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All Journal MABIS: Manajemen dan Bisnis PREDATECS: Public Research Journal of Engineering, Data Technology and Computer Science
Ihza, Nurul
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Social Sciences

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Implementation of C4.5 and Support Vector Machine (SVM) Algorithm for Classification of Coronary Heart Disease Anugrah, Muhammad Ridho; Al-Qadr, Nola Ardelia; Nazira, Nanda; Ihza, Nurul
Public Research Journal of Engineering, Data Technology and Computer Science Vol. 1 No. 1: PREDATECS July 2023
Publisher : Institute of Research and Publication Indonesia (IRPI).

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/predatecs.v1i1.805

Abstract

Coronary Heart Disease (CHD) is a chronic disease that is not contagious and can cause heart attacks. This makes CHD one of the diseases that cause the highest mortality globally. CHD can be caused by the main factor, namely an unhealthy lifestyle, so that in an effort to identify and deal with CHD, many studies have been conducted, one of which is the use of information technology. With so many CHD patient data, data mining can be used using. classification methods include C4.5 algorithm and Support Vector Machine (NBC). The C4.5 algorithm is a decision tree-like algorithm that groups attribute values into classes so that it resembles a tree, while SVM is an algorithm that separates data with a hyperplane. This study aims to classify the CHD dataset by comparing the C4.5 and SVM algorithms. So that the best accuracy value for this data is produced, namely the SVM algorithm of 64.51% and followed by the C4.5 algorithm of 64.30%.
The role of mobile shopping in customer brand identification to increase repurchase intention Putra, Edy Yulianto; Ihza, Nurul; Aliandrina, Dessy
Manajemen dan Bisnis Vol 25, No 1 (2026): March 2026
Publisher : Department of Management - Faculty of Business and Economics. Universitas Surabaya.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24123/mabis.v25i1.1008

Abstract

This study aims to analyze the influence of mobile shopping, brand experience, and shopping enjoyment on customer brand identification and repurchase intention in local fashion brands. It is proposed to address a gap where prior research overlooks these factors' interplay for Indonesian brands, focusing instead on international contexts or price/promotions. A total of 312 respondents from Batam City participated in this study. Quantitative and associative approach design is applied in this study, in order to measure the quantity of data with relevant statistical procedures, especially with the SEM-PLS. The results of the study indicate that the use of mobile shopping is not significant to boost customer brand identification. On the contrary, positive consumer experience with the brand and shopping pleasure have been shown to influence customer brand identification. Strong brand identification significantly increases repurchase intention. This research is expected to provide a new contribution to the literature on consumer behavior in the fashion industry, particularly in the context of mobile shopping. This research provides practical guidance for marketers and local fashion brands in designing effective marketing strategies, especially in improving a pleasant shopping experience, creating a positive brand experience, and utilizing the mobile shopping potential to increase purchasing interest.
Co-Authors Al-Qadr, Nola Ardelia Aliandrina, Dessy Anugrah, Muhammad Ridho Nazira, Nanda Putra, Edy Yulianto