PREDIKSI JUMLAH KEDATANGAN WISATAWAN MANCANEGARA DI INDONESIA BERDASARKAN PINTU MASUK KEDATANGAN UDARA
PREDICTION OF THE NUMBER OF ARRIVALS OF FOREIGN TOURISTS IN INDONESIA BASED ON AIR ARRIVAL ENTRANCES
:
Abstract
Indonesia has diversity and natural wealth that attracts tourism in Indonesia. Tourism is one of the industries that provides the highest foreign exchange for the country because it has a positive impact. However, the existence of COVID-19 has resulted in a decrease in the number of visits due to restrictions on foreign tourists. From January to November 2021, there was a drastic decrease of 61.82% in the number of foreign tourist visits compared to the same period in 2020. In addition to COVID-19, as well as support in building facilities that support the increase in the number of foreign tourists. From these conditions, predictions are needed that are used as a basis for planning and helping decision making. The purpose of this study is to develop a more accurate prediction model in similar studies using the same data in predicting foreign tourist arrivals in Indonesia through air entrances using the XGBoost, Random Forest, and Catboost methods by focusing on the accuracy evaluation results metrics RMSE, MAE, and MAPE and making predictions for the next 12 months. The dataset used is taken from the Central Statistics Agency (BPS), namely data on foreign tourist arrivals based on the arrival entrance in the period January 2017 to November 2021. The data used are time series and non-stationary. From the research results, it can be seen based on the accuracy evaluation results that the XGBoost model of this study gets better accuracy evaluation results than the other two models by getting the results of the RMSE accuracy evaluation value of 671935.2, MAE 648139.1, and MAPE 20985.35. The XGBoost model is better with a smaller accuracy error value than the Random Forest model, Catboost, and similar research using the ARIMA method with an RMSE value of 779670.7, MAE 749030.4, and MAPE 23196.45.
References
T. Kincowati, M. T. Furqon, Dan B. Rahayudi, “Prediksi Jumlah Kunjungan Wisatawan Mancanegara Ke Indonesia Menggunakan Metode Average-Based Fuzzy Time Series Models,” 2019. [Daring]. Tersedia Pada: Http://J-Ptiik.Ub.Ac.Id
H. Mukhtar, R. Muhammad, T. Reny Medikawati, Dan Yoze Rizki, “Peramalan Kedatangan Wisatawan Mancanegara Ke Indonesia Menurut Kebangsaan Perbulannya Menggunakan Metode Multilayer Perceptron,” Jurnal Coscitech (Computer Science And Information Technology), Vol. 2, No. 2, Hlm. 113–119, Des 2021, Doi: 10.37859/Coscitech.V2i2.3324.
F. Mu Dan A. Gunaryati, “Prediksi Kunjungan Wisatawan Mancanegara Melalui Pintu Udara Menggunakan Arima, Glmnet, Dan Prophet Prediction Of Foreign Tourist Visits Via Airline Using Arima, Glmnet, And Prophet.”
S. A. Salimu Dan Y. Yunus, “Prediksi Tingkat Kedatangan Wisatawan Asing Menggunakan Metode Backpropagation (Studi Kasus: Kepulauan Mentawai),” Jurnal Informatika Ekonomi Bisnis, Hlm. 98–103, Des 2020, Doi: 10.37034/Infeb.V2i4.50.
F. Islamiyah, R. Nurafni, E. Kartika, D. Sri, S. Politeknik, Dan N. Malang, “Peramalan Kedatangan Wisatawan Mancanegara Indonesia: Metode Holt’s Winter Exponential Smoothing.”
A. Meimela, “Prediksi Jumlah Kunjungan Wisatawan Mancanegara Ke Indonesia,” Vol. 19, No. 1, 2021, Doi: 10.36275/Mws.
A. Ramadhani, S. Wahyuningsih, Dan M. Siringoringo, “Forecasting The Number Of Foreign Tourist Visits To Indonesia Used Intervention Analysis With Step Function,” Jurnal Matematika, Statistika Dan Komputasi, Vol. 19, No. 1, Hlm. 146–162, Sep 2022, Doi: 10.20956/J.V19i1.21607.
A. Fitrianida Lutfiajati Pradhyani, A. Maulana, Dan J. Haerul Jaman, “Prediksi Jumlah Kedatangan Wisatawan Mancanegara Se-Asia Ke Indonesia Berdasarkan Kewarganegaraan Menggunakan Fuzzy Time Series,” 2023.
F. D. Pratama, I. Zufria, Dan T. Triase, “Implementasi Data Mining Menggunakan Algoritma Naïve Bayes Untuk Klasifikasi Penerima Program Indonesia Pintar,” Rabit : Jurnal Teknologi Dan Sistem Informasi Univrab, Vol. 7, No. 1, Hlm. 77–84, Jan 2022, Doi: 10.36341/Rabit.V7i1.2217.
Nofriansyah Dicky Dan Nurcahyo Gunadi Widi, Algoritma Data Mining Dan Pengujian. Deepublish, 2019.
D. Nababan, V. Fajar Alexandro Nipu, R. Rizald, B. Baso, Dan D. Arisandi, “Optimalisasi Kinerja Mikrokomputer Raspberry Pi Pada Smart Greenhouse Berbasis Internet Of Things (Iot) Dengan Algoritma Forecasting Moving Average,” Rabit : Jurnal Teknologi Dan Sistem Informasi Univrab, Vol. 8, No. 2, Hlm. 164–172, Jul 2023, Doi: 10.36341/Rabit.V8i2.3452.
