{"id":"W4286436713","doi":"10.18280/isi.270317","title":"Student Performance Prediction in Sebelas Maret University Based on the Random Forest Algorithm","year":2022,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Random forest; Support vector machine; Feature selection; Decision tree; Computer science; Machine learning; Data pre-processing; Artificial intelligence; Preprocessor; Statistical classification; Feature (linguistics); Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009243593,0.00009370226,0.00008827355,0.0002368702,0.0007859842,0.0001573978,0.0006824258,0.0000250802,0.00003549005],"category_scores_gemma":[0.00004937978,0.00008268457,0.00003209384,0.0006801996,0.00004252365,0.001364671,0.0002305952,0.0002684715,0.00005170151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003604378,"about_ca_system_score_gemma":0.00007506002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007554624,"about_ca_topic_score_gemma":0.000006208086,"domain_scores_codex":[0.9989651,0.0001681559,0.0002244103,0.0001310812,0.0003432247,0.0001680457],"domain_scores_gemma":[0.9992192,0.0001464764,0.0001551271,0.0003968514,0.00005084703,0.00003153861],"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":[0.0001018406,0.0001614414,0.03599397,0.00005568498,0.00002320296,0.000004843372,0.01289587,0.5377764,0.000005472774,0.02064707,0.005094424,0.3872398],"study_design_scores_gemma":[0.0007159997,0.0001403935,0.07128498,0.00002195591,0.000003659017,0.000007606267,0.0008938598,0.9045227,0.000007495185,0.0001516894,0.02216307,0.00008665774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2184986,0.000007291379,0.7674803,0.0006415246,0.0002819114,0.0005423058,0.00009164984,0.0002451778,0.01221129],"genre_scores_gemma":[0.9957067,0.000004286213,0.003546299,0.0002921605,0.00001447504,0.00008610482,0.0001730929,0.000003616502,0.0001732067],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7772082,"threshold_uncertainty_score":0.6045234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00804468182461166,"score_gpt":0.204745272260683,"score_spread":0.1967005904360714,"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."}}