{"id":"https://openalex.org/W3211220652","doi":"https://doi.org/10.1109/isemantic52711.2021.9573225","title":"Linear Regression Analysis and SVR in Predicting Motor Vehicle Theft","display_name":"Linear Regression Analysis and SVR in Predicting Motor Vehicle Theft","publication_year":2021,"publication_date":"2021-09-18","ids":{"openalex":"https://openalex.org/W3211220652","doi":"https://doi.org/10.1109/isemantic52711.2021.9573225","mag":"3211220652"},"language":"en","primary_location":{"id":"doi:10.1109/isemantic52711.2021.9573225","doi":"https://doi.org/10.1109/isemantic52711.2021.9573225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isemantic52711.2021.9573225","pdf_url":null,"source":{"id":"https://openalex.org/S4306498372","display_name":"International Seminar on Application for Technology of Information and Communication (iSemantic)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Seminar on Application for Technology of Information and Communication (iSemantic)","raw_type":"proceedings-article"},"parent_works":[],"lineage":["https://openalex.org/W3211220652"],"child_works_count":0,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056963594","display_name":"Nur Nafi\u2019iyah","orcid":"https://orcid.org/0000-0002-6015-3872","observed_orcids":["https://orcid.org/0000-0002-6015-3872"]},"institutions":[{"id":"https://openalex.org/I4210161641","display_name":"Universitas Islam Lamongan","ror":"https://ror.org/052crx470","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210161641"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Nur Nafi'iyah","raw_affiliation_strings":["Informatic Engineering, Universitas Islam Lamongan, Lamongan, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Informatic Engineering, Universitas Islam Lamongan, Lamongan, Indonesia","institution_ids":["https://openalex.org/I4210161641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035461788","display_name":"Kemal Farouq Mauladi","orcid":"https://orcid.org/0000-0003-2356-2201","observed_orcids":["https://orcid.org/0000-0003-2356-2201"]},"institutions":[{"id":"https://openalex.org/I4210161641","display_name":"Universitas Islam Lamongan","ror":"https://ror.org/052crx470","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210161641"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Kemal Farouq Mauladi","raw_affiliation_strings":["Informatic Engineering, Universitas Islam Lamongan, Lamongan, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Informatic Engineering, Universitas Islam Lamongan, Lamongan, Indonesia","institution_ids":["https://openalex.org/I4210161641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210161641"],"apc_list":null,"apc_paid":null,"fwci":0.6699,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.63172901,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"54","last_page":"58"},"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":0.9984999895095825,"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":0.9984999895095825,"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/T13141","display_name":"Statistical Methods and Applications","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10574","display_name":"Crime Patterns and Interventions","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/motor-vehicle-theft","display_name":"motor vehicle theft","score":0.9660000205039978},{"id":"https://openalex.org/keywords/crime-prediction","display_name":"crime prediction","score":0.9620000123977661},{"id":"https://openalex.org/keywords/linear-regression","display_name":"linear regression","score":0.9259999990463257},{"id":"https://openalex.org/keywords/support-vector-regression","display_name":"support vector regression","score":0.9990000128746033},{"id":"https://openalex.org/keywords/police-statistics","display_name":"police statistics","score":0.5479999780654907},{"id":"https://openalex.org/keywords/east-java-regional-police","display_name":"East Java Regional Police","score":0.8970000147819519},{"id":"https://openalex.org/keywords/crime-pattern-analysis","display_name":"crime pattern