{"id":"https://openalex.org/W4412901834","doi":"https://doi.org/10.30865/jurikom.v12i2.8519","title":"Deteksi Kualitas Buah Sawo dengan Pendekatan Ekstraksi Fitur GLCM dan Algoritma Support Vector Machine","display_name":"Deteksi Kualitas Buah Sawo dengan Pendekatan Ekstraksi Fitur GLCM dan Algoritma Support Vector Machine","publication_year":2025,"publication_date":"2025-04-30","ids":{"openalex":"https://openalex.org/W4412901834","doi":"https://doi.org/10.30865/jurikom.v12i2.8519"},"language":"en","primary_location":{"id":"doi:10.30865/jurikom.v12i2.8519","doi":"https://doi.org/10.30865/jurikom.v12i2.8519","is_oa":true,"landing_page_url":"https://doi.org/10.30865/jurikom.v12i2.8519","pdf_url":null,"source":{"id":"https://openalex.org/S4210198570","display_name":"JURIKOM (Jurnal Riset Komputer)","issn_l":"2407-389X","issn":["2407-389X","2715-7393"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"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":"JURIKOM (Jurnal Riset Komputer)","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.30865/jurikom.v12i2.8519","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119185637","display_name":"Karisma Risma Fidiya","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karisma Risma Fidiya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068700885","display_name":"Muhammad Jauhar Vikri","orcid":"https://orcid.org/0009-0005-1369-3162","observed_orcids":["https://orcid.org/0009-0005-1369-3162"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Muhammad Jauhar Vikri","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5087856900","display_name":"Alif Yuanita Kartini","orcid":"https://orcid.org/0009-0007-4651-9763","observed_orcids":["https://orcid.org/0009-0007-4651-9763"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alif Yuanita Kartini","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15137045,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":"2","first_page":"74","last_page":"83"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.448199987411499,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.448199987411499,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.2930000126361847,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant 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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.13529999554157257,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/fruit-quality-detection","display_name":"fruit quality detection","score":0.9559999704360962},{"id":"https://openalex.org/keywords/gray-level-co-occurrence-matrix","display_name":"gray level co-occurrence matrix","score":0.8709999918937683},{"id":"https://openalex.org/keywords/texture-feature-extraction","display_name":"texture feature extraction","score":0.9760000109672546},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.9929999709129333},{"id":"https://openalex.org/keywords/fruit-ripeness-classification","display_name":"fruit ripeness classification","score":0.9100000262260437},{"id":"https://openalex.org/keywords/fruit-damage-detection","display_name":"fruit damage detection","score":0.8889999985694885},{"id":"https://openalex.org/keywords/data-augmentation","display_name":"data augmentation","score":0.8059999942779541},{"id":"https://openalex.org/keywords/image-based-fruit-classification","display_name":"image-based fruit classification","score":0.5600000023841858},{"id":"https://openalex.org/keywords/graphical-user-interface","display_name":"graphical user interface","score":0.878000020980835}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5628176927566528},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41793763637542725},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33960577845573425}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.30865/jurikom.v12i2.8519","doi":"https://doi.org/10.30865/jurikom.v12i2.8519","is_oa":true,"landing_page_url":"https://doi.org/10.30865/jurikom.v12i2.8519","pdf_url":null,"source":{"id":"https://openalex.org/S4210198570","display_name":"JURIKOM (Jurnal Riset Komputer)","issn_l":"2407-389X","issn":["2407-389X","2715-7393"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"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":"JURIKOM (Jurnal Riset Komputer)","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.30865/jurikom.v12i2.8519","doi":"https://doi.org/10.30865/jurikom.v12i2.8519","is_oa":true,"landing_page_url":"https://doi.org/10.30865/jurikom.v12i2.8519","pdf_url":null,"source":{"id":"https://openalex.org/S4210198570","display_name":"JURIKOM (Jurnal Riset Komputer)","issn_l":"2407-389X","issn":["2407-389X","2715-7393"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"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":"JURIKOM (Jurnal Riset Komputer)","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6875,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4242982862","https://openalex.org/W2902965117","https://openalex.org/W2996132143","https://openalex.org/W4380894697","https://openalex.org/W4402040455","https://openalex.org/W7220819205","https://openalex.org/W4407304816","https://openalex.org/W3033519704","https://openalex.org/W3183317137","https://openalex.org/W4403061498"],"abstract_inverted_index":{"The":[0,81],"quality":[1,22,137],"of":[2,23,49,118],"sapodilla":[3,24,50,108,136],"fruit":[4,25,51,109],"is":[5],"a":[6,86,125],"crucial":[7],"factor":[8],"in":[9,124],"ensuring":[10],"product":[11],"standards":[12],"and":[13,38,55,71,90,97,114,139],"consumer":[14],"satisfaction.":[15],"This":[16,120],"study":[17],"aims":[18],"to":[19,61,133],"detect":[20],"the":[21,27,44,78,103],"using":[26,57,85],"Gray":[28],"Level":[29],"Co-occurrence":[30],"Matrix":[31],"(GLCM)":[32],"method":[33,105],"for":[34,77],"texture":[35],"feature":[36],"extraction":[37],"Support":[39],"Vector":[40],"Machine":[41],"(SVM)":[42],"as":[43,75],"classification":[45],"algorithm.":[46],"A":[47],"dataset":[48],"images":[52],"was":[53,83,122],"collected":[54],"processed":[56],"data":[58],"augmentation":[59],"techniques":[60],"enhance":[62],"image":[63],"variation.":[64],"Extracted":[65],"features,":[66],"including":[67],"contrast,":[68],"homogeneity,":[69],"energy,":[70],"correlation,":[72],"were":[73],"used":[74],"input":[76],"SVM":[79],"model.":[80],"model":[82,121],"developed":[84],"train-test":[87],"split":[88],"approach":[89],"evaluated":[91],"based":[92],"on":[93],"accuracy,":[94],"precision,":[95],"recall,":[96],"F1-score.":[98],"Experimental":[99],"results":[100],"show":[101],"that":[102],"proposed":[104],"successfully":[106],"classifies":[107],"into":[110],"three":[111],"categories\u2014raw,":[112],"ripe,":[113],"damaged\u2014with":[115],"an":[116],"accuracy":[117],"85%.":[119],"implemented":[123],"MATLAB-based":[126],"Graphical":[127],"User":[128],"Interface":[129],"(GUI),":[130],"enabling":[131],"users":[132],"automatically":[134],"classify":[135],"easily":[138],"efficiently.":[140]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-10-19T00:00:00"}
