COVID-19 is a current global pandemic, which has prompted many countries to develop ways to deal with it. Peptides have many medicinal and diagnostic benefits, so recently, many researchers have been developing peptide-based vaccines against COVID-19. In peptide-based vaccines, peptides act as specific antigens that will provide a faster immune response because they do not go through the process of cutting proteins in the Major Histocompatibility complex (MHC) antigen-presenting cells (APC) and can be directly presented outside the cells so that they can be recognized by the host killer T cells (CTL). Vaccine development can be accelerated with the help of immunoinformatic to predict specific epitopes to induce the CTL. We have predicted the CTL epitope through the immunoinformatic method. This study aims to synthesize candidate CTL epitopes as a candidate for the SARS-CoV-2 vaccine using the SPPS method with the Fmoc/t-Bu strategy. In this study, two CTL epitopes were synthesized through a conventional solid-phase peptide synthesis (SPPS) method, and another CTL epitope was synthesized using a semi-automated peptide synthesizer. The SPPS method is faster because the purification is only carried out at the final stage, while the Fmoc/t-Bu strategy was applied because it provides a mild reaction condition. Both synthetic approaches were compared. The semi-automated peptide synthesizer made the synthesis faster and more efficient due to the use of an inert gas (N2) during the synthesis. The synthetic peptides were characterized by TOF-ESI-MS. The three peptides showed ion peaks at m/z 1137.5509 (M+H)+, 1064.3468 (M+H)+, and 916.5859 (M+H)+, indicating correct molecular ion peaks for EILDITPCSF, IPIGAGICASY, and FIAGLIAIV, respectively.