from django import template from django.db.models import Sum from bengkel.models import ( ContributionFile, SpafPainPoint, AnalisisSWOT, AnalisisPESTEL, AnalisisVMOST, Analisis5C, AnalisisSOAR, SpafRootCauseAnalysis, SpafRiskAnalysis, ThemeVote, PillarVote, ThemeIdea, PillarIdea, StrategyIdea, ActionPlanIdea, AllocationIdea, SpafRootCauseValidation ) register = template.Library() @register.simple_tag def kira_skor_peserta(user, bengkel): """ Template Tag ini membaca pangkalan data dan mengira skor keseluruhan dengan mengambil kira status Plagiat dan Gred Relevansi AI. """ skor_keseluruhan = 0 if not user.is_authenticated: return 0 # --------------------------------------------------------- # 1. NODE 1 (RUJUKAN): Formula AI (Kalis Sampah & Plagiat) # --------------------------------------------------------- skor_fail_ai = 0 # Hanya kira fail TULEN (bukan ciplak) fail_tulen = ContributionFile.objects.filter( contribution__jemputan__user=user, contribution__bengkel=bengkel, is_duplicate=False ) fail_dinilai = fail_tulen.exclude(skor_novelty=0.0) for f in fail_dinilai: pengali_relevansi = (f.skor_relevansi / 10.0) if getattr(f, 'skor_relevansi', 0) else 0 mata_mentah = (f.skor_novelty * 0.5) + (f.indeks_kebolehtindakan * 0.05) skor_fail_ai += int(mata_mentah * pengali_relevansi) fail_belum_dinilai = fail_tulen.count() - fail_dinilai.count() deposit_fail = fail_belum_dinilai * 2 skor_keseluruhan += (skor_fail_ai + deposit_fail) # --------------------------------------------------------- # 2. NODE 2 (SPAF): Penilaian Dinamik AI (Kalis Sampah) # --------------------------------------------------------- skor_spaf = 0 # A. Markah dari Aduan/Pain Points (Max 10 pts per aduan) aduan_dinilai = SpafPainPoint.objects.filter(user=user, bengkel=bengkel, is_processed_by_ai=True) for a in aduan_dinilai: pengali_aduan = (a.skor_relevansi / 10.0) if getattr(a, 'skor_relevansi', 0) else 0 skor_spaf += int(10 * pengali_aduan) aduan_belum_dinilai = SpafPainPoint.objects.filter(user=user, bengkel=bengkel, is_processed_by_ai=False).count() skor_spaf += (aduan_belum_dinilai * 2) # B. Markah Dinamik dari Situational Analysis (Max 10 pts per kerangka) def kira_situasi(qs): total = 0 for obj in qs: skor_ai = getattr(obj, 'skor_relevansi', 0.0) mata = int(10 * (skor_ai / 10.0)) total += max(5, mata) if skor_ai > 0 else 5 return total skor_spaf += kira_situasi(AnalisisSWOT.objects.filter(user=user, bengkel=bengkel)) skor_spaf += kira_situasi(AnalisisPESTEL.objects.filter(user=user, bengkel=bengkel)) skor_spaf += kira_situasi(AnalisisVMOST.objects.filter(user=user, bengkel=bengkel)) skor_spaf += kira_situasi(Analisis5C.objects.filter(user=user, bengkel=bengkel)) skor_spaf += kira_situasi(AnalisisSOAR.objects.filter(user=user, bengkel=bengkel)) # C. Markah Dinamik dari RCA (Max 15 pts per RCA) rca_list = SpafRootCauseAnalysis.objects.filter(user=user, bengkel=bengkel) for rca in rca_list: skor_ai_rca = getattr(rca, 'skor_relevansi', 0.0) mata_rca = int(15 * (skor_ai_rca / 10.0)) skor_spaf += max(5, mata_rca) if skor_ai_rca > 0 else 5 # D. Markah Dinamik dari RCA Validation / RCV (Max 10 pts per semakan) rcv_list = SpafRootCauseValidation.objects.filter(user=user, bengkel=bengkel) for rcv in rcv_list: skor_ai_rcv = getattr(rcv, 'skor_relevansi', 0.0) mata_rcv = int(10 * (skor_ai_rcv / 10.0)) skor_spaf += max(3, mata_rcv) if skor_ai_rcv > 0 else 3 # E. Markah Dinamik dari Penilaian Risiko (Max 15 pts per Risiko) risk_list = SpafRiskAnalysis.objects.filter(user=user, bengkel=bengkel) for risk in risk_list: skor_ai_risk = getattr(risk, 'skor_relevansi', 0.0) mata_risk = int(15 * (skor_ai_risk / 10.0)) skor_spaf += max(5, mata_risk) if skor_ai_risk > 0 else 5 skor_keseluruhan += skor_spaf # --------------------------------------------------------- # 3. NODE 3 & 4 (UNDIAN TEMA/TERAS): 2 pts per undian # --------------------------------------------------------- jum_undi_tema = ThemeVote.objects.filter(user=user, tema__bengkel=bengkel).count() jum_undi_teras = PillarVote.objects.filter(user=user, pillar__bengkel=bengkel).count() total_undian = jum_undi_tema + jum_undi_teras skor_keseluruhan += (total_undian * 2) # --------------------------------------------------------- # 4. SUNTIKAN DNA / IDEA (SEMUA MODUL) # --------------------------------------------------------- # Markah Dinamik dari Idea Tema (Max 10 pts per idea) idea_tema_list = ThemeIdea.objects.filter(user=user, tema__bengkel=bengkel) for idea in idea_tema_list: skor_ai_idea = getattr(idea, 'skor_relevansi', 0.0) mata_idea = int(10 * (skor_ai_idea / 10.0)) skor_keseluruhan += max(3, mata_idea) if skor_ai_idea > 0 else 8 # Markah Dinamik dari Idea Teras/Pillar (Max 10 pts per idea) idea_pillar_list = PillarIdea.objects.filter(user=user, pillar__bengkel=bengkel) for idea in idea_pillar_list: skor_ai_idea_p = getattr(idea, 'skor_relevansi', 0.0) mata_idea_p = int(10 * (skor_ai_idea_p / 10.0)) skor_keseluruhan += max(3, mata_idea_p) if skor_ai_idea_p > 0 else 8 # Markah Dinamik dari Idea Strategi (Max 10 pts per idea) idea_strategi_list = StrategyIdea.objects.filter(user=user, strategi__bengkel=bengkel) for idea in idea_strategi_list: skor_ai_idea_s = getattr(idea, 'skor_relevansi', 0.0) mata_idea_s = int(10 * (skor_ai_idea_s / 10.0)) skor_keseluruhan += max(3, mata_idea_s) if skor_ai_idea_s > 0 else 8 # Markah Dinamik dari Idea Action Plan / KPI (Max 10 pts per idea) idea_action_list = ActionPlanIdea.objects.filter(user=user, action_plan__strategi__bengkel=bengkel) for idea in idea_action_list: skor_ai_idea_a = getattr(idea, 'skor_relevansi', 0.0) mata_idea_a = int(10 * (skor_ai_idea_a / 10.0)) skor_keseluruhan += max(3, mata_idea_a) if skor_ai_idea_a > 0 else 8 # Markah Dinamik & Flat dari Kalibrasi KPI (Max 5 pts / Minimum 2 pts) from bengkel.models import BlueprintIndicatorCalibration kpi_calib_list = BlueprintIndicatorCalibration.objects.filter(user=user, kpi__action_plan__strategi__bengkel=bengkel) for calib in kpi_calib_list: if calib.penilaian == 'ideal': skor_keseluruhan += 2 else: skor_ai_calib = getattr(calib, 'skor_relevansi', 0.0) mata_calib = int(5 * (skor_ai_calib / 10.0)) skor_keseluruhan += max(2, mata_calib) if skor_ai_calib > 0 else 2 # Markah Dinamik & Flat dari Idea Peruntukan (Allocation Idea) alloc_list = AllocationIdea.objects.filter(user=user, action_plan__strategi__bengkel=bengkel) for alloc in alloc_list: if '[SETUJU]' in alloc.idea_sumber: skor_keseluruhan += 2 else: skor_ai_alloc = getattr(alloc, 'skor_relevansi', 0.0) mata_alloc = int(5 * (skor_ai_alloc / 10.0)) skor_keseluruhan += max(2, mata_alloc) if skor_ai_alloc > 0 else 2 return skor_keseluruhan