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Hendri Ahmadian

Hi, I am

Dr.

Hendri Ahmadian

M.I.M

Researcher

Natural Language Processing

Hendri Ahmadian received his B.S. degree from Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala Banda Aceh in 200 from the Department of Mathematics. He obtained an M.I.M. degree from Chung Hua University, Taiwan, in 2011 from the Department of Department of Information Management.

He then received a Ph.D. degree from Universitas Syiah Kuala, in 2025 from Graduate School of Mathematics and Applied Sciences Universitas Syiah Kuala Banda Aceh (Advised by Prof Taufik Fuadi Abidin, Prof Hammam Riza and Dr. Kahlil Muchtar).

Hendri Ahmadian joined the Department of Information Technology, Universitas Islam Negeri (UIN) Ar-Raniry Banda Aceh as a Lecturer and Researcher in 2014. Furthermore, he is also an AI Research member of Data Science and Artificial Intelligence (DSAI) Lab at the Department of Informatics, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala.

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Project Contributed

February 16, 2025

Transformers-based Indonesian Language Understanding Model

This research explores improving the performance of Indonesian natural language processing (NLP) benchmarks, focusing on emotion classification, sentiment analysis, and textual entailment tasks. Utilizing the IndoBERT, a Transformer-based model tailored for the Indonesian language, the study employs a hybrid approach that combines the modified IndoBERT model — using the sum of its last four layers […]

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Researches

January 21, 2025

Transformer-based Indonesian Language Model for Emotion Classification and Sentiment Analysis

Abstract The rapid expansion of social networks has made a vast amount of user-generated data readily available for public analysis. Such data can be leveraged for various purposes, including textual analysis of comments and reviews. This study utilizes a variant of the Bidirectional Encoder Representations from Transformers (BERT) model, specifically designed for Bahasa Indonesia (IndoBERT), […]

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January 21, 2025

Hybrid Models for Emotion Classification and Sentiment Analysis in Indonesian Language

Abstract The swift growth of social networks has enabled easy access to a wealth of user-created information for public assessment. These data hold potential for various uses, including analyzing comments and reviews through text analysis. The study utilizes a specialized version of the Bidirectional Encoder Representations from Transformers (BERT) model known as IndoBERT, tailored explicitly […]

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