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Menampilkan 1–2 dari 2 artikel
Leveraging SAMME for Improved Multi-Class Cirrhosis Diagnosis in Clinical Settings
Sulistyawati, Arum Kurnia
; Meliala, Dyan Avando
; Soejono, Ajie Wibowo
; Sari, Dini
; Hiswati, Marselina Endah
; Diqi, Mohammad
Jurnal Informatika dan Rekayasa Perangkat Lunak
Vol 7
, No 1
(2025)
This study explores the use of the SAMME algorithm to develop a predictive model for identifying various stages of cirrhosis. The dataset includes 418 records with 20 attributes, targeting the classification of cirrhosis stages: C (censored), CL (censored due to liver transplantation), and D (death). The model achieved an overall accuracy of 94%, demonstrating high precision and recall for classes C and D. However, the precision for class CL was lower, indicating a tendency to over-predict this...
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Sentiment Analysis of ChatGPT Tweets Using Transformer Algorithms
Jurnal Informatika dan Rekayasa Perangkat Lunak
Vol 5
, No 2
(2023)
This study explores the application of the Transformer model in sentiment analysis of tweets generated by ChatGPT. We used a Kaggle dataset consisting of 217,623 instances labeled as "Good", "Bad", and "Neutral". The Transformer model demonstrated high accuracy (90%) in classifying sentiments, particularly predicting "Bad" tweets. However, it showed slightly lower performance for the "Good" and "Neutral" categories, indicating areas for future research and model refinement. Our findings contribu...
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