Implementasi Feed Forward Neural Network (FFNN) dalam Memprediksi Penyakit Diabetes


DOI: https://doi.org/10.30998/.v3i1.3048

Septian Wulandari(1*), Dian Novita(2),

(1) Universitas Indraprasta PGRI
(2) Universitas Indraprasta PGRI
(*) Corresponding Author

Abstract


Diabetes is a non-communicable disease that has the seventh highest mortality rate in the world. Diabetes causes a high frequency of thirst, frequent urination, decreased body weight and endurance, resulting in the body becoming easily weak and sick. Not infrequently, patients suffering from diabetes die at a relatively young age. This research aims to identify or predict diabetes using the Artificial Neural Network Training (ANN) method, namely Feed Forward Neural Network (FFNN). The variables used in the input values are personal data and medical records, totaling 8 independent variables and 1 dependent variable which is used as training and testing data. The data was processed using R software and the resulting error value was 0.002857, meaning less than 1%, proving that the resulting model was accurate enough as shown by the proximity of the target to the output results and the steps or number of iterations required by the system during the calculation process and 265 iterations were obtained. The Cohen's Kappa value or Kappa value in this study is 1 or 100%, meaning that there is perfect agreement between the prediction model and its accuracy value.

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References


Ahmad Setiadi. (2012). Penerapan Algoritma Multilayer Perception untuk Deteksi Dini Penyakit Diabetes. Paradigma, 14(1), 46–59. http://archive.ics.uci.edu/ml/.

Antares, J. (2020). Artificial Neural Network Dalam Mengidentifikasi Penyakit Stroke Menggunakan Metode Backpropagation (Studi Kasus di Klinik Apotik Madya Padang). In Djtechno : Journal of Information Technology Research (Vol. 1, Issue 1).

Ariesta, M., & Setiawan, I. (2022). Algoritma Neural Network Menggunakan Model Particle Swarm Optimization Untuk Prediksi Penyakit Kanker Payudara. In Jurnal Prodi Teknik Informatika UNW "Multimatrix (Issue 1).

Bhakti, H. D. (2019). Aplikasi Artificial Neural Network (ANN) untuk Memprediksi Masa Studi Mahasiswa Program Studi Teknik Informatika Universitas Muhammadiyah Gresik. Eksplora Informatika, 9(1), 88–95. https://doi.org/10.30864/eksplora.v9i1.234

Eka Mustofa, E., Purwono, J., & Keperawatan Dharma Wacana Metro, A. (2022). Penerapan Senam Kaki Terhadap Kadar Glukosa Darah Pada Pasien Diabetes Melitus Di Wilayah Kerja Puskesmas Purwosari Kec. Metro Utara Tahun 2021 Implementation Of Foot Exercise On Blood Glucose Levels In Diabetes Mellitus Patients In The Work Area Puskesmas Purwosari Kec. North Metro In 2021. Jurnal Cendikia Muda, 2(1).

Leonardus Sandy Ade Putra, Eka Kusumawardhani, Putranty Widha Nugraheni, Lalak Tarbiyatun Nasyin Maleiva, & Vincentius Abdi Gunawan. (2022). Sistem Identifikasi Dini Penyakit Stroke Dengan Menggunakan Jaringan Syaraf Tiruan Perambatan Balik. Jurnal Teknologi Informasi, 16(2), 145–157.

Maliki, M., Jember, U., Wardhana, A. Y., Jember, U., Austra, N., Putra, D., Jember, U., Hariyono, J., & Jember, U. (2021). Analisis Faktor Pemicu Penyakit Diabetes Analysis of Diabetes Trigger Factors. December.

Muhajir, M. (2023). Perbandingan Akurasi Peramalan Antara Model Neural Network Dan Regresi Berganda Comparison Of Accuracy Between Neural Network And Multiple Regression Models In Forecasting. Mathematics and Application Journal (MAP), 61–69.

Noradina, Herlina, M., Suryani Mastari, E., & Magdalena Tampubolon, C. (2022). Edukasi Kesehatan Tentang Faktor Risiko Dan Pencegahan Diabetes Di Kelurahan Labuhan Deli, Medan Marelan Tahun 2022. Jurnal Pengabdian Ilmu Kesehatan, 2(2), 38–43.

Novianti, F., Aisyah Yasmin, Y. R., & Novitasari, D. C. R. (2022). Penerapan Algoritma Fuzzy C-Means (FCM) dalam Pengelompokan Provinsi di Indonesia berdasarkan Indikator Penyakit Menular Manusia. JUMANJI (Jurnal Masyarakat Informatika Unjani), 6(1), 23. https://doi.org/10.26874/jumanji.v6i1.103

Nuraisyah, F., Srikandhia Purnama, J., Nuryanti, Y., Dika Agustin, R., Desriani, R., & Utami Putri, M. (2022). Edukasi Pengetahuan Penyakit Tidak Menular dan GERMAS Pada Usia Produktif di Dusun Karangbendo. Jurnal Panrita Abdi, Volume 6, Issue 1, 6(1), 1–7.

Pradana, D., Luthfi Alghifari, M., Farhan Juna, M., & Palaguna, D. (2022). Klasifikasi Penyakit Jantung Menggunakan Metode Artificial Neural Network. Indonesian Journal of Data and Science, 3(2), 55–60. https://doi.org/10.56705/ijodas.v3i2.35

Ramadhandi Resky Santoso, Rani Megasari, & Hambali Yudi Ahmad. (2020). Implementasi Metode Machine Learning Menggunakan Algoritma Evolving Artificial Neural Network Pada Kasus Prediksi Diagnosis Diabetes Implementation of Machine Learning Method Using Evolving Artificial Neural Network Algorithm in Prediction of Diabetes Diagnosis. Jatikom (Jurnal Aplikasi Dan Teori Ilmu Komputer), 3(2), 8597. https://ejournal.upi.edu/index.php/JATIKOM

Wahjono, E., Anggriawan, D. O., Satriawan, A. L., Firdaus, A. A., Prasetyono, E., Sudiharto, I., Tjahjono, A., & Budikarso, A. (2020). Pendeteksian Harmonisa Arus Berbasis Feed Forward Neural Network Secara Real Time. Jurnal Rekayasa Elektrika, 16(1). https://doi.org/10.17529/jre.v16i1.15093

Wulandari, S. (2020). Clustering Kecamatan Di Kota Bandung Berdasarkan Indikator Jumlah Penduduk Dengan Menggunakan Algoritma K-Means. Seminar Nasional Riset Dan Teknologi (Semnasristek), 128–132.




DOI: https://doi.org/10.30998/.v3i1.3048

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