{"id":"https://openalex.org/W4401045274","doi":"https://doi.org/10.30865/mib.v8i3.7716","title":"Implementasi Data Mining Metode K-Means Menggunakan Framework Python Dalam Mengelompokkan Pegawai Berdasarkan Data Presensi","display_name":"Implementasi Data Mining Metode K-Means Menggunakan Framework Python Dalam Mengelompokkan Pegawai Berdasarkan Data Presensi","publication_year":2024,"publication_date":"2024-07-26","ids":{"openalex":"https://openalex.org/W4401045274","doi":"https://doi.org/10.30865/mib.v8i3.7716"},"language":"en","primary_location":{"id":"doi:10.30865/mib.v8i3.7716","doi":"https://doi.org/10.30865/mib.v8i3.7716","is_oa":true,"landing_page_url":"http://dx.doi.org/10.30865/mib.v8i3.7716","pdf_url":null,"source":{"id":"https://openalex.org/S4210182618","display_name":"JURNAL MEDIA INFORMATIKA BUDIDARMA","issn_l":"2548-8368","issn":["2548-8368","2614-5278"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"JURNAL MEDIA INFORMATIKA BUDIDARMA","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"http://dx.doi.org/10.30865/mib.v8i3.7716","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019249768","display_name":"Mira Mira","orcid":"https://orcid.org/0000-0002-1599-1615","observed_orcids":["https://orcid.org/0000-0002-1599-1615"]},"institutions":[{"id":"https://openalex.org/I4405276367","display_name":"Institut Shanti Bhuana","ror":"https://ror.org/0592a9t34","country_code":"ID","type":"education","lineage":["https://openalex.org/I4405276367"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Mira Mira","raw_affiliation_strings":["Institut Shanti Bhuana, Bengkayang"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Shanti Bhuana, Bengkayang","institution_ids":["https://openalex.org/I4405276367"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074419579","display_name":"Azriel Christian Nurcahyo","orcid":"https://orcid.org/0000-0002-6082-4891","observed_orcids":["https://orcid.org/0000-0002-6082-4891","https://orcid.org/0000-0002-3363-8268"]},"institutions":[{"id":"https://openalex.org/I4405276367","display_name":"Institut Shanti Bhuana","ror":"https://ror.org/0592a9t34","country_code":"ID","type":"education","lineage":["https://openalex.org/I4405276367"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Azriel Christian Nurcahyo","raw_affiliation_strings":["Institut Shanti Bhuana, Bengkayang"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Shanti Bhuana, Bengkayang","institution_ids":["https://openalex.org/I4405276367"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083684053","display_name":"Candra Gudiato","orcid":"https://orcid.org/0000-0001-6220-7881","observed_orcids":["https://orcid.org/0000-0001-6220-7881"]},"institutions":[{"id":"https://openalex.org/I4405276367","display_name":"Institut Shanti Bhuana","ror":"https://ror.org/0592a9t34","country_code":"ID","type":"education","lineage":["https://openalex.org/I4405276367"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Candra Gudiato","raw_affiliation_strings":["Institut Shanti Bhuana, Bengkayang"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Shanti Bhuana, Bengkayang","institution_ids":["https://openalex.org/I4405276367"]}]},{"author_position":"last","author":{"id":null,"display_name":"Kusnanto Kusnanto","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405276367","display_name":"Institut Shanti Bhuana","ror":"https://ror.org/0592a9t34","country_code":"ID","type":"education","lineage":["https://openalex.org/I4405276367"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Kusnanto Kusnanto","raw_affiliation_strings":["Institut Shanti Bhuana, Bengkayang"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Shanti Bhuana, Bengkayang","institution_ids":["https://openalex.org/I4405276367"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5019249768","https://openalex.org/A5074419579","https://openalex.org/A5083684053"],"corresponding_institution_ids":["https://openalex.org/I4405276367"],"apc_list":null,"apc_paid":null,"fwci":0.5079,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66247562,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":"8","issue":"3","first_page":"1334","last_page":"1334"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13812","display_name":"AI and HR Technologies","score":0.005499999970197678,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/employee-attendance","display_name":"employee attendance","score":0.7990000247955322},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"K-means clustering","score":0.8339999914169312},{"id":"https://openalex.org/keywords/water-utility-employees","display_name":"water utility