Prediction model for agro-tourism development using adaptive neuro-fuzzy inference system method

Abstract: Indonesia is one of the most important centers for biodiversity in the world with the highest level of endemism. Meanwhile, tourism is one of the important and strategic economic sectors in the future. It is hoped that the development of the tourism industry will also be able to support efforts to conserve nature, biological wealth, and national cultural wealth. The identification and development planning of the tourism industry needs to be done in more detail and carefully. In this article, the identification and prediction model of support from the local government and the community in developing agro-tourism was proposed. The prediction model was built using the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. Data were taken from 56 community members as respondents around the agro-tourism area. The results of modeling using the ANFIS method showed satisfactory results with an accuracy of 98.89%. The support of the local government and the surrounding community for the development of community-based agro-tourism is still considered not optimal. There needs to be a synergy between the two with various recommendations for more realistic development support.

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch

Erschienen in
Prediction model for agro-tourism development using adaptive neuro-fuzzy inference system method ; volume:7 ; number:1 ; year:2022 ; pages:644-655 ; extent:12
Open agriculture ; 7, Heft 1 (2022), 644-655 (gesamt 12)

Urheber
Andayani, Sri Ayu
Umyati, Sri
Dinar
Tampubolon, George Michael
Ismail, Agus Yadi
Dani, Umar
Nugraha, Dadan Ramdani
Turnip, Arjon

DOI
10.1515/opag-2022-0086
URN
urn:nbn:de:101:1-2022083014144029307122
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
15.08.2025, 07:27 MESZ

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Beteiligte

  • Andayani, Sri Ayu
  • Umyati, Sri
  • Dinar
  • Tampubolon, George Michael
  • Ismail, Agus Yadi
  • Dani, Umar
  • Nugraha, Dadan Ramdani
  • Turnip, Arjon

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