Aspect-based sentiment analysis is a method in natural language processing aimed at identifying and understanding sentiments related to specific aspects of an entity. Aspects are words or phrases that represent an aspect or attribute of a particular entity. Previous research has utilized generative pre-trained language models to perform aspect-based sentiment analysis. LEGO-ABSA is one framework that has successfully employed generative pre-trained language models in aspect-based sentiment analysis, particularly in English. LEGO-ABSA uses a multitask learning and prompting approach to enhance model performance. However, the application of this approach has not been done in the context of Bahasa Indonesia. Therefore, this research aims to implement the multitask learning and prompting approach in aspect-based sentiment analysis for Bahasa Indonesia using generative pre-trained language models. In this study, the Indo LEGO-ABSA model is developed, which is an aspect-based sentiment analysis model utilizing generative pre-trained language models and trained with multitask learning and prompting. Indo LEGO-ABSA is trained with a hotel domain dataset in the Indonesian language. The obtained results include an f1-score of 79.55% for the Aspect Sentiment Triplet Extraction task, 86.09% for Unified Aspect-based Sentiment Analysis, 79.85% for Aspect Opinion Pair Extraction, 87.45% for Aspect Term Extraction, and 88.09% for Opinion Term Extraction. Indo LEGO-ABSA adopts the LEGO-ABSA framework that employs the T5 model, specifically mT5, by applying multitask learning to train all tasks within aspect-based sentiment analysis.

翻译：方面级情感分析是自然语言处理中的一种方法，旨在识别和理解与实体特定方面相关的情感。方面是代表某个实体特定特征或属性的词或短语。以往研究已利用生成式预训练语言模型进行方面级情感分析。LEGO-ABSA是一个成功将生成式预训练语言模型应用于方面级情感分析的框架，尤其在英语领域表现突出。该框架采用多任务学习和提示方法以提升模型性能。然而，该方法尚未在印尼语语境中应用。因此，本研究旨在利用生成式预训练语言模型，将多任务学习和提示方法引入印尼语的方面级情感分析中。研究中开发了Indo LEGO-ABSA模型，该模型基于生成式预训练语言模型，并通过多任务学习和提示方法进行训练。Indo LEGO-ABSA使用印尼语酒店领域数据集进行训练，取得了以下结果：方面情感三元组抽取任务的F1得分为79.55%，统一方面级情感分析为86.09%，方面意见对抽取为79.85%，方面词抽取为87.45%，意见词抽取为88.09%。Indo LEGO-ABSA采用了LEGO-ABSA框架，该框架基于T5模型（具体为mT5），通过多任务学习对方面级情感分析中的所有任务进行联合训练。