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Journal : International Conference on Digital Advanced Tourism, Management, and Technology

Can Google Trends(GT) be used to predict tourist arrivals?: FB Prophet Machine Learning(ML) for Predicting Tourist Arrivals Indra Gunawan; Dwi Purnomo Putro; Adhika Pramita Widyassari 
International Conference On Digital Advanced Tourism Management And Technology Vol. 1 No. 1 (2023): International Conference on Digital Advanced Tourism, Management, and Technolog
Publisher : Sekolah Tinggi Ilmu Ekonomi Pariwisata Indonesia Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/ictmt.v1i1.57

Abstract

The big problem in tourism is how to provide appropriate preparations to serve tourists so that when the tourist season is low, resources can be saved and when the tourist season is busy, all resources can be provided effectively. Machine learning is a derivative branch of artificial intelligence, one of whose capabilities can be used to carry out data/dataset-based forecasting. This research uses a dataset obtained from GT from 2013-2023 with several keywords combining city names and tourist destination names in Yogyakarta Indonesia, then it will be compared with a dataset of tourist arrivals in the city of Yogyakarta obtained from the Central Statistics Agency. The Machine Learning model that will be used is Prophet Facebook.. This model uses a Bayessian as a backend algorithm. The results obtained from this research are that GTs can be used to predict tourist arrivals with some tweaks on the dataset. However, to get accurate results, various combinations of keywords are needed for the desired destination, and it is recommended to add some column namely max and mean to the dataset to prevent insufficiency of data of some keywords that make prediction result bad. In this research it can be concluded that the use of an additional max column can increase the COERR, MAPE and R2 values. Meanwhile, we found that the GT dataset can be used for forecasting best in time periods under 200 days. Also we found that using the GT dataset alone produces unstable COERR, MAPE and R2 values. Another finding is that the GT dataset that uses the YouTube filter is only suitable for use in Indonesia for the time period above 2018 considering that Indonesian people's access to YouTube has increased massively over that year and tends to decrease below that year. However, the trend shows that the use of searches on YouTube after 2018 tends to increase drastically, beating searches on the Google web.
Analysis Of Readiness For Smart City Implementation In Blora City Indonesia Joko Handoyo; Indra Gunawan; Retno Wahyusari
International Conference On Digital Advanced Tourism Management And Technology Vol. 1 No. 1 (2023): International Conference on Digital Advanced Tourism, Management, and Technolog
Publisher : Sekolah Tinggi Ilmu Ekonomi Pariwisata Indonesia Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/ictmt.v1i1.58

