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All Journal Engineering, Mathematics and Computer Science Journal (EMACS)
Anderies Anderies
Bina Nusantara University
Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Industrial & Manufacturing Engineering Mathematics

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Prediction of Heart Disease UCI Dataset Using Machine Learning Algorithms Anderies Anderies; Jalaludin Ar Raniry William Tchin; Prambudi Herbowo Putro; Yudha Putra Darmawan; Alexander Agung Santoso Gunawan
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 4 No. 3 (2022): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v4i3.8683

Abstract

Heart disease is inflammation or damage to the heart and blood vessels over time. the disease can affect anyone of any age, gender, or social status. After many studies trying to overcome and learn about heart disease, in the end, this disease can be detected using machine learning systems. It predicts the likelihood of developing heart disease. The results of this system give the probability of heart disease as a percentage. Data collection using secret data mining. The data assets handled in python programming use two main algorithms for machine learning, the decision tree algorithm, and the Bayes naive algorithm which shows the best of both for heart disease accuracy. The results we get from this study show that the SVM algorithm is the algorithm with the most excellent precision. and the highest accuracy with a score of 85% in predicting heart disease using machine learning algorithms.Heart disease is inflammation or damage to the heart and blood vessels over time. the disease can affect anyone of any age, gender, or social status. After many studies trying to overcome and learn about heart disease, in the end, this disease can be detected using machine learning systems. It predicts the likelihood of developing heart disease. The results of this system give the probability of heart disease as a percentage. Data collection using secret data mining. The data assets handled in python programming use two main algorithms for machine learning, the decision tree algorithm, and the Bayes naive algorithm which shows the best of both for heart disease accuracy. The results we get from this study show that the SVM algorithm is the algorithm with the most excellent precision. and the highest accuracy with a score of 85% in predicting heart disease using machine learning algorithms.
User Experience Analysis of Duolingo Using User Experience Questionnaire Anderies Anderies; Cindy Agustina; Tania Lipiena; Ayunda Raaziqi; Alexander Agung Santoso Gunawan
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 5 No. 3 (2023): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v5i3.9227

Abstract

The internet is one of the vital means for everyone to get various information easily and exact like they’re looking for. The use of internet-based learning that is applied in modern times is very influential in the field of education compared to the past, because it can develop language skills in a country, besides that increasingly sophisticated technology can help students learn in a structured manner. One of the impacts we can see or feel is on the learning process. With the internet, it is so much easier either for the students or the teachers. One of the well-known applications in the world is Duolingo. Duolingo is one of many applications that give so much influence to language learning applications. More than 300 million people already use Duolingo for their learning. The purpose of this experiment is to analyze the User Experience of the Duolingo application. The experimental method was applied using surveys distributed via social media. There are 103 Duolingo users who were willing to take the surveys and answer all of the questions given. The result of the survey showed Novelty’s scale has the lowest mean, and Perspicuity’s scale has the highest. That means some of Duolingo’s users found that the application is less interesting. Hence, that could affect the effectiveness of the application.
Co-Authors Alexander Agung Santoso Gunawan Ayunda Raaziqi Cindy Agustina Jalaludin Ar Raniry William Tchin Prambudi Herbowo Putro Tania Lipiena Yudha Putra Darmawan