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All Journal Applied Information System and Management Gema Wisata
Wardani, Dyah
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Languange, Linguistic, Communication & Media Social Sciences

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Pengembangan Ekowisata Bantaran Sungai Gajah Wong Kapanewon Nologaten Kabupaten Sleman Yogyakarta Saputro, Lilik Edi; Wardani, Dyah
Gemawisata: Jurnal Ilmiah Pariwisata Vol. 21 No. 1 (2025): Jurnal Ilmiah Pariwisata
Publisher : Sekolah Tinggi Ilmu Ekonomi Pariwisata Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/gemawisata.v21i1.584

Abstract

This study uses a qualitative approach with the aim of identifying the potential and challenges in the development of ecotourism on the banks of the Gajah Wong River, as well as formulating the right strategy in its management so that it can become a sustainable ecotourism destination. By focusing on the participation of local communities and the collaboration of various stakeholders, this research is expected to contribute to the development of ecotourism that supports the preservation of the local environment and culture. Ecotourism has a positive impact on the preservation of the local environment and indigenous culture, which is ultimately expected to be able to foster identity and pride among local residents through increased ecotourism activities. Kepanewon Nologaten, Caturtunggal which was previously known as a slum area has now been converted into an ecotourism area. It was concluded that the riverbank in Kepanewon nologaten, Sleman Regency, Yogyakarta has ecotourism potential that can be developed into an ecotourism destination.
Non-Rating Recommender System for Choosing Tourist Destinations Using Artificial Neural Network Arif, Yunifa Miftachul; Wardani, Dyah; Nurhayati, Hani; Diah, Norizan Mat
Applied Information System and Management (AISM) Vol. 6 No. 2 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i2.26741

Abstract

The development of tourist destinations in Batu City makes it hard for the tourists to decide their destinations. The recommender system is a solution that provides a lot of information or tourist attraction data. Collaborative filtering is often used in recommender systems. However, it has drawbacks; one of which is the cold-start problem, where the system cannot recommend items to new users. It was caused by the new user who had no history of rating on any item, or the system had no information. This study aims to apply a non-rated travel destination recommendation system to address the cold-start problem for new users. We use a multi-layer perceptron or artificial neural networks to overcome the problem by training user preference data to produce high training accuracy. Based on four experiments in the training data, the network architecture shows 5 – 7 – 5 – 3 –14, which is the highest accuracy. The architecture uses five variables as inputs and three hidden layers, with each layer was activated using the ReLU activation function. The output layer produces 14 binary outputs and is activated using the sigmoid activation function. The system can give recommendations to new users using feedforward from test data with updated values in weights and biases. The test results from 46 test data showed an accuracy of 67.235%.
Co-Authors Diah, Norizan Mat Hani Nurhayati Saputro, Lilik Edi Yunifa Miftachul Arif