Pembaharuan Sistem Penentuan Untuk Klasifikasi Jenis Penyakit pada RSUD Sekayu Menggunakan Pendekatan Extreme Programming
DOI:
https://doi.org/10.30865/mib.v5i1.2273Keywords:
Classification, K-Nearest Neighbor, Extreme ProgrammingAbstract
This research is done to create a system or software that can classify a type of disease suffered by the patient, by conducting anamnese technique, this technique is done in the early stages of the patient before the treatment of doctors, the examination is done by questioning the patient about the condition and complaints that the patient feels to know the health condition of the patient. The Anamnese stage is performed by the nurse station before the patient is directed to the doctor where it corresponds to the results of the Anamnese. In the implementation of this stage is important for nurse station to direct the patient according to the patient's health condition with the Doctor who will handle the patient. But some diseases have similarities or similar symptoms but with different types of diseases, in the HOSPITAL Sekayu in Nurse station does not have a special system to classify the types of diseases of the patient this is what is the background of this research is made. The benefit is that the system can classify the types of diseases of patients according to the condition of the patient, helping nurse station to direct the patient to a classification of diseases suffered, as a storage media of the patient's medical record. The research was made to adopt the algorithm of K-Nearest Neighbor and the Extreme programming approach as a system development method.
References
R. Amalia dan N. Huda, “mplementasi Sistem Informasi Pelayanan Kesehatan Pada Klinik Smart Medica,†SISFOKOM, vol. 9, no. 3, hal. 332–338, 2020.
M. Amaliyah;, H. Tanuwijaya;, dan T. Wurijanto, “Rancang Bangun Sistem Informasi Administrasi Layanan Pasien Berbasis Web Pada Klinik Paradise Surabaya,†jsika, vol. 6, no. 3, 2016.
Y. Ervinaeni;, A. S. Hidayat;, dan E. Riana, “Sistem Pakar Diagnosa Gangguan Hiperaktif Pada Anak Dengan Metode Naive Bayes Berbasis Web,†J. Media Inform. Budi Darma, vol. 3, no. 2, 2019.
M. Sadli;, F. Fajriana;, W. Fuadi, E. Ermatita;, dan I. Pahendra;, “Penerapan Model K-Nearest Neighbors Dalam Klasifikasi Kebutuhan Daya Listrik Untuk Masing-Masing Daerah Di Kota Lhokseumawe,†J. ecotipe, vol. 5, no. 2, 2018.
N. Aini;, Ramadiani;, dan H. R. Hatta, “Sistem Pakar Pendiagnosa Penyakit Tuberkulosis,†J. Inform. Mulawarman, vol. 12, no. 1, 2017.
P. D. Dyan;, F. Perdana;, dan M. T. S. Rizal;, “Klasifikasi Penyakit Kulit Pada Manusia Menggunakan Metode Binary Decision Tree Support Vector Machine (BDTSVM) (Studi Kasus: Puskesmas Dinoyo Kota Malang),†J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 2, no. 5, 2018.
P. D. Nugraha, S. Al Faraby, dan Adiwijaya;, “Klasifikasi Dokumen Menggunakan Metode k-Nearest Neighbor (kNN) dengan Information Gain,†in e-Proceeding of Engineering, 2018.
N. Hadari, Penelitian Terapan. Yogyakarta: Gajah Mada University Press, 2005.
R. H. D. Satriya, E. Santoso, dan Sutrisno, “Implementasi Metode Ensemble K-Nearest Neighbor untuk Prediksi Nilai Tukar Rupiah Terhadap Dollar Amerika,†J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 2, no. 4, 2018.
N. K. Wahyudin, “Rancang Bangun Sistem Akademik Berbasis Web Menggunakan Metode Extreme Programming,†in Seminar Nasional dan Inovasi (SNIT), 2018.
T. S. Jaya, “Pengujian Aplikasi dengan Metode Blackbox Testing Boundary Value Analysis (Studi Kasus: Kantor Digital Politeknik Negeri Lampung),†J. Pengemb. IT, vol. 3, no. 2, 2018.
N. Huda, “Sistem Informasi Wisata Sumatera Selatan Berbasis Mobile,†J. Tek. Inform. Politek. Sekayu, vol. 7, no. 2, hal. 51–56, 2017.
R. Amalia dan N. Huda, “Sistem Informasi Pengarsipan Surat Masuk dan Surat Keluar Pada Dinas Tenaga Kerja dan Transmigrasi Kabupaten Musi Banyuasin,†Media Inform. Budi Darma, vol. 4, no. 2, hal. 363–368, 2020.
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