Artificial Synapse has been an emerging research field as emulating the functions of biological synapse. It is regarded as a basic building block for neuromorphic computing. Organic lead-based perovskites including CH₃NH₃PbI₃ and CH₃NH₃PbBr₃ have been researched as materials for synaptic devices based on Resistive Random Access Memory(RRAM). They have shown gradual increase and decrease of conductivity that represent the synaptic plasticity such as STP (Short Term Potentiation), LTP (Long Term Potentiation), and LTD (Long Term Depression) which imitate learning and forgetting in human brain. However, there have been some environmental concerns about using lead-based materials in large-scale applications because of the possibility of lead contamination. Also, it is still required to increase perovskites’ air-stability. All-inorganic halide perovskites are considered as promising alternatives for RRAM and synaptic devices because of their remarkable stability. Therefore, this study focused on fully inorganic CsPb_(1-x)Bi_xI₃ perovskite to achieve lower lead content and better stability. Optimized bismuth content was discovered according to their morphology, grain size, and synaptic performances. CsPb_(1-x)Bi_xI₃ emulates synapse by showing similar functions such as STP and LTP by different current change rate depending on the intensities and frequencies of pulses. Also, STD and LTD can be obtained by applying opposite pulses. Therefore, based on these synaptic functions that optimized CsPb_(1-x)Bi_xI₃ achieves_, it can be applied as a single synapse with low energy consumption for neuromorphic computing which works by parallel operation to connect and store information.