{"id":"W4384573781","doi":"10.59697/jsik.v6i2.191","title":"Pemamfaatan Metode Clustering Pada Nasabah Peminjaman Modal (Studi Kasus: PT. Faderal International Finance Binjai)","year":2022,"lang":"id","type":"article","venue":"Jurnal Sistem Informasi Kaputama (JSIK)","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":"Humanities; Mathematics; Art","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":[0.002426713,0.0007496264,0.0005957434,0.00202974,0.001227842,0.004631846,0.0008779198,0.0009336402,0.06268561],"category_scores_gemma":[0.004840949,0.0005091499,0.0005348501,0.004456833,0.0004763617,0.002429825,0.00182143,0.001528281,0.02353543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002410465,"about_ca_system_score_gemma":0.002697171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01989466,"about_ca_topic_score_gemma":0.02456512,"domain_scores_codex":[0.9987057,0.0002848237,0.00006670525,0.000328014,0.0004848246,0.00013],"domain_scores_gemma":[0.9982421,0.000560625,0.0001349965,0.0001987327,0.0006985241,0.0001650074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003341646,0.0002150515,0.01647202,0.0005386402,0.00008135284,0.0001563108,0.001269202,0.006758321,0.003520013,0.01450317,0.3226155,0.6335362],"study_design_scores_gemma":[0.00006717058,0.0002766452,0.06878664,0.0006991173,0.0001031799,0.0005520016,0.004458919,0.03462308,0.01031862,0.01572511,0.8642585,0.0001310927],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.178241,0.03987384,0.1441806,0.05501812,0.004441152,0.0014529,0.02998467,0.008343102,0.5384645],"genre_scores_gemma":[0.3669948,0.01657345,0.07849745,0.001930406,0.0008689663,0.0007157683,0.01715,0.002233315,0.5150359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06268561,"threshold_uncertainty_score":0.2097043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01556088417083635,"score_gpt":0.2604049958346533,"score_spread":0.2448441116638169,"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."}}