Penggunaan Machine Learning Di Bidang Kesehatan

Telaumbanua, Fangatulo Dodo; Hulu, Peringatan; Nadeak, Togar Zulfiter; Lumbantong, Rikky Romeo; Dharma, Abdi

doi:10.34012/jutikomp.v2i2.657

Cited by 12 publications

(12 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Perkembangan teknologi terus meningkat khususnya dibidang kesehatan [9]. Salah satu teknologi dalam dunia kesehatan diantaranya adalah pemanfaatan machine learning pada berbagai aplikasi keperawatan dan medis namun tidak terbatas pada resiko kardiovaskular dan identifikasi penyakit jantung [10].…”

Section: Pendahuluanunclassified

Pemanfaatan Teknologi Machine Learning pada Klasifikasi Jenis Hipertensi Berdasarkan Fitur Pribadi

2022

View full text Add to dashboard Cite

Hipertensi tampaknya menjadi faktor utama dalam perkembangan penyakit seperti stroke, gagal jantung, infark miokard, fibrilasi atrium, penyakit arteri perifer, dan diseksi aorta. Prediksi dini jenis hipertensi dari riwayat kesehatan merupakan hal yang penting agar kita dapat mengetahui penyakit yang disebabkan olehnya. Prediksi ini dapat diperoleh dengan memanfaatkan teknologi machine learning untuk menemukan pengetahuan baru dari data dasar sehingga menemukan pola yang valid, berguna, dan mudah dipelajari. Model klasifikasi random forest diusulkan dalam penelitian ini. Kontribusi kami dalam penelitian ini adalah membuat model klasifikasi random forest dengan teknik baru yaitu perbaikan data untuk melakukan tuning hyperparameter. Kami melihat peneliti sebelumnya hanya mengejar nilai akurasi yang tinggi semata. Berbeda dengan penelitian sebelumnya, kami menggunakan teknik optimasi hyperparameter gridsearch cv pada model klasifikasi random forest. Parameter terbaik untuk model random forest yaitu max_depth = 80, max_features = 3, min_samples_leaf = 3, min_samples_split = 8, dan n_estimators = 1000 yang direkomendasikan dari teknik gridsearch cv. Akurasi sebelum optimasi adalah 72,3%, sedangkan setelah optimasi adalah 86,1%. Hal ini menunjukkan peningkatan akurasi sebesar 13,7% setelah menerapkan metode grid search cv pada klasifikasi jenis hipertensi menggunakan model random forest

show abstract

Section: Pendahuluanunclassified

Pemanfaatan Teknologi Machine Learning pada Klasifikasi Jenis Hipertensi Berdasarkan Fitur Pribadi

2022

View full text Add to dashboard Cite

show abstract

“…Machine learning is machine learning that is very helpful in solving problems, making it easy to do things. In the hospital or health sector, machine learning makes it easy to do something, for example, doctors can diagnose heart disease in a fast time without taking a long time [18]. Machine learning (ML) is employed to train machines how to more efficiently handle data.…”

Section: Machine Learningmentioning

confidence: 99%

Implementation of Decision Tree Algorithm Machine Learning in Detecting Covid-19 Virus Patients Using Public Datasets

Nadiah

Soim

Sholihin

2022

IJAIDM

View full text Add to dashboard Cite

The advancement of AI (Artificial Intelligence) technology has been widely implemented in numerous sectors of daily life. Machine Learning is one of the subfields of Artificial Intelligence. Using statistics, mathematics, and data mining, machine learning is developed so that machines may learn by assessing data without being reprogrammed. At this time the world is on alert for the spread of a popular virus, the corona virus. Coronaviruses are part of a family of viruses caused by diseases ranging from the flu. The disease caused by the coronavirus is known as Covid-19. Therefore, to help identify whether a somebody has coronavirus disease based on certain symptoms, a model is created that can classify people with the covid-19 virus using machine learning. The classification methods utilized in this study are decision trees and large-scale machine learning projects. The study employed Python 3.7 as its programming language and PyCharm as its Integrated Development Environment (IDE). Based on the results, the accuracy rate as expected after conducting various trials is 99%.

show abstract

“…Machine Learning (ML) is one technology that can be utilized. ML makes the work in classifying diseases in the health field easy such as, knowing the type of disease and providing results in the form of more optimal images (Telaumbanua, Hulu, Nadeak, Lumbantong, & Dharma, 2019). One of the methods that can be used in ML for classification is K-Nearest Neighbor (KNN) (Yuliati & Sihombing, 2021).…”

Section: Introductionmentioning

confidence: 99%

Comparison of Drug Type Classification Performance Using KNN Algorithm

Aldi

Nozomi

Soeheri³

2022

SinkrOn

View full text Add to dashboard Cite

The error of decommissioning is a serious problem that is often faced in medicine. In the face of these problems, information technology has a very important role. One of the information technologies that can be used is to use the machine learning classification algorithm K-Nearest Neighbor KNN. KNN is a type of machine learning algorithm that can be applied to problems with classification and regression prediction. The classification of types of drugs for patients greatly affects the health of the patient. The patient data is processed and transformed to numbers, which are then divided into training data and test data from 90:10, 80:20, 70:30 and using the Cross Validation model. KNN works through the nearest neighboring value with a value of k = 3 calculated by the calculation of Euclidean Distance, and then evaluated using the Confusion Matrix. The performance of the KNN algorithm resulted in the highest Accuracy value of 98.33%, a Precision value of 98.8%, a Recall value of 96.2%, and an F-measure value of 97.48%. The performance is obtained from the sharing of training data and 90:10 test data. The data share results in high performance compared to other data shares, including using the Cross Validation model. And the lower the k value, the higher the value of the resulting performance. The results show that the performance of the KNN algorithm is working well.

show abstract

Penggunaan Machine Learning Di Bidang Kesehatan

Cited by 12 publications

References 0 publications

Pemanfaatan Teknologi Machine Learning pada Klasifikasi Jenis Hipertensi Berdasarkan Fitur Pribadi

Pemanfaatan Teknologi Machine Learning pada Klasifikasi Jenis Hipertensi Berdasarkan Fitur Pribadi

Implementation of Decision Tree Algorithm Machine Learning in Detecting Covid-19 Virus Patients Using Public Datasets

Comparison of Drug Type Classification Performance Using KNN Algorithm

Contact Info

Product

Resources

About