DIAGNOSTIK PENYAKIT GINJAL KRONIS MENGGUNAKAN MODEL KLASIFIKASI SUPPORT VECTOR MACHINE

Penulis

  • Taryadi Taryadi STMIK Widya Pratama
  • Era Yunianto STMIK Widya Pratama
  • Kasmari Kasmari Universitas Stikubank Semarang

DOI:

https://doi.org/10.47775/ictech.v19i1.291

Kata Kunci:

Penyakit Ginjal; diagnosa; decision support system; support vector machine;klasifikasi;

Abstrak

Penyakit ginjal atau biasa dikenal dengan gagal ginjal merupakan suatu kondisi menurunnya fungsi ginjal yang dapat mengakibatkan ketidakmampuan ginjal dalam menjalankan tugasnya. Penderita penyakit ginjal berpotensi masuk ke fase kronis. Penyakit ginjal kronik merupakan penurunan fungsi ginjal secara bertahap selama tiga bulan yang mengakibatkan terhentinya fungsi ginjal secara total. Tujuan dari pengembangan ini adalah suatu sistem pendukung keputusan bagi dokter dalam mendiagnosis pasien penyakit ginjal. Sistem menampilkan hasil prediksi apakah pasien penyakit ginjal sudah memasuki fase penyakit ginjal kronis atau belum. Metodologi penelitian ini terdiri dari dua tahap utama: pemodelan klasifikasi dan pengembangan sistem. Pemodelan klasifikasi terdiri dari pengumpulan data, persiapan data, pengelompokan data, klasifikasi, ekstraksi aturan. Pengembangan sistem didasarkan pada aturan yang diekstraksi sebelumnya. Penelitian ini menghasilkan suatu sistem yang dapat mendeteksi suatu kondisi penyakit ginjal kronis berdasarkan beberapa faktor dengan akurasi sebesar 96,34%.

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Unduhan

Diterbitkan

2024-04-30

Cara Mengutip

Taryadi, T., Yunianto, E., & Kasmari, K. (2024). DIAGNOSTIK PENYAKIT GINJAL KRONIS MENGGUNAKAN MODEL KLASIFIKASI SUPPORT VECTOR MACHINE. IC-Tech, 19(1), 39–44. https://doi.org/10.47775/ictech.v19i1.291