Prediksi dengan model sistem pendukung keputusan merupakan cara yang tepat sasaran untuk digunakan dalam memecahkan masalah. Demam Berdarah Dengue (DBD) adalah penyakit endemik di Indonesia yang memerlukan penanganan cepat untuk mencegah komplikasi lebih lanjut. Prediksi diagnosis DBD dengan menggunakan algoritma Decision Tree C4.5 memiliki tingkat akurasi 100% dan meyakinkan. Dataset yang digunakan mencakup data medis pasien, seperti gejala klinis yaitu demam, nyeri sendi, mual, hasil laboratorium berupa trombosit, hematokrit, uji NS1, serta riwayat komorbiditas dan durasi gejala. Proses pre-processing dilakukan untuk memastikan data siap digunakan, dengan menangani data yang hilang dan menyesuaikan format data agar konsisten. Model Decision Tree C4.5 dipilih karena kemampuannya mengolah data dengan berbagai format dan hasilnya dapat dengan mudah dipahami. Model C4.5 dievaluasi menggunakan metrik akurasi, presisi, sensitivitas, dan spesifisitas. Dengan performa yang baik, model ini memiliki potensi untuk digunakan dalam sistem pendukung keputusan medis. Implementasinya di lapangan dapat membantu tenaga medis dalam mempercepat diagnosis dan memberikan penanganan yang lebih tepat waktu, yang sangat penting dalam menangani pasien DBD.

Forest and land fires are a serious problem that has a negative impact on the environment and the economy, especially in the Riau Islands region, including Bintan Regency. The background of this research is the high frequency of forest fires that cause ecosystem damage, air pollution, and significant economic losses. This study aims to analyze the forest and land fire prevention and law enforcement strategies that have been implemented and identify obstacles in their implementation. The research method used is qualitative with a case study approach. The data was collected through in-depth interviews with law enforcement officials, forestry officers, and local communities, as well as analysis of documents related to forest fires in Bintan over the past few years. In addition, questionnaires were also distributed to get a broader perspective on the effectiveness of existing strategies. The results of the study show that although there have been various prevention efforts such as routine patrols, socialization, and the installation of prohibition signs, the effectiveness is still not optimal. The main obstacles identified include limited resources, lack of community participation, difficulty in identifying perpetrators, hard-to-reach terrain, and pressure from certain parties. The lack of resources such as personnel and equipment, as well as the low level of public awareness and participation in forest fire prevention, are the main factors hindering the effectiveness of these strategies. In addition, pressure from landowners or influential parties often hinders firm and fair law enforcement. Suggestions for improving the effectiveness of prevention and enforcement strategies include increasing the budget and capacity of officers, the use of advanced technology for monitoring and investigation, and education and empowerment of local communities. In addition, there is a need for increased coordination between agencies and legal protection for officers who face pressure in carrying out their duties. With a comprehensive and inclusive approach, it is hoped that forest and land fires in Bintan can be minimized, so that a more sustainable environment and a stable economy can be realized