Analysis of Instagram Online Promotion Factors and
Electronic Word of Mouth (E-Wom) on Decisions to
Visit Cikadongdong River Tubing Tourism
Carolin Nurwulan Adiyanto1, Clarisa Seviani2, Ferry Andika3, Rahmadi4*
Swadaya Gunung Jati University, Cirebon, Indonesia1234*
Email: [email protected]1, [email protected]2, [email protected]3, [email protected]4*
Abstract |
This study investigates
how travelers' decisions to attend the Cikadongdong
River Tubing activity are influenced by online marketing and electronic
word-of-mouth (eWOM). The study employed a
quantitative and associative technique, collecting data using a Likert scale
questionnaire and selecting a sample of one hundred visitors using deliberate
non-probability selection. The data was analyzed using SPSS version 25. The
findings demonstrate that online marketing (X1) and eWOM
(X2) both strongly and favorably affect the decision to visit (Y). This
illustrates the importance of digital engagement for the tourism sector and
demonstrates the necessity of effective online marketing strategies and
favorable eWOM for attracting tourists to the Cikadongdong River Tubing site. |
Keywords: |
Online promotion,
electronic word of mouth, Visiting Decision |
RESEARCH METHODS
An associative
technique combined with a quantitative method is used in this study
19,351 people
visited Majalengka Regency's Cikadongdong
River Tubing attraction in 2023, based on the population count of the research.The sample size was calculated using the Slovin technique with a 10% margin of error, producing a
non-probability sample of 100 respondents. The data was collected using a
Likert scale in a questionnaire, and the analysis was performed using SPSS 25.
Table 1.
Demographic Data
Category |
Alternative Answers |
Frequency (F) |
Percent (100) |
Gender |
Man |
46 |
46% |
Woman |
54 |
54% |
|
Age |
<17 Years |
13 |
13% |
18-28 Years |
78 |
78% |
|
29-37 Years |
9 |
9% |
|
>38 Years |
0 |
0% |
|
Work |
Already working |
44 |
44% |
Student / Students |
56 |
56% |
|
Instagram
Application Users |
Yes |
100 |
100% |
No |
0 |
0% |
Instrument Testing Results
Validity test
The
validity test shows the degree of consistency between the actual data collected
to answer the query and the potential research data
N-2 = 98 df = 100-2 =
Rtable = 0.196 indicates that the Rtable value is significant at 0.05.
Table 2. Results
of the Validity Test
No |
Variable |
Corrected
Item-Total Correlation |
Description |
Online Marketing (X1) |
|||
1 |
X1.1 |
0,744 |
Valid |
2 |
X2.2 |
0,684 |
Valid |
3 |
X3.3 |
0,725 |
Valid |
4 |
X4.4 |
0,718 |
Valid |
5 |
X5.5 |
0,501 |
Valid |
6 |
X6.6 |
0,681 |
Valid |
7 |
X7.7 |
0,721 |
Valid |
8 |
X8.8 |
0,738 |
Valid |
9 |
X9.9 |
0,727 |
Valid |
10 |
X10.10 |
0,765 |
Valid |
Digital Referrals (X2) |
|||
1 |
X2.1 |
0,790 |
Valid |
2 |
X2.2 |
0,795 |
Valid |
3 |
X2.3 |
0,847 |
Valid |
4 |
X2.4 |
0,756 |
Valid |
5 |
X2.5 |
0,759 |
Valid |
6 |
X2.6 |
0,816 |
Valid |
7 |
X2.7 |
0,743 |
Valid |
8 |
X2.8 |
0,782 |
Valid |
The visitation decision (Y) |
|||
1 |
Y.1 |
0,804 |
Valid |
2 |
Y.2 |
0,768 |
Valid |
3 |
Y.3 |
0,669 |
Valid |
4 |
Y.4 |
0,803 |
Valid |
5 |
Y.5 |
0,471 |
Valid |
6 |
Y.6 |
0,793 |
Valid |
7 |
Y.7 |
0,820 |
Valid |
8 |
Y.8 |
0,898 |
Valid |
9 |
Y.9 |
0,797 |
Valid |
10 |
Y.10 |
0,730 |
Valid |
According
to the previous table, any instrument related to the variables of online promotion
(X1), electronic word-of-mouth (X2), and visiting decision (Y) is regarded as
authentic.
