R. Prawiro, Kusumo R. (2016) Pemodelan Kunjungan Wisatawan Pada Objek Dan Daya Tarik Wisata (ODTW) Di Surabaya Menggunakan Neural Network - Modeling Of Tourists Visit At The Object And Tourism Attraction In Surabaya Using Neural Network. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pariwisata mempunyai peran yang cukup strategis dalam pembangunan
perekonomian daerah dan masyarakat. Surabaya memiliki objek dan daya tarik
wisata (ODTW) yang berpotensial menarik wisatawan mancanegara maupun
wisatawan nusantara. Data dari Dinas Kebudayaan dan Pariwisata Kota Surabaya,
menunjukkan peningkatan kunjungan wistawan ke kota Surabaya pada tahun 2013-
2014 sebesar 52,83% untuk wisatawan mancanegara, dan sebesar 30,18% untuk
wisatawan nusantara.
Data jumlah kunjungan wisatawan ke beberapa ODTW tersebut berupa
data deret waktu (time series), musiman, dan dapat saling mempengaruhi antar
objek wisata, sehingga memerlukan metode analisis yang khusus, seperti vector
autoregressive (VAR) dan neural network. Neural network dapat dipakai untuk
meramalkan apa yang terjadi di masa depan berdasarkan pola yang terbentuk di
masa lampau. Hal ini dapat dilakukan karena kemampuan neural network untuk
mengingat dan membuat generalisasi dari apa yang sudah ada sebelumnya.
Hasil peramalan dengan metode neural network yang menggunakan VAR
sebagai input, mendapat hasil lebih baik dari pada cara VAR itu sendiri.
Penambahan jumlah neuron pada hidden layer tidak selalu memberikan pengaruh
kepada penurunan nilai MAPE.
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Tourism has a strategic role in the development of regional economy and
society. Surabaya has the object and tourism attraction potentially attract foreign
tourists and domestic tourists. Data from the Department of Culture and Tourism
of Surabaya City, showed an increasing the number of tourists who visit to
Surabaya in 2013-2014. The increments are 52.83% for foreign tourists, and
30.18% for domestic tourists.
The number of tourist who visits to several tourism objects of Surabaya
shows as a pattern time series data, seasonal and can correlate between tourism
attractions. To analyze this kind of data requires special analytical methods, such
as vector autoregressive (VAR) and neural network. Neural networks can be used
to predict what happens in the future based on the patterns formed in the past. This
can be done due to the neural network's ability to remember and to generalize from
what already exists.
Results of neural network that uses VAR as its input, give better
performance than directly using VAR only. This research also shows that the
increasing number of neurons in the hidden layer does not always give effect to the
decreasing the value of MAPE
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | RTMT 658.403 55 Rpr p |
| Uncontrolled Keywords: | pariwisata, jumlah kunjungan, time series, VAR, neural network. |
| Subjects: | T Technology > T Technology (General) > T174 Technological forecasting |
| Divisions: | 61101-Magister Management Technology |
| Depositing User: | ansi aflacha |
| Date Deposited: | 25 Nov 2019 02:42 |
| Last Modified: | 25 Nov 2019 02:42 |
| URI: | http://repository.its.ac.id/id/eprint/72004 |
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