PREDIKSI TREN PUBLIKASI BLOCKCHAIN DAN KRIPTOGRAFI DI INDONESIA MENGGUNAKAN BIBLIOMETRIK DAN LSTM

Authors

  • Fathimah Azzahro Hasni Rifayanti Universitas Esa Unggul
  • Rahmat Budiarsa Universitas Esa Unggul

DOI:

https://doi.org/10.36080/skanika.v9i2.3843

Keywords:

Blockchain, Cryptography, Bibliometric, LSTM, Trend Prediction

Abstract

The rapid adoption of digital technologies in Indonesia has driven increasing research on Blockchain and Cryptography, yet comprehensive mapping and projections of their development remain limited. This study aims to analyze the intellectual landscape and predict publication trends in these two technologies in Indonesia using a quantitative approach integrating bibliometric analysis and Machine Learning. Data were obtained from Dimensions.ai for the 2020–2024 period, yielding 2,193 relevant documents after data cleansing. Network analysis using VOSviewer reveals a shift in Blockchain research from financial assets toward practical applications, particularly Supply Chain management and system efficiency. Meanwhile, Cryptography research shows polarization between the development of classical algorithms and applications for IoT security. A Long Short-Term Memory (LSTM) model was then developed to predict publication trends for 2025–2029 based on annual data from 2020–2024. The model achieved a Mean Absolute Percentage Error (MAPE) below 5% on the test data; however, the limited number of data points should be considered when interpreting this accuracy. LSTM projects a flattening publication trend through 2029, with Cryptography expected to surpass Blockchain by approximately 55 documents. These findings indicate that security and trust may become increasingly critical priorities compared with Blockchain infrastructure development.

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Published

2026-07-31

How to Cite

[1]
Fathimah Azzahro Hasni Rifayanti and R. Budiarsa, “PREDIKSI TREN PUBLIKASI BLOCKCHAIN DAN KRIPTOGRAFI DI INDONESIA MENGGUNAKAN BIBLIOMETRIK DAN LSTM”, SKANIKA, vol. 9, no. 2, pp. 284–295, Jul. 2026.