{"id":"W4384347896","doi":"10.59697/jsik.v6i2.166","title":"PENERAPAN DATA MINING PENGELOMPOKAN PESERTA BPJS KETENAGAKERJAAN BERDASARKAN PROGRAM YANG DIAMBIL MENGGUNAKAN METODE CLUSTERING","year":2022,"lang":"en","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":"Social security; Cluster analysis; Competence (human resources); Computer science; Process (computing); Wage; Business; Data collection; Minimum wage; Artificial intelligence; Management; Economics; Statistics; 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":[0.001477423,0.001431842,0.00166319,0.003103332,0.001383621,0.002629518,0.001700179,0.0009816342,0.00880869],"category_scores_gemma":[0.003407525,0.0007030308,0.001648499,0.003648934,0.0004107626,0.002502863,0.00133891,0.001393382,0.003235906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007921756,"about_ca_system_score_gemma":0.002155492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008769272,"about_ca_topic_score_gemma":0.007506193,"domain_scores_codex":[0.998453,0.0001897979,0.0001606271,0.000547897,0.0005341913,0.0001144161],"domain_scores_gemma":[0.9984444,0.0004883205,0.0001118095,0.0001392093,0.0007453953,0.00007091719],"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":[0.0006982782,0.0006053168,0.01302634,0.001636316,0.0003059133,0.0005967242,0.0008348387,0.05435889,0.01653259,0.006066452,0.02976414,0.8755742],"study_design_scores_gemma":[0.0001758953,0.0004100977,0.02505052,0.0004393672,0.0002625604,0.001184826,0.002403609,0.7950797,0.05217001,0.01718604,0.1053621,0.00027529],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08547445,0.002995195,0.8711836,0.001701395,0.0004748734,0.0009272417,0.00792498,0.01219638,0.01712194],"genre_scores_gemma":[0.2837162,0.002934686,0.665723,0.0003331757,0.0001604999,0.001730759,0.02045842,0.001213153,0.02373014],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00880869,"threshold_uncertainty_score":0.02946806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03912985820783694,"score_gpt":0.2996038636729942,"score_spread":0.2604740054651573,"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."}}