{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002377701,0.001440747,0.001598669,0.001709021,0.0008148696,0.002763204,0.001039406,0.001024827,0.008445215],"category_scores_gemma":[0.004006705,0.0005180997,0.001265034,0.001061448,0.000436807,0.0021013,0.0005158611,0.00155719,0.005848023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007592953,"about_ca_system_score_gemma":0.001449268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00895904,"about_ca_topic_score_gemma":0.006755064,"domain_scores_codex":[0.9986666,0.0002397057,0.0001743798,0.0003506319,0.0004405775,0.0001280495],"domain_scores_gemma":[0.9985984,0.0005538995,0.00007236502,0.00007532397,0.0006623422,0.00003767612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005699076,0.0002495105,0.006728243,0.0005023097,0.0001968341,0.0002533125,0.0001835304,0.02705644,0.009772363,0.002178635,0.01423657,0.9380723],"study_design_scores_gemma":[0.0001201038,0.0004690276,0.01194655,0.0004665189,0.0005741894,0.001415963,0.0006061526,0.923413,0.02557223,0.007129868,0.02814319,0.000143197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.159831,0.01348062,0.7859494,0.00376083,0.001974446,0.0006717501,0.001367357,0.005799172,0.02716549],"genre_scores_gemma":[0.5060753,0.00716179,0.4438206,0.001006158,0.0006063904,0.0004887376,0.003618568,0.0005082896,0.03671417],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00895904,"threshold_uncertainty_score":0.02825201,"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."}}