employees","score":0.4440000057220459}],"concepts":[{"id":"https://openalex.org/C2778173179","wikidata":"https://www.wikidata.org/wiki/Q25339289","display_name":"Attendance","level":2,"score":0.6801327466964722},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.6445640325546265},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.6388838887214661},{"id":"https://openalex.org/C56666940","wikidata":"https://www.wikidata.org/wiki/Q788790","display_name":"Documentation","level":2,"score":0.6271068453788757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5777931809425354},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.506278395652771},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4577779173851013},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.3899981677532196},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3520277440547943},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17850276827812195},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15279051661491394},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10833758115768433},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.10126248002052307},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.08075928688049316},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.30865/mib.v8i3.7716","doi":"https://doi.org/10.30865/mib.v8i3.7716","is_oa":true,"landing_page_url":"http://dx.doi.org/10.30865/mib.v8i3.7716","pdf_url":null,"source":{"id":"https://openalex.org/S4210182618","display_name":"JURNAL MEDIA INFORMATIKA BUDIDARMA","issn_l":"2548-8368","issn":["2548-8368","2614-5278"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"JURNAL MEDIA INFORMATIKA BUDIDARMA","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.30865/mib.v8i3.7716","doi":"https://doi.org/10.30865/mib.v8i3.7716","is_oa":true,"landing_page_url":"http://dx.doi.org/10.30865/mib.v8i3.7716","pdf_url":null,"source":{"id":"https://openalex.org/S4210182618","display_name":"JURNAL MEDIA INFORMATIKA BUDIDARMA","issn_l":"2548-8368","issn":["2548-8368","2614-5278"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"JURNAL MEDIA INFORMATIKA BUDIDARMA","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.48510000109672546}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2945386406","https://openalex.org/W3098192932","https://openalex.org/W3156196409","https://openalex.org/W3215459048","https://openalex.org/W4291890784","https://openalex.org/W4313003867","https://openalex.org/W4318541481","https://openalex.org/W4320070453","https://openalex.org/W4321366168","https://openalex.org/W4377824323","https://openalex.org/W4383739670","https://openalex.org/W4388758680","https://openalex.org/W4391900807","https://openalex.org/W4396649041"],"related_works":["https://openalex.org/W7142673428","https://openalex.org/W4375843350","https://openalex.org/W2941794145","https://openalex.org/W7155224091","https://openalex.org/W7167584278","https://openalex.org/W7163145006","https://openalex.org/W4367604334","https://openalex.org/W4318815821","https://openalex.org/W7127981618","https://openalex.org/W4401540734"],"abstract_inverted_index":{"Computerized":[0],"employee":[1,54,103,121],"attendance":[2,14,55,62,71,122],"data":[3,15,32,41,93,107,123,146],"collection":[4,16,33],"provides":[5],"convenience":[6],"in":[7,53,83],"terms":[8],"of":[9,67,78,86,130,158,186,191,194,204,207,217,221,231],"real-time":[10],"monitoring.":[11],"The":[12,40,92,140,151],"computerized":[13,29],"process":[17,34,129],"has":[18,43,95],"been":[19,44,96],"widely":[20],"implemented":[21],"by":[22,144,154,171],"government":[23],"and":[24,73,80,133,161,189,219],"private":[25],"agencies.":[26],"With":[27],"a":[28],"system,":[30],"the":[31,84,90,111,128,156,165,168,173,184,187,201,214,228],"is":[35,74,98,127],"easier":[36],"to":[37,89,101,119],"carry":[38],"out.":[39],"that":[42,94],"collected":[45,97],"increases":[46],"as":[47,177],"time":[48],"passes.":[49],"To":[50],"improve":[51],"discipline":[52,104],"patterns.":[56,124],"Perumdam":[57],"Tirta":[58],"Bengkayang":[59],"implements":[60],"an":[61],"application":[63],"with":[64,76],"features":[65],"consisting":[66],"working":[68],"hours,":[69],"shifts,":[70],"location":[72],"equipped":[75],"documentation":[77],"incoming":[79],"outgoing":[81],"absences":[82],"form":[85],"selfies":[87],"attached":[88],"application.":[91],"then":[99],"analyzed":[100],"assess":[102],"levels":[105],"using":[106],"mining":[108,115,126],"techniques,":[109],"namely":[110,200,213,227],"K-Means":[112,141],"method.":[113],"Data":[114,125],"methods":[116],"are":[117],"used":[118],"group":[120],"collecting":[131],"data,":[132],"finding":[134],"patterns":[135],"or":[136],"relationships":[137],"between":[138],"data.":[139],"method":[142],"works":[143],"dividing":[145],"into":[147,197,210,224],"k":[148],"closest":[149,162],"clusters.":[150],"calculation":[152],"begins":[153],"determining":[155],"value":[157],"k,":[159],"centroid,":[160],"point.":[163],"Meanwhile,":[164],"analysis":[166,188],"uses":[167],"Python":[169],"library":[170],"importing":[172],"necessary":[174],"libraries":[175],"such":[176],"numpy,":[178],"pandas,":[179],"matplotlib,":[180],"sklearn.":[181],"Based":[182],"on":[183],"results":[185],"grouping":[190],"employees,":[192],"26.76%":[193],"employees":[195,208,222],"fall":[196,209,223],"cluster":[198,211,225],"0,":[199],"low":[202],"level":[203,216,230],"discipline,":[205,218],"71.83%":[206],"1,":[212],"medium":[215],"1.41%":[220],"2,":[226],"high":[229],"discipline.":[232]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2024-07-31T00:00:00"}