{"id":"https://openalex.org/W4313068053","doi":"https://doi.org/10.21512/commit.v16i2.7970","title":"Comparison of Supervised Learning Methods for COVID-19 Classification on Chest X-Ray Image","display_name":"Comparison of Supervised Learning Methods for COVID-19 Classification on Chest X-Ray Image","publication_year":2022,"publication_date":"2022-06-08","ids":{"openalex":"https://openalex.org/W4313068053","doi":"https://doi.org/10.21512/commit.v16i2.7970"},"language":"en","primary_location":{"id":"doi:10.21512/commit.v16i2.7970","doi":"https://doi.org/10.21512/commit.v16i2.7970","is_oa":true,"landing_page_url":"https://doi.org/10.21512/commit.v16i2.7970","pdf_url":"https://journal.binus.ac.id/index.php/commit/article/download/7970/4577","source":{"id":"https://openalex.org/S4210181841","display_name":"CommIT (Communication and Information Technology) Journal","issn_l":"1979-2484","issn":["1979-2484","2460-7010"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","poland-20","russia-white-list-4"],"host_organization":"https://openalex.org/P4310314957","host_organization_name":"Bina Nusantara University","host_organization_lineage":["https://openalex.org/P4310314957"],"host_organization_lineage_names":["Bina Nusantara University"],"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":"CommIT (Communication and Information Technology) Journal","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://journal.binus.ac.id/index.php/commit/article/download/7970/4577","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065613937","display_name":"Faisal Dharma Adhinata","orcid":"https://orcid.org/0000-0002-2624-173X","observed_orcids":["https://orcid.org/0000-0002-2624-173X"]},"institutions":[{"id":"https://openalex.org/I4387155996","display_name":"Institut Teknologi Telkom Purwokerto","ror":"https://ror.org/018zc6p18","country_code":"ID","type":"education","lineage":["https://openalex.org/I4387155996","https://openalex.org/I862893732"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Faisal Dharma Adhinata","raw_affiliation_strings":["Institut Teknologi Telkom Purwokerto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Teknologi Telkom Purwokerto","institution_ids":["https://openalex.org/I4387155996"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052181694","display_name":"Nur Ghaniaviyanto Ramadhan","orcid":"https://orcid.org/0000-0003-0304-516X","observed_orcids":["https://orcid.org/0000-0003-0304-516X"]},"institutions":[{"id":"https://openalex.org/I4387155996","display_name":"Institut Teknologi Telkom Purwokerto","ror":"https://ror.org/018zc6p18","country_code":"ID","type":"education","lineage":["https://openalex.org/I4387155996","https://openalex.org/I862893732"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Nur Ghaniaviyanto Ramadhan","raw_affiliation_strings":["Institut Teknologi Telkom Purwokerto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Teknologi Telkom Purwokerto","institution_ids":["https://openalex.org/I4387155996"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060798822","display_name":"Arif Amrulloh","orcid":"https://orcid.org/0000-0003-2765-0655","observed_orcids":["https://orcid.org/0000-0003-2765-0655"]},"institutions":[{"id":"https://openalex.org/I4387155996","display_name":"Institut Teknologi Telkom Purwokerto","ror":"https://ror.org/018zc6p18","country_code":"ID","type":"education","lineage":["https://openalex.org/I4387155996","https://openalex.org/I862893732"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Arif Amrulloh","raw_affiliation_strings":["Institut Teknologi Telkom Purwokerto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Teknologi Telkom Purwokerto","institution_ids":["https://openalex.org/I4387155996"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057915006","display_name":"Arief Rais Bahtiar","orcid":"https://orcid.org/0000-0003-2903-0150","observed_orcids":["https://orcid.org/0000-0003-2903-0150"]},"institutions":[{"id":"https://openalex.org/I4387155996","display_name":"Institut Teknologi Telkom Purwokerto","ror":"https://ror.org/018zc6p18","country_code":"ID","type":"education","lineage":["https://openalex.org/I4387155996","https://openalex.org/I862893732"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Arief Rais Bahtiar","raw_affiliation_strings":["Institut Teknologi Telkom Purwokerto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Teknologi Telkom Purwokerto","institution_ids":["https://openalex.org/I4387155996"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4387155996"],"apc_list":{"value":2000000,"currency":"IDR","value_usd":131},"apc_paid":{"value":2000000,"currency":"IDR","value_usd":131},"fwci":0.2388,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.40510762,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"16","issue":"2","first_page":"195","last_page":"201"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.0,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sars-cov-2-detection","display_name":"COVID-19 detection","score":0.9570000171661377},{"id":"https://openalex.org/keywords/chest-x-ray-images","display_name":"chest X-ray images","score":0.9919999837875366},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"supervised learning","score":0.5609999895095825},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.9900000095367432},{"id":"https://openalex.org/keywords/k-nearest-neighbors","display_name":"k-nearest neighbors","score":0.878000020980835},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":1.0},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"polynomial kernel","score":0.9190000295639038},{"id":"https://openalex.org/keywords/training-duration","display_name":"training duration","score":0.6980000138282776},{"id":"https://openalex.org/keywords/early-diagnosis","display_name":"early