{"id":"W2779556253","doi":"10.26798/jiko.2016.v1i1.10","title":"PENERAPAN NAÃVE BAYES UNTUK PREDIKSI KELAYAKAN KREDIT","year":2016,"lang":"id","type":"article","venue":"JIKO (Jurnal Informatika dan Komputer)","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Agricultural science; Environmental 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":[0.004964763,0.00156334,0.00130883,0.002646678,0.001196787,0.005451803,0.001763705,0.001601849,0.01169391],"category_scores_gemma":[0.02588432,0.0009013939,0.001589513,0.00196511,0.001232474,0.005328535,0.001430902,0.003252685,0.004416235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002285397,"about_ca_system_score_gemma":0.002745664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01547158,"about_ca_topic_score_gemma":0.02090403,"domain_scores_codex":[0.997261,0.0006207249,0.0002164848,0.0009422608,0.0007622911,0.0001971797],"domain_scores_gemma":[0.9890905,0.007899174,0.0004943047,0.0008774981,0.001459118,0.0001793907],"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":[0.000845233,0.0002626192,0.07374278,0.001025436,0.0006932718,0.0008205618,0.001423466,0.07293902,0.005136949,0.07071128,0.01675373,0.7556456],"study_design_scores_gemma":[0.0001284569,0.0004295816,0.04782672,0.001540064,0.0008853225,0.001778631,0.002253839,0.5289721,0.01023824,0.3255105,0.08006321,0.0003732508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1539931,0.01376302,0.7651796,0.009715849,0.001406293,0.0004814184,0.005361381,0.002433553,0.04766575],"genre_scores_gemma":[0.747234,0.006303596,0.1995932,0.001252007,0.0007652827,0.000396386,0.004168497,0.0004284344,0.03985861],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01547158,"threshold_uncertainty_score":0.03912008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01193546187938579,"score_gpt":0.2459626361589483,"score_spread":0.2340271742795625,"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."}}