Optimalisasi Algoritma C4.5 dalam Menganalisis Indikasi Penyebab Penyakit Feline Immunodeficiency Virus (FIV) pada Kucing
DOI:
https://doi.org/10.37034/jsisfotek.v4i4.152Keywords:
Cat, Feline Immunodeficiency Virus, Data Mining, C4.5 Algorithm, ClassificationAbstract
The health of a cat is an aspect and a major concern for someone who maintains it. Cats can be exposed to many diseases, one of which is Feline Immunodeficiency Virus. Feline Immunodeficiency Virus, also known as feline aids, is a disease that attacks the cat's immune system. This virus causes a decrease in the cat's immune system so that cats become vulnerable and susceptible to disease. This disease is difficult to detect because the symptoms are almost invisible. This study aims to explore new knowledge stored in the data list of cats suffering from FIV so that the cause of the disease can be known and how to solve it. The data used in this study were 50 data obtained from the Animal Hospital of West Sumatra with attributes of Body Weight (BB), Body Temperature (ST), Breathing (PN), Appetite (NM), Vomiting (MN), Dental Condition (KG), Feather Condition (KB), Skin Condition (KK) and yield. The data is processed using the C4.5 Algorithm method based on the symptoms experienced by the cat. After processing, the data will produce the entropy value and gain value for each symptom, then the right decision tree is made for cats with FIV disease. The results of this study are new knowledge about FIV disease in cats in the form of a decision tree from the symptoms they experience. The results show that there are 21 rules with the chosen determinant attribute, namely the Skin Condition (KK) attribute with a gain value of 0.398683. This research is useful for the community, especially those who keep cats so that they can be used as a reference in knowing the symptoms experienced by cats if there is an indication of FIV disease.
References
Amalia, N., Wulan, R., & Septiani, N. W. P. (2022). Rancangan Aplikasi Sistem Pakar Untuk Mendeteksi Penyakit Kucing Pada E-Petcare. JRKT (Jurnal Rekayasa Komputasi Terapan), 2(02). DOI: https://doi.org/10.30998/jrkt.v2i02.6726
Kiswanto, R. H., Bakti, S., & Thamrin, R. M. (2021). Rancang Bangun Sistem Pakar Diagnosa Penyakit Kucing Menggunakan Metode Backward Chaining. Jurnal Eksplora Informatika, 11(1), 67-76. DOI: https://doi.org/10.30864/eksplora.v11i1.610
Fadilah, R. (2022). Analisis Hukum terhadap praktik Sterilisasi Kucing Menurut Pendapat Mazhab Syafi'i (Studi Kasus Pet Shop Kota Padangsidimpuan) (Doctoral dissertation, Universitas Islam Negeri Sumatera Utara). DOI: http://repository.uinsu.ac.id/id/eprint/15006
Kokkinaki, K. G., Saridomichelakis, M. N., Leontides, L., Mylonakis, M. E., Konstantinidis, A. O., Steiner, J. M., ... & Xenoulis, P. G. (2021). A prospective epidemiological, clinical, and clinicopathologic study of feline leukemia virus and feline immunodeficiency virus infection in 435 cats from Greece. Comparative Immunology, Microbiology and Infectious Diseases, 78, 101687. DOI: https://doi.org/10.1016/j.cimid.2021.101687
Broughton, H., Govender, D., Serrano, E., Shikwambana, P., & Jolles, A. (2021). Equal contributions of feline immunodeficiency virus and coinfections to morbidity in African lions. International Journal for Parasitology: Parasites and Wildlife, 16, 83-94. DOI: https://doi.org/10.1016/j.ijppaw.2021.07.003
Permana, B. A. C., Djamaluddin, M., Afandi, M., & Bahtiar, H. (2022). Penerapan Sistem Pakar Untuk Diagnosa Penyakit Kucing Pada Aplikasi Berbasis Android Dengan Metode Forward Chaining. Infotek: Jurnal Informatika dan Teknologi, 5(1), 93-98. DOI : https://doi.org/10.29408/jit.v5i1.4444