diagnosis","score":0.6650000214576721}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7918421626091003},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7600686550140381},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7122734189033508},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.660788893699646},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.6361455917358398},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6198088526725769},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5709105730056763},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5322990417480469},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5193537473678589},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.42527422308921814},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38345664739608765},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3277340531349182},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16464823484420776},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.13637763261795044},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.21512/commit.v16i2.7970","doi":"https://doi.org/10.21512/commit.v16i2.7970","is_oa":true,"landing_page_url":"https://doi.org/10.21512/commit.v16i2.7970","pdf_url":"https://journal.binus.ac.id/index.php/commit/article/download/7970/4577","source":{"id":"https://openalex.org/S4210181841","display_name":"CommIT (Communication and Information Technology) Journal","issn_l":"1979-2484","issn":["1979-2484","2460-7010"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","poland-20","russia-white-list-4"],"host_organization":"https://openalex.org/P4310314957","host_organization_name":"Bina Nusantara University","host_organization_lineage":["https://openalex.org/P4310314957"],"host_organization_lineage_names":["Bina Nusantara University"],"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":"CommIT (Communication and Information Technology) Journal","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0583aa38786344128f36592e43a50d0d","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/0583aa38786344128f36592e43a50d0d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"CommIT Journal, Vol 16, Iss 2, Pp 195-201 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.21512/commit.v16i2.7970","doi":"https://doi.org/10.21512/commit.v16i2.7970","is_oa":true,"landing_page_url":"https://doi.org/10.21512/commit.v16i2.7970","pdf_url":"https://journal.binus.ac.id/index.php/commit/article/download/7970/4577","source":{"id":"https://openalex.org/S4210181841","display_name":"CommIT (Communication and Information Technology) Journal","issn_l":"1979-2484","issn":["1979-2484","2460-7010"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","poland-20","russia-white-list-4"],"host_organization":"https://openalex.org/P4310314957","host_organization_name":"Bina Nusantara University","host_organization_lineage":["https://openalex.org/P4310314957"],"host_organization_lineage_names":["Bina Nusantara University"],"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":"CommIT (Communication and Information Technology) Journal","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8048999905586243,"display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4313068053.pdf","grobid_xml":"https://content.openalex.org/works/W4313068053.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1485635514","https://openalex.org/W2087347434","https://openalex.org/W2101234009","https://openalex.org/W2776146695","https://openalex.org/W2918346691","https://openalex.org/W2943160824","https://openalex.org/W2991164609","https://openalex.org/W3003217347","https://openalex.org/W3006643024","https://openalex.org/W3007273493","https://openalex.org/W3012476712","https://openalex.org/W3013277995","https://openalex.org/W3027174256","https://openalex.org/W3030419021","https://openalex.org/W3044853528","https://openalex.org/W3048680137","https://openalex.org/W3087265446","https://openalex.org/W3108633990","https://openalex.org/W3110197146","https://openalex.org/W3135057764","https://openalex.org/W3136166083","https://openalex.org/W4213113494","https://openalex.org/W4312888967"],"related_works":["https://openalex.org/W4200119984","https://openalex.org/W4220905407","https://openalex.org/W4313549251","https://openalex.org/W4400009130","https://openalex.org/W3162909563","https://openalex.org/W3119002188","https://openalex.org/W4224997321","https://openalex.org/W7222787542","https://openalex.org/W4388022987","https://openalex.org/W3123768286"],"abstract_inverted_index":{"The":[0,14,104,125,183],"Coronavirus":[1],"(COVID-19)":[2],"pandemic":[3],"is":[4,19,26,148,176],"still":[5],"ongoing":[6],"in":[7,11,100,168],"almost":[8],"all":[9],"countries":[10],"the":[12,17,23,42,50,70,73,80,88,130,133,145,161,164,173,179,188],"world.":[13],"spread":[15],"of":[16,44,52,56,132,163,170,191],"virus":[18],"very":[20],"fast":[21,101],"because":[22],"transmission":[24],"process":[25,75,175],"through":[27,194],"air":[28],"contaminated":[29],"with":[30],"viruses":[31],"from":[32,95],"COVID-19":[33,57,192],"patients\u2019":[34],"droplets.":[35],"Several":[36],"previous":[37],"studies":[38],"have":[39],"suggested":[40],"that":[41,72,87,129,199],"use":[43,63],"chest":[45,59,195],"X-Ray":[46,60,196],"images":[47,61,197],"can":[48,62,140,158,203],"detect":[49,123],"presence":[51],"this":[53],"virus.":[54],"Detection":[55],"using":[58,136],"deep":[64,96,165,180],"learning":[65,84,97,109,156,166,181],"techniques,":[66],"but":[67],"it":[68],"has":[69],"disadvantage":[71],"training":[74,102,146,174],"takes":[76],"too":[77,93],"long.":[78],"Therefore,":[79],"research":[81,105,184],"uses":[82],"machine":[83,155],"techniques":[85,157],"hoping":[86],"accuracy":[89,131],"results":[90,127,162],"are":[91],"not":[92],"different":[94],"and":[98,119,144,172],"result":[99],"time.":[103],"evaluates":[106],"three":[107],"supervised":[108],"methods,":[110],"namely":[111],"Support":[112],"Vector":[113],"Machine":[114],"(SVM),":[115],"K-Nearest":[116],"Neighbor":[117],"(K-NN),":[118],"Random":[120],"Forest,":[121],"to":[122],"COVID-19.":[124],"experimental":[126],"show":[128],"SVM":[134],"method":[135],"a":[137],"polynomial":[138],"kernel":[139],"reach":[141],"90%":[142],"accuracy,":[143,171],"time":[147],"only":[149],"462":[150],"ms.":[151],"Through":[152],"these":[153],"results,":[154],"compensate":[159],"for":[160],"technique":[167],"terms":[169],"faster":[177],"than":[178],"technique.":[182],"provides":[185],"insight":[186],"into":[187],"early":[189],"detection":[190],"patients":[193],"so":[198],"further":[200],"medical":[201],"treatment":[202],"be":[204],"carried":[205],"out":[206],"immediately.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2023-01-06T00:00:00"}
