Classification of the Number of Malaria Cases in Asahan Regency Using Random Forest Application
DOI:
https://doi.org/10.30871/jaic.v9i4.9960Keywords:
Classification, Malaria, Random Forest, accuracyAbstract
This study aims to classify the number of malaria cases in Asahan Regency using the Random Forest method. This method was chosen because it is able to handle data with many and complex variables and reduce the risk of overfitting. Data were collected from the Asahan Regency Health Office. The research stages include data collection, preprocessing, model training, and model evaluation. The dataset used consists of 568 malaria case data from 25 sub-districts. The data is divided into 80% for training and 20% for testing. Of the total data, there are 109 data 19.2% in the low category, 334 data 58.8% in the medium category, and 125 data 22.0% in the high category. This classification aims to assist in mapping the level of malaria risk in the area. In this study, several variables were used for model training, including health centers, sub-districts, age, month, and gender. The results of the analysis showed that the most influential variables were health centers 47.53%, followed by sub-districts 43.77%, age 6.07%, months 2.18%, and gender 0.45%. The Random Forest model built was evaluated using accuracy, precision, recall, and F1-Score metrics. The evaluation results showed that the model was able to classify the number of malaria cases well, with an accuracy value of 0.97. With these results, Random Forest has proven effective as a classification method in malaria cases in Asahan Regency.
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[1] D. A. Rokhayati, R. C. Putri, N. A. Said, and D. S. S. Rejeki, “Analisis Faktor Risiko Malaria di Asia Tenggara,” Balaba J. Litbang Pengendali. Penyakit Bersumber Binatang Banjarnegara, vol. 18, no. 1, pp. 79–86, 2022, doi: 10.22435/blb.v18i1.5002.
[2] P. V. K. Tchuenkam et al., “Distribution of non-falciparum malaria among symptomatic malaria patients in Dschang, West Region of Cameroon,” medRxiv, p. 2025.03.24.25324523, Mar. 2025, doi: 10.1101/2025.03.24.25324523.
[3] WHO, “World malaria report 2019,” in Genewa: World Health Organization, france, 2019, p. Hal. 232.
[4] A. R. M. Nazhid and S. Wulandari, “Mengulas Eliminasi Malaria,” Bul. APBN, vol. Vol. VIII, no. No. 23, p. Hal. 2-13, 2023.
[5] KemenKesRI, Profil Kesehatan Indonesia 2018, vol. No. 1227. Jakarta: Kementrian Kesehatan Republik Indonesia, 2017. [Online]. Available: website: http://www.kemkes.go.id
[6] H. Agustina Br Ginting et al., “Analisis Faktor Risiko dan Upaya Pencegahan Malaria di Kecamatan Medan Labuhan Analysis of Risk Factors and Malaria Prevention Efforts in Medan Labuhan District,” J. Kolaboratif Sains, vol. 8, no. 3, pp. 1428–1436, 2025, doi: 10.56338/jks.v8i3.6918.
[7] Dinkes Kab.Asahan, “Profil Pemerintah Kabupaten Asahan.” Accessed: Nov. 19, 2024. [Online]. Available: https://portal.asahankab.go.id/2018/
[8] W. M. Essendi et al., “Epidemiological Risk Factors for Clinical Malaria Infection In The Highlands Of Western Kenya,” Malar. J., vol. Vol. 18, no. No.1, pp. 1–7, 2019, doi: 10.1186/s12936-019-2845-4.
[9] H. Hidayat, A. Sunyoto, and H. Al Fatta, “Klasifikasi Penyakit Jantung Menggunakan Random Forest Clasifier,” J. SisKom-KB (Sistem Komput. dan Kecerdasan Buatan), vol. Vol. 7, no. No. 1, p. Hal. 31-40, 2023, doi: 10.47970/siskom-kb.v7i1.464.
[10] D. A. Hadi and D. A. N. Sirodj, “Metode Random Forest untuk Klasifikasi Penyakit Diabetes,” Bandung Conf. Ser. Stat., vol. 3, no. 2, pp. 428–435, 2022, doi: 10.29313/bcss.v3i2.8354.
[11] R. Dewi, “EPIDEMIOLOGI PENYAKIT MALARIA DI WILAYAH KERJA PUSKESMAS LABUHAN RUKU KABUPATEN BATU-BARA TAHUN 2020 SKRIPSI Diajukan Sebagai Salah Satu Syarat,” Universitas Islam Negeri Sumatra Utara, Medan, 2021.
[12] F. Alghifari and D. Juardi, “Penerapan Data Mining Pada Penjualan Makanan Dan Minuman Menggunakan Metode Algoritma Naïve Bayes,” J. Ilm. Inform., vol. 9, no. 02, pp. 75–81, 2021, doi: 10.33884/jif.v9i02.3755.
[13] A. Agung, A. Daniswara, I. Kadek, and D. Nuryana, “Data Preprocessing Pola Pada Penilaian Mahasiswa Program Profesi Guru,” J. Informatics Comput. Sci., vol. 05, pp. 97–100, 2023, doi: 10.26740/jinacs.v4n03.
[14] G. Louppe, “Understanding random forests: From theory to practice,” arXiv Prepr. arXiv1407.7502, vol. 3, no. 2, p. 225, 2014, doi: 10.48550/arXiv.1407.7502.
[15] Syaidatussalihah and Abdurrahim, “Klasifikasi Status Kemiskinan Menggunakan Algoritma Random Forest,” J. Mat., vol. 5, no. 1, pp. 38–44, 2022, doi: 10.29303/emj.v5i1.133.
[16] M. L. Suliztia, “Penerapan Analisis Random Forest pada Prototype Sistem Prediksi Harga Kamera Bekas Menggunakan Flask,” Univ. Islam Indones., vol. Vol. 3, no. NO. 12, p. Hal. 122, 2020, doi: /dspace.uii.ac.id/123456789/23969.
[17] N. Novianti, S. P. A. Alkadri, and I. Fakhruzi, “Klasifikasi Penyakit Hipertensi Menggunakan Metode Random Forest,” Progresif J. Ilm. Komput., vol. 20, no. 1, pp. 380–392, Feb. 2024, doi: 10.35889/PROGRESIF.V20I1.1663.
[18] S. D. Amalia, M. A. Barata, and P. E. Yuwita, “Optimization of Random Forest Algorithm with Backward Elimination Method in Classification of Academic Stress Levels,” J. Appl. Informatics Comput., vol. 9, no. 3, pp. 633–641, Jun. 2025, doi: 10.30871/jaic.v9i3.9280.
[19] D. M. U. Atmaja, A. R. Hakim, A. Basri, and A. Ariyanto, “Klasifikasi Metode Persalinan pada Ibu Hamil Menggunakan Algoritma Random Forest Berbasis Mobile,” JRST (Jurnal Ris. Sains dan Teknol., vol. Vol. 7, no. No. 2, p. Hal. 161, 2023, doi: 10.30595/jrst.v7i2.16705.
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