{"id":"https://openalex.org/W4401765151","doi":"https://doi.org/10.51903/pixel.v17i1.2006","title":"The Implementation of a Logistic Regression Algorithm and Gradient Boosting Classifier for Predicting Telco Customer Churn","display_name":"The Implementation of a Logistic Regression Algorithm and Gradient Boosting Classifier for Predicting Telco Customer Churn","publication_year":2024,"publication_date":"2024-07-24","ids":{"openalex":"https://openalex.org/W4401765151","doi":"https://doi.org/10.51903/pixel.v17i1.2006"},"language":"en","primary_location":{"id":"doi:10.51903/pixel.v17i1.2006","doi":"https://doi.org/10.51903/pixel.v17i1.2006","is_oa":true,"landing_page_url":"http://dx.doi.org/10.51903/pixel.v17i1.2006","pdf_url":"https://journal.stekom.ac.id/index.php/pixel/article/download/2006/1488","source":{"id":"https://openalex.org/S4210213265","display_name":"Pixel Jurnal Ilmiah Komputer Grafis","issn_l":"1979-0414","issn":["1979-0414","2621-6256"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4387153296","host_organization_name":"Universitas Sains dan Teknologi Komputer","host_organization_lineage":["https://openalex.org/I4387153296"],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Pixel :Jurnal Ilmiah Komputer Grafis","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://journal.stekom.ac.id/index.php/pixel/article/download/2006/1488","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5106642801","display_name":"Angga Adiansya","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I148158369","display_name":"State University of Semarang","ror":"https://ror.org/02fsk7e17","country_code":"ID","type":"education","lineage":["https://openalex.org/I148158369"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Angga Adiansya","raw_affiliation_strings":["Universitas Negeri Semarang"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Negeri Semarang","institution_ids":["https://openalex.org/I148158369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010186387","display_name":"Zaenal Abidin","orcid":"https://orcid.org/0000-0003-4237-7167","observed_orcids":["https://orcid.org/0000-0003-4237-7167"]},"institutions":[{"id":"https://openalex.org/I148158369","display_name":"State University of Semarang","ror":"https://ror.org/02fsk7e17","country_code":"ID","type":"education","lineage":["https://openalex.org/I148158369"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Zaenal Abidin","raw_affiliation_strings":["Universitas Negeri Semarang"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Negeri Semarang","institution_ids":["https://openalex.org/I148158369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I148158369"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16081126,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":"1","first_page":"168","last_page":"178"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"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/T12384","display_name":"Customer churn and segmentation","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.0,"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/T10154","display_name":"Customer Service Quality and Loyalty","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/customer-churn-prediction","display_name":"customer churn prediction","score":0.9860000014305115},{"id":"https://openalex.org/keywords/telecommunications-customers","display_name":"telecommunications customers","score":0.9020000100135803},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"logistic regression","score":0.9700000286102295},{"id":"https://openalex.org/keywords/gradient-boosting-classifier","display_name":"gradient boosting classifier","score":0.9700000286102295},{"id":"https://openalex.org/keywords/customer-retention","display_name":"customer retention","score":0.8460000157356262},{"id":"https://openalex.org/keywords/classification-model-comparison","display_name":"classification model