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Journal : J-Icon : Jurnal Komputer dan Informatika

PENAMBANGAN DATA PENGUNJUNG HOTEL MENGGUNAKAN MODEL SNOWFLAKE UNTUK MENDUKUNG KEBIJAKAN PEMERINTAH BANGKA BELITUNG DIBIDANG PARIWISATA Yurindra yurindra; Parlia Romadiana; Sarwindah Sarwindah
J-Icon : Jurnal Komputer dan Informatika Vol 8 No 2 (2020): Oktober 2020
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v8i2.2696

Abstract

Hotel visitor data processing is currently felt to be increasingly needed for processing tourist information, especially if it will be used as information to make policies for local governments who want to advance the tourism sector in their regions. Local governments must be able to determine strategic and tactical policies in promoting the objectives of the tourism sector in question. The problem is that not all local governments have and are aware of the importance of hotel visitor data as supporting information for the advancement of the tourism sector in their area. For this reason, it is necessary to make and determine indicators based on the final data needed as a data mining tool that can be used as a database for local governments in analyzing hotel visitors. Indicators of visitor data include: visitor name, religion, occupation, purpose of stay, origin of visitors, age range, payment procedure, length of stay, type of room type they generally order. Data from these indicators will be important information for the local government of Bangka Belitung to determine policies to accelerate the increase in tourists in the Bangka Belitung archipelago. Mining data from the intended indicator uses the Snowflake model in data mining, so as to reduce storage space and data that is easily updated. The research method uses applied research because the results of the research are expected to be directly used for practical purposes, namely the development of policies in the tourism sector, in addition, applied research makes it possible to modify indicators from hotels and related services to find new indicators and combinations of these indicators.