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All Journal Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen
Riany, Agus Fajar
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Computer Science & IT Decision Sciences, Operations Research & Management

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Penerapan Data Mining untuk Klasifikasi Penyakit Stroke Menggunakan Algoritma Naïve Bayes Riany, Agus Fajar; Testiana, Gusmelia
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 13 No 1 (2023): Maret 2023
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v13i1.352

Abstract

Stroke is a disturbance of brain function, both local and general, that occurs suddenly, progressively, and rapidly due to non-traumatic brain blood circulation disorders that lasts more than 24 hours or ends in death. Stroke is also one of the deadliest diseases in Indonesia. In this study, stroke data was used to explore new information or knowledge in it. The process of extracting new information from a set of data is known as data mining. Therefore, this research aims to classify data related to stroke using the Naïve Bayes algorithm to find out whether the patient has a stroke or not. There are 10 attributes that are included in the causes of stroke, among others, gender, age, history of hypertension, history of heart disease, marital status, type of work, type of residence, glucose level, body mass index and smoking status. The results showed that classification with the Naïve Bayes algorithm can be applied in classifying stroke data resulting in an accuracy value of 92.48% in the Good Classification category.
Implementasi Support Vector Machine dalam Analisis Sentimen Ulasan Aplikasi IndiHome TV di Google Play Store Riany, Agus Fajar; Purwani, Fenny; Dwi Jaya, Irfan
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 15 No 2 (2025): September 2025
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v15i2.954

Abstract

Sentiment analysis is used to determine the responses or opinions of a group or individual regarding a topic of discussion in the context of the entire document. The Indihome TV application is currently widely used by the public, so that reviews of the Indihome TV application on the Google Play Store are very numerous. The exact number of reviews given by users is not yet known based on their sentiment class. Therefore, a method is needed to facilitate the analysis of these user reviews. The purpose of this study is to determine the polarity of sentiment towards the Indihome TV application and to determine the performance and accuracy resulting from the application of the Support Vector Machine algorithm. The method used to convert unstructured reviews into structured reviews uses the Text Mining method. The results of this study indicate that using the SVM algorithm in sentiment analysis of the Indihome TV application data produces the highest accuracy value at a ratio of 90:10 at 94%. Furthermore, from the results of data visualization, the most frequently appearing words are applications, watch, channel, open, please, good, login, indihome, complete and so on.
Co-Authors Dwi Jaya, Irfan Gusmelia Testiana