Diterbitkan Oleh:
Lembaga Penelitian Pengabdian Masyarakat Universitas Nusa Mandiri
Ciptaan disebarluaskan di bawah Lisensi Creative Commons Atribusi-NonKomersial 4.0 Internasional.
ANALISIS TINGKAT KEBERHASILAN CRYOTERAPY MENGGUNAKAN NEURAL NETWORK
Abstract
Human health is very important to always pay attention especially after someone has been declared suffering from an illness that can inhibit positive activities. One of the most feared diseases of the 20th century is cancer. This disease requires treatment that is quite expensive. Alternative treatments are cryotherapy or ice therapy. But cryotherapy also has side effects, it is necessary to do research on its success by taking into account certain conditions of the parameters. So the purpose of this study is to analyze the success of cryotherapy so that the dataset can be used as one of the benchmarks for the success of the cryotherapy tratment method. The method used in this study is the machine learning method of Neural Network with 500 training cycles, learning rate of 0,003 and momentum 0,9 which results in a good classification of obtaining quite high accuracy of 87,78% and AUC value of 0,955.
Downloads
References
Adil, R., Elektronika, P., & Surabaya, N. (2005). Pembuatan alat bantu pemantau kondisi tubuh dan keberadaan seseorang saat beraktifitas dengan tampilan web. 1–9.
Andini, W. C. (2018). Cryotherapy , Inovasi Baru untuk Menurunkan Berat Badan. Cryotherapy , Inovasi Baru Untuk Menurunkan Berat Badan, 1–7.
Aulia Adam. (2017). Cryotherapy , Senjata Alternatif Cry Melawan Kanker.
Badrul, M. (2013). PREDIKSI HASIL PEMILU LEGISLATIF DKI JAKARTA DENGAN METODE NEURAL NETWORK BERBASIS PARTICLE SWARM OPTIMIZATION Pendahuluan. PREDIKSI HASIL PEMILU LEGISLATIF DKI JAKARTA DENGAN METODE NEURAL NETWORK BERBASIS PARTICLE SWARM OPTIMIZATION, IX(1), 37–47.
Basarslan, M. S., & Kayaalp, F. (2018). A Hybrid Classification Example in the Diagnosis of Skin Disease with Cryotherapy and Immunotherapy Treatment. 2018 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 1–5.
Cüvitoğlu, A., & Işik, Z. (2018). Evaluation Machine-Learning Approaches for Classification of Cryotherapy and Immunotherapy Datasets. 8(4). https://doi.org/10.18178/ijmlc.2018.8.4.707
Eko Susanto, W., & Riana, D. (2016). Komparasi Algoritma. 8(3), 18–27.
Hastuti, K. (2012). Analisis komparasi algoritma klasifikasi data mining untuk prediksi mahasiswa non aktif. 2012(Semantik), 241–249.
Indriani, A., & Nbc, D. (2014). Klasifikasi Data Forum dengan menggunakan Metode Naïve Bayes Classifier. 5–10.
Khozeimeh, F., Alizadehsani, R., Roshanzamir, M., Khosravi, A., Layegh, P., & Nahavandi, S. (2017). An expert system for selecting wart treatment method. Computers in Biology and Medicine, 81(January), 167–175. https://doi.org/10.1016/j.compbiomed.2017.01.001
Rahayu, S., Nugraha, F. S., & Shidiq, M. J. (2019). Analisa tingkat keberhasilan cryoterapy menggunakan neural network. 14(2), 1–7.
Sucipto, A. (2012). CREDIT PREDICTION WITH NEURAL NETWORK ALGORITHM Ir . Adi Sucipto , M . Kom . Sains and Technology Faculty Universitas Islam Nahdlatul Ulama Jepara. (15), 978–979.
Widowati, L., & Mudahar, H. (2009). Ujiaktivitas ekstrak etanol 50% umbi keladi tikus (typhoniumflagelliforme (lood) bi) terhadap sel kanker payudara mcf-7 in vitro. XIX, 3–8.
Abstract viewed = 707 times
PDF downloaded = 1154 times
Copyright (c) 2019 Sri Rahayu, Fitra Septia Nugraha, Muhammad Ja’far Shidiq
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
An author who publishes in the Pilar Nusa Mandiri: Journal of Computing and Information System agrees to the following terms:
- Author retains the copyright and grants the journal the right of first publication of the work simultaneously licensed under the Creative Commons Attribution-NonCommercial 4.0 License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal
- Author is able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book) with the acknowledgement of its initial publication in this journal.
- Author is permitted and encouraged to post his/her work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of the published work (See The Effect of Open Access).
Read more about the Creative Commons Attribution-NonCommercial 4.0 Licence here: https://creativecommons.org/licenses/by-nc/4.0/.