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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA
Hadistio, Ryan Rinaldi
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Perbandingan Algoritma Stochastic Gradient Descent dan Naïve Bayes Pada Klasifikasi Diabetic Retinopathy Hadistio, Ryan Rinaldi; Mawengkang, Herman; Zarlis, Muhammad
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 1 (2022): Januari 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i1.3426

Abstract

The purpose of this research is to compare the performance of the Stochastic Gradient Descent and Naïve Bayes algorithms in classifying Diabetic Retinopathy. Diabetic retinopathy is a complication of diabetes that causes damage to the retina of the eye. These disturbances can be detected by early detection through data extracted from eye images. This research uses source data from the UCI Machine Learning Repository, namely Diabetic Retinopathy Debrecen, totaling 1,151 data records with 19 attributes consisting of 18 attributes and 1 target attribute. The validation test uses the Cross Validation method with a total of 10 k. From the comparison of the two proposed methods, the Stochastic Gradient Descent algorithm produces an average test accuracy of 70.16%, while Naïve Bayes produces an average accuracy of 56.74%. From the comparison of the two algorithms, the Stochastic Gradient Descent algorithm is known to be superior in classifying the Diabetic Retinopathy Debrecen Dataset.
Development of Android-Based Smart System for Gingivitis Diagnosis Using Certainty Factor Hadistio, Ryan Rinaldi; Simamora, Windi Saputri; Muis, Abdul
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13361

Abstract

Gingivitis is a gum disease that causes bleeding, swelling, redness, discharge, changes in normal contours, and although health authorities take this seriously, sometimes some patients consider it normal. This study aims to educate the public about the importance of understanding the condition of their bodies, especially the most vulnerable teeth. Lack of time to consult an expert leads to this disease being neglected. Therefore, it is necessary to develop a consultation application in the form of an expert system. The built system adopts the deterministic factor method. The certainty factor works by reading the entire data submitted by the expert and giving the result as a percentage of confidence that the patient has gingivitis. The experts used in this system are dental experts. Data obtained from direct experts and consultations resulted in new knowledge in the form of the percentage of trust patients suffering from gingivitis. The data collected are symptoms and solutions obtained from experts. This research provides a new service for patients suffering from gingivitis without the need to see a specialist directly. Based on the testing data provided to the patient and based on the patient's condition at that time, the test results of the system reached a confidence level of 98.74%. So that the results of consultation are obtained in the form of information about the disease and the solutions needed.
Co-Authors Abdul Muis Herman Mawengkang Muhammad Zarlis, Muhammad Simamora, Windi Saputri