{"_buckets": {"deposit": "2357c13f-95f1-417d-b449-2697fcda7e47"}, "_deposit": {"id": "3373", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "3373"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/3373", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Clustering Approach to Analyzing Student Data by using K-Means Algorithm", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Clustering is the process of grouping data intoclasses of clusters so that objects within a clusterhave high similarity in comparison to one another,but are very dissimilar to objects in other clusters.K-means clustering is a partitioning method. . Kmeansclustering algorithm is used to cluster thestudent data. The proposed system finds therelationship between students’ governmenttechnology high school (G.T.H.S) entranceexamination results and their success using clusteranalysis. Euclidean distance measure also used tocalculate the closest centroids for each object."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Clustering Approach"}, {"interim": "K-means Algorithm"}, {"interim": "Euclidean distance"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-07-22"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "psc2010paper (191).pdf", "filesize": [{"value": "39 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 39000.0, "url": {"url": "https://meral.edu.mm/record/3373/files/psc2010paper (191).pdf"}, "version_id": "6582b085-62c0-44b0-b3e7-974b4b3ba8f2"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Fifth Local Conference on Parallel and Soft Computing", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Wai, Khin Su Su"}, {"subitem_authors_fullname": "Min, Myat Myat"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2010-12-16"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/1130"}, "item_title": "Clustering Approach to Analyzing Student Data by using K-Means Algorithm", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000003373", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-22"}, "publish_date": "2019-07-22", "publish_status": "0", "recid": "3373", "relation": {}, "relation_version_is_last": true, "title": ["Clustering Approach to Analyzing Student Data by using K-Means Algorithm"], "weko_shared_id": -1}