analysis","score":0.550000011920929}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7236113548278809},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.659644603729248},{"id":"https://openalex.org/C548217200","wikidata":"https://www.wikidata.org/wiki/Q251","display_name":"Java","level":2,"score":0.6469236612319946},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.646192729473114},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.6380597352981567},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4247402846813202},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42266008257865906},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.42214399576187134},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.41936302185058594},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3592469096183777},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2336062788963318},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13899484276771545},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.09218266606330872},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isemantic52711.2021.9573225","doi":"https://doi.org/10.1109/isemantic52711.2021.9573225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isemantic52711.2021.9573225","pdf_url":null,"source":{"id":"https://openalex.org/S4306498372","display_name":"International Seminar on Application for Technology of Information and Communication (iSemantic)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Seminar on Application for Technology of Information and Communication (iSemantic)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5142999887466431},{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4943999946117401},{"display_name":"Peace, justice, and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.46149998903274536}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2013222108","https://openalex.org/W2096896574","https://openalex.org/W2128338591","https://openalex.org/W2255897396","https://openalex.org/W2334775835","https://openalex.org/W2346552988","https://openalex.org/W2465972858","https://openalex.org/W2514945220","https://openalex.org/W2592481615","https://openalex.org/W2616853374","https://openalex.org/W2728654203","https://openalex.org/W2775402959","https://openalex.org/W2888794980","https://openalex.org/W2888964392","https://openalex.org/W2946497961","https://openalex.org/W2975843264"],"related_works":["https://openalex.org/W4392292616","https://openalex.org/W2946497961","https://openalex.org/W7115978146","https://openalex.org/W4312734456","https://openalex.org/W4408277248","https://openalex.org/W3044669619","https://openalex.org/W7217420291","https://openalex.org/W4210759194","https://openalex.org/W4415996478","https://openalex.org/W3210876794"],"abstract_inverted_index":{"Computer-based":[0],"systems":[1],"that":[2,180],"apply":[3],"machine":[4],"learning":[5,17],"methods":[6,18],"can":[7,19,26],"help":[8],"analyze":[9,22],"crime":[10,14],"patterns":[11],"and":[12,25,38,71,101,139,159],"predict":[13,42],"rates.":[15],"Machine":[16],"function":[20],"to":[21,41,55,63],"data":[23,75,104,111,149,158],"automatically":[24],"display":[27],"visual":[28],"analysis":[29],"results.":[30],"We":[31],"propose":[32],"analyzing":[33],"the":[34,47,65,78,85,94,110,116,130,134,137,140,143,191],"Linear":[35,166,181],"Regression":[36,40,167,182],"algorithm":[37],"SVM":[39],"motor":[43,58],"vehicle":[44,59],"theft":[45,60],"in":[46,67],"East":[48,79],"Java":[49,80],"Regional":[50,81],"Police.":[51],"The":[52,103,121,147,163,171],"goal":[53],"is":[54,112,118,126,153,190],"create":[56],"a":[57,184],"prediction":[61,117],"system":[62],"assist":[64],"police":[66,86],"monitoring":[68],"regional":[69],"security":[70],"reducing":[72],"crime.":[73],"Initial":[74],"obtained":[76],"from":[77],"Police":[82],"consisted":[83],"of":[84,93,98,106,136,145,150,165],"column,":[87],"date,":[88],"month,":[89],"year,":[90],"city,":[91],"location":[92,135],"theft,":[95,138],"mode,":[96],"number":[97,144],"wheels,":[99],"brand,":[100],"thefts.":[102,146],"consists":[105],"7264":[107],"lines;":[108],"however,":[109],"processed":[113],"first":[114],"before":[115],"carried":[119],"out.":[120],"processing":[122],"result":[123],"dataset":[124],"used":[125],"60":[127,151],"lines,":[128],"with":[129],"month's":[131],"input":[132],"variables,":[133],"output":[141],"variable,":[142],"total":[148],"lines":[152],"divided":[154],"into":[155],"52":[156],"training":[157],"six":[160],"testing":[161],"data.":[162],"method":[164,173],"has":[168,174,183],"MAE":[169,175],"34.26.":[170],"SVR":[172],"134.7.":[176],"This":[177],"study":[178],"concludes":[179],"more":[185],"petite":[186],"MAE,":[187],"so":[188],"it":[189],"best.":[192]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2021-11-08T00:00:00"}