{"id":"https://openalex.org/W7117566812","doi":"https://doi.org/10.55579/jaec.202594.515","title":"Credit card fraud classification using applied machine learning \u2013 a comparative study of 24 machine learning algorithms","display_name":"Credit card fraud classification using applied machine learning \u2013 a comparative study of 24 machine learning algorithms","publication_year":2025,"publication_date":"2025-12-30","ids":{"openalex":"https://openalex.org/W7117566812","doi":"https://doi.org/10.55579/jaec.202594.515"},"language":null,"primary_location":{"id":"doi:10.55579/jaec.202594.515","is_oa":true,"landing_page_url":"https://doi.org/10.55579/jaec.202594.515","pdf_url":"https://jaec.vn/index.php/JAEC/article/download/515/280","source":{"id":"https://openalex.org/S4210230331","display_name":"Journal of Advanced Engineering and Computation","issn_l":"1859-2244","issn":["1859-2244","2588-123X"],"is_oa":true,"is_in_doaj":true,"is_core":false,"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":"Journal of Advanced Engineering and Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://jaec.vn/index.php/JAEC/article/download/515/280","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5118790415","display_name":"Kelechi Amamba","orcid":"https://orcid.org/0009-0003-1394-764X"},"institutions":[{"id":"https://openalex.org/I149910238","display_name":"Kent State University","ror":"https://ror.org/049pfb863","country_code":"US","type":"education","lineage":["https://openalex.org/I149910238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kelechi K Amamba","raw_affiliation_strings":["Kent State University"],"raw_orcid":"https://orcid.org/0009-0003-1394-764X","affiliations":[{"raw_affiliation_string":"Kent State University","institution_ids":["https://openalex.org/I149910238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118118244","display_name":"Olufemi Oloniluyi","orcid":null},"institutions":[{"id":"https://openalex.org/I149910238","display_name":"Kent State University","ror":"https://ror.org/049pfb863","country_code":"US","type":"education","lineage":["https://openalex.org/I149910238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Olufemi S Oloniluyi","raw_affiliation_strings":["Kent State University"],"raw_orcid":"https://orcid.org/0009-0002-0749-7198","affiliations":[{"raw_affiliation_string":"Kent State University","institution_ids":["https://openalex.org/I149910238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5118236762","display_name":"Olayinka Sikiru","orcid":null},"institutions":[{"id":"https://openalex.org/I149910238","display_name":"Kent State University","ror":"https://ror.org/049pfb863","country_code":"US","type":"education","lineage":["https://openalex.org/I149910238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Olayinka H Sikiru","raw_affiliation_strings":["Kent State University"],"raw_orcid":"https://orcid.org/0009-0007-9164-2146","affiliations":[{"raw_affiliation_string":"Kent State University","institution_ids":["https://openalex.org/I149910238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149910238"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.74750836,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":"4","first_page":"202","last_page":"202"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9670000076293945,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9670000076293945,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.017100000753998756,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"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/T11644","display_name":"Spam and Phishing Detection","score":0.0010000000474974513,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/credit-card-fraud","display_name":"Credit card fraud","score":0.7210999727249146},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5673999786376953},{"id":"https://openalex.org/keywords/credit-card","display_name":"Credit card","score":0.5092999935150146},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.489300012588501},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4846999943256378},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.47920000553131104},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.47189998626708984},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4697999954223633}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.8375999927520752},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7631000280380249},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7531999945640564},{"id":"https://openalex.org/C2780747020","wikidata":"https://www.wikidata.org/wiki/Q83873","display_name":"Credit card fraud","level":4,"score":0.7210999727249146},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5673999786376953},{"id":"https://openalex.org/C2983355114","wikidata":"https://www.wikidata.org/wiki/Q161380","display_name":"Credit