Reliability Test
The
consistency of each instrument was evaluated using Cronbach's Alpha in the
reliability test
Table 3. Results of Reliability Testing
Variable |
Cornbach's Alpha |
Final Analysis |
Online Marketing |
0,881 |
Reliable |
Digital Referrals |
0,910 |
Reliable |
The visitation decision |
0,915 |
Reliable |
The reliability test results show in the above table that every variable has a Cronbach's Alpha value greater than 0.60. This implies that the inquiries about online advertising, accessible visitor routes, and electronic word-of-mouth (eWOM) are reliable.
Classic Assumption Test Results
Normality test
Table 4. Kolmogorov-Smirnov
Test for One Sample
Non-standard Residual |
||
N |
100 |
|
Standard Parametersa,b |
Mean |
0,0000000 |
Standard Deviation |
3,49781541 |
|
The Most Severe
Disparities |
Completely |
0,082 |
Positive |
0,063 |
|
Negative |
-0,082 |
|
Examine Statistics |
0,082 |
|
Asymptotic Signal
(2-tailed) |
,094c |
|
a. The
test's distribution is normal. |
||
b. Based
on the data. |
||
c. Lilliefors
Significance has been corrected. |
IBM SPSS
version 25 findings show that the residual data appears to have a normal
distribution with an asymp.sig value of 0.94, which
is more than the significance level of 0.05.
Multicollinearity Test
Table 5. Coefficients
of Examining Multicollinearity using Coefficients
Model |
Statistics of Collinearity |
||
Tolerance |
VIF |
||
1 |
(Constant) |
||
X1 |
0,313 |
3,195 |
|
X2 |
0,313 |
3,195 |
Data
from IBM SPSS version 25 show that neither of the independent variables has a
multicollinearity problem, with a variance inflation factor (VIF) of 3.195,
below the limit of 10. It also confirms that the variables internet marketing
(X1) and electronic word-of-mouth (X2), with tolerance values of 0.313 or 0.313
> 0.10, are not troublesome.
Multiple Linear Regression Test Results
Simultaneous Test (F Test)
Table 6. Results
of the Simultaneous Test (f test)
ANOVAa |
||||||
Model |
Sum
of Squares |
Df |
Mean
Square |
F |
Sig. |
|
1 |
Regression |
2656,323 |
2 |
1328,162 |
106,364 |
,000b |
Residual |
1211,237 |
97 |
12,487 |
|||
Total |
3867,560 |
99 |
||||
a. Dependent Variable: Y |
||||||
b. P
Forecasters: (Invariant), X2, X1 |
The
output findings in Table 8 show that the f-count value is 104.354 > f-table
(3.09) and the significance value is 0.000 < 0.05. One may draw the
conclusion that, either separately or in combination, internet advertising (X1)
and electronic word-of-mouth (X2) significantly influence the decision to
attend.
Partial Test (T-Test)
Table 7.
Partial Test Results (t-test)
Coefficientsa |
||||||||
Model |
Non-standard Coefficients |
Typical Coefficients |
T |
Sig. |
Statistics of Collinearity |
|||
B |
Std. Error |
Beta |
Tolerance |
VIF |
||||
1 |
(Constant) |
4,928 |
2,550 |
1,933 |
0,056 |
|||
X1 |
0,406 |
0,111 |
0,371 |
3,648 |
0,000 |
0,313 |
3,195 |
|
X2 |
0,598 |
0,123 |
0,495 |
4,877 |
0,000 |
0,313 |
3,195 |
|
a. Dependent Variable: Y |
a. The Impact of Online
Promotion on Visiting Choices.
The degree to which internet
marketing affects visitors' decisions to attend is displayed in Table 7. This
is supported by the significance value of 0.000, which is less than 0.05, and
the t-value of 3.648, which is higher than the crucial t-value of 1.984.
