{"id":"https://openalex.org/W4288096958","doi":"https://doi.org/10.37600/tekinkom.v5i1.446","title":"PERBANDINGAN AKURASI ALGORITMA NA\u00cfVE BAYES, K-NN DAN SVM DALAM MEMPREDIKSI PENERIMAAN PEGAWAI","display_name":"PERBANDINGAN AKURASI ALGORITMA NA\u00cfVE BAYES, K-NN DAN SVM DALAM MEMPREDIKSI PENERIMAAN PEGAWAI","publication_year":2022,"publication_date":"2022-07-07","ids":{"openalex":"https://openalex.org/W4288096958","doi":"https://doi.org/10.37600/tekinkom.v5i1.446"},"language":"en","primary_location":{"id":"doi:10.37600/tekinkom.v5i1.446","doi":"https://doi.org/10.37600/tekinkom.v5i1.446","is_oa":true,"landing_page_url":"https://doi.org/10.37600/tekinkom.v5i1.446","pdf_url":"https://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/download/446/305","source":{"id":"https://openalex.org/S4210190873","display_name":"Jurnal Teknik Informasi dan Komputer (Tekinkom)","issn_l":"2621-1556","issn":["2621-1556","2621-3079"],"is_oa":false,"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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Jurnal Teknik Informasi dan Komputer (Tekinkom)","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/download/446/305","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090406342","display_name":"Novendra Adisaputra Sinaga","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405276222","display_name":"Politeknik Bisnis Indonesia","ror":"https://ror.org/051c1w333","country_code":"ID","type":"education","lineage":["https://openalex.org/I4405276222"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Novendra Adisaputra Sinaga","raw_affiliation_strings":["Politeknik Bisnis Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politeknik Bisnis Indonesia","institution_ids":["https://openalex.org/I4405276222"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022338020","display_name":"Bambang Herawan Hayadi","orcid":"https://orcid.org/0000-0003-4645-2662","observed_orcids":["https://orcid.org/0000-0003-4645-2662"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"B Herawan Hayadi","raw_affiliation_strings":["Universitas Potensi Utama"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Potensi Utama","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112637404","display_name":"Zakarias Situmorang","orcid":"https://orcid.org/0000-0002-8920-7942","observed_orcids":["https://orcid.org/0000-0002-8920-7942"]},"institutions":[{"id":"https://openalex.org/I4210102140","display_name":"Universitas Katolik Santo Thomas","ror":"https://ror.org/01bwbjs64","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210102140"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Zakarias Situmorang","raw_affiliation_strings":["Universitas Katolik Santo Thomas"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Katolik Santo Thomas","institution_ids":["https://openalex.org/I4210102140"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7233,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.85310889,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"5","issue":"1","first_page":"27","last_page":"27"},"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":0.9970999956130981,"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":0.9970999956130981,"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":0.002099999925121665,"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":0.0003000000142492354,"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/naive-bayes","display_name":"naive Bayes","score":0.7960000038146973},{"id":"https://openalex.org/keywords/k-nearest-neighbors","display_name":"k-nearest neighbors","score":0.8690000176429749},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.9980000257492065},{"id":"https://openalex.org/keywords/classifier-comparison","display_name":"classifier comparison","score":0.7720000147819519},{"id":"https://openalex.org/keywords/human-resource-management","display_name":"human resource management","score":0.6399999856948853},{"id":"https://openalex.org/keywords/data-mining","display_name":"data mining","score":0.7400000095367432}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7711503505706787},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.7048524618148804},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5722081065177917},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5461146235466003},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45749837160110474},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.4570465683937073},{"id":"https://openalex.org/C2779529714","wikidata":"https://www.wikidata.org/wiki/Q2632744","display_name":"Graduation (instrument)","level":2,"score":0.44971784949302673},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19306236505508423},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.11342307925224304},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.37600/tekinkom.v5i1.446","doi":"https://doi.org/10.37600/tekinkom.v5i1.446","is_oa":true,"landing_page_url":"https://doi.org/10.37600/tekinkom.v5i1.446","pdf_url":"https://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/download/446/305","source":{"id":"https://openalex.org/S4210190873","display_name":"Jurnal Teknik Informasi dan Komputer (Tekinkom)","issn_l":"2621-1556","issn":["2621-1556","2621-3079"],"is_oa":false,"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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Jurnal Teknik Informasi dan Komputer (Tekinkom)","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.37600/tekinkom.v5i1.446","doi":"https://doi.org/10.37600/tekinkom.v5i1.446","is_oa":true,"landing_page_url":"https://doi.org/10.37600/tekinkom.v5i1.446","pdf_url":"https://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/download/446/305","source":{"id":"https://openalex.org/S4210190873","display_name":"Jurnal Teknik Informasi dan Komputer (Tekinkom)","issn_l":"2621-1556","issn":["2621-1556","2621-3079"],"is_oa":false,"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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Jurnal Teknik Informasi dan Komputer (Tekinkom)","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4288096958.pdf","grobid_xml":"https://content.openalex.org/works/W4288096958.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W2953618482","https://openalex.org/W2991232928","https://openalex.org/W3006515843","https://openalex.org/W3036246613","https://openalex.org/W3081606957","https://openalex.org/W3092590335","https://openalex.org/W3095758237","https://openalex.org/W3122308606","https://openalex.org/W3132482581","https://openalex.org/W3159269958","https://openalex.org/W3195903324","https://openalex.org/W3215000360","https://openalex.org/W4206016236","https://openalex.org/W4214598376","https://openalex.org/W4244851097","https://openalex.org/W4313189778"],"related_works":["https://openalex.org/W4387574076","https://openalex.org/W4409403770","https://openalex.org/W3014583683","https://openalex.org/W4212890887","https://openalex.org/W2991036069","https://openalex.org/W7223449357","https://openalex.org/W4410607277","https://openalex.org/W2945582994","https://openalex.org/W7219229548","https://openalex.org/W4379932569"],"abstract_inverted_index":{"To":[0],"supporting":[1],"academic":[2],"and":[3,27,32,90,112,132,138],"non-academic":[4],"activities,":[5],"the":[6,48,51,61,104],"Polytechnic":[7],"Business":[8],"Indonesian":[9],"(PBI)":[10],"must":[11],"be":[12,44],"supported":[13],"by":[14,80],"employees":[15],"with":[16],"reliable":[17],"Human":[18],"Resources":[19],"(HRD)":[20],"who":[21],"have":[22],"good":[23,25],"behavior,":[24],"abilities":[26],"can":[28],"complete":[29],"work":[30],"professionally":[31],"responsibly.":[33],"Conventional":[34],"techniques":[35],"for":[36,50],"analyzing":[37],"existing":[38],"large":[39],"amounts":[40],"of":[41,53,57,63],"data":[42,68,79,117],"cannot":[43],"handled":[45],"which":[46,70],"is":[47,71,107],"background":[49],"emergence":[52],"a":[54],"new":[55],"branch":[56],"science":[58],"to":[59,77],"overcome":[60],"problem":[62],"extracting":[64],"important":[65],"information":[66],"from":[67],"sets,":[69],"called":[72],"Data":[73],"Mining.":[74],"Utilizing":[75],"methods":[76,82],"classify":[78],"utilizing":[81],"including:":[83],"Na\u00efve":[84,110,133],"Bayes":[85,111,134],"method,":[86],"K-Nearest":[87],"Neighbor":[88],"(K-NN)":[89],"Supervise":[91],"Vector":[92],"Machine":[93],"(SVM).":[94],"From":[95],"this":[96],"research,":[97],"in":[98],"Predicting":[99],"Applicants":[100],"Graduation":[101],"at":[102],"PBI,":[103],"SVM":[105,119],"method":[106],"better":[108],"than":[109],"K-NN.":[113],"With":[114],"33":[115],"test":[116],"used,":[118],"has":[120,127,135],"84.9%":[121],"accuracy,":[122,129],"85.1%":[123],"precision":[124,131],"while":[125],"K-NN":[126],"81.8%":[128],"84.1%":[130],"78.8%":[136],"accuracy":[137],"80.1%":[139],"precision.":[140]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2022-07-28T00:00:00"}
