{"id":"https://openalex.org/W7127095358","doi":"https://doi.org/10.55606/juisik.v6i1.2083","title":"Model Prediksi Kelulusan Siswa Menggunakan Algoritma Adaptive Boosting (Adaboost) dan Extreme Gradient Boosting (Xgboost): Studi pada SMK Setiabudhi Semarang","display_name":"Model Prediksi Kelulusan Siswa Menggunakan Algoritma Adaptive Boosting (Adaboost) dan Extreme Gradient Boosting (Xgboost): Studi pada SMK Setiabudhi Semarang","publication_year":2026,"publication_date":"2026-02-03","ids":{"openalex":"https://openalex.org/W7127095358","doi":"https://doi.org/10.55606/juisik.v6i1.2083"},"language":"en","primary_location":{"id":"doi:10.55606/juisik.v6i1.2083","doi":"https://doi.org/10.55606/juisik.v6i1.2083","is_oa":true,"landing_page_url":"https://doi.org/10.55606/juisik.v6i1.2083","pdf_url":"https://journal.sinov.id/index.php/juisik/article/download/2083/1466","source":{"id":"https://openalex.org/S4387285186","display_name":"Jurnal ilmiah Sistem Informasi dan Ilmu Komputer","issn_l":"2827-7953","issn":["2827-7953","2827-8135"],"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":"Jurnal ilmiah Sistem Informasi dan Ilmu Komputer","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W7127095358"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://journal.sinov.id/index.php/juisik/article/download/2083/1466","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124859636","display_name":"Gati Gati","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405270227","display_name":"Universitas Nasional Karangturi","ror":"https://ror.org/009eer679","country_code":"ID","type":"education","lineage":["https://openalex.org/I4405270227"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Gati Gati","raw_affiliation_strings":["Universitas Nasional Karangturi Semarang"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Nasional Karangturi Semarang","institution_ids":["https://openalex.org/I4405270227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088453603","display_name":"Siska Narulita","orcid":"https://orcid.org/0000-0002-6256-5184","observed_orcids":["https://orcid.org/0000-0002-6256-5184"]},"institutions":[{"id":"https://openalex.org/I4405270227","display_name":"Universitas Nasional Karangturi","ror":"https://ror.org/009eer679","country_code":"ID","type":"education","lineage":["https://openalex.org/I4405270227"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Siska Narulita","raw_affiliation_strings":["Universitas Nasional Karangturi Semarang"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Nasional Karangturi Semarang","institution_ids":["https://openalex.org/I4405270227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4405270227"],"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":"6","issue":"1","first_page":"169","last_page":"179"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9711999893188477,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11122","display_name":"Online Learning and Analytics","score":0.9711999893188477,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.027799999341368675,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/student-graduation-prediction","display_name":"student graduation prediction","score":0.9890000224113464},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.9850000143051147},{"id":"https://openalex.org/keywords/xgboost","display_name":"XGBoost","score":0.9990000128746033},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"ensemble learning","score":0.8159999847412109},{"id":"https://openalex.org/keywords/boosting","display_name":"boosting","score":0.9589999914169312},{"id":"https://openalex.org/keywords/academic-decision-making","display_name":"academic decision-making","score":0.6880000233650208},{"id":"https://openalex.org/keywords/vocational-high-school-students","display_name":"vocational high school students","score":0.902999997138977},{"id":"https://openalex.org/keywords/model-comparison","display_name":"model comparison","score":0.5080000162124634}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8084999918937683},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.7263000011444092},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5875999927520752},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5848000049591064},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.572700023651123},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5378000140190125},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.5205000042915344},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4399000108242035},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.42739999294281006},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.39660000801086426},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.374099999666214},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.34950000047683716},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C2779714256","wikidata":"https://www.wikidata.org/wiki/Q25305062","display_name":"Multiple