{"id":"W4319262744","doi":"10.36080/skanika.v6i1.2982","title":"PENERAPAN METODE CLUSTERING DENGAN ALGORITMA K-MEANS PADA PENGELOMPOKAN INDEKS PRESTASI AKADEMIK MAHASISWA","year":2023,"lang":"id","type":"article","venue":"SKANIKA Sistem Komputer dan Teknik Informatika","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"Mathematics; Selection (genetic algorithm); Artificial intelligence; Computer science","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","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.00256533,0.001411569,0.001314098,0.001155412,0.001874379,0.003078805,0.005603668,0.0006790703,0.00004708399],"category_scores_gemma":[0.0001783035,0.001488929,0.0006057249,0.00333853,0.0003004575,0.003763482,0.004531779,0.002135949,0.004192312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004006644,"about_ca_system_score_gemma":0.0006245742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004516948,"about_ca_topic_score_gemma":0.0002459474,"domain_scores_codex":[0.9911612,0.0004657468,0.002496597,0.00179121,0.001672684,0.002412534],"domain_scores_gemma":[0.9927149,0.0006395573,0.001321557,0.003899744,0.0004044736,0.001019793],"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":[0.00006390349,0.0004722404,0.001587925,0.002172929,0.00110818,0.0002286507,0.05600732,0.01375909,0.0008452216,0.01015575,0.1750734,0.7385254],"study_design_scores_gemma":[0.001288187,0.0003268408,0.007881485,0.0005505361,0.0001521754,0.0002846694,0.001598393,0.5545014,0.0007756934,0.0001126062,0.4308906,0.001637428],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07123455,0.001335984,0.8296853,0.009306259,0.01006237,0.005286873,0.0009698978,0.01242141,0.05969742],"genre_scores_gemma":[0.7901796,0.0008593542,0.164465,0.003615782,0.002741651,0.001013574,0.003736904,0.0005706968,0.03281746],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7368879,"threshold_uncertainty_score":0.9998634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02388675878536045,"score_gpt":0.2667803418528745,"score_spread":0.242893583067514,"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."}}