{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001949893,0.001715725,0.001894567,0.002316527,0.001316457,0.003054992,0.00216239,0.001715046,0.007625651],"category_scores_gemma":[0.004401439,0.0007720058,0.001785406,0.003362765,0.0005955385,0.002930059,0.001171167,0.001649997,0.004828246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001420706,"about_ca_system_score_gemma":0.002584077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01564499,"about_ca_topic_score_gemma":0.01468343,"domain_scores_codex":[0.9978991,0.0003733713,0.0001923185,0.000602315,0.0007734331,0.0001594667],"domain_scores_gemma":[0.9976103,0.0006539228,0.0001528375,0.0002316197,0.00127237,0.00007888216],"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":[0.000469446,0.0002103063,0.004936416,0.001075264,0.0003715476,0.0001615675,0.0004846459,0.06976415,0.02331836,0.005252342,0.01226041,0.8816956],"study_design_scores_gemma":[0.00009848792,0.0004857155,0.01092651,0.000258178,0.0003555074,0.0006374532,0.001063592,0.855989,0.04765118,0.01593142,0.06631444,0.0002885212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02057547,0.002399043,0.9642501,0.0008921916,0.0004769572,0.0003316554,0.0008044196,0.003384933,0.006885206],"genre_scores_gemma":[0.2128104,0.003613007,0.7535608,0.0005412853,0.0003227539,0.0007703145,0.002524489,0.0008024102,0.02505441],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01564499,"threshold_uncertainty_score":0.03110784,"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."}}