Consequently, the null hypothesis (Ho) is rejected and the alternative
hypothesis (Ha) is accepted.
b. How
Electronic Word of Mouth Affects Travel Decisions.
Electronic word-of-mouth is a
major factor in visitor decisions, as Table 7 illustrates. This assertion is
supported by the t-value of 4.877, which is more than the significant t-value
of 1.984, and the significance value of 0.000, which indicates significance at
the 0.05 level. Consequently, Ha is accepted whereas Ho is refused. Therefore, it
is clear that Visitor Decisions (Y) are significantly influenced by both Online
Promotion (X1) and Electronic Word of Mouth (X2).
Determination Coefficient Test (R Test)
Table 8. Results
of the Coefficient of Determination Test (r test)
Model
Summaryb |
||||
Model |
R |
R
Square |
Adjusted
R Square |
Std.
Error of the Estimate |
1 |
,829a |
0,687 |
0,680 |
3,53369 |
a.
Predictors: (Constant), X2, X1 |
||||
b.
Dependent Variable: Y |
68%,
or 0.680, is the modified R Square value, also known as the coefficient of
determination. This graph illustrates how online marketing and electronic
word-of-mouth work together to greatly influence consumers' visitation
decisions. It is believed that the remaining 32% is connected to additional
factors not included in this study.
CONCLUSION
Agag, G., Ali Durrani, B., Hassan Abdelmoety, Z.,
Mostafa Daher, M., & Eid, R. (2024). Understanding the link between net
promoter score and e-WOM behaviour on social media: The role of national
culture. Journal of Business Research, 170.
https://doi.org/10.1016/j.jbusres.2023.114303
Ahn, H., & Park, E. (2024). The impact of
consumers� sustainable electronic-word-of-mouth in purchasing sustainable
mobility: An analysis from online review comments of e-commerce. Research
in Transportation Business and Management, 52.
https://doi.org/10.1016/j.rtbm.2023.101086
Astuti, R. P., Kartono, K., & Rahmadi, R. (2020).
Pengembangan UMKM melalui Digitalisasi Tekonolgi dan Integrasi Akses
Permodalan. ETHOS: Jurnal Penelitian Dan Pengabdian Kepada Masyarakat, 8(2),
248�256. https://doi.org/10.29313/ethos.v8i2.5764
Bowo, A. N. A., Paryanto, P., & Iqbal, M. (2023).
Pengaruh Media Sosial Instagram terhadap Gaya Hidup Mahasiswa. Jurnal Ilmu
Manajemen Dan Pendidikan (JIMPIAN), 3(1).
https://doi.org/10.30872/jimpian.v3i1.2249
Fatimah, Siska Ernawati; Komara, Acep; Srisuk,
Prattana; Saha, Sanchita; Rahmatika, D. N. (2023). Educational Tourism Of
Local Wisdom Products In. Journal of Sustainable Community Service, 4(2),
1�8.
Islamiyah, D., Kurniati, R. R., & Krisdianto, D.
(2020). Analisis Pengaruh Celerity Endorser Dan Promosi Online Terhadap
Keputusan Pembelian Pada Online Shop. Jiagabi, 9(1).
Jannah, R., Rohman, N., Kiswantoro, A., Hayatri, M.
A. S., & Ashartono, R. (2023). Pengaruh Media Sosial Instagram Terhadap
Keputusan Berkunjung Ke Gunung Api Purba Nglanggeran Gunungkidul. Jurnal
Manajemen Perhotelan Dan Pariwisata, 6(2), 361�369.
https://doi.org/10.23887/jmpp.v6i2.60942
Jeljeli, R., Farhi, F., & Hamdi, M. E. (2022).
The mediating role of gender in social media shopping acceptance: from the WOM
perspective. Heliyon, 8(10).
https://doi.org/10.1016/j.heliyon.2022.e11065
Kayeser Fatima, J., Khan, M. I., Bahmannia, S.,
Chatrath, S. K., Dale, N. F., & Johns, R. (2024). Rapport with a chatbot?
