{"id":"W3120572750","doi":"10.47111/jti.v15i1.1907","title":"PENGEMBANGAN WEBSITE SISTEM INFORMASI ADMINISTRASI KEPENDUDUKAN PADA KELURAHAN TUMBANG RUNGAN KOTA PALANGKA RAYA MENGGUNAKAN METODE WATERFALL","year":2021,"lang":"en","type":"article","venue":"JURNAL TEKNOLOGI INFORMASI","topic":"Information Retrieval and Data Mining","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cascades (Canada)","funders":"","keywords":"Waterfall model; Certificate; Computer science; Birth certificate; Waterfall; Population; Computer security; World Wide Web; Software; Geography; Cartography; Operating system","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00111286,0.0006752922,0.0007214267,0.0004037004,0.0007813381,0.001506084,0.002373377,0.0004214898,0.00007602874],"category_scores_gemma":[0.0003774426,0.0005663183,0.0003718621,0.001200912,0.0001476282,0.006605098,0.001572322,0.001120073,0.0004335005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002244471,"about_ca_system_score_gemma":0.0007007968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009456205,"about_ca_topic_score_gemma":0.00006162492,"domain_scores_codex":[0.9949887,0.0001359692,0.001731589,0.0005879517,0.001164114,0.001391663],"domain_scores_gemma":[0.9964178,0.0001996632,0.0007643664,0.001478846,0.0005713362,0.0005679647],"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":[0.0003434319,0.0007244963,0.01824675,0.001103148,0.001180984,0.003883492,0.02874707,0.0006770814,0.01216855,0.4087206,0.01188895,0.5123155],"study_design_scores_gemma":[0.002286098,0.000773648,0.01441768,0.000186657,0.0000689992,0.002874868,0.00272041,0.009248526,0.08243417,0.0003394347,0.8831282,0.001521341],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5925262,0.0009806423,0.05664834,0.007771583,0.006576195,0.001623455,0.0001327289,0.003601628,0.3301392],"genre_scores_gemma":[0.9630235,0.0002986926,0.02129244,0.003118041,0.0004520764,0.00005617509,0.0006773185,0.00005055195,0.01103121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8712392,"threshold_uncertainty_score":0.9996789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02039631985104475,"score_gpt":0.2424899062335298,"score_spread":0.2220935863824851,"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."}}