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All Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) J-SAKTI (Jurnal Sains Komputer dan Informatika)
Sukraeni, Ni Putu Popy
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy

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Peramalan Jumlah Kunjungan Wisatawan Mancanegara Ke Bali dengan Jaringan Saraf Tiruan Backpropagation Parwita, Wayan Gede Suka; Sukraeni, Ni Putu Popy
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.464

Abstract

The Central Statistics Agency declared that the number of foreign tourist visits to Indonesia in January 2020 reached 1,272,083 visits, where the number of visits increased by 5.85 percent compared to the number of visits in January 2019. Meanwhile, when compared to December 2019, the number of foreign tourists visiting in January 2020 decreased by 7.62 percent. One of the areas that become a destination for foreign tourists in Indonesia is Bali Currently Bali, especially in the tourism sector, provides a major contribution to the Indonesian economy. As a form of tourism development in Bali and to responses this surge, it is necessary to have a strategy for the future that can anticipate dynamic environmental changes and as much as possible the negative impacts such as a decrease in the number of foreign tourists to Bali. One of the ways to anticipate these obstacles can be done by forecasting the number of tourist arrival due to the need readiness of related parties. This study uses the backpropagation neural network method. The architecture used for air lines is 12-7-1 and for sea routes is 12-10-1. The results showed that the airline forecast accuracy rate was 88,137% with MSE value of 0.133751 and a sea lane accuracy rate of 42,044% with MSE value of 0.052258
Peramalan Jumlah Kunjungan Wisatawan Mancanegara Ke Bali dengan Jaringan Saraf Tiruan Backpropagation Parwita, Wayan Gede Suka; Sukraeni, Ni Putu Popy
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.464

Abstract

The Central Statistics Agency declared that the number of foreign tourist visits to Indonesia in January 2020 reached 1,272,083 visits, where the number of visits increased by 5.85 percent compared to the number of visits in January 2019. Meanwhile, when compared to December 2019, the number of foreign tourists visiting in January 2020 decreased by 7.62 percent. One of the areas that become a destination for foreign tourists in Indonesia is Bali Currently Bali, especially in the tourism sector, provides a major contribution to the Indonesian economy. As a form of tourism development in Bali and to responses this surge, it is necessary to have a strategy for the future that can anticipate dynamic environmental changes and as much as possible the negative impacts such as a decrease in the number of foreign tourists to Bali. One of the ways to anticipate these obstacles can be done by forecasting the number of tourist arrival due to the need readiness of related parties. This study uses the backpropagation neural network method. The architecture used for air lines is 12-7-1 and for sea routes is 12-10-1. The results showed that the airline forecast accuracy rate was 88,137% with MSE value of 0.133751 and a sea lane accuracy rate of 42,044% with MSE value of 0.052258
Co-Authors Wayan Gede Suka Parwita