{"_buckets": {"deposit": "891f87b4-0509-4344-9a00-a37010cf6e86"}, "_deposit": {"created_by": 143, "id": "8180", "owner": "143", "owners": [143], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "depid", "value": "8180"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/00008180"}, "author_link": [], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "ARIMA Model for Time Series Forecasting: A Study on Tourist Arrivals in Mandalay", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Tourism is one of the most important service export industries and earners of foreign exchange for several countries today. The tourism phenomenon is vital interest not only to government and other organizations but also to other related industries such as hotel industries, transportation services and so on. Especially, for region such as Mandalay, in which tourism region a very important sector of the economy and possess a large part of GDP. It is usually essential to measure seasonal variation of tourism time series data in order to provide relevant information to related organization and department. The\nobjectives of the study are to examine the best-fitted model and to forecast the future of monthly tourist arrival in Mandalay. The number of international monthly tourist’s arrival to Mandalay by region from January 2012 to December 2019 was applied to investigate in this study. It was found that this time series was likely to have seasonal cycle, the lowest value of seasonal index is in June and the highest is in November. Theoretical framework that it was used the Box- Jenkins methodology for seasonal ARIMA models. After constructing the appropriate models, SARIMA (𝟏, 𝟏, 𝟎) × (𝟎, 𝟏, 𝟏)𝟏𝟐 was occurred as valid and appropriate model can be considered for forecasting. This appropriate model was utilized them to generate the forecasts of demand within Mandalay tourism. The obtain result can provide important information needed for an adequate destination."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Tourism"}, {"interim": "Seasonal Autoregressive Integrated Moving Average(SARIMA)"}, {"interim": "Mandalay"}, {"interim": "International Tourist Arrivals"}, {"interim": "Forecasting"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2022-03-23"}], "download_preview_message": "", "file_order": 0, "filename": "Chaw Ei Ei Tun.pdf", "filesize": [{"value": "367 KB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "mimetype": "application/pdf", "size": 367000.0, "url": {"objectType": "other", "url": "https://meral.edu.mm/record/8180/files/Chaw Ei Ei Tun.pdf"}, "version_id": "5011b235-e6f8-4efd-b3ff-d5bbb7bab0dc"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "December,2021", "subitem_journal_title": "University of Co-operative and Management,Sagaing Research Journal", "subitem_pages": "33-45", "subitem_volume": "Vol.4,No.2"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Chaw Ei Ei Tun1"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Journal article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2021-12-01"}, "item_title": "ARIMA Model for Time Series Forecasting: A Study on Tourist Arrivals in Mandalay", "item_type_id": "21", "owner": "143", "path": ["1607960099348", "1608035612363"], "permalink_uri": "https://meral.edu.mm/records/8180", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2021-12-01"}, "publish_date": "2021-12-01", "publish_status": "0", "recid": "8180", "relation": {}, "relation_version_is_last": true, "title": ["ARIMA Model for Time Series Forecasting: A Study on Tourist Arrivals in Mandalay"], "weko_shared_id": -1}