comparison","score":0.6060000061988831}],"concepts":[{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.7884103059768677},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.7754290103912354},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7468792200088501},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6545025110244751},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5619051456451416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5145666003227234},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4900147020816803},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4420650899410248},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35287636518478394},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.344776451587677},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3240433931350708},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.26942190527915955},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19501522183418274},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15432721376419067}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.51903/pixel.v17i1.2006","doi":"https://doi.org/10.51903/pixel.v17i1.2006","is_oa":true,"landing_page_url":"http://dx.doi.org/10.51903/pixel.v17i1.2006","pdf_url":"https://journal.stekom.ac.id/index.php/pixel/article/download/2006/1488","source":{"id":"https://openalex.org/S4210213265","display_name":"Pixel Jurnal Ilmiah Komputer Grafis","issn_l":"1979-0414","issn":["1979-0414","2621-6256"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4387153296","host_organization_name":"Universitas Sains dan Teknologi Komputer","host_organization_lineage":["https://openalex.org/I4387153296"],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Pixel :Jurnal Ilmiah Komputer Grafis","raw_type":"journal-article"},{"id":"pmh:oai:journal.stekom.ac.id:article/2006","doi":null,"is_oa":true,"landing_page_url":"https://journal.stekom.ac.id/index.php/pixel/article/view/2006","pdf_url":null,"source":{"id":"https://openalex.org/S4210213265","display_name":"Pixel Jurnal Ilmiah Komputer Grafis","issn_l":"1979-0414","issn":["1979-0414","2621-6256"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4387153296","host_organization_name":"Universitas Sains dan Teknologi Komputer","host_organization_lineage":["https://openalex.org/I4387153296"],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"10.51903/pixel.v17i1","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.51903/pixel.v17i1.2006","doi":"https://doi.org/10.51903/pixel.v17i1.2006","is_oa":true,"landing_page_url":"http://dx.doi.org/10.51903/pixel.v17i1.2006","pdf_url":"https://journal.stekom.ac.id/index.php/pixel/article/download/2006/1488","source":{"id":"https://openalex.org/S4210213265","display_name":"Pixel Jurnal Ilmiah Komputer Grafis","issn_l":"1979-0414","issn":["1979-0414","2621-6256"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4387153296","host_organization_name":"Universitas Sains dan Teknologi Komputer","host_organization_lineage":["https://openalex.org/I4387153296"],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Pixel :Jurnal Ilmiah Komputer Grafis","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/W4401765151.pdf","grobid_xml":"https://content.openalex.org/works/W4401765151.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W6968462256","https://openalex.org/W7223576500","https://openalex.org/W4408018020","https://openalex.org/W7131373733","https://openalex.org/W4415884037","https://openalex.org/W7203492705","https://openalex.org/W4414680576","https://openalex.org/W4399274215","https://openalex.org/W7140310154","https://openalex.org/W4399422559"],"abstract_inverted_index":{"This":[0,110],"research":[1],"aims":[2],"to":[3,107],"predict":[4],"customer":[5,119],"churn":[6,22],"in":[7,117],"a":[8,24,57,88],"telecommunications":[9],"company":[10],"using":[11,56,87],"Logistic":[12],"Regression":[13],"(LR)":[14],"and":[15,44,54,67,74,85],"Gradient":[16],"Boosting":[17],"Classifier":[18],"(GBC)":[19],"algorithms.":[20],"Customer":[21],"poses":[23],"significant":[25],"challenge":[26],"as":[27],"acquiring":[28],"new":[29],"customers":[30],"is":[31,62],"costlier":[32],"than":[33],"retaining":[34],"existing":[35],"ones.":[36],"The":[37,47,60],"dataset":[38],"from":[39],"Kaggle":[40],"comprises":[41],"7043":[42],"records":[43],"21":[45],"attributes.":[46],"process":[48],"includes":[49],"data":[50,61],"pre-processing,":[51],"cleaning,":[52],"transformation,":[53],"normalization":[55],"Min-Max":[58],"Scaler.":[59],"split":[63],"into":[64,72],"features":[65],"(X)":[66],"target":[68],"(y),":[69],"then":[70],"divided":[71],"training":[73],"testing":[75],"sets":[76],"with":[77,101],"an":[78,102],"80:20":[79],"ratio.":[80],"Both":[81],"models":[82],"were":[83],"trained":[84],"evaluated":[86],"confusion":[89],"matrix.":[90],"Results":[91],"show":[92],"that":[93],"the":[94,98,113],"GBC":[95,116],"model":[96],"outperforms":[97],"LR":[99],"model,":[100],"accuracy":[103],"of":[104,115],"83%":[105],"compared":[106],"LR's":[108],"81%.":[109],"study":[111],"demonstrates":[112],"effectiveness":[114],"predicting":[118],"churn.":[120]},"counts_by_year":[],"updated_date":"2026-10-10T09:11:00.788812","created_date":"2024-08-23T00:00:00"}