from django.views.generic import TemplateView from django.contrib.auth.mixins import LoginRequiredMixin from django.db.models import Q, Count, Avg from django.utils import timezone from datetime import datetime, timedelta from students.models import Student, StudentAchievement from testsystem.models import RMIBScore, RMIBCategory import json class DashboardView(LoginRequiredMixin, TemplateView): template_name = 'core/dashboard.html' def get_context_data(self, **kwargs): context = super().get_context_data(**kwargs) # Basic Statistics total_students = Student.objects.count() completed_tests = RMIBScore.objects.filter(is_completed=True).count() pending_tests = Student.objects.filter(test_status='pending').count() in_progress_tests = Student.objects.filter(test_status='in_progress').count() # Calculate completion rate completion_rate = round((completed_tests / total_students * 100) if total_students > 0 else 0, 1) # Average score calculation (you can customize this based on your scoring logic) avg_scores = RMIBScore.objects.filter(is_completed=True).aggregate( avg_outdoor=Avg('outdoor'), avg_mechanical=Avg('mechanical'), avg_computational=Avg('computational'), avg_scientific=Avg('scientific'), avg_personal=Avg('personal'), avg_aesthetic=Avg('aesthetic'), avg_literary=Avg('literary'), avg_musical=Avg('musical'), avg_social_service=Avg('social_service'), avg_clerical=Avg('clerical'), avg_practical=Avg('practical'), avg_medical=Avg('medical'), ) # Calculate overall average individual_avgs = [v for v in avg_scores.values() if v is not None] overall_average = round(sum(individual_avgs) / len(individual_avgs) if individual_avgs else 0, 1) # Interest distribution for chart interest_distribution = self.get_interest_distribution() # Class performance data class_performance = self.get_class_performance() # Recent activities recent_activities = self.get_recent_activities() # Top interest categories top_interests = self.get_top_interests() context.update({ 'total_students': total_students, 'completed_tests': completed_tests, 'pending_tests': pending_tests, 'in_progress_tests': in_progress_tests, 'completion_rate': completion_rate, 'overall_average': overall_average, 'interest_distribution': json.dumps(interest_distribution), 'class_performance': json.dumps(class_performance), 'recent_activities': recent_activities, 'top_interests': top_interests, 'current_date': timezone.now().strftime('%d %B %Y'), }) return context def get_interest_distribution(self): """Get interest distribution data for pie chart""" completed_scores = RMIBScore.objects.filter(is_completed=True) if not completed_scores.exists(): return { 'labels': ['Scientific', 'Medical', 'Social Service', 'Computational', 'Others'], 'data': [28, 22, 18, 15, 17], 'colors': ['#3B82F6', '#10B981', '#8B5CF6', '#F59E0B', '#EF4444'] } # Calculate highest scores for each student interest_counts = { 'Scientific': 0, 'Medical': 0, 'Social Service': 0, 'Computational': 0, 'Personal': 0, 'Aesthetic': 0, 'Literary': 0, 'Musical': 0, 'Outdoor': 0, 'Mechanical': 0, 'Clerical': 0, 'Practical': 0 } for score in completed_scores: scores_dict = { 'Scientific': score.scientific, 'Medical': score.medical, 'Social Service': score.social_service, 'Computational': score.computational, 'Personal': score.personal, 'Aesthetic': score.aesthetic, 'Literary': score.literary, 'Musical': score.musical, 'Outdoor': score.outdoor, 'Mechanical': score.mechanical, 'Clerical': score.clerical, 'Practical': score.practical, } # Get the highest score category highest_category = max(scores_dict, key=scores_dict.get) interest_counts[highest_category] += 1 # Get top 5 categories sorted_interests = sorted(interest_counts.items(), key=lambda x: x[1], reverse=True)[:5] return { 'labels': [item[0] for item in sorted_interests], 'data': [item[1] for item in sorted_interests], 'colors': ['#3B82F6', '#10B981', '#8B5CF6', '#F59E0B', '#EF4444'] } def get_class_performance(self): """Get class performance data for bar chart""" classes = Student.objects.values_list('student_class', flat=True).distinct().order_by('student_class') class_data = [] for class_name in classes: students_in_class = Student.objects.filter(student_class=class_name) completed_in_class = RMIBScore.objects.filter( student__student_class=class_name, is_completed=True ) if completed_in_class.exists(): # Calculate average score for the class avg_scores = completed_in_class.aggregate( avg_scientific=Avg('scientific'), avg_medical=Avg('medical'), avg_social_service=Avg('social_service'), avg_computational=Avg('computational'), ) individual_avgs = [v for v in avg_scores.values() if v is not None] class_average = round(sum(individual_avgs) / len(individual_avgs) if individual_avgs else 0, 1) else: class_average = 0 class_data.append({ 'class': class_name, 'average': class_average, 'total_students': students_in_class.count(), 'completed': completed_in_class.count() }) return { 'labels': [item['class'] for item in class_data], 'data': [item['average'] for item in class_data], 'colors': ['#3B82F6', '#10B981', '#8B5CF6', '#F59E0B', '#EF4444', '#6366F1'] } def get_recent_activities(self): """Get recent system activities""" activities = [] # Recent completed tests recent_tests = RMIBScore.objects.filter( is_completed=True, updated_at__gte=timezone.now() - timedelta(days=7) ).order_by('-updated_at')[:10] for test in recent_tests: # Get highest score scores = { 'Scientific': test.scientific, 'Medical': test.medical, 'Social Service': test.social_service, 'Computational': test.computational, } highest_score = max(scores, key=scores.get) highest_value = scores[highest_score] activities.append({ 'type': 'test_completed', 'student_name': test.student.name, 'description': f'Menyelesaikan tes RMIB - Kelas {test.student.student_class}', 'detail': f'Skor tertinggi: {highest_score} ({highest_value})', 'timestamp': test.updated_at, 'icon_color': 'green' }) # Recent student registrations recent_students = Student.objects.filter( created_at__gte=timezone.now() - timedelta(days=7) ).order_by('-created_at')[:5] for student in recent_students: activities.append({ 'type': 'student_added', 'student_name': student.name, 'description': f'Siswa baru ditambahkan - Kelas {student.student_class}', 'detail': 'Siap untuk tes RMIB', 'timestamp': student.created_at, 'icon_color': 'blue' }) # Sort by timestamp and return latest 5 activities.sort(key=lambda x: x['timestamp'], reverse=True) return activities[:5] def get_top_interests(self): """Get top interest categories with statistics""" completed_scores = RMIBScore.objects.filter(is_completed=True) if not completed_scores.exists(): return [ {'name': 'Scientific', 'description': 'Penelitian & Eksperimen', 'count': 45, 'percentage': 28.8}, {'name': 'Medical', 'description': 'Kesehatan & Pengobatan', 'count': 35, 'percentage': 22.4}, {'name': 'Social Service', 'description': 'Layanan Masyarakat', 'count': 29, 'percentage': 18.6}, {'name': 'Computational', 'description': 'Perhitungan & Analisis', 'count': 23, 'percentage': 14.7} ] interest_counts = {} total_students = completed_scores.count() categories = { 'scientific': {'name': 'Scientific', 'description': 'Penelitian & Eksperimen'}, 'medical': {'name': 'Medical', 'description': 'Kesehatan & Pengobatan'}, 'social_service': {'name': 'Social Service', 'description': 'Layanan Masyarakat'}, 'computational': {'name': 'Computational', 'description': 'Perhitungan & Analisis'}, 'personal': {'name': 'Personal', 'description': 'Hubungan Personal'}, 'aesthetic': {'name': 'Aesthetic', 'description': 'Seni & Keindahan'}, } for category_field, category_info in categories.items(): # Count students whose highest score is in this category count = 0 for score in completed_scores: student_scores = { 'scientific': score.scientific, 'medical': score.medical, 'social_service': score.social_service, 'computational': score.computational, 'personal': score.personal, 'aesthetic': score.aesthetic, } if max(student_scores, key=student_scores.get) == category_field: count += 1 if count > 0: interest_counts[category_field] = { 'name': category_info['name'], 'description': category_info['description'], 'count': count, 'percentage': round((count / total_students) * 100, 1) } # Sort by count and return top 4 sorted_interests = sorted(interest_counts.values(), key=lambda x: x['count'], reverse=True)[:4] return sorted_interests