{"id":"W2990789842","doi":"10.30865/komik.v3i1.1628","title":"SISTEM PENDUKUNG KEPUTUSAN DALAM MENENTUKAN HAKIM TERBAIK PADA PENGADILAN AGAMA KELAS 1A MEDAN MENERAPKAN METODE ANALYTICAL HIERARCY PROCESS (AHP) DAN PROMETHEE II","year":2019,"lang":"en","type":"article","venue":"KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer)","topic":"Legal Studies and Policies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Analytic hierarchy process; Economic Justice; Law; Law enforcement; Ranking (information retrieval); Operations research; Business; Sociology; Computer science; Political science; Mathematics; Artificial intelligence","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":[0.001777638,0.0006065808,0.0007847238,0.0009390102,0.001684255,0.005414642,0.0007997699,0.000872026,0.01313677],"category_scores_gemma":[0.002320019,0.0003282687,0.0005038098,0.001381367,0.0007289387,0.002237412,0.001988614,0.001200673,0.003671902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008449958,"about_ca_system_score_gemma":0.002389608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001550019,"about_ca_topic_score_gemma":0.0023244,"domain_scores_codex":[0.9988217,0.0002869338,0.0001470543,0.000227029,0.0004059048,0.0001114285],"domain_scores_gemma":[0.9988613,0.0004468219,0.0001120481,0.00006937131,0.0004479835,0.00006250809],"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":[0.0009311634,0.0006149395,0.01129843,0.003448817,0.0002121207,0.001823754,0.005843471,0.01514923,0.04614368,0.04502777,0.01961792,0.8498886],"study_design_scores_gemma":[0.0002851758,0.001553907,0.03122269,0.001843112,0.0006215807,0.002834051,0.02383278,0.1309151,0.07562253,0.08437426,0.6464642,0.0004306718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3440406,0.01803655,0.4535155,0.006333769,0.002257427,0.001797755,0.002234397,0.00275593,0.1690281],"genre_scores_gemma":[0.7335753,0.008799586,0.1800828,0.0005803857,0.0003322127,0.0006539039,0.002286896,0.0002551558,0.07343371],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01313677,"threshold_uncertainty_score":0.04394686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02819281284558881,"score_gpt":0.3027264692443437,"score_spread":0.2745336563987548,"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."}}