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All Journal Jurnal Pendidikan dan Teknologi Indonesia Journal of Digital Market and Digital Currency Journal of Current Research in Blockchain
Berlilana
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering

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Pengembangan dan Evaluasi Protokol VHE-PIR Berbasis Multi-Server untuk Pengambilan Informasi yang Privat dan Skalabel Widodo, Slamet; Setyo Utomo, Fandy; Berlilana
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 9 (2025): JPTI - September 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.1026

Abstract

Penelitian ini bertujuan untuk mengembangkan protokol Private Information Retrieval (PIR) berbasis multi-server yang mengintegrasikan enkripsi homomorfik terverifikasi (Verifiable Homomorphic Encryption - VHE) untuk meningkatkan privasi, efisiensi, dan keandalan dalam pengambilan informasi dari basis data. Protokol ini dirancang untuk mengatasi keterbatasan arsitektur server tunggal, seperti risiko kegagalan sistem, beban kerja yang tinggi, dan keterbatasan skalabilitas. Metode penelitian melibatkan distribusi basis data ke beberapa server, penggunaan public key dan private key untuk enkripsi dan verifikasi hasil, serta penerapan modul akselerasi untuk mendukung pemrosesan paralel. Simulasi dilakukan pada lingkungan terdistribusi untuk mengevaluasi waktu respons, penggunaan memori, serta kemampuan failover dalam kondisi server bermasalah. Hasil penelitian menunjukkan bahwa pada skenario normal, arsitektur multi-server secara konsisten memiliki waktu respons lebih rendah dibandingkan arsitektur server tunggal, baik untuk protokol non-VHE maupun VHE-PIR. Misalnya, pada 200 pengguna, waktu respons multi-server VHE adalah 3,6070 detik dibandingkan dengan 4,2433 detik pada single server. Selain itu, dalam kondisi server bermasalah, arsitektur multi-server tetap mampu melayani permintaan dengan mendistribusikan beban ke server lain, sementara server tunggal mengalami kegagalan total. Protokol VHE-PIR menunjukkan privasi yang lebih tinggi dengan memastikan elemen yang diakses tidak dapat diketahui oleh server, meskipun memerlukan sumber daya memori dan waktu respons sedikit lebih besar dibandingkan protokol non-VHE. Implikasi dari penelitian ini mencakup kontribusi akademik dalam desain protokol PIR tahan gangguan dan kontribusi praktis terhadap sistem informasi modern yang membutuhkan skala besar, kecepatan akses, serta jaminan kerahasiaan. Penelitian ini relevan untuk implementasi nyata, dan membuka ruang eksplorasi lebih lanjut dalam penerapan teknologi PIR di lingkungan cloud publik dan sistem basis data terdistribusi.
Time Series Analysis of Bitcoin Prices Using ARIMA and LSTM for Trend Prediction Berlilana; Wahid, Arif Mu’amar
Journal of Digital Market and Digital Currency Vol. 1 No. 1 (2024): Regular Issue June 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jdmdc.v1i1.1

Abstract

This study investigates the efficacy of ARIMA and LSTM models in predicting Bitcoin prices, emphasizing the importance of accurate price prediction for trading, risk management, and investment strategies in the volatile cryptocurrency market. The objectives are to analyze Bitcoin prices to identify underlying patterns and trends, compare the predictive performance of ARIMA and LSTM models, and provide insights into their practical applications for Bitcoin price prediction. A comprehensive dataset of Bitcoin prices from January 1, 2011, to December 31, 2023, sourced from CoinMarketCap, was used. Data preprocessing included handling missing values, removing duplicates, achieving stationarity through differencing, and normalizing data using MinMaxScaler. The ARIMA model's best-fitting parameters were identified using ACF and PACF plots, and it was trained with the statsmodels library. The LSTM model involved data preparation through windowing and train-test splitting, constructing a neural network with LSTM layers, and training using TensorFlow/Keras. Evaluation metrics included Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), with comparisons based on accuracy and computational efficiency. The ARIMA model demonstrated impressive performance with an MAE of 2.308392356829177e-215 and an RMSE of 0.0, indicating a near-perfect fit to the training data. The LSTM model achieved an MAE of 0.00021804577826689423 and an RMSE of 0.00021916977109865863, showing robust performance in handling nonlinear and long-term dependencies. The ARIMA model excelled in computational efficiency with a training time of 2.548070192337036 seconds and a prediction time of 0.0009970664978027344 seconds, while the LSTM model required 378.69622468948364 seconds for training and 0.6859967708587646 seconds for prediction. The results highlight ARIMA's effectiveness in capturing linear trends and its suitability for short-term trading strategies, while LSTM is better for long-term investment strategies due to its ability to model complex patterns. Despite potential overfitting in ARIMA and high computational demands for LSTM, the study suggests exploring hybrid models, incorporating additional data sources, and developing advanced techniques to enhance predictive accuracy in future research.
Economic Decentralization through Blockchain Opportunities Challenges and New Business Models Berlilana; Mu’amar, Arif
Journal of Current Research in Blockchain Vol. 1 No. 2 (2024): Regular Issue September
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jcrb.v1i2.14

Abstract

Blockchain technology has emerged as a transformative force with the potential to decentralize economic systems and create innovative business models. This paper explores the opportunities and challenges associated with economic decentralization through blockchain, focusing on the development and sustainability of new business models such as Decentralized Finance (DeFi) platforms and Decentralized Autonomous Organizations (DAOs). The study employs a qualitative research design, incorporating a comprehensive literature review and detailed case studies of prominent blockchain-based platforms. The findings highlight the significant potential of blockchain to democratize access to financial services, enhance transparency, and reduce reliance on intermediaries. However, the study also identifies critical challenges that must be addressed for blockchain to achieve widespread adoption. These include scalability issues, regulatory uncertainty, and security vulnerabilities, all of which pose significant risks to the sustainability of blockchain-based business models. A SWOT analysis is conducted to provide a structured evaluation of these strengths, weaknesses, opportunities, and threats, offering insights into the strategic position of blockchain in various industries. The analysis reveals that while the opportunities for innovation and disruption are vast, the path to realizing these benefits is fraught with technical, legal, and operational challenges. The paper concludes that ongoing research, technological advancements, and regulatory clarity will be essential to unlocking the full potential of blockchain technology in driving economic decentralization.
Co-Authors Fandy Setyo Utomo Mu’amar, Arif Slamet Widodo Wahid, Arif Mu’amar