)
|
T Statistics (|O/STDEV|)
|
P Values
|
|
Attraction -> Interest in Visiting
|
0.424
|
3.435
|
0.001
|
|
Facility -> Interest in Visiting
|
0.353
|
3.948
|
0.000
|
Based on the
results of the analysis on hypothesis testing, it shows that
1.
H1: Attractiveness has a direct positive effect on visiting interest.
Hypothesis 1 is accepted because it has a p-value of 0.001 or <0.05 and a
t-statistic value of 3.435 or> 1.96, so attractiveness positively affects
visiting interest of 0.424. The more attractiveness increases, the more
interest in visiting will increase by 42.4%.
2.
H2: Facilities have a direct positive effect on visiting interest.
Hypothesis 2 is accepted because it has a p-value of 0.000 or <0.05 and a
t-statistic value of 3.948 or> 1.96, so facilities positively affect
visiting interest of 0.353. The more facilities there are, the more interest in
visiting will increase by 35.3%.
H1: The effect of tourist attraction on visiting interest
The analysis results show that attractiveness has a direct positive
effect on visiting interest of 0.424. This is because it has a p-value of 0.001
or <0.05 and a t-statistic value of 3.435 or> 1.96, so attractiveness
positively affects visiting interest of 0.424. The more attractiveness
increases, the interest in visiting will increase by 42.4%. When viewed in
research shows that tourist attractions include the sea that is used as a dive
tourism spot, which has a variety of abundant fish species, has extensive coral
reefs, the sea that is used as a dive tourism spot has good visibility, dive
tourism spots protects shipwrecks (shipwrecks) and historical artifacts in the
sea, dive tourism spots have strict rules about not allowing the illegal use of
dynamite or nets, the sea that is used as a dive tourism spot has a strict
nature reserve, is safe for divers, and has development restrictions so that
sustainability is maintained. These tourist attractions can affect tourists'
interest in visiting them. This is because tourists have an interest in
visiting diving tourism on Weh Island. After all, they want to see the
uniqueness, authenticity, and beauty of the underwater; tourists want to enjoy
the available diving tourism facilities and infrastructure and are interested
in visiting to have fun (recreation); tourists are interested in doing diving
tourism to find new experiences and friends and because they are bored with
routine activities and want to find peace. These results align with research
conducted by (Normalasari et al., 2023) which reveals
that tourist attraction influences interest in tourist visits. This explains
that if a tourist attraction has an attraction that includes originality,
diversity, security (rarity), and the integrity of the tourist attraction, it
is able to influence the interest of tourist visits. Tourism attraction is an
important factor for destinations in bringing in tourists. This is because the
elements contained in tourist attractions, which include originality,
diversity, security, and wholeness, can influence the interest of tourist
visits (Normalasari et al., 2023). According to (Sucipto, 2022), tourist
attraction is the main motivation for tourists to visit an attractive place in
the eyes of visitors based on its beauty and uniqueness. According to (Murdani & Martha, 2023), attractiveness
is one of the main factors for tourists who want to make tourist visits, with a
good attraction that is presented to tourists resulting in a better interest in
visiting, meaning that the better the tourist attraction of a tourist
attraction, the more tourists will want to visit.
H2: The effect of facilities on visiting interest
The analysis results show that the facility has a direct positive effect
on visiting interest of 0.353. This is because it has a p-value of 0.000 or
<0.05 and a statistical t-value of 3.948 or> 1.96, so the facility has a
positive effect on visiting interest of 0.353. The more facilities there are,
the more interest in visiting will increase by 35.3%. When viewed in research
shows that tourist facilities include tourist attractions having a reception
desk for checking in and checking out, having a swimming pool used for training
amateur divers, having a dive center, having an area for other sports,
providing a multipurpose room that can be used as a place to study theory for
amateur divers, offering indoor and outdoor activities other than diving
activities, having sufficient parking space, having lodging/hotels in the dive
tourism location area, having a minimarket in the dive tourism location area,
having a restaurant/restaurant in the dive tourism location area. Fully
available facilities at tourist sites influence tourists to be interested in
visiting. This shows that tourist facilities are one of the shapers of creating
a sense of interest in visiting because the fulfillment of good tourist
facilities will increase interest in visiting (Lestari et al., 2022). Facilities are
everything that visitors need while in a tourist spot so that visitors feel
comfortable and happy to visit. Therefore, the manager of the tourist
attraction must be able to provide regular improvement and maintenance of the
facilities provided so that visitors feel safe and comfortable (Sari & Suyuthie, 2022). According to (Murdani & Martha, 2023), facilities such
as facilities and infrastructure support tourists when visiting a tourist
attraction and make it easier for tourists to carry out their activities
because if the facilities provided by the tourist attraction manager are
completely adequate and comfortable to use, there is a sense of satisfaction
for tourists when visiting the tourist attraction.
CONCLUSION
Based on the
results and discussions that have been explained, it can be explained that
attraction has a direct positive effect on the interest of visiting, with the
Significance value being 0.001 or <0.05 so that the increased attraction,
the interest in visiting will increase by 42.4%. In addition, the facility has
a direct positive effect on the interest in visits with a significance value of
0.000 or <0.05, so that with the increase in the facility, the interest in
visits will increase by 35.3%. It is hoped that managers and stakeholders will
be more active in posting about the uniqueness of Weh Island diving tourist
attractions and inviting tourists who have visited to be more active in
recommending diving tours through social media in an effort to attract tourists.
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