The underlying role of anthropomorphism in socio-cognitive perceptions of
rapport and e-word of mouth. Journal of Retailing and Consumer Services,
77. https://doi.org/10.1016/j.jretconser.2023.103666
Komalasari, Y., & Eka Putri Suryantari, N. P. D.
K. (2021). Pemanfaatan Media Daring sebagai Upaya Peningkatan Penjualan Nasi
Koco di Banjar Gerenceng Desa Pemecutan Kaja Denpasar Utara Bali. Jurnal
Paradharma, 5(1).
Kumar, S., Prakash, G., Gupta, B., & Cappiello,
G. (2023). How e-WOM influences consumers� purchase intention towards private
label brands on e-commerce platforms: Investigation through IAM (Information
Adoption Model) and ELM (Elaboration Likelihood Model) Models. Technological
Forecasting and Social Change, 187.
https://doi.org/10.1016/j.techfore.2022.122199
Lee, W. L., Liu, C. H., & Tseng, T. W. (2022).
The multiple effects of service innovation and quality on transitional and
electronic word-of-mouth in predicting customer behaviour. Journal of
Retailing and Consumer Services, 64. https://doi.org/10.1016/j.jretconser.2021.102791
Liu, H., Jayawardhena, C., Shukla, P., Osburg, V. S.,
& Yoganathan, V. (2024). Electronic word of mouth 2.0 (eWOM 2.0) � The
evolution of eWOM research in the new age. Journal of Business Research,
176. https://doi.org/10.1016/j.jbusres.2024.114587
Mareta, R. K., Farida, N., & Dewi, R. S. (2022).
Pengaruh Citra Destinasi dan Produk Wisata terhadap Keputusan Berkunjung
melalui Electronic Word Of Mouth (Studi pada Pengunjung Wisata Eling Bening). Jurnal
Ilmu Administrasi Bisnis, 11(1). https://doi.org/10.14710/jiab.2022.33569
Mohajan, H. K. (2020). Quantitative research: A
successful investigation in natural and social sciences. Journal of
Economic Development, Environment and People, 9(4), 50�79.
Putra, P. P. A. (2021). Pengaruh City Branding Dan
City Image Terhadap Keputusan Berkunjung Dan Minat Berkunjung Kembali Ke Objek
Wisata Heritage Di Kota Denpasar. Tulisan Ilmiah Pariwisata (TULIP), 4(2).
https://doi.org/10.31314/tulip.4.2.51-64.2021
Ristiani. (2021). Pengaruh harga dan daya tarik wisata
terhadap keputusan berkunjung. Forum Ekonomi, 23(2).
Romdonny, J., & Maulany, S. (2020). Contribution
of Social Media in Increasing Marketing of Creative Economy Product. 123(Icamer
2019), 87�90. https://doi.org/10.2991/aebmr.k.200305.022
Sari, T., Pradhanawati, A., & Pinem, R. J.
(2021). Pengaruh Fasilitas , Electronic Word Of Mouth, Dan Destination Image
Terhadap Keputusan Berkunjung (Studi Pada Pengunjung Objek Wisata Pantai Suwuk
Kebumen). Jurnal Ilmu Administrasi Bisnis, 10(2). https://doi.org/10.14710/jiab.2021.30407
Sutrisno, A. P., & Mayangsari, I. D. (2022). Pengaruh
Penggunaan Media Sosial Instagram @Humasbdg Terhadap Pemenuhan Kebutuhan
Informasi Followers. Jurnal Common, 5(2).
https://doi.org/10.34010/common.v5i2.5143
Yuli, & Marpaung, H. (2021). Pengaruh Gaya Hidup,
Promosi Online, dan Kepercayaan Merek Terhadap Keputusan Pembelian Online
Produk Miniso di Asahan (Studi Kaus Mahasiswa Fakultas Ekonomi UNA). Jurnal
Manajemen, Ekonomi Sains, 2(2).
Copyright holder: Carolin Nurwulan Adiyanto, Clarisa Seviani, Ferry Andika, Rahmadi(2024) |
First publication right: |
This article is licensed under: |