{"id":"W4403084003","doi":"10.60076/indotech.v2i2.644","title":"Pengelompokan Data Siswa Berdasarkan Profil Pelajar Pancasila Menggunakan Metode Clustering (Studi Kasus SMK Putra Anda Binjai)","year":2024,"lang":"id","type":"article","venue":"Indonesian Journal of Education And Computer Science","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 analysis; Mathematics; Psychology; Humanities; Statistics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003136776,0.00144372,0.001439218,0.002352308,0.001589746,0.00561664,0.001788599,0.001500664,0.01379228],"category_scores_gemma":[0.008979647,0.001002131,0.001572774,0.003818502,0.001051093,0.005179384,0.002675242,0.002320385,0.007993283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001788099,"about_ca_system_score_gemma":0.002580262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009241998,"about_ca_topic_score_gemma":0.0122483,"domain_scores_codex":[0.9966369,0.0005508107,0.0002546579,0.0007496155,0.001611372,0.0001967183],"domain_scores_gemma":[0.9944702,0.001827727,0.0003015144,0.0008364632,0.002334025,0.0002301305],"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":[0.0007960818,0.0002827235,0.01208223,0.001760906,0.0003558387,0.0004249513,0.002176174,0.0556351,0.04972476,0.02648178,0.02764038,0.8226391],"study_design_scores_gemma":[0.0001334695,0.0007750794,0.0395742,0.0009289393,0.000549129,0.001714195,0.005502156,0.4330036,0.1314149,0.07182502,0.3140165,0.0005628379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08976188,0.005616733,0.8421326,0.003356461,0.0007557265,0.0004865295,0.00264289,0.00603285,0.04921441],"genre_scores_gemma":[0.3652491,0.005978313,0.5498391,0.0007478128,0.0002946209,0.0007258066,0.005185286,0.002370252,0.06960958],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01379228,"threshold_uncertainty_score":0.04613978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03387993591077443,"score_gpt":0.3303383851433516,"score_spread":0.2964584492325771,"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."}}