{"id":"https://openalex.org/W3189772211","doi":"https://doi.org/10.1109/icaicst53116.2021.9497843","title":"Identification of Tomato Maturity Based on HIS Color Space Using The K-Nearest Neighbour Method","display_name":"Identification of Tomato Maturity Based on HIS Color Space Using The K-Nearest Neighbour Method","publication_year":2021,"publication_date":"2021-06-29","ids":{"openalex":"https://openalex.org/W3189772211","doi":"https://doi.org/10.1109/icaicst53116.2021.9497843","mag":"3189772211"},"language":"en","primary_location":{"id":"doi:10.1109/icaicst53116.2021.9497843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaicst53116.2021.9497843","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Artificial Intelligence and Computer Science Technology (ICAICST)","raw_type":"proceedings-article"},"type":"article","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/A5027625074","display_name":"Dewi Ayuningtyas","orcid":"https://orcid.org/0000-0003-4366-5259"},"institutions":[{"id":"https://openalex.org/I119896790","display_name":"Sebelas Maret University","ror":"https://ror.org/021hq5q33","country_code":"ID","type":"education","lineage":["https://openalex.org/I119896790"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Dewi Ayuningtyas","raw_affiliation_strings":["Universitas Sebelas Maret, Surakarta, Indonesia"],"affiliations":[{"raw_affiliation_string":"Universitas Sebelas Maret, Surakarta, Indonesia","institution_ids":["https://openalex.org/I119896790"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031821746","display_name":"Esti Suryani","orcid":"https://orcid.org/0000-0003-3304-9022"},"institutions":[{"id":"https://openalex.org/I119896790","display_name":"Sebelas Maret University","ror":"https://ror.org/021hq5q33","country_code":"ID","type":"education","lineage":["https://openalex.org/I119896790"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Esti Suryani","raw_affiliation_strings":["Universitas Sebelas Maret, Surakarta, Indonesia"],"affiliations":[{"raw_affiliation_string":"Universitas Sebelas Maret, Surakarta, Indonesia","institution_ids":["https://openalex.org/I119896790"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044373110","display_name":"Wiharto Wiharto","orcid":"https://orcid.org/0000-0001-7014-7620"},"institutions":[{"id":"https://openalex.org/I119896790","display_name":"Sebelas Maret University","ror":"https://ror.org/021hq5q33","country_code":"ID","type":"education","lineage":["https://openalex.org/I119896790"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Wiharto Wiharto","raw_affiliation_strings":["Universitas Sebelas Maret, Surakarta, Indonesia"],"affiliations":[{"raw_affiliation_string":"Universitas Sebelas Maret, Surakarta, Indonesia","institution_ids":["https://openalex.org/I119896790"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027625074"],"corresponding_institution_ids":["https://openalex.org/I119896790"],"apc_list":null,"apc_paid":null,"fwci":1.9432,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.87569268,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"73","last_page":"78"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14119","display_name":"Agricultural and Environmental Management","score":0.8474000096321106,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T14119","display_name":"Agricultural and Environmental Management","score":0.8474000096321106,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14127","display_name":"Food and Agricultural Sciences","score":0.8274000287055969,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13674","display_name":"Computer Science and Engineering","score":0.7717000246047974,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hue","display_name":"Hue","score":0.8655484914779663},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.7713803052902222},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7279080152511597},{"id":"https://openalex.org/keywords/ripeness","display_name":"Ripeness","score":0.6698519587516785},{"id":"https://openalex.org/keywords/color-space","display_name":"Color space","score":0.6663888692855835},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.621753990650177},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5738766193389893},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5546758770942688},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.554552435874939},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.46655505895614624},{"id":"https://openalex.org/keywords/ripening","display_name":"Ripening","score":0.25323742628097534},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09938353300094604},{"id":"https://openalex.org/keywords/horticulture","display_name":"Horticulture","score":0.07927259802818298}],"concepts":[{"id":"https://openalex.org/C126537357","wikidata":"https://www.wikidata.org/wiki/Q372948","display_name":"Hue","level":2,"score":0.8655484914779663},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.7713803052902222},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7279080152511597},{"id":"https://openalex.org/C2780393073","wikidata":"https://www.wikidata.org/wiki/Q7335586","display_name":"Ripeness","level":3,"score":0.6698519587516785},{"id":"https://openalex.org/C2961294","wikidata":"https://www.wikidata.org/wiki/Q166863","display_name":"Color