{"id":"W4412676143","doi":"10.58776/jriti.v2i3.158","title":"Klasifikasi Penentuan Siswa Berprestasi Menggunakan Algoritma Naïve Bayes Classifier DI PT.Yes Study Education Group Indonesia","year":2025,"lang":"en","type":"article","venue":"Jurnal Riset Informatika dan Teknologi Informasi","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Naive Bayes classifier; Artificial intelligence; Computer science; Support vector machine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001063065,0.0005992407,0.0005776325,0.0009804544,0.001053107,0.001162983,0.003195612,0.0002906505,0.00000937016],"category_scores_gemma":[0.0003919447,0.0005220188,0.000202896,0.001575246,0.0001847692,0.004747545,0.001391562,0.001181533,0.0001557877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002484584,"about_ca_system_score_gemma":0.0007781659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001066081,"about_ca_topic_score_gemma":0.00005255544,"domain_scores_codex":[0.996097,0.0001838103,0.001546703,0.0005567204,0.0007600811,0.0008556559],"domain_scores_gemma":[0.9963481,0.0003192977,0.000835881,0.001849056,0.0003447519,0.0003029314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00006040628,0.001067318,0.1031374,0.0001393451,0.0002420633,0.000008033104,0.009698903,0.0002691225,0.00002493997,0.07527985,0.01517888,0.7948937],"study_design_scores_gemma":[0.002360811,0.0009960599,0.5897434,0.0002407743,0.0001591689,0.0001508297,0.01876348,0.02910879,0.0003053975,0.001507617,0.3553598,0.001303897],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7603428,0.0004510788,0.1501354,0.002889316,0.002485545,0.002777777,0.0000675049,0.002277701,0.07857283],"genre_scores_gemma":[0.9828588,0.0001765167,0.0134506,0.001265879,0.0001236917,0.0006438214,0.0004687304,0.00002655179,0.0009854124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7935898,"threshold_uncertainty_score":0.9998739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008750255239420343,"score_gpt":0.2800126257103752,"score_spread":0.2712623704709548,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}