This study aims to analyze the potential for drought disasters in Nunukan Regency, North Kalimantan, as well as mitigation efforts that can be taken to reduce their negative impacts. Based on disaster mitigation theory, this study adopts two main approaches, Disaster Risk Reduction (DRR) and Disaster Risk Management (DRM), which lead to the prevention and mitigation of drought impacts. The research method used is qualitative descriptive with secondary data analysis from various related sources. The results showed that Nunukan Regency faces a serious threat of drought, with more than 1.3 million hectares of land at risk and 48,411 hectares at high risk. Structural mitigation, such as the construction of reservoirs and retention basins, as well as non-structural mitigation, such as community education and training, have proven effective in reducing the impact of drought. Further discussion shows that mitigation efforts must involve collaboration between government agencies, the private sector, and the community to increase the capacity of the region to deal with increasingly erratic climate change. In conclusion, a comprehensive, data-driven mitigation strategy can increase the Nunukan Regency's resilience to future drought disasters.Penelitian ini bertujuan untuk menganalisis potensi bencana kekeringan di Kabupaten Nunukan, Kalimantan Utara, serta upaya mitigasi yang dapat dilakukan untuk mengurangi dampak negatifnya. Berdasarkan teori mitigasi bencana, penelitian ini mengadopsi dua pendekatan utama, yaitu Pengurangan Risiko Bencana (PRB) dan Manajemen Risiko Bencana (DRM), yang mengarah pada pencegahan dan penanggulangan dampak kekeringan. Metode penelitian yang digunakan adalah deskriptif kualitatif dengan analisis data sekunder dari berbagai sumber terkait. Hasil penelitian menunjukkan bahwa Kabupaten Nunukan menghadapi ancaman kekeringan yang serius dengan lebih dari 1,3 juta hektar lahan terancam, dan 48.411 hektar di antaranya memiliki risiko tinggi. Mitigasi struktural, seperti pembangunan waduk dan embung, serta mitigasi non-struktural, seperti edukasi dan pelatihan masyarakat, terbukti efektif dalam mengurangi dampak kekeringan. Pembahasan lebih lanjut menunjukkan bahwa upaya mitigasi harus melibatkan kolaborasi antar instansi pemerintah, sektor swasta, dan masyarakat untuk meningkatkan kapasitas daerah dalam menghadapi perubahan iklim yang semakin tidak menentu. Kesimpulannya, strategi mitigasi yang komprehensif dan berbasis data dapat meningkatkan ketahanan Kabupaten Nunukan terhadap bencana kekeringan di masa depan.

Data mining helps provide precise and careful decisions. Student graduation on time is one of the assessment points in the higher education accreditation process. However, student graduation cannot always be detected quickly, which can reduce the assessment of a university in the accreditation process. This problem arises to find out whether students will be able to graduate on time or not Classification method for predicting student graduates using the Naïve Bayes algorithm. Whether a student graduates on time or not, it is hoped that the results will provide information and input for the university in making future policies. From the results of this test, it was found that by applying the Naïve Bayes algorithm the system can predict student graduation in a timely manner. After comparing several literatures, it can be concluded that this method can be used for this prediction with an accuracy rate of 90%. This literature review is important as a supporting factor for research.