<![CDATA[The rapid growth of Indonesian crypto assets, such as Ethereum, has led investors and traders to need a technical analysis strategy to mitigate the risks associated with the high volatility of Ethereum (ETH) price movements. The purpose of this study is to determine how to effectively generate information for investors and traders using the Simple Moving Average (SMA) indicator to predict Ethereum price movements or trends on Indonesian crypto exchanges. Technical analysis using the SMA is crucial given the 24/7 operation of the Ethereum cryptocurrency market, which is highly responsive to global sentiment and domestic regulations from Bappepti (Indonesian Commodity Futures Trading Regulatory Agency).This study uses quantitative descriptive data analysis, using the ETH/IDR digital currency exchange rate at closing time as secondary data for the 2020-2025 period. The data used are short-term SMAs (SMA 50 and SMA 200). Testing was conducted by observing signal movements and identifying the Golden Cross, a bullish momentum indicator, and the Death Cross, a bearish indicator. The effectiveness of the data measured using the backtesting method was also measured to determine how the information from the movement was calculated using the Mean Absolute Percentage Error (MAPE).The research results show that the SMA indicator used provides more significant analytical information regarding movements for investors and traders in Indonesia. The most responsive indicator for currency market analysis in Indonesia is the SMA-50, while the SMA-200 only provides psychological support during market corrections. Legging signals were also found during periods of extreme volatility in digital currencies, where the SMA tends to produce delays in executing transactions. Therefore, this study concludes that the SMA will reach its optimal point when combined with a trading volume indicator, in this case, to validate changes or trend strength patterns. The implications for local investors and traders are that it can be used to make decisions at crucial times for investment or trading, with a more measured and informed SMA amidst the highly complex dynamics of the digital asset market]]>
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