{"id":"W3013936196","doi":"","title":"ANALISA DAN PERBANDINGAN METODE ALGORITMA APRIORI DAN FP-GROWTH UNTUK MENCARI POLA DAERAH STRATEGIS PENGENALAN KAMPUS STUDI KASUS DI STKIP ADZKIA PADANG","year":2018,"lang":"id","type":"article","venue":"","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Humanities; Computer science; Mathematics; Philosophy","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"],"consensus_categories":[],"category_scores_codex":[0.002019663,0.001128112,0.00106716,0.0004955542,0.002279698,0.002171254,0.004020843,0.000394526,0.0001801239],"category_scores_gemma":[0.0003599502,0.001048715,0.0003378682,0.002225715,0.0007416672,0.001248787,0.001695146,0.001395694,0.000612763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003491724,"about_ca_system_score_gemma":0.000723228,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00708749,"about_ca_topic_score_gemma":0.001094882,"domain_scores_codex":[0.9921205,0.0007970891,0.001223584,0.002615254,0.001414359,0.001829206],"domain_scores_gemma":[0.9939899,0.0005295377,0.0006958108,0.003076992,0.0007172066,0.0009905271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002404528,0.003952062,0.103892,0.0005645068,0.00418039,0.0004498334,0.06829102,0.0001642464,0.01929719,0.486323,0.1372397,0.1754056],"study_design_scores_gemma":[0.009817769,0.01009497,0.2738976,0.001127154,0.003271384,0.000798372,0.0283636,0.2784318,0.01872991,0.003796691,0.3607478,0.01092296],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3745037,0.002477271,0.480845,0.01085371,0.005660834,0.002620936,0.000501602,0.002828292,0.1197086],"genre_scores_gemma":[0.9624571,0.0002189467,0.02491251,0.0007222043,0.001650726,0.00006899912,0.0004124466,0.0001266905,0.009430331],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5879534,"threshold_uncertainty_score":0.9995244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0259836335049272,"score_gpt":0.2926541658426853,"score_spread":0.2666705323377581,"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."}}