A Big Data-Based Kratom Plant Threat Forecasting Model for National Intelligence Needs
DOI:
https://doi.org/10.55927/fjas.v4i8.310Keywords:
Kratom, Big Data, Intelligence, Forecasting, National ThreatsAbstract
The abuse of the kratom plant (Mitragyna speciosa) is a growing national concern due to its links to health, online trading, and potential unconventional threats to national security. The prediction model was built using the ARIMA (1,1,1) method and validated using RMSE, MAPE, and the Ljung-Box test. The results showed that the average CKTS during 2023–2024 was at a moderate level (51.88), with significant fluctuations. The results showed that the average CKTS during 2023–2024 was at a moderate level (51.88), with significant fluctuations. The conclusions of this study emphasize the importance of strengthening predictive intelligence systems, monitoring online distribution, and establishing specific regulations for kratom as preventive measures to maintain national resilience against non-conventional threats based on psychoactive plants.
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