{"id":"W4387786091","doi":"10.46880/methoda.vol13no2.pp189-194","title":"PENERAPAN ALGORITMA C4.5 DALAM MENGUKUR TINGKAT KEPUASAN NASABAH PADA PT BANK MUAMALAT INDONESIA KCU MEDAN BARU BERBASIS WEB","year":2023,"lang":"en","type":"article","venue":"Majalah Ilmiah METHODA","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":"Business; Sharia; Service (business); Product (mathematics); Service quality; Quality (philosophy); Customer satisfaction; Database; Business administration; Marketing; Computer science; Islam; Mathematics","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":[0.0008429556,0.00159278,0.001039098,0.001172934,0.0007691423,0.002733606,0.001909756,0.001144216,0.04542216],"category_scores_gemma":[0.002128002,0.0004403869,0.0009171815,0.001191026,0.0003075372,0.001379399,0.000920682,0.001388993,0.01777424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007264873,"about_ca_system_score_gemma":0.001468178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006535623,"about_ca_topic_score_gemma":0.005033422,"domain_scores_codex":[0.9993317,0.00009229093,0.00009030257,0.0001685771,0.0001959987,0.0001211481],"domain_scores_gemma":[0.9994854,0.0001597048,0.00002984479,0.00007049023,0.0002203426,0.00003431087],"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":[0.001154251,0.0002585755,0.0008211314,0.0003747719,0.0001164231,0.000247578,0.0001117411,0.01644801,0.01148959,0.003394921,0.04086675,0.9247162],"study_design_scores_gemma":[0.0005773559,0.0006638914,0.003313661,0.0001871816,0.0001960569,0.001219816,0.0002947132,0.6949295,0.08418781,0.009628895,0.2046321,0.0001689936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02367225,0.003169777,0.8756378,0.0008063764,0.001179528,0.0006810462,0.002094989,0.06427042,0.02848785],"genre_scores_gemma":[0.1523341,0.001967976,0.7897807,0.0008890973,0.0002181886,0.001384002,0.005186645,0.002764647,0.0454746],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04542216,"threshold_uncertainty_score":0.1519523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0276948109373371,"score_gpt":0.3107616878791741,"score_spread":0.283066876941837,"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."}}