space","level":3,"score":0.6663888692855835},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.621753990650177},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5738766193389893},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5546758770942688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.554552435874939},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46655505895614624},{"id":"https://openalex.org/C172353545","wikidata":"https://www.wikidata.org/wiki/Q2121926","display_name":"Ripening","level":2,"score":0.25323742628097534},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09938353300094604},{"id":"https://openalex.org/C144027150","wikidata":"https://www.wikidata.org/wiki/Q48803","display_name":"Horticulture","level":1,"score":0.07927259802818298},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaicst53116.2021.9497843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaicst53116.2021.9497843","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Artificial Intelligence and Computer Science Technology (ICAICST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W107968503","https://openalex.org/W2793174787","https://openalex.org/W2884768711","https://openalex.org/W2912259478","https://openalex.org/W2936159756","https://openalex.org/W2989833736","https://openalex.org/W3016798463","https://openalex.org/W3214905207","https://openalex.org/W4252813286","https://openalex.org/W6758512377","https://openalex.org/W6775711688"],"related_works":["https://openalex.org/W4377969315","https://openalex.org/W1580699584","https://openalex.org/W4255532429","https://openalex.org/W4252650332","https://openalex.org/W1655795019","https://openalex.org/W2078415748","https://openalex.org/W3094657558","https://openalex.org/W2805159267","https://openalex.org/W4240358042","https://openalex.org/W4377997101"],"abstract_inverted_index":{"Post-harvest":[0],"activities,":[1],"namely":[2],"sorting":[3],"and":[4,32,63,70,96,113,127,151,181],"grading,":[5],"are":[6],"usually":[7],"done":[8],"by":[9,13,26,90,204],"the":[10,16,19,22,34,48,58,65,68,99,123,134,136,139,160,173,182,210,219],"visual":[11],"method":[12,55,141,163,175,184],"looking":[14],"at":[15],"color":[17,53,115],"or":[18],"size":[20],"of":[21,37,42,60,67,81,138,149,155,169,179,188,212],"fruit.":[23],"Technological":[24],"advancements":[25],"using":[27,110,122],"computer":[28],"assistance":[29],"make":[30],"harvesting":[31],"detecting":[33],"ripening":[35,91],"process":[36],"tomatoes":[38,62],"easier.":[39],"The":[40,153],"purpose":[41],"this":[43,77,120,156],"research":[44,121,157],"is":[45,102,142,164,191,194],"to":[46,56,172,198],"apply":[47],"Hue,":[49],"Intensity,":[50],"Saturation":[51],"(HIS)":[52],"transformation":[54],"detect":[57],"ripeness":[59],"vegetable":[61],"determine":[64],"accuracy":[66,137],"HIS":[69,109,165,197],"Red,":[71],"Green,":[72],"Blue":[73],"(RGB)":[74],"methods.":[75],"In":[76,118],"research,":[78],"some":[79],"samples":[80],"tomatoes'":[82],"RGB":[83,100,174],"values":[84,214],"were":[85],"taken":[86],"through":[87],"image":[88],"processing":[89],"level,":[92],"between":[93],"unripe,":[94],"under-ripe,":[95],"ripe.":[97],"After":[98],"value":[101,208],"obtained,":[103],"it":[104,193],"will":[105],"be":[106],"converted":[107],"into":[108],"means,":[111],"variance,":[112],"range":[114,211],"feature":[116],"extraction.":[117],"classifying":[119],"K-Nearest":[124],"Neighbour":[125],"(KNN)":[126],"Support":[128],"Vector":[129],"Machine":[130],"(SVM)":[131],"method.":[132],"With":[133],"results,":[135],"KNN":[140],"better":[143],"than":[144],"SVM":[145],"with":[146,166,176,185,201],"an":[147,167,177,186],"average":[148,168,178,187],"87.80%":[150],"74.38%.":[152],"result":[154],"indicates":[158],"that":[159,217],"more":[161],"accurate":[162],"89.65%":[170],"compared":[171],"89.35%":[180],"CIElab":[183],"84.41%.":[189],"This":[190],"because":[192],"easier":[195],"for":[196],"identify":[199],"objects":[200],"different":[202],"hues":[203],"providing":[205],"a":[206],"threshold":[207],"in":[209],"hue":[213],"(spectral":[215],"wavelengths)":[216],"surround":[218],"object.":[220]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}