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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) Computer Science and Information Technologies
Andang Wijanarko
University of Bengkulu
Computer Science & IT Engineering

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Comparative study of ensemble deep learning models to determine the classification of turtle species Ruvita Faurina; Andang Wijanarko; Aknia Faza Heryuanti; Sahrial Ihsani Ishak; Indra Agustian
Computer Science and Information Technologies Vol 4, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v4i1.p24-32

Abstract

Sea turtles are reptiles listed on the international union for conservation of nature (IUCN) red list of threatened species and the convention on international trade in endangered species of wild fauna and flora (CITES) Appendix I as species threatened with extinction. Sea turtles are nearly extinct due to natural predators and people who are frequently incorrect or even ignorant in determining which turtles should not be caught. The aim of this study was to develop a classification system to help classify sea turtle species. Therefore, the ensemble deep learning of convolutional neural network (CNN) method based on transfer learning is proposed for the classification of turtle species found in coastal communities. In this case, there are five well-known CNN models (VGG-16, ResNet-50, ResNet-152, Inception-V3, and DenseNet201). Among the five different models, the three most successful were selected for the ensemble method. The final result is obtained by combining the predictions of the CNN model with the ensemble method during the test. The evaluation result shows that the VGG16 - DenseNet201 ensemble is the best ensemble model, with accuracy, precision, recall, and F1-Score values of 0.74, 0.75, 0.74, and 0.76, respectively. This result also shows that this ensemble model outperforms the original model.
ASSESSING USER SATISFACTION AND ALTERNATIVE DESIGN RECOMMENDATION OF MOBILE BANKING APPLICATIONS Andang Wijanarko; Bagus Mirzana; Aan Erlansari; Yudi Setiawan
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 12 No. 1 (2026): JITK Issue August 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v12i1.7802

Abstract

Advances in information technology in the banking sector have led banking institutions to continuously innovate and improve their services. One such service is the emergence of mobile-based banking applications. Bank Bengkulu has introduced a mobile-based banking application, but it has received poor ratings and negative feedback from its users. This study aims to evaluate user satisfaction with the Bengkulu mobile banking application using the End User Computing Satisfaction (EUCS) method, then improve user satisfaction by redesigning the application using the Double Diamond method, and re-evaluate the results of the application redesign using the System Usability Scale (SUS) method and sentiment analysis using Natural Language Processing (NLP) with the IndoBERT model. The results show that user satisfaction with the Bengkulu mobile banking application was 2.77 when measured using the EUCS method. This measurement falls into the ‘adequate’ category but is very close to the ‘dissatisfied’ category. After the application redesign, user satisfaction improved, as indicated by the evaluation of users using the SUS method with a score of 87.975, which falls into the ‘excellent’ category. The results of qualitative user satisfaction measured using sentiment analysis methods show that there were 75 positive sentiments, 22 neutral sentiments, and only 3 negative comments. The results of the study show that there was a notable improvement in user satisfaction after the Bengkulu Bank application was redesigned.
Co-Authors Aan Erlansari Aknia Faza Heryuanti Bagus Mirzana Indra Agustian Ruvita Faurina Sahrial Ihsani Ishak Yudi Setiawan