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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI IJID (International Journal on Informatics for Development) Aplikasia: Jurnal Aplikasi Ilmu-Ilmu Agama Jurnal Linguistik Komputasional Progresif: Jurnal Ilmiah Komputer JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Profesi Insinyur Universitas Lampung Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Kecerdasan Buatan dan Teknologi Informasi INTECH - Informatika Dan Teknologi
Ahmad Subhan Yazid
Universitas Alma Ata
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Social Sciences Other

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PREDICTION OF HYPERTENSION COMORBIDITIES USING THE RANDOM FOREST ALGORITHM (CASE STUDY AT PUSKESMAS KASIHAN 2) Luqman Luqman; Ahmad Subhan Yazid; Dita Danianti; Dhina Puspasari Wijaya
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 2 (2026): May 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i2.493

Abstract

Hypertension is a chronic non-communicable disease often accompanied by comorbidities, which can increase complication risks and reduce patients' quality of life. Currently, the identification of comorbidities in hypertension patients is frequently conducted manually, making it time-consuming and highly dependent on healthcare workers' thoroughness. This study aims to develop a predictive model for hypertension comorbidities using a machine learning-based Random Forest algorithm, designed as an early screening tool for the general population. The research method follows the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework, encompassing business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Clinical data were collected from medical records, focusing on predicting eight primary comorbidities using a multi-label classification approach. Data preprocessing involved data cleaning, transformation, splitting into training and testing sets, and handling class imbalances. The Random Forest model was trained and evaluated using subset accuracy and hamming loss metrics. The results demonstrate that the Random Forest algorithm successfully predicts hypertension comorbidities with a subset accuracy of 0.3361 and a hamming loss of 0.1502, indicating robust performance for multi-label prediction. The model was successfully deployed into a Streamlit-based web application, enabling healthcare professionals to obtain direct prediction results. This system is expected to assist in the early screening and monitoring of hypertension patients.
Co-Authors Adawiyyah, Andi Rabiatul Agung Fatwanto Agung Fatwanto Agung Fatwanto, Agung Agung Nur Hidayat Akhmad Imam Fahrizal Andri Pramuntadi Anita Sofiyati Antoni, Fajria Arif Setiawan Ariyani Kusuma Dewi, Ariyani Kusuma Asdistia, Sindy Asyhab, Naufal Aulia Faqih Rifa’i Ayami, Zaenita Sayidatil Bambang Sugiantoro Dadang Heksaputra Dhina Puspasari Wijaya Dhina Puspasari Wijaya, Dhina Puspasari Dita Danianti Edi Winarko Eko Setiawan Eko Setiawan Eko Setiawan Fahrizal Surya Panuntun Gutama, Deden Hardan Gutama, Deden Hardan Hadromi, Aang Hari Surrisyad Ida Ayu Putu Sri Widnyani Ixnu Subextyo Jailani, Moh. Juansa, Andra Kharisma, Razendra Bintang Khurin 'ien Mukhoyyaroh Laili Alfi Rohmah Luqman Luqman M Didik Rohmad Wahyudi M Mustakim Maria Ulfah Siregar Moh. Jailani Muhammad Taufiq Nuruzzaman Mukhoyyaroh, Khurin 'ien Musyafa, Muhammad Akid Naufal Asyhab Nisaa Ratna Marliana Nur ‘Azah Nuramadanti, Izati Nurlany, Wa Ode Paryati Paryati PIPIT FEBRIANA DEWI Pramuntadi, Andri Prasetyawan, Daru Pratama, Bayuaji Wahyu Pratami, Jauharoh Puguh Jayadi Puji Winar Cahyo Ragil Satria Wicaksana Ramadhani, Aisyah Razendra Bintang Kharisma rifa'i, m._rafly Riski Nurhadi Rochmadi, Tri Rosalia Susilowati Sayekti Abriani Shofwatul ‘Uyun Siti Aisah Solikin, Mokhamad son, Sumarsono Sugiarno, Bayu Supriyati, Hikmah Tri Rochmadi Wibowo, Leni Tri Wijaya, Dhina Pusapasari Yanuar Wicaksono Yanuar Wicaksono Yanuar Wicaksono Yudistira Yudistira Yusnita, Shella