{"id":"W4387216697","doi":"10.59697/jik.v4i1.351","title":"PEMANFAATAN DUA METODE CLUSTERING DAN ASSOCIATION RULE TERHADAP PRESTASI BELAJAR BERDASARKAN NILAI MATA PELAJARAN SISWA","year":2020,"lang":"en","type":"article","venue":"Jurnal Informatika Kaputama (JIK)","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":"Centroid; Cluster analysis; Association rule learning; Apriori algorithm; Computer science; Student achievement; Process (computing); k-means clustering; A priori and a posteriori; Educational data mining; Mathematics education; Data mining; Artificial intelligence; Psychology; Academic achievement","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008612038,0.0003996231,0.0004555105,0.0002012026,0.0006437378,0.00120054,0.002046178,0.0001832609,0.00004854483],"category_scores_gemma":[0.0003740881,0.0003934071,0.0001822816,0.0007541105,0.00004209906,0.003145171,0.001159912,0.0008650466,0.0004849441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002202452,"about_ca_system_score_gemma":0.0001559961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008115382,"about_ca_topic_score_gemma":0.00001776507,"domain_scores_codex":[0.9967241,0.0001425836,0.0009912848,0.0005201765,0.0009042925,0.0007176035],"domain_scores_gemma":[0.9973832,0.0002189503,0.0008155626,0.0009376124,0.0001703363,0.0004743071],"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":[0.0002037111,0.0007854622,0.03845735,0.001315267,0.001293249,0.0001387304,0.08537892,0.04456361,0.003809486,0.04533361,0.2990425,0.4796781],"study_design_scores_gemma":[0.001285046,0.0002715889,0.02020362,0.0001227508,0.00009005624,0.0001328594,0.0007217506,0.5960245,0.0006863772,0.0002894397,0.3792821,0.0008899477],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1201366,0.0001964884,0.763471,0.04012489,0.0009393199,0.001119401,0.0002219377,0.002396721,0.07139368],"genre_scores_gemma":[0.9150679,0.0000651934,0.07572711,0.006510702,0.0005429473,0.0001106278,0.0004825251,0.00007059365,0.001422451],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7949313,"threshold_uncertainty_score":0.9998518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01614067702170933,"score_gpt":0.2476258125023209,"score_spread":0.2314851354806115,"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."}}