PENERAPAN ALGORITMA NEURAL NETWORK UNTUK KLASIFIKASI KANKER PARU

Evy Priyanti

Abstract


Neural Network Algorithm is an algorithm that is used to study the workings of the human brain which is applied to neurons connected to billions of network requirements and is able to work in many data learning processes, in this case the neural network algorithm will study the classification of lung cancer. Lung cancer is the third largest type of cancer in Indonesia. Lung cancer is divided into three classes of lung cancer pathologically. Class 1 consists of 9 observations, class 2 consists of 13 observations and class 3 consists of 10 observations. The results of lung cancer testing with this neural network algorithm produce an accuracy value of 75%, thus the neural network algorithm can be ascertained in classifying the pathology of lung cancer obtained from a survey by Stefan Aeberhard with a total sample size of 32 people and a total of 57 attributes. , one class label attribute and 56 attributes in the form of a nominal integer with a limit between 0-3 classes in the UCI Dataset.


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References


Aeberhard, S. (1991). UCI Dataset. Retrieved from https://archive.ics.uci.edu/ml/datasets/Lung+Cancer

AG Farizawani, M. P. (2019). A review of artificial neural network learning rule based on multiple variant of conjugate gradient approaches . Journal of Physics: Conference Series, 1-13.

Ananda, R. R., Ermayanti, S., & Abdiana. (2018). Hubungan Staging Kanker Paru dengan Skala Nyeri pada Pasien Kanker Paru yang Dirawat di Bagian Paru RSUP DR M Djamil Padang. Jurnal Kesehatan Andalas, 7(3). Retrieved from file:///D:/jurnal/lung cancer/kanker paru 2.pdf

Cancer, G. B. O. (2018). Estimated number of new cases in 2018. Retrieved from https://gco.iarc.fr/today/online-analysis-table?v=2018&mode=cancer&mode_population=continents&population=900&populations=900&key=asr&sex=0&cancer=39&type=0&statistic=5&prevalence=0&population_group=0&ages_group%5B%5D=0&ages_group%5B%5D=17&group_cancer=1&include_nmsc=1&include_nmsc_other=1

Elizabeth, M. (2021). Mount Elizabeth. Retrieved from https://www.mountelizabeth.com.sg/id/facilities-services/centre-excellence/cancer/lung-cancer

Fariha Ramadhaniah, Desy Khairina, Dian Triana Sinulingga, E. S., & Mulawarman, A. (2019). Gambaran Pasien Kanker Paru di Rumah Sakit Kanker Dharmais (RSKD) Tahun 2008-2012. Jurnal Respirologi Indonesia, 39, 31. Retrieved from https://jurnalrespirologi.org/index.php/jri/article/viewFile/1/23

Iqbalawaty, I., Machillah, N., Farjriah, Abdullah, A., Yani, M., Ilzana, T. M., … Khaled, T. M. (2019). Profil hasil pemeriksaan CT-Scan pada pasien tumor paru di Bagian Radiologi RSUD Dr. Zainoel Abidin periode Juli 2018-Oktober 2018. Intisari Sains Medis, 10, 625–630. Retrieved from https://isainsmedis.id/index.php/ism/article/viewFile/661/411

Nicholson, C. (n.d.). Pathmind. Retrieved from https://wiki.pathmind.com/neural-network

RapidMiner. (2020). Regularized Discriminant Analysis. Retrieved from https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/discriminant_analysis/regularized_discriminant_analysis.html#:~:text=The regularized discriminant analysis (RDA,quadratic discreminant analysis (QDA).&text=Discriminant analysis is used to determine which variables discriminate,or more naturally occurring groups.

RI, K. K. (2018). Pedoman Pengendalian Faktor Risiko Kanker Paru. Jakarta. Retrieved from http://yayasankankerindonesia.org/storage/article/59a98dea4515c2f3845fa8d9be4b5c7c.pdf

Willy, d. T. (2019, 06 21). alodokter.com. Retrieved from https://www.alodokter.com/kanker-paru-paru

Xiongwen Pang, Y. Z. (2018). An innovative neural network approach for stock market prediction. Springer Science+Business Media.




DOI: https://doi.org/10.31294/bi.v9i1.9989

DOI (PDF): https://doi.org/10.31294/bi.v9i1.9989.g4828

ISSN2338-9761 (media online), 2338-8145 (media cetak)

Dipublikasikan oleh LPPM Universitas Bina Sarana Informatika

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