ACSIE (International Journal of Application Computer Science and Informatic Engineering), Volume 6 Number 1 (May 2024) presents a collection of applied research in financial information systems, machine learning, and time-series forecasting contributed by researchers from the Institut Bisnis dan Teknologi Indonesia (INSTIKI), Okayama University (Japan), Politeknik Pertanian Negeri Samarinda, Universitas Kristen Duta Wacana (UKDW) Yogyakarta, and Sekolah Tinggi Bisnis Runata. This issue highlights the integration of advanced computational techniques with real-world applications in finance, agriculture, and digital asset analysis.

The published studies include the implementation of a web-based accrual accounting information system using the variable costing method, aimed at improving financial reporting accuracy and efficiency. In the field of predictive analytics, this issue features Ethereum price forecasting using Bidirectional GRU neural networks optimized with SGD, as well as Bitcoin price prediction using LSTM networks with the Adam optimizer, and Solana price prediction using BiLSTM models, demonstrating the growing role of deep learning in cryptocurrency market analysis. Additionally, a LightGBM-based model for crop green energy score prediction is presented, integrating climate and geographic variables to support sustainable agricultural decision-making.

This issue reflects ACSIE’s commitment to publishing interdisciplinary, data-driven, and solution-oriented research that bridges computational intelligence with practical applications. By bringing together contributions from national and international institutions, this volume strengthens the journal’s role in advancing applied computer science and informatics engineering across diverse domains.