{"id":"W4417142765","doi":"10.56971/jwi.v9i2.323","title":"ANALISIS KLASIFIKASI SARAN PESERTA PELATIHAN MENGGUNAKAN PENDEKATAN MACHINE LEARNING","year":2024,"lang":"","type":"article","venue":"Jurnal Kewidyaiswaraan/Jurnal kewidyaiswaraan","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Naive Bayes classifier; AdaBoost","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004161311,0.001438999,0.001180387,0.003124991,0.001128829,0.00455318,0.001162662,0.001406181,0.01117824],"category_scores_gemma":[0.01514028,0.0005951883,0.001738906,0.003840478,0.0006946966,0.003608656,0.001174717,0.002505842,0.005568583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001919943,"about_ca_system_score_gemma":0.002082724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01708667,"about_ca_topic_score_gemma":0.01963215,"domain_scores_codex":[0.9967644,0.0005998263,0.0002324933,0.000857509,0.001277287,0.000268487],"domain_scores_gemma":[0.988744,0.006344681,0.0007009151,0.0009776222,0.00300439,0.0002283407],"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":[0.001002309,0.0004730213,0.1390091,0.001742986,0.000760523,0.0007762747,0.001616249,0.04200764,0.01841999,0.008214651,0.03557548,0.7504018],"study_design_scores_gemma":[0.0001031981,0.001115507,0.2819301,0.001245141,0.001418084,0.001696626,0.008058351,0.4021395,0.05906966,0.0429596,0.1997611,0.0005032535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5699088,0.01893708,0.3011117,0.01114124,0.001686197,0.0007300412,0.01817059,0.006534771,0.07177959],"genre_scores_gemma":[0.8354115,0.006456556,0.09339885,0.0009115013,0.000315601,0.0003978668,0.0142289,0.0008424325,0.0480369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01708667,"threshold_uncertainty_score":0.03739488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0203131134102322,"score_gpt":0.2843137575026259,"score_spread":0.2640006440923937,"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."}}