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Yusmar Palapa Wijaya
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Journal of Electronics Technology Exploration (JOeTEx)
Published by shm publisher
ISSN : 30253470     EISSN : 30261066     DOI : https://doi.org/10.52465/joetex.v1i2
Journal of Electronics Technology Exploration (JoETEX) p-ISSSN: 3025-3470, e-ISSSN: 3026-1066 is a peer-review and open-access journal published in every six months, namely in June and December. The Journal of Electronics Technology Exploration (JoETEX), published by SHM Publisher. The Journal aims to offer a digital platform for academics and specialists to submit novel concepts and critical reviews that consider past successes and upcoming difficulties in electronics and sustainable electrical engineering. The scope of the journal comprises the state-of-the-art developments in electronics and electrical engineering related fields. The scope includes, but is not limited to the following topics: Electronic Circuits and Systems Embedded Systems Electronics Analogue Circuits Microelectronics Power Electronics Digital Electronics Medical Electronics Semiconductor Devices Electrical and Autonomous Vehicles Electronic Materials and Devices Systems and Control Engineering Cyber Security, Artificial Intelligence and Internet of Things Circuits for Communication Systems Realization of Microwave, Antenna, and Radar Systems Flexible AC Transmission Systems Modern Power Systems (Microgrids and Smart Grids) Renewable Energy and Energy Storage Systems Electric Power Sustainable Technologies Power Equipment Planning & Asset Management Energy Efficiency and Low Carbon Emission Substation Automation Systems Faults Identification and Quantification Online Condition Monitoring and Self-Healing Technologies
Articles 1 Documents
Search results for , issue "Vol. 4 No. 1 (2026): June 2026" : 1 Documents clear
Classification of Pancreatic Cancer Diagnosis with CatBoost Using Urine Biomarker Combination Tanga, Yulizchia Malica Pinkan; Utami, Putri; Darmawan, Aditya Yoga; Unjung, Jumanto
Journal of Electronics Technology Exploration Vol. 4 No. 1 (2026): June 2026
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joetex.v4i1.651

Abstract

Uncontrolled cell growth in the pancreatic gland, is one of the most aggressive types of cancer with a high mortality rate, called pancreatic cancer. This research focuses on improving early diagnosis methods for pancreatic cancer by using CatBoost. Urine biomarker datasets were collected and subjected to pre-processing, including label coding, standardized scaling, and balancing via the Synthetic Minority Oversampling Technique (SMOTE). The CatBoost model achieved an accuracy of 98.89%, specificity of 99.35%, sensitivity of 98.71%, and Area Under the Curve (AUC) of 0.9951. These results show that the CatBoost model significantly outperforms the diagnosis models in previous studies, overcoming the challenges of early detection and classification of pancreatic cancer. This study shows that CatBoost is effective for diagnosing pancreatic cancer and suggests that future research explore other models on larger and more diverse datasets.

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