{"id":"https://openalex.org/W7218947271","doi":"https://doi.org/10.36708/ls.2023.i02.006","title":"Mitigating challenges: Handling mis sing values and imbalanced data in bankruptcy prediction using machine learning","display_name":"Mitigating challenges: Handling mis sing values and imbalanced data in bankruptcy prediction using machine learning","publication_year":2023,"publication_date":"2023-12-01","ids":{"openalex":"https://openalex.org/W7218947271","doi":"https://doi.org/10.36708/ls.2023.i02.006"},"language":"en","primary_location":{"id":"doi:10.36708/ls.2023.i02.006","doi":"https://doi.org/10.36708/ls.2023.i02.006","is_oa":true,"landing_page_url":"https://doi.org/10.36708/ls.2023.i02.006","pdf_url":"https://littera-scripta.com/api/v1/public/files/0d6866a9-391d-46ba-824c-5e4fa542e9ad","source":{"id":"https://openalex.org/S4210201167","display_name":"Littera Scripta","issn_l":"1802-503X","issn":["1802-503X","1805-9112"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","erih-plus","norway-1"],"host_organization":"https://openalex.org/P4310314216","host_organization_name":"Institute of Technology and Business","host_organization_lineage":["https://openalex.org/P4310314216"],"host_organization_lineage_names":["Institute of Technology and Business"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Littera Scripta","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://littera-scripta.com/api/v1/public/files/0d6866a9-391d-46ba-824c-5e4fa542e9ad","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074131973","display_name":"Ednawati Rainarli","orcid":"https://orcid.org/0000-0002-5770-1970","observed_orcids":["https://orcid.org/0000-0002-5770-1970"]},"institutions":[{"id":"https://openalex.org/I4210117444","display_name":"Universitas Komputer Indonesia","ror":"https://ror.org/02j652854","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210117444"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Ednawati Rainarli","raw_affiliation_strings":["Universitas Komputer Indonesia"],"raw_orcid":"https://orcid.org/0000-0002-5770-1970","affiliations":[{"raw_affiliation_string":"Universitas Komputer Indonesia","institution_ids":["https://openalex.org/I4210117444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011433429","display_name":"Amine Sabek","orcid":"https://orcid.org/0000-0002-6970-4183","observed_orcids":["https://orcid.org/0000-0002-6970-4183"]},"institutions":[{"id":"https://openalex.org/I4210096460","display_name":"University of Tamanghasset","ror":"https://ror.org/00r0rx657","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210096460"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Amine Sabek","raw_affiliation_strings":["University of Tamanghasset"],"raw_orcid":"https://orcid.org/0000-0002-6970-4183","affiliations":[{"raw_affiliation_string":"University of Tamanghasset","institution_ids":["https://openalex.org/I4210096460"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":150,"currency":"EUR","value_usd":161},"apc_paid":{"value":150,"currency":"EUR","value_usd":161},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"2","first_page":"79","last_page":"96"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":1.0,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.0,"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/T12509","display_name":"Corporate Insolvency and Governance","score":0.0,"subfield":{"id":"https://openalex.org/subfields/3308","display_name":"Law"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bankruptcy-prediction","display_name":"bankruptcy prediction","score":0.9980000257492065},{"id":"https://openalex.org/keywords/financial-distress","display_name":"financial distress","score":0.9750000238418579},{"id":"https://openalex.org/keywords/financial-ratios","display_name":"financial ratios","score":0.6669999957084656},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.6970000267028809},{"id":"https://openalex.org/keywords/missing-data-imputation","display_name":"missing data imputation","score":0.8360000252723694},{"id":"https://openalex.org/keywords/nearest-neighbor-imputation","display_name":"nearest neighbor imputation","score":0.828000009059906},{"id":"https://openalex.org/keywords/downsampling","display_name":"downsampling","score":0.890999972820282},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.8960000276565552},{"id":"https://openalex.org/keywords/early-warning-systems","display_name":"early warning systems","score":0.5960000157356262},{"id":"https://openalex.org/keywords/polish-companies","display_name":"Polish enterprises","score":0.7620000243186951}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7131999731063843},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6797000169754028},{"id":"https://openalex.org/C2777388754","wikidata":"https://www.wikidata.org/wiki/Q1664594","display_name":"Bankruptcy prediction","level":3,"score":0.6104000210762024},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5892000198364258},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5652999877929688},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.557699978351593},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5174000263214111},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4894999861717224},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4372999966144562},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.430400013923645},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.42809998989105225},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41620001196861267},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.40779998898506165},{"id":"https://openalex.org/C504631918","wikidata":"https://www.wikidata.org/wiki/Q152074","display_name":"Bankruptcy","level":2,"score":0.3785000145435333},{"id":"https://openalex.org/C49895821","wikidata":"https://www.wikidata.org/wiki/Q5227368","display_name":"Data