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All Journal Journal of Soft Computing Exploration Journal of Student Research Exploration
Fadhilah, Muhammad Syafiq
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Classification of risk of death from heart disease or cigarette influence using the k-nearest neighbors (KNN) method Fadhilah, Muhammad Syafiq; Muzayanah, Rini
Journal of Student Research Exploration Vol. 2 No. 2: July 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/josre.v2i2.359

Abstract

Heart disease is one of the leading causes of death in Indonesia. In addition to coronary heart disease, smoking is the leading contributor to the death rate in Indonesia. This study aims to analyze the risk of death with the main variables of heart disease history and smoking history. This study classifies the risk of death of heart disease sufferers and smokers using the KNearest Neighbors (KNN) algorithm. The results showed that the KNN model had an accuracy of 52.38% in predicting the risk of death of smokers and heart disease patients. Confusion matrix analysis revealed that the model performed well in predicting classes 0 and 2, but had difficulty in predicting class 1. This study shows that KNN can be used to predict the risk of death of smokers and patients with heart disease with a satisfactory success rate.
Optimizing the implementation of the BFS and DFS algorithms using the web crawler method on the kumparan site Mustaqim, Amirul; Dinova, Dony Benaya; Fadhilah, Muhammad Syafiq; Seivany, Ravenia; Prasetiyo, Budi; Muslim, Much Aziz
Journal of Soft Computing Exploration Vol. 5 No. 2 (2024): June 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i2.309

Abstract

Efficient access to timely information is critical in today's digital era. Web crawlers, automated programs that navigate the Internet, play an important role in collecting data from websites such as Kumparan, a leading news site in Indonesia. This research shows the effectiveness of the Breadth-First Search (BFS) and Depth-First Search (DFS) algorithms in indexing Kumparan content. The results of the research show that BFS consistently indexes more files comprehensively but with longer execution times compared to DFS, which provides faster initial results but with fewer files. For example, at depth 4 BFS indexed 949 files in 886.94 seconds, while DFS indexed 470 files in 233.02 seconds. These findings highlight the balance between precision and speed when selecting a crawling algorithm tailored to the needs of a particular website. This research provides insights into optimizing web crawler technology for complex websites such as Coil and suggests avenues for further research to improve permission efficiency and adaptability across a variety of crawling scenarios.
Co-Authors Budi Prasetiyo, Budi Dinova, Dony Benaya Much Aziz Muslim Mustaqim, Amirul Muzayanah, Rini Seivany, Ravenia