Models","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C138602881","wikidata":"https://www.wikidata.org/wiki/Q2709591","display_name":"Confusion matrix","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C2779529714","wikidata":"https://www.wikidata.org/wiki/Q2632744","display_name":"Graduation (instrument)","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27320000529289246},{"id":"https://openalex.org/C5481197","wikidata":"https://www.wikidata.org/wiki/Q16766476","display_name":"Decision tree learning","level":3,"score":0.2619999945163727},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.2547999918460846},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.2531000077724457},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.55606/juisik.v6i1.2083","doi":"https://doi.org/10.55606/juisik.v6i1.2083","is_oa":true,"landing_page_url":"https://doi.org/10.55606/juisik.v6i1.2083","pdf_url":"https://journal.sinov.id/index.php/juisik/article/download/2083/1466","source":{"id":"https://openalex.org/S4387285186","display_name":"Jurnal ilmiah Sistem Informasi dan Ilmu Komputer","issn_l":"2827-7953","issn":["2827-7953","2827-8135"],"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":"Jurnal ilmiah Sistem Informasi dan Ilmu Komputer","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.55606/juisik.v6i1.2083","doi":"https://doi.org/10.55606/juisik.v6i1.2083","is_oa":true,"landing_page_url":"https://doi.org/10.55606/juisik.v6i1.2083","pdf_url":"https://journal.sinov.id/index.php/juisik/article/download/2083/1466","source":{"id":"https://openalex.org/S4387285186","display_name":"Jurnal ilmiah Sistem Informasi dan Ilmu Komputer","issn_l":"2827-7953","issn":["2827-7953","2827-8135"],"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":"Jurnal ilmiah Sistem Informasi dan Ilmu Komputer","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality education","score":0.8278999924659729,"id":"https://metadata.un.org/sdg/4"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7127095358.pdf","grobid_xml":"https://content.openalex.org/works/W7127095358.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W4285446420","https://openalex.org/W4293729205","https://openalex.org/W4406809344","https://openalex.org/W4407063955","https://openalex.org/W4408475777","https://openalex.org/W4408675743","https://openalex.org/W4411074611","https://openalex.org/W4411361012","https://openalex.org/W4413060170","https://openalex.org/W4413402344","https://openalex.org/W4413468300","https://openalex.org/W4416834556","https://openalex.org/W4417149417","https://openalex.org/W6911397108","https://openalex.org/W7083422949","https://openalex.org/W7092531778","https://openalex.org/W7117463896","https://openalex.org/W7162087482"],"related_works":["https://openalex.org/W7133553059","https://openalex.org/W7171292883","https://openalex.org/W4416893747","https://openalex.org/W7216732456","https://openalex.org/W7115569782","https://openalex.org/W7202042103","https://openalex.org/W4407102285","https://openalex.org/W4376605958","https://openalex.org/W7212371442","https://openalex.org/W4415765780"],"abstract_inverted_index":{"Student":[0],"graduation":[1,160],"is":[2,18,153],"one":[3],"indicator":[4],"in":[5,44,137,157,168],"evaluating":[6],"the":[7,10,30,37,51,108,129,146,150,169],"success":[8],"of":[9,32,50,72,94,97,100,105,114,117,120,125,139,145],"learning":[11,42],"process,":[12],"so":[13],"an":[14,92,103,112,123],"accurate":[15],"prediction":[16,33],"model":[17,61,90,110],"needed":[19],"to":[20,28,165],"support":[21,166],"academic":[22,170],"decision":[23],"making.":[24],"This":[25],"study":[26,52,147],"aims":[27],"compare":[29],"performance":[31,136],"models":[34,84],"generated":[35],"by":[36],"AdaBoost":[38,89,132],"and":[39,60,76,102,122,141,161],"XGBoost":[40,109],"ensemble":[41],"algorithms":[43],"predicting":[45,158],"student":[46,159],"graduation.":[47],"The":[48,78,88,143],"stages":[49],"include":[53],"data":[54,56],"collection,":[55],"pre-processing,":[57],"validation,":[58],"evaluation,":[59],"comparison.":[62],"Model":[63],"evaluation":[64],"used":[65,164],"a":[66],"confusion":[67],"matrix,":[68],"producing":[69],"measurement":[70],"metrics":[71],"accuracy,":[73],"precision,":[74],"recall,":[75],"F1-score.":[77],"comparison":[79,130],"results":[80,144],"showed":[81,133],"that":[82,149],"both":[83],"performed":[85],"very":[86],"well.":[87],"produced":[91,111],"accuracy":[93,113,140],"0.95,":[95,98],"precision":[96,116],"recall":[99,119],"0.99,":[101,121],"F1-score":[104,124],"0.97.":[106,126],"Meanwhile,":[107],"0.94,":[115,118],"Based":[127],"on":[128],"results,":[131],"slightly":[134],"superior":[135],"terms":[138],"precision.":[142],"show":[148],"boosting":[151],"algorithm":[152],"effective":[154],"for":[155],"implementation":[156],"can":[162],"be":[163],"decision-making":[167],"field.":[171]},"counts_by_year":[],"updated_date":"2026-11-13T13:42:25.865203","created_date":"2026-02-03T00:00:00"}
