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Klasifikasi Penyakit Jantung Menggunakan Algoritma Decision Tree Series C4.5 Dengan Rapidminer I Made Agus Oka Gunawan; I Dewa Ayu Indah Saraswati; I Dewa Gede Riswana Agung; I Putu Eka Putra
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 5 No 2 (2023): April 2023
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v5i2.775

Abstract

Heart disease is still one of the leading causes of death in Indonesia and the world for both men and women of all ages. To reduce the number of deaths from heart disease, it is, therefore, necessary to conduct research to analyze data related to the causes of heart disease. In this study, the decision tree series C4.5 algorithm was used to classify heart disease data. The decision tree series C4.5 algorithm is processed in rapidminer version 9.10 tools. through the stages of Pre-processing, Set roles, modeling the decision tree series C4.5 algorithm on training data, applying the model to data testing, and testing to calculate the accuracy of the model on data testing. Testing using the confusion matrix resulted in an accuracy rate of 80.43% and a classification error of 19.57% was obtained. As well as the results of the Visualization of AUC (Area Under Curve) from the ROC curve, the value of AUC: 0.798 (Positive class): Heart Disease.
Benchmarking User Experience on Mobile Banking Applications in Indonesia: A Comparative Study Using the User Experience Questionnaire Kadek Yunita Dewi; I Dewa Ayu Indah Saraswati; Yulia Mariasmi Kiuk; Gede Rasben Dantes; Gede Indrawan; I Made Agus Oka Gunawan
Jurnal Teknologi Informasi dan Pendidikan Vol. 19 No. 1 (2026): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v19i1.1087

Abstract

Intense competition in digital banking services demands the optimization of User Experience (UX); however, the UX quality across mobile banking applications has not yet been comprehensively mapped. This study conducts a comparative analysis of mobile banking applications in Indonesia through a preliminary observation using a purposive sampling technique. The evaluation was carried out using the User Experience Questionnaire (UEQ) to measure six UX dimensions, with reliability testing confirming that the instrument was reliable. The results show all applications achieved positive scores across the six UEQ dimensions. BRImo (BRI) ranked highest overall, particularly in the efficiency (2.225) and dependability (2.188) dimensions, BNI Mobile Banking excelled in the novelty dimension, with the highest score (2.088). In addition, BNI Mobile Banking recorded higher efficiency (2.113) and dependability (1.913) scores compared to Livin’ by Mandiri and BCA Mobile. Meanwhile, BCA Mobile outperformed Livin’ by Mandiri in the perspicuity (1.988) and stimulation (1.925) dimensions, whereas Livin’ by Mandiri only surpassed BNI Mobile Banking and BCA Mobile in the attractiveness dimension (1.900). However, the results of the Kruskal–Wallis test indicate that the differences in scores among the applications were not statistically significant. Based on the global UEQ benchmark, all four applications demonstrate very good UX quality, predominantly in the excellent category. BRImo is the only application that achieved the excellent category across all dimensions, while Livin’ by Mandiri obtained two dimensions in the good category, followed by BNI Mobile Banking and BCA Mobile, each with one dimension in the good category.