Abstract

Smart city is a concept initiated by the forum for the future which is predicted to be able to solve all aspects of problems in the lives of urban communities. The Smart City Framework consists of six aspects, namely Smart Governance, Smart Economy, Smart Branding, Smart Living, Smart Society and Smart Environment. However, this concept is too broad and complex, covers many things and involves many parties who will be involved in its implementation, so it is needed mature concepts and frameworks as a reference in implementation. Apart from that, each city has different problem characteristics, so it is necessary to carry out analytical studies to find out the problems in each aspect of a smart city. This research aims to analyze the readiness for smart city implementation in the city of Blora, Central Java Province, Indonesia. This analysis will be carried out on 6 aspects of smart cities which will be divided into 17 variables. The approach taken is a qualitative method where an assessment of readiness to achieve achievement targets is carried out through interviews. From the analysis that has been carried out, it can be said that the readiness achieved by the City of Blora for Smart City implementation has reached 66.7% so it still really needs to be improved.
Co-Authors Abdi Rahim Damanik Adhika Pramita Widyassari  Adi Rahmat Adven Agape Sinamo Adyatma, Davin Afrianto Agramanisti Azdy, Rezania Agung Prayitno Agus Maulizar Agus Seswandi Ahmad Arbiansyah Aidil Ikhsan Aldi Lesmana AlFahri, Nabil Alisa Putri Amanda Nasution Andri Machmury Angghita Muthiara Yusfadhila Anggieta Fatia Sari Aprillya Zahra Iswandy Lubis Ardiningrum, Fahriya Aris Sudianto Armanda Afridan Arrijal Fadillah Arrijal Fadillah Mz Nasuttion Auralia Izmi Ayu Vinlandari Wahyudi Ayuhana Vanesya Purba Azura Intan Pertiwi Baiq Andriska Candra Permana Bella Gusmita Sari Darmansyah Darmansyah Dava Ardiansyah Rangkuti Dava Setyawan Hadi Daviqho Suaditya Dea Cindiasyahwa Dewi Santika Dhany Tampe Silalahi Diva Ayu Ananda Manik Divy Nayla Yasmin Dwi Purnomo Putro Efti Sara br Haloho Ega Saputra Ega Saputra Unsil Erdiansyah Putra, B Ernawati, Yeni Esta Rendra RS Eva Sortariani Situmorang Ewin Irwansyah Fadila Syeftriana Febby Shania Utami Febi Sofia Azzura Febiola, Adinda Fernando Siahaan Fittri Royani Gadis Fitria Aulia Dhini Gery Al Ghazali Hamzan Ahmadi Hanie Ardina Sofianti Harianto Harianto Harianto Haya Atiqah Tampubolon Hendry Qurniawan Herman Saputra Heru Satria Tambunan Ida Wahidah Imam Fathurrahman Intan Fauziah Saragih Irfan Aprianda Isniar Hutapea Jadigia Ginting Jeremi Sibarani Jumawal Kirani Cikal Anggraeni Kris Sandi Kusnanda Kristin Juni Harni Sinaga Lalu Kerta Wijaya Lalu Kertawijaya Leon Andretti Abdillah Livia Helen Naibaho M Ihsan Raditya M Ikraman M. Bukhari Izdihar M. Inaka Akbar Lubis Mahpuz Mahyuddin Dalimunthe Marzuki Marzuki Masyunita Siregar Meta Wulansari Malau Michael Orlando A. Purba Mona Artha Mevia Simarmata Muh. Jamaludin Muh. Kamarur Rijali Hilali Muhammad Djamaluddin Muhammad Fadillah Arief Muhammad Hatta Muhammad Rizky Fauzan Muhammad Wasil Mustopa Mustopa Nanik Hariyana Natanael Napitupulu Nenan Juli Nopita Agustina Tampubolon Novri Azzahra Batubara Nurhayati Nurul Aini Siregar Pakpahan, Clara Marsella Pakpahan Prahda Ginting, Muhammad Aditya Purba, Michael Putri Agriana Purba Putri Gracia Sianipar Putri Intan Gracia Sianipar Putri Septiani Rachtikawati, Yayan Rafika Lutfiah Rahmi Dwi Handayani Rambe Raisul Muslim Ramzy Ramadhanu Ratih Manalu Rayhan Praditya Saruji Resti Pebrianti Retno Ajeng Kartika Said Rifky Adriansyah Rohayanti, Wulan Sadali, Muhamad Sahbuki Ritonga Salsabila Shahibah Amanullah Salsabillah R. Jannah Sany Sugara Sarah Annisa Zahwaa Sasha Aiko Leana Shintiya Hanida Yohana Silalahi Simanungkalit, Khaswa Giovani Simon Bonar Purba Sintia Rohani Sintia Rohani Hutabarat Sophia Salsabila Sri Kartikowati Suci Ananda Sudaryanto Suhartini Sumarno . SUSANTI Syamsafitri Syawaluddin Kadafi Parinduri Tarigan, Vitryani Tegar Syahputra Adha Pratama Tenny Setiani Dewi Thalita Nazwa Aulia Tiara Berliani Tirmidzi Firmansyah Uci Julya Ningsih Wahyusari, Retno Wico Jontarudi Tarigan Wilman Arif Telaumbanua Wira Handika Wiwik Handayani Yani Sri Astuti Yenny Susanto Yesica Vioretti Manullang Yosi Anggraini Manurung Yusril Hadi Yustinus P. Zulkarnaen Zurifah Nurdin