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Analisis Perbandingan Algoritma SHA-256 dan Keccak-256 dalam Smart Contract EVM Ida Bagus Rizky Brahmantya; Gst. Ayu Vida Mastrika Giri
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 3 (2026): JNATIA Vol. 4, No. 3, Mei 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i03.p04

Abstract

The advancement of blockchain technology has increased the demand for efficient and secure hash algorithms, particularly in the development of smart contracts. This study uses smart contracts on the Ethereum network with inputs of 32, 128, and 1024 characters to evaluate SHA-256 and Keccak-256 based on execution cost, gas fees, and security. According to the results, Keccak-256 is more effective for smart contract computations because it consistently has lower execution costs for all input sizes. Both algorithms perform similarly for big inputs (1024 characters), suggesting comparable storage efficiency at scale, even if its gas charge is marginally greater than SHA-256 for tiny inputs (32 and 128 characters). Keccak-256 and SHA-256 both have strong defenses against brute-force assaults. Both provide similar security, while Keccak-256 takes a little longer to calculate. All things considered, Keccak-256 offers better efficiency, which qualifies it for widespread smart contract implementation. Further research is recommended to explore performance in more complex blockchain environments and execution gas and to optimize gasĀ  for practical implementation.
Analisis Sentimen Berbasis Aspek dengan LDA dan IndoBERT pada Ulasan Aplikasi Stockbit Dewa Made Sutha Raditya Mahattama; Gst Ayu Vida Mastrika Giri
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 3 (2026): JNATIA Vol. 4, No. 3, Mei 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i03.p09

Abstract

This study aims to analyze sentiment in user reviews of the Stockbit application using a topic modeling approach combined with IndoBERT-based sentiment classification. Aspect extraction was carried out using Latent Dirichlet Allocation (LDA), and the experimental results indicate that selecting five topics (n_components = 5) provides the most optimal representation, as evidenced by a topic coherence score of 0.6191. These five topics reflect semantic structures that are highly relevant to the content of the reviews. For the sentiment classification stage, the IndoBERT-base model achieved an accuracy of 90.86%. The best performance was observed for the positive class, with an F1-score of 93.73%, while the negative class yielded an F1-score of 83.12%. This performance gap is attributed to the imbalanced data distribution, where positive sentiments are more dominant. Nevertheless, the macro-average F1-score of 88.43% demonstrates that the model is still capable of classifying both classes in a relatively balanced manner.
Co-Authors Adi Guna, I Made Dirga Agus Harjoko Agus Muliantara Al Habib Muhammad Anak Agung Istri Ngurah Eka Karyawati Andika Putra, Ida Bagus Angriani, Husni Arianata Putra, I Gusti Bagus Sutha Dewa Made Sutha Raditya Mahattama Dhita, I Made Ryan Prana Edo Krishnanda Aditya Febrian Valentino Agape Gede Agung Aji Andar Sakti Giri, I Nyoman Yusha Tresnatama Gusto Gibeon Ginting I Gede Arta Wibawa I Gede Arta Wibawa I Gede Diva Dwijayana I Gede Diva Dwijayana I Gede Laksmana Yudha I Gede Liyang Anugrah Oktapian I Gede Made Widi Anditya I Gede Santi Astawa I Gede Surya Diva Ananda I Gede Widiantara Mega Saputra I Gusti Bagus Sutha Arianata Putra I Gusti Ngurah Anom Cahyadi Putra I Kadek Agus Wijaya Kusuma I Ketut Gede Suhartana I Ketut Gede Suhartana I Komang Ari Mogi I Komang Ari Mogi I Made Rovan Puja Wardana I Made Ryan Prana Dhita I Made Widiartha I Made Yoga Mahendra I Nyoman Budhiarta Suputra I Putu Ananta Wijaya I Putu Fajar Tapa Mahendra I Putu Rizky Pratama Putra I Wayan Gobang Edy Sucipto I WAYAN SANTIYASA I Wayan Supriana Ida Ayu Gde Suwiprabayanti Putra Ida Bagus Oka Agastya Ida Bagus Rizky Brahmantya Ivan Luis Simarmata izmy alwiah musdar Jaya, I Nyoman Wiratma Kadek Nanda Banyu Permana Komang Arsa Wiguna Leo Radhitya, Made Luh Arida Ayu Rahning Putri Luh Gede Tresna Dewi Luh Ristiario Mega Saputra, I Gede Widiantara Muhammad Arief Budiman Ngurah Agus Sanjaya ER Ni Ketut Intan Setiawati Ni Made Desni Dwi Arisaputri Ni Made Elvina Aryadhika Putri Ni Putu Novia Ardiyanti Ni Putu Suci Paramita Nyoman Hendradinata Dharma Pasha Renaisan Prasetya, Putu Rikky Mahendra Pratama Putra, I Putu Rizky Putu Audy Cipta Pratiwi Putu Krisna Udayana Radhitya, Made Leo Raharja, Made Agung Rahelita Pasaribu Siaka, Made Bayu Maha Krisna Sutanti, Putu Asri Sri Taruk, Medi Wiratama Putra, I Putu Andi Yoga, I Putu Harta