{"id":"W4415349534","doi":"10.59934/jaiea.v5i1.1625","title":"Analysis of Student Satisfaction Sentiment Towards Lecturer Performance using the Naive Bayes Classifier Method (Case Study: STMIK KAPUTAMA)","year":2025,"lang":"","type":"article","venue":"Journal of Artificial Intelligence and Engineering Applications (JAIEA)","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Naive Bayes classifier; Classifier (UML); Weighting; Preprocessor; Python (programming language); Bayes' theorem; Terminology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002024671,0.0003250962,0.0006526774,0.001195376,0.0006229987,0.0004149022,0.0007631095,0.0001212245,0.00001768269],"category_scores_gemma":[0.00007496079,0.0002676694,0.0002784697,0.003851661,0.0001275351,0.000379739,0.0003123042,0.0007203716,0.000002546915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001575957,"about_ca_system_score_gemma":0.0002475728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004355906,"about_ca_topic_score_gemma":0.00004069573,"domain_scores_codex":[0.9969734,0.0001878931,0.001491356,0.0005013914,0.000529834,0.0003161512],"domain_scores_gemma":[0.9971305,0.0004469059,0.000852974,0.0008349757,0.0006058799,0.0001288256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001503183,0.0003495569,0.003746083,0.00004810782,0.001749925,0.000009596553,0.004466473,0.559002,0.001614019,0.00237883,0.00001665263,0.4266037],"study_design_scores_gemma":[0.00006860779,0.0002361172,0.01469727,0.00009974993,0.003019206,0.0001748745,0.006116207,0.9720397,0.002540556,0.0001495572,0.0006206823,0.0002374911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3630232,0.0004471589,0.63552,0.0003491675,0.000229344,0.0003843709,0.00001142083,0.00001856624,0.0000167555],"genre_scores_gemma":[0.9555843,0.0002778579,0.04386014,0.00004035472,0.0001307694,0.00006001479,0.000002804938,0.00001512265,0.00002864619],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5925611,"threshold_uncertainty_score":0.9999775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04645079977028761,"score_gpt":0.3716912860643848,"score_spread":0.3252404862940972,"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."}}