“Peramalan Jumlah Kunjungan Wisatawan Mancanegara Ke Indonesia Menggunakan Autoregressive Integrated Moving Average (Arima)”.
Firdaus M, Aplikasi Ekonometrika Untuk Data Panel Dan Time Series, Vol. Cetakan 7. Bogor: Ipb Press, 2018.
Diana Tri Susetianingtias, Eka Patriya, Dan Rodiah, “Model Random Forest Regression Untuk Peramalan Penyebaran Covid-19 Di Indonesia,” Decode: Jurnal Pendidikan Teknologi Informasi, Vol. 2, No. 2, Hlm. 84–95, Sep 2022, Doi: 10.51454/Decode.V2i2.48.
“Prediksi Curah Hujan Menggunakan Metode Categorical Boosting (Catboost).”
J. Khatib Sulaiman, M. Dzul Asmi Alhamdi, Dan W. Astuti, “Peramalan Kebutuhan Obat Menggunakan Xgboost Studi Kasus Pada Rumah Sakit Xyz,” Indonesian Journal Of Computer Science Attribution, Vol. 12, No. 5, Hlm. 2023–2757.
M. R. Susila, “Pemodelan Multivariate Kunjungan Wisatawan Mancanegara Ke Indonesia Melalui Pintu Udara, Laut, Dan Darat Yang Melibatkan Dampak Wabah Covid-19,” Barekeng: Jurnal Ilmu Matematika Dan Terapan, Vol. 15, No. 3, Hlm. 467–478, Sep 2021, Doi: 10.30598/Barekengvol15iss3pp467-478.
F. Indra Sanjaya Dan D. Heksaputra, “Prediksi Rerata Harga Beras Tingkat Grosir Indonesia Dengan Long Short Term Memory,” Vol. 7, No. 2, Hlm. 163–174, 2020, [Daring]. Tersedia Pada: Http://Jurnal.Mdp.Ac.Id
A. A. Suryanto, A. Muqtadir, Dan S. Artikel, “Penerapan Metode Mean Absolute Error (Mea) Dalam Algoritma Regresi Linear Untuk Prediksi Produksi Padi Info Artikel: Abstrak,” No. 1, Hlm. 11, 2019.
I. Nabillah Dan I. Ranggadara, “Mean Absolute Percentage Error Untuk Evaluasi Hasil Prediksi Komoditas Laut,” Joins (Journal Of Information System), Vol. 5, No. 2, Hlm. 250–255, Nov 2020, Doi: 10.33633/Joins.V5i2.3900.
Copyright (c) 2024 Rabit : Jurnal Teknologi dan Sistem Informasi Univrab
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright Notice
The copyright of the received article shall be assigned to the publisher of the journal. The intended copyright includes the right to publish the article in various forms (including reprints). The journal maintains the publishing rights to published articles. Therefore, the author must submit a statement of the Copyright Transfer Agreement.*)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
In line with the license, authors and any users (readers and other researchers) are allowed to share and adapt the material only for non-commercial purposes. In addition, the material must be given appropriate credit, provided with a link to the license, and indicated if changes were made. If authors remix, transform or build upon the material, authors must distribute their contributions under the same license as the original.
Please find the rights and licenses in RABIT : Jurnal Teknologi dan Sistem Informasi Univrab. By submitting the article/manuscript of the article, the author(s) accept this policy.
1. License
The non-commercial use of the article will be governed by the Creative Commons Attribution license as currently displayed on Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
2. Author’s Warranties
The author warrants that the article is original, written by stated author(s), has not been published before, contains no unlawful statements, does not infringe the rights of others, is subject to copyright that is vested exclusively in the author and free of any third party rights, and that any necessary written permissions to quote from other sources have been obtained by the author(s).
3. User Rights
RABIT's spirit is to disseminate articles published are as free as possible. Under the Creative Commons license, RABIT permits users to copy, distribute, display, and perform the work for non-commercial purposes only. Users will also need to attribute authors and RABIT on distributing works in the journal.
4. Rights of Authors
Authors retain all their rights to the published works, such as (but not limited to) the following rights;
- Copyright and other proprietary rights relating to the article, such as patent rights,
- The right to use the substance of the article in own future works, including lectures and books,
- The right to reproduce the article for own purposes,
- The right to self-archive the article,
- The right to enter into separate, additional contractual arrangements for the non-exclusive distribution of the article's published version (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal (RABIT : Jurnal Teknologi dan Sistem Informasi Univrab).
5. Co-Authorship
If the article was jointly prepared by other authors, any authors submitting the manuscript warrants that he/she has been authorized by all co-authors to be agreed on this copyright and license notice (agreement) on their behalf, and agrees to inform his/her co-authors of the terms of this policy. RABIT will not be held liable for anything that may arise due to the author(s) internal dispute. RABIT will only communicate with the corresponding author.
6. Royalties
This agreement entitles the author to no royalties or other fees. To such extent as legally permissible, the author waives his or her right to collect royalties relative to the article in respect of any use of the article by RABIT.
7. Miscellaneous
RABIT will publish the article (or have it published) in the journal if the article’s editorial process is successfully completed. RABIT's editors may modify the article to a style of punctuation, spelling, capitalization, referencing and usage that deems appropriate. The author acknowledges that the article may be published so that it will be publicly accessible and such access will be free of charge for the readers as mentioned in point 3.
PDF (Bahasa Indonesia)
Abstract views: 300
downloads: 158