verification","level":2,"score":0.33820000290870667},{"id":"https://openalex.org/C2984760201","wikidata":"https://www.wikidata.org/wiki/Q1785212","display_name":"Financial distress","level":2,"score":0.3328999876976013},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.3292999863624573},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3156000077724457},{"id":"https://openalex.org/C98014903","wikidata":"https://www.wikidata.org/wiki/Q832161","display_name":"Financial ratio","level":2,"score":0.3127000033855438},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C13926793","wikidata":"https://www.wikidata.org/wiki/Q3507155","display_name":"Group method of data handling","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C29825287","wikidata":"https://www.wikidata.org/wiki/Q1427940","display_name":"Warning system","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2606000006198883}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.36708/ls.2023.i02.006","doi":"https://doi.org/10.36708/ls.2023.i02.006","is_oa":true,"landing_page_url":"https://doi.org/10.36708/ls.2023.i02.006","pdf_url":"https://littera-scripta.com/api/v1/public/files/0d6866a9-391d-46ba-824c-5e4fa542e9ad","source":{"id":"https://openalex.org/S4210201167","display_name":"Littera Scripta","issn_l":"1802-503X","issn":["1802-503X","1805-9112"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","erih-plus","norway-1"],"host_organization":"https://openalex.org/P4310314216","host_organization_name":"Institute of Technology and Business","host_organization_lineage":["https://openalex.org/P4310314216"],"host_organization_lineage_names":["Institute of Technology and Business"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Littera Scripta","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.36708/ls.2023.i02.006","doi":"https://doi.org/10.36708/ls.2023.i02.006","is_oa":true,"landing_page_url":"https://doi.org/10.36708/ls.2023.i02.006","pdf_url":"https://littera-scripta.com/api/v1/public/files/0d6866a9-391d-46ba-824c-5e4fa542e9ad","source":{"id":"https://openalex.org/S4210201167","display_name":"Littera Scripta","issn_l":"1802-503X","issn":["1802-503X","1805-9112"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","erih-plus","norway-1"],"host_organization":"https://openalex.org/P4310314216","host_organization_name":"Institute of Technology and Business","host_organization_lineage":["https://openalex.org/P4310314216"],"host_organization_lineage_names":["Institute of Technology and Business"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Littera Scripta","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7218947271.pdf","grobid_xml":"https://content.openalex.org/works/W7218947271.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1566740849","https://openalex.org/W2041255922","https://openalex.org/W2046792933","https://openalex.org/W2072768981","https://openalex.org/W2083352970","https://openalex.org/W2097752063","https://openalex.org/W2124532504","https://openalex.org/W2341983589","https://openalex.org/W2430129386","https://openalex.org/W2587322985","https://openalex.org/W2601418844","https://openalex.org/W2606916050","https://openalex.org/W2789043468","https://openalex.org/W2803437104","https://openalex.org/W2892786225","https://openalex.org/W2991634377","https://openalex.org/W3115533876","https://openalex.org/W3165933971","https://openalex.org/W3217479894","https://openalex.org/W4224231419","https://openalex.org/W4385076030","https://openalex.org/W4387122277","https://openalex.org/W6926596274"],"related_works":["https://openalex.org/W4396983338","https://openalex.org/W3171201115","https://openalex.org/W4321260660","https://openalex.org/W4380551592","https://openalex.org/W4389221569","https://openalex.org/W4388822957","https://openalex.org/W4408770525","https://openalex.org/W4414096309","https://openalex.org/W3036682278","https://openalex.org/W6911991010"],"abstract_inverted_index":{"The":[0],"research":[1],"on":[2],"financial":[3,27],"distress":[4],"has":[5],"become":[6],"essential":[7],"because":[8],"the":[9,35,40,57,91,101,116,118,122,145,159],"predicted":[10],"results":[11],"can":[12,29,162],"serve":[13,30,163],"as":[14,31,83,164],"an":[15,69,165],"early":[16],"warning":[17],"for":[18,43,67,168],"managers,":[19],"investors,":[20],"and":[21,56,85,114,138],"banks.":[22],"Financial":[23],"ratios":[24],"calculated":[25],"in":[26,96,156],"reports":[28],"indicators":[32],"to":[33,59,133],"assess":[34],"company's":[36],"condition.":[37],"One":[38],"of":[39,93,121,171],"approaches":[41],"used":[42,144],"bankruptcy":[44,71],"prediction":[45,72,102,123],"is":[46],"employing":[47],"machine":[48,175],"learning":[49,176],"methods.":[50,177],"Data":[51],"requirements":[52],"with":[53,62],"balanced":[54],"classes":[55],"need":[58],"process":[60],"data":[61,79,97,137,139],"complete":[63],"parameters/features":[64],"are":[65],"prerequisites":[66],"building":[68],"accurate":[70],"model.":[73,103],"In":[74],"this":[75],"study,":[76],"we":[77,107],"employed":[78],"balancing":[80,115],"techniques":[81],"such":[82],"downsampling":[84],"filling":[86],"missing":[87,112,136],"feature":[88],"values":[89,113],"using":[90,125,174],"average":[92],"nearest":[94],"neighbors":[95],"preprocessing":[98],"before":[99],"training":[100,169],"From":[104],"our":[105,142],"experiments,":[106],"found":[108],"that":[109],"by":[110,130],"addressing":[111,135],"data,":[117],"F1":[119],"score":[120],"model":[124],"Random":[126],"Forest":[127],"(RF)":[128],"improved":[129],"30%":[131],"compared":[132],"not":[134],"imbalance.":[140],"Although":[141],"testing":[143],"Polish":[146],"company":[147],"dataset,":[148],"which":[149],"may":[150],"have":[151],"different":[152],"characteristics":[153],"from":[154],"companies":[155,173],"other":[157,172],"countries,":[158],"proposed":[160],"strategies":[161],"initial":[166],"approach":[167],"datasets":[170]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-10-04T00:00:00"}
