{"id":"https://openalex.org/W7219475210","doi":null,"title":"PENERAPAN METODE MOVENET UNTUK DETEKSI KETEPATAN GERAKAN DALAM OLAHRAGA BULU TANGKIS","display_name":"PENERAPAN METODE MOVENET UNTUK DETEKSI KETEPATAN GERAKAN DALAM OLAHRAGA BULU TANGKIS","publication_year":2026,"publication_date":"2026-01-07","ids":{"openalex":"https://openalex.org/W7219475210"},"language":"id","primary_location":{"id":"pmh:oai:jurnal.ubd.ac.id/index.php:article/4295","doi":null,"is_oa":true,"landing_page_url":"https://jurnal.ubd.ac.id/index.php/poters/article/view/4295","pdf_url":"https://jurnal.ubd.ac.id/index.php/poters/article/download/4295/3113","source":{"id":"https://openalex.org/S7407068099","display_name":"POTERS (Proceedings of Technology, Engineering and Computers)","issn_l":"3090-3602","issn":["3090-3602","3109-127X"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"3109-127X","raw_type":"info:eu-repo/semantics/article"},"parent_works":[],"lineage":["https://openalex.org/W7219475210"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://jurnal.ubd.ac.id/index.php/poters/article/download/4295/3113","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119341426","display_name":"Sendy Jonathan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405271229","display_name":"Universitas Buddhi Dharma","ror":"https://ror.org/02392yc18","country_code":"ID","type":"education","lineage":["https://openalex.org/I4405271229"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Jonathan, Sendy","raw_affiliation_strings":["Universitas Buddhi Dharma"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Buddhi Dharma","institution_ids":["https://openalex.org/I4405271229"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012362640","display_name":"Yo Ceng Giap","orcid":"https://orcid.org/0009-0008-5040-5096","observed_orcids":["https://orcid.org/0009-0008-5040-5096"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ceng Giap, Yo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9940999746322632,"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"}},"topics":[{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9940999746322632,"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"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.0015999999595806003,"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"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.0010000000474974513,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/badminton","display_name":"badminton","score":0.8740000128746033},{"id":"https://openalex.org/keywords/movenet","display_name":"MoveNet","score":0.7379999756813049},{"id":"https://openalex.org/keywords/pose-estimation","display_name":"pose estimation","score":0.8140000104904175},{"id":"https://openalex.org/keywords/android-application","display_name":"Android application","score":0.8389999866485596},{"id":"https://openalex.org/keywords/tensorflow-lite","display_name":"TensorFlow Lite","score":0.9160000085830688},{"id":"https://openalex.org/keywords/real-time-visual-feedback","display_name":"real-time visual feedback","score":0.7459999918937683},{"id":"https://openalex.org/keywords/independent-training","display_name":"independent training","score":0.503000020980835},{"id":"https://openalex.org/keywords/motion-classification","display_name":"movement classification","score":0.46700000762939453}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5806999802589417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5692999958992004},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.48730000853538513},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.4390999972820282},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3937000036239624},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3212999999523163},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.29339998960494995},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:jurnal.ubd.ac.id/index.php:article/4295","doi":null,"is_oa":true,"landing_page_url":"https://jurnal.ubd.ac.id/index.php/poters/article/view/4295","pdf_url":"https://jurnal.ubd.ac.id/index.php/poters/article/download/4295/3113","source":{"id":"https://openalex.org/S7407068099","display_name":"POTERS (Proceedings of Technology, Engineering and Computers)","issn_l":"3090-3602","issn":["3090-3602","3109-127X"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"3109-127X","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:jurnal.ubd.ac.id/index.php:article/4295","doi":null,"is_oa":true,"landing_page_url":"https://jurnal.ubd.ac.id/index.php/poters/article/view/4295","pdf_url":"https://jurnal.ubd.ac.id/index.php/poters/article/download/4295/3113","source":{"id":"https://openalex.org/S7407068099","display_name":"POTERS (Proceedings of Technology, Engineering and Computers)","issn_l":"3090-3602","issn":["3090-3602","3109-127X"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"3109-127X","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7219475210.pdf","grobid_xml":"https://content.openalex.org/works/W7219475210.grobid-xml"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W2803008851","https://openalex.org/W2951856387","https://openalex.org/W4221126731","https://openalex.org/W4229073080","https://openalex.org/W4286222405","https://openalex.org/W4291238046","https://openalex.org/W4367045737","https://openalex.org/W4394003229","https://openalex.org/W4411224827"],"related_works":["https://openalex.org/W4409898304","https://openalex.org/W4396939922","https://openalex.org/W4398162451","https://openalex.org/W4403421273","https://openalex.org/W7160374626","https://openalex.org/W2211352189","https://openalex.org/W7168369535","https://openalex.org/W7202392734","https://openalex.org/W7212159410","https://openalex.org/W4415058875"],"abstract_inverted_index":{"Badminton":[0],"is":[1,98,112,122,134,154],"a":[2,125,165],"sport":[3],"that":[4,14,53,131],"requires":[5],"mastery":[6],"of":[7,64,143,146,150,164],"precise":[8],"movement":[9,169],"techniques.":[10],"Conventional":[11],"training":[12],"methods":[13],"rely":[15],"heavily":[16],"on":[17,108],"coaches\u2019":[18],"visual":[19,159],"observations":[20],"are":[21],"often":[22],"subjective":[23],"and":[24,30,47,60,73,82,94,119,148,168,177],"have":[25],"limitations":[26],"in":[27,33,161],"monitoring":[28],"fast":[29],"detailed":[31],"movements":[32,138],"real":[34],"time,":[35],"especially":[36],"for":[37],"players":[38],"who":[39],"train":[40],"independently.":[41],"This":[42],"study":[43],"aims":[44],"to":[45,58,76,104,136,156,180],"design":[46],"develop":[48],"an":[49,140,175],"Android-based":[50],"mobile":[51,109],"application":[52,97],"utilizes":[54],"the":[55,62,115,132,162],"MoveNet":[56],"algorithm":[57],"detect":[59],"evaluate":[61],"accuracy":[63,142],"basic":[65],"badminton":[66],"movements.":[67],"The":[68,96,128,152],"system":[69,153],"employs":[70],"computer":[71],"vision":[72],"pose":[74],"estimation":[75],"track":[77],"17":[78],"human":[79],"body":[80,166],"keypoints":[81],"analyze":[83],"seven":[84],"fundamental":[85],"movements:":[86],"smash,":[87],"drop":[88],"shot,":[89],"drive,":[90],"serve,":[91],"lob,":[92],"backhand,":[93],"netting.":[95],"developed":[99],"with":[100,139],"TensorFlow":[101],"Lite":[102],"integration":[103],"enable":[105],"efficient":[106],"processing":[107],"devices.":[110],"Testing":[111],"conducted":[113],"using":[114,124],"black-box":[116],"testing":[117],"method,":[118],"model":[120,133],"performance":[121],"evaluated":[123],"confusion":[126],"matrix.":[127],"results":[129],"show":[130],"able":[135],"classify":[137],"average":[141],"78%,":[144,147],"precision":[145],"recall":[149],"78%.":[151],"proven":[155],"provide":[157],"real-time":[158],"feedback":[160],"form":[163],"skeleton":[167],"evaluation,":[170],"making":[171],"it":[172],"effective":[173],"as":[174],"objective":[176],"data-driven":[178],"tool":[179],"support":[181],"independent":[182],"training.":[183]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-10-04T00:00:00"}
