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Journal : Brilliance: Research of Artificial Intelligence

Family Hope Program Recipient Determination System Using The Naive Bayes Method Irsyada, Rahmat; Cahyani, Nita; Mu’afa , M Rif’an Fawajul; Perdana , Chepy; Febriyanto, Erick
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.6362

Abstract

Poverty is still a problem that Indonesian people continue to face. To achieve prosperity and social justice for all Indonesian citizens, poverty can be considered a situation where a person does not have the ability to fulfill their basic needs, such as food, shelter, clothing, has a low income, has limited access to education, and has work skills. which is inadequate. The government, as a policy maker, has made various efforts to reduce poverty, one of which is through the Family Hope Program (PKH). However, in its implementation, the distribution of PKH assistance still faces problems in terms of targeting accuracy. To overcome this problem, a system is needed that can provide recommendations about who is worthy of receiving PKH assistance. One approach that can be used is a decision support system (DSS) using the Naïve Bayes method. Naïve Bayes is an algorithm used for text classification and is a Machine Learning method that focuses on calculating probability and statistics to predict future probabilities based on past experience. With the help of SPK, this system is able to provide recommendations about who should receive assistance. PKH is based on criteria such as school children, toddlers, pregnant women, the elderly and people with disabilities. Test results using the Naïve Bayes method with Confusion Matrix calculations show an accuracy level of 75%. Next, a comparison was carried out with testing using Cross Validation, which showed an increase in accuracy compared to previous testing without using 10-fold Cross Validation.
Integrated Community-Based Disaster Response Information System: A Case Study of the Subang Regency BPBD Iqbal, Mohammad; Febriyanto, Erick; Irsyada, Rahmat
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6985

Abstract

Subang Regency is an area highly prone to natural disasters such as floods, landslides, and strong winds. In emergency situations, the absence of an efficient and integrated reporting system greatly hinders Badan Penanggulangan Bencana Daerah (BPBD) in carrying out rapid responses, evacuations, and aid distribution. If not addressed promptly, public safety and the effectiveness of disaster management will remain at risk. Therefore, a disaster mitigation application system is needed that allows the community to quickly report disasters through photos, videos, and descriptions directly integrated with the BPBD dashboard. This application is equipped with multi-channel notifications via WhatsApp, SMS Gateway, and alarms, as well as an AI-based heatmap analytics system to predict potential disasters using historical data and weather information from BMKG. In addition, BPBD administrators can verify disaster reports by checking personal biodata linked to the reporter’s account. The system development method applied is Agile Development, which includes observation, planning, design, development, testing, and deployment, enabling intensive collaboration and rapid system iterations based on field feedback. With this system, BPBD Subang is expected to be more responsive and resilient in facing disasters.
Co-Authors Aa Mustopa Adam Faturahman Afitri, Afni Agung Ahmad Sururi Ainul Mutakin Alpian Sah, Rizki Andini, Nadila Anita Bawaiqki Wandanaya Arsi Yulianjani Bachri, Egi Wijatriana budiarty, frizca Citra Yulian Kristanti Danang Suprayogi Danang Suprayogi Dandy Saputra Devi Iswara Difa Amrullah Egi Wijatriana Bachri Euis Sitinur Aisyah Fajar nur iman Fauziyyah Husna Nurdiayanah Lestari Fauziyyah Husna Nurdiayanah Lestari ferdiansyah winardi Fernanda Setyobudi Armansyah Fikrah Syafa’ah Fina andhara khumaida Firman Ramadhan Fitria Supyaningsih Gigih Sulistianto Handayani, Indri Hani Dewi Ariessanti hartanto hartanto Ilham Ramadhan Indri Handayani Indri Handayani Indri Handayani Indri Handayani Indri Handayani, Indri Indriyani Astuti Ningsih Iqbal Fikri Irsyada, Rahmat Iskandar, Nur Ita Sari Perbina Manik Ivan Bagus Widodo Jenny Januarini Jethro, Andrew Karmelia Karmelia khumaida, Fina andhara Kristanti, Citra Yulian Kusumah, Hendra Lidya Wijayanti M Farhan Al Fakhriza Mildan, Abd Rachman Mohammad Iqbal Much Alvin Aldiya Muhammad Fadli Purnama muhammad Shofwatullah mulyati mul Mu’afa , M Rif’an Fawajul Nadya Cahyaningsih Nanda Dian Prasetyo Naufal, Romzi Syauqi Nejwa Ayuni Nida Hanifah niko alnabawi Ninda Lutfian Ninda Lutfiani Nita Cahyani Nurbaiti, Resti Padeli Padeli Perdana , Chepy Po Abas Sunarya Pradana, Restu Adi Qurotul Aini Rafika, Ageng Setiani Rahayu, Nina Rahmat Hidayat Rais, Nurlaila Suci Rahayu Reyhan Archy Rizkisyah Safriyati, Evi Saputra, Rendy Angga Solichin, Kevin Rama Putra Suhendra, Yoke Sulistiawati Sulistiawati Suprayogi, Danang Syafaah, Fikrah Taufan Abdurrachman Triyono Triyono Untung Rahardja Utomo, Anggit Panji Pangestu Wahyu Hidayat Yoga Ulil Albaab Yudanto, Teguh Arya Yuli Ana Yulianto Yulianto Yulianto Yulianto Zebua, Vivid Kristiani Alfad Zulfa, Sima Hasina