Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Ekonomi, Manajemen dan Bisnis (EKMABIS) Journal Of Applied Multidisciplinary Studies (JAMS)
Jayaun
STIE Ganesha Jakarta
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
PEMASARAN DAN BUDI DAYA BUNGA ANGGREK DI PAMULANG TANGERANG SELATAN Jayaun Jayaun; Suhermanto Suhermanto
Jurnal Ilmiah Ekonomi, Manajemen dan Bisnis Vol. 5 No. 2 (2024): July 2024
Publisher : Sekolah Tinggi Ilmu Ekonomi Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60023/12dk4m61

Abstract

The orchid cultivation and marketing industry in South Tangerang has shown significant development within the horticultural sector. This study explores the general conditions of orchid cultivation, including environmental factors conducive to plant growth and common cultivation techniques. Additionally, the study delves into aspects of orchid marketing, covering strategies employed in marketing local orchid products and addressing challenges in both local and export markets. In the context of technology, the research highlights the role of modern technology in orchid cultivation development, from growth monitoring to harvest processing systems. Key constraints in the industry are also discussed, alongside case studies of successful farmers or companies navigating challenges and leveraging opportunities in the orchid cultivation and marketing industry. The findings aim to provide valuable insights for further development in the orchid industry in South Tangerang, serving as a foundation for sustainable policies and best practices to advance the sector
Neuromorphic Computing Model Based on Spiking Neural Network for an Efficient and Resilient Tsunami Early Warning System in Indonesia’s Small Islands Jayaun Jayaun
Journal Of Applied Multidisiplinary Studies Vol 1 No 2 (2025): May 2025
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to develop a fault-tolerant neuromorphic computing system for tsunami early detection in Indonesia’s small islands, which face significant limitations in energy and network infrastructure. The research was conducted over a three-month period (January–March 2025) using a simulated experimental approach with ocean wave data obtained from BMKG and NOAA. The system model was designed using a Spiking Neural Network (SNN) that mimics biological neuron activity to adaptively recognize ocean wave anomaly patterns. Simulation results show a detection accuracy rate of 94%, maintaining stable performance above 85% even under 25% signal interference. Furthermore, the system’s power consumption was recorded at only 0.42 watts—approximately 40–60% more efficient than conventional CNN-based models. The implications of this study include scientific contributions to the development of adaptive and energy-efficient artificial intelligence, as well as practical benefits for agencies such as BMKG and BNPB in designing autonomous and resilient tsunami early warning systems for remote and underdeveloped regions. In the future, this system has the potential to serve as a prototype for edge computing–based disaster mitigation solutions powered by artificial intelligence, particularly relevant for archipelagic nations.
Co-Authors Suhermanto Suhermanto