{"id":"W4415360001","doi":"10.59934/jaiea.v5i1.1548","title":"Sentiment Analysis of Students on Campus Facilities and Infrastructure Using the Naïve 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); Sentiment analysis; Weighting; Precision and recall; Recall; The Internet","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":[0.001583541,0.0003170134,0.0006288635,0.001091371,0.000541068,0.0005257925,0.0008213262,0.0001153322,0.00001087404],"category_scores_gemma":[0.0001413248,0.0002557424,0.0001861544,0.002394281,0.0001768932,0.0002413957,0.0003873005,0.0006679646,0.00000113572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008375182,"about_ca_system_score_gemma":0.0001294221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000294923,"about_ca_topic_score_gemma":0.00003471954,"domain_scores_codex":[0.9973168,0.0001805408,0.001238499,0.000490935,0.0004972775,0.000275892],"domain_scores_gemma":[0.9973211,0.0007699235,0.0006473133,0.0007480914,0.0003729487,0.0001406143],"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":[0.00003534398,0.0006642592,0.005825115,0.0001009919,0.003018059,0.00002972389,0.01174181,0.6673328,0.001232999,0.01459672,0.00005235808,0.2953698],"study_design_scores_gemma":[0.0001064399,0.0003377029,0.005586305,0.0001323612,0.002468517,0.0002030519,0.02326123,0.9639801,0.001088191,0.001039241,0.001511745,0.0002851296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3839912,0.0003698787,0.6148691,0.0002394141,0.0001358618,0.0003342586,0.00003590862,0.00001361205,0.00001078934],"genre_scores_gemma":[0.9718217,0.0001389427,0.02779596,0.00004166497,0.00008097847,0.00003856682,0.000002623934,0.0000120959,0.00006745841],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5878305,"threshold_uncertainty_score":0.9999895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03083718718412034,"score_gpt":0.362656783589094,"score_spread":0.3318195964049737,"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."}}