{"id":"W4388833133","doi":"10.61805/fahma.v20i1.41","title":"ANALISIS KEPUASAN MAHASISWA TERHADAP SISTEM PEMBELAJARAN ONLINE PADA MASA PANDEMIC COVID 19 DI STMIK AKAKOM DENGAN METODE NAIVE BAYES","year":2023,"lang":"en","type":"article","venue":"Jurnal Informatika Komputer Bisnis dan Manajemen","topic":"Educational Methods and Media Use","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Likert scale; Coronavirus disease 2019 (COVID-19); Online learning; Pandemic; Distance education; Virtual learning environment; Computer science; Scale (ratio); Mathematics education; Psychology; World Wide Web; Statistics; Mathematics; Medicine; Infectious disease (medical specialty); Physics","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"],"consensus_categories":[],"category_scores_codex":[0.001758605,0.0006329431,0.0007295094,0.0009997077,0.0006406978,0.0008285485,0.002475752,0.0002281624,0.00002745895],"category_scores_gemma":[0.0002395179,0.0005570134,0.000388842,0.001884628,0.0001467669,0.002291641,0.001019957,0.000681092,0.0000750296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004189383,"about_ca_system_score_gemma":0.0006980777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001223788,"about_ca_topic_score_gemma":0.0001222996,"domain_scores_codex":[0.9949881,0.0004103049,0.001447589,0.0007448185,0.001283787,0.001125383],"domain_scores_gemma":[0.9958695,0.0008040276,0.000680727,0.001238929,0.0002737547,0.001133029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001439711,0.001045873,0.1879907,0.001605543,0.001928298,0.0006337771,0.05479575,0.01029511,0.0007784624,0.06453939,0.09919925,0.5770439],"study_design_scores_gemma":[0.00285119,0.0006227545,0.2921997,0.0003463312,0.0001975306,0.0005011297,0.008267686,0.1938124,0.0005850416,0.002826406,0.4956098,0.002179977],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5115368,0.0004348684,0.467187,0.01233064,0.003209447,0.001186206,0.0001059883,0.001660872,0.002348102],"genre_scores_gemma":[0.5701156,0.002045826,0.3936391,0.02819019,0.002415586,0.0003351015,0.001186738,0.0001736164,0.001898257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5748639,"threshold_uncertainty_score":0.9996881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0657577305497127,"score_gpt":0.3433168587134864,"score_spread":0.2775591281637737,"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."}}