TREND ANALYSIS AND CORRELATION OF TOURIST, RESTAURANT AND HOTEL VISITS IN KUNINGAN REGENCY

  • Rizki Hesananda Universitas Siber Indonesia
  • Agus Trihandoyo Universitas Siber Indonesia
  • Ninuk Wiliani Universitas Siber Indonesia
  • Nidya Sari Rahmawati Universitas Siber Indonesia
Keywords: Correlation, Kuningan Regency, Sustainable Development, Trend Analysis, Tourism

Abstract

This study conducts an in-depth analysis of the tourism sector in Kuningan Regency, focusing specifically on hotel stays, tourist arrivals, and restaurant visits. Utilizing forecasting models and correlation analyses, the research aims to uncover trends and interdependencies within the sector. The primary objective is to identify actionable insights that can inform data-driven decision-making. The study employs the FBProphet algorithm for forecasting future trends and conducts Kendall correlation analysis to examine relationships among key variables. Data collected spans a time series of 84 months, from January 2016 to December 2022. FBProphet accurately predicts trends in hotel stays, while variations exist in predictions for tourist arrivals and restaurant visits. Mean values for hotel stays, tourist arrivals, and restaurant visits are 21,098.67, 135,647.33, and 130,660.83, respectively. Kendall correlation analysis reveals a moderate positive correlation (0.214, p-value = 0.004) between tourist arrivals and restaurant visits, a strong positive correlation (0.324, p-value = 1.291e-05) between tourist arrivals and hotel stays, and a weaker positive correlation (0.176, p-value = 0.019) between restaurant visits and hotel stays. These findings underscore the intricate dynamics of Kuningan Regency's tourism sector, providing stakeholders with critical insights for strategic planning. The research contributes significantly to sustainable growth initiatives by guiding stakeholders in leveraging the interconnected elements of tourism and making well-informed decisions.

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Author Biography

Rizki Hesananda, Universitas Siber Indonesia

Hi, my name is Hesa. I am a practitioner of the IT industry who is also active in teaching, research and community service as a computer science lecturer. I work as a Web Developer. I have done several types of work such as freelance, corporate companies, ministries and start-ups. I have come to understand, different types of organizations, different needs and their approach to IT needs.

Early in my career, I started a career in the IT industry to apply the computer science I learned in college. I want to know what the real world is like as an IT worker. Not that I'm an expert, but that the industrial world is far more sophisticated than I imagined. I am more and more interested in exploring this field. Then I decided to take my Masters and took some online courses on Computer Science. I work on more than 50 websites, whether it's done in a team or alone, both successful and unsuccessful.

I am a teacher and a learner. At this time, I want to share the knowledge that I got in my master's degree course and my experience from practicing in the IT industry. What I understand is that teaching is the most effective way to learn compared to just reading or taking notes. As a lecturer, I think it is very necessary to understand new fields and always be updated about the outside world. Therefore, now I am starting to explore the fields of Artificial Intelligence such as Data Mining and Computer Vision.

As far as I know, Science and practice in the IT world is developing at an exponential rate. Therefore, the ability to work in teams, adapt to the environment and habits to increase self- capacity are very essential skills.

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Published
2024-09-23
How to Cite
Hesananda, R., Trihandoyo, A., Wiliani, N., & Rahmawati, N. (2024). TREND ANALYSIS AND CORRELATION OF TOURIST, RESTAURANT AND HOTEL VISITS IN KUNINGAN REGENCY. Jurnal Pilar Nusa Mandiri, 20(2), 94-102. https://doi.org/10.33480/pilar.v20i2.4618