card","level":3,"score":0.5092999935150146},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.489300012588501},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4846999943256378},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.47920000553131104},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.47189998626708984},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4697999954223633},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.43050000071525574},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4244000017642975},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.385699987411499},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.36910000443458557},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.359499990940094},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3467999994754791},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.31150001287460327},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3068999946117401},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C164516710","wikidata":"https://www.wikidata.org/wiki/Q1166072","display_name":"Financial transaction","level":3,"score":0.28110000491142273},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.55579/jaec.202594.515","is_oa":true,"landing_page_url":"https://doi.org/10.55579/jaec.202594.515","pdf_url":"https://jaec.vn/index.php/JAEC/article/download/515/280","source":{"id":"https://openalex.org/S4210230331","display_name":"Journal of Advanced Engineering and Computation","issn_l":"1859-2244","issn":["1859-2244","2588-123X"],"is_oa":true,"is_in_doaj":true,"is_core":false,"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":"Journal of Advanced Engineering and Computation","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.55579/jaec.202594.515","is_oa":true,"landing_page_url":"https://doi.org/10.55579/jaec.202594.515","pdf_url":"https://jaec.vn/index.php/JAEC/article/download/515/280","source":{"id":"https://openalex.org/S4210230331","display_name":"Journal of Advanced Engineering and Computation","issn_l":"1859-2244","issn":["1859-2244","2588-123X"],"is_oa":true,"is_in_doaj":true,"is_core":false,"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":"Journal of Advanced Engineering and Computation","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7966242432594299}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7117566812.pdf","grobid_xml":"https://content.openalex.org/works/W7117566812.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,162],"paper":[1,163],"presents":[2],"a":[3,28,54,186,190],"comprehensive":[4,187],"study":[5,85],"on":[6,136],"credit":[7],"card":[8],"fraud":[9,95,176],"detection,":[10,177],"addressing":[11],"the":[12,33,90,100,165],"escalating":[13],"issue":[14],"of":[15,36,94,167],"fraudulent":[16],"activities":[17],"that":[18,114,141],"significantly":[19],"impact":[20],"both":[21,89],"financial":[22,192],"institutions":[23],"and":[24,51,64,77,92,109,126,151,169,184],"consumers.":[25],"We":[26],"introduce":[27],"novel":[29],"framework":[30],"for":[31,81,105,173,181],"evaluating":[32],"collective":[34],"performance":[35],"diverse":[37],"machine":[38],"learning":[39],"(ML)":[40],"models\u2014including":[41],"Logistic":[42],"Regression,":[43],"Decision":[44],"Trees,":[45],"Random":[46],"Forests,":[47],"Support":[48],"Vector":[49],"Machines,":[50],"Neural":[52,128],"Networks\u2014using":[53],"synthetic":[55],"dataset":[56,76],"carefully":[57],"constructed":[58],"to":[59,72,87,157,189],"mirror":[60],"real-world":[61],"transaction":[62],"features":[63],"behavioral":[65],"patterns.":[66],"By":[67],"applying":[68],"various":[69],"sampling":[70],"strategies":[71],"this":[73,84],"highly":[74],"imbalanced":[75],"leveraging":[78],"domain":[79],"knowledge":[80],"feature":[82,102],"selection,":[83],"aims":[86],"enhance":[88],"accuracy":[91],"stability":[93],"detection":[96,107,149],"models,":[97],"while":[98],"identifying":[99],"minimum":[101],"set":[103],"required":[104],"optimal":[106],"speed":[108],"efficiency.":[110],"Our":[111],"results":[112],"reveal":[113],"algorithms":[115],"such":[116],"as":[117],"Gaussian":[118],"Naive":[119,122],"Bayes,":[120,123],"Kernel":[121],"Cubic":[124],"SVM,":[125],"Trilayered":[127],"Networks":[129],"each":[130],"provide":[131],"strong,":[132],"balanced":[133],"performance.":[134,161],"Building":[135],"these":[137,143],"findings,":[138],"we":[139],"propose":[140],"ensembling":[142],"top-performing":[144],"models":[145],"could":[146],"further":[147],"improve":[148],"rates":[150],"reliablity,":[152],"harnessing":[153],"their":[154],"complementary":[155],"strengths":[156],"achieve":[158],"superior":[159],"overall":[160],"underscores":[164],"necessity":[166],"advanced":[168],"integrated":[170],"ML":[171],"techniques":[172],"robust,":[174],"timely":[175],"offering":[178],"valuable":[179],"insights":[180],"real-time":[182],"implementation":[183],"presenting":[185],"solution":[188],"pressing":[191],"security":[193],"challenge.":[194]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-12-30T00:00:00"}
