{"id":"W7115071877","doi":"10.46576/device.v6i2.7277","title":"PENGCLUSTERAN JENIS USAHA UKM BERDASARKAN PROGRAM BANTUAN DI KOTA BINJAI MENGGUNAKAN ALGORITMA K-MEANS","year":2025,"lang":"","type":"article","venue":"DEVICE JOURNAL OF INFORMATION SYSTEM COMPUTER SCIENCE AND INFORMATION TECHNOLOGY","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":"Cluster (spacecraft); Research Object; Cluster development","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":[0.001654363,0.001841506,0.001433224,0.001337605,0.001445643,0.003257768,0.00184523,0.001147116,0.02224846],"category_scores_gemma":[0.00465439,0.0008798204,0.001661282,0.001762841,0.0007327537,0.002870323,0.002114535,0.002382823,0.01283832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001694876,"about_ca_system_score_gemma":0.003680923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01815948,"about_ca_topic_score_gemma":0.02360715,"domain_scores_codex":[0.9986398,0.0002129925,0.000104485,0.0004556933,0.0004374432,0.0001495434],"domain_scores_gemma":[0.9980636,0.0005064105,0.0001205192,0.0003175547,0.0008570674,0.0001348149],"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":[0.001302891,0.0004559924,0.01279008,0.001472383,0.0003617701,0.0002711722,0.001452307,0.09471861,0.03875392,0.01321675,0.05972824,0.775476],"study_design_scores_gemma":[0.0002325982,0.0005823145,0.02044395,0.0004028967,0.0004029009,0.0003409376,0.002131779,0.6239179,0.08181603,0.02198357,0.2474361,0.0003090042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07636998,0.002140574,0.8362142,0.002520808,0.000935165,0.0006663501,0.005154945,0.03145478,0.04454318],"genre_scores_gemma":[0.3029086,0.002178335,0.5991427,0.0008172222,0.0002550756,0.00134134,0.01048499,0.005739183,0.07713254],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02224846,"threshold_uncertainty_score":0.0744285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006302317644186224,"score_gpt":0.2580249890898697,"score_spread":0.2517226714456835,"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."}}