Wicaksono, D. B. (2022). Strategi Peningkatan Kompetensi SDM Dalam Penggunaan Teknologi Informasi Di Dinas Pendidikan Kabupaten Gresik (Doctoral dissertation, Universitas Muhammadiyah Malang. DOI: http://eprints.umm.ac.id/id/eprint/90246
Eniyati, S. (2011). Perancangan sistem pendukung pengambilan keputusan untuk penerimaan beasiswa dengan metode SAW (Simple Additive Weighting). Dinamik, 16(2). DOI: https://doi.org/10.35315/dinamik.v16i2.364
Ilda, I., Utamajaya, J. N., & Setyaningsih, E. (2022). Evaluasi Layanan Sistem Informasi GO PPU Menggunakan Metode Pieces Framework Pada Disdukcapil Penajam. JURIKOM (Jurnal Riset Komputer), 9(2), 352-358. DOI: http://dx.doi.org/10.30865/jurikom.v9i2.4046
Solikhah, F., Febianah, M., Kamil, A. L., Arifin, W. A., & Tyas, S. J. S. (2021). Analisis Perbandingan Algoritma Naive Bayes Dan C. 45 Dalam Klasifikasi Data Mining Untuk Memprediksi Kelulusan. Tematik: Jurnal Teknologi Informasi Komunikasi (e-Journal), 8(1), 96-103. DOI: https://doi.org/10.38204/tematik.v8i1.576
Isra, M. (2022). Behavior Analysis and Prediction of Civil Services Staff in Occupational Functional Positions Using C4. 5 Algorithm. Jurnal Informasi dan Teknologi, 58-63. DOI: https://doi.org/10.37034/jidt.v4i1.186
Ucha Putri, S., Irawan, E., Rizky, F., Tunas Bangsa, S., -Indonesia Jln Sudirman Blok No, P. A., & Utara, S. (2021). Implementasi Data Mining Untuk Prediksi Penyakit Diabetes Dengan Algoritma C4.5. Januari, 2(1), 39–46. DOI: https://doi.org/10.30645/kesatria.v2i1.56.g56
Molina-Coronado, B., Mori, U., Mendiburu, A., & Miguel-Alonso, J. (2020). Survey of network intrusion detection methods from the perspective of the knowledge discovery in databases process. IEEE Transactions on Network and Service Management, 17(4), 2451-2479. DOI: https://ieeexplore.ieee.org/document/9165817
Lalo, A. K., Batarius, P., & Siki, Y. C. H. (2021). Implementasi Algoritma C4. 5 Untuk Klasifikasi Penjualan Barang di Swalayan Dutalia. Jurnal Teknik Informatika UNIKA Santo Thomas, 6, 1-12. DOI: https://doi.org/10.54367/jtiust.v6i1.1089
Mijwil, M. M., & Abttan, R. A. (2021). Utilizing the Genetic Algorithm to Pruning the C4.5 Decision Tree Algorithm. Asian Journal of Applied Sciences, 9(1), 45–52. DOI: https://doi.org/10.24203/ajas.v9i1.6503
Sahoo, S., Subudhi, A., Dash, M., & Sabut, S. (2020). Automatic Classification of Cardiac Arrhythmias Based on Hybrid Features and Decision Tree Algorithm. International Journal of Automation and Computing, 17(4), 551–561. DOI: https://doi.org/10.1007/s11633-019-1219-2
Umam, K., Puspitasari, D., & Nurhadi, A. (2020). Penerapan Algoritma C4.5 Untuk Prediksi Loyalitas Nasabah PT Erdika Elit Jakarta. Jurnal Media Informatika Budidarma, 4(1), 65. https://doi.org/10.30865/mib.v4i1.1652
Hendri, H., & Oscar, D. (2021). Penerapan Algoritma C4.5 Dalam Mengukur Kepuasan Pengunjung Terhadap Fasilitas Di Taman Margasatwa Jakarta. Jurnal Infortech, 3(1), 73–78. DOI: https://doi.org/10.31294/infortech.v3i1.10504
Sunanto, N., & Falah, G. (2022). Penerapan Algoritma C4. 5 Untuk Membuat Model Prediksi Pasien Yang Mengidap Penyakit Diabetes. Rabit: Jurnal Teknologi dan Sistem Informasi Univrab, 7(2), 208-216. DOI: https://doi.org/10.36341/rabit.v7i2.2435
Zaluchu, S. E. (2020). Strategi Penelitian Kualitatif Dan Kuantitatif Di Dalam Penelitian Agama. Evangelikal: Jurnal Teologi Injili dan Pembinaan Warga Jemaat, 4(1), 28-38. DOI: https://doi.org/10.46445/ejti.v4i1.167
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