Kedai Kopi Abah is one of the SMEs that has good business development potensial in Blitar City because it has a strategic location in the middle of the busy center of Blitar City. However, there are challenge that must be faced by Kedai Kopi Abah namely that the use of social media as a digital marketing platform is still not optimal. This Community Service Program was conducted using training and socialization methods aimed directly at managers of Kedai Kopi Abah. This training and socialization activity takes the form of optimizing rebranding and strengthening digital marketing communications at Kedai Kopi Abah with the aim of improving the skills of Kedai Kopi Abah managers in producing interesting content on Instagram account. This training activity can attract a positive response from participants who attended the training and socialization on optimizing rebranding and strengthening digital marketing communication at Kedai Kopi Abah.

Karang Taruna is one of the community organizations focused on social affairs in society. Bendo Village, Blitar City, is one of the areas with potential for developing young community potential. Bendo Village already has a youth community called Karang Taruna. However, Karang Taruna in Bendo Village faces challenges that can hinder its development. One such challenge is the lack of ability to conduct organizational marketing or Personal branding through social media. To address this, videography-based Personal branding training was conducted with the aim of providing new understanding and skills to Karang Taruna in Bendo Village. The implementation method in this community service consists of preparation, briefing, training implementation, and monitoring evaluation. The Personal branding training conducted received a positive response from Karang Taruna members. With this positive response, it is hoped that in future activities, Karang Taruna in Bendo Village can further develop and improve their ability to conduct videography-based Personal branding on social media.

Character education has become the primary focus in efforts to develop individuals with strong moral values and ethics. In the context of modern education, character education goes beyond teaching discipline or enforcing rules; it strengthens the core of good personality and fosters positive behaviors in daily life. This paper reviews character education from various perspectives, including the conceptual understanding, implementation approaches in educational institutions, and its impact on shaping a better future generation. By integrating values such as integrity, empathy, honesty, and responsibility, character education plays a crucial role in shaping individuals who are not only academically competent but also ethically sound and capable of making positive contributions to society. Through a profound understanding of these values, educational institutions can play a crucial role in laying a solid moral foundation for future generations.

This research explores the classification of brass instrument sounds using Convolutional Neural Network (CNN) combined with Mel-Frequency Cepstrum Coefficient (MFCC) feature extraction. This research aims to improve the accuracy of brass instrument sound recognition by utilizing CNN's ability to process audio data. Through experiments conducted with different audio durations and variations in CNN model architecture, this study evaluates the impact of dataset separation and model design on classification performance. The results show that dataset duration and CNN model architecture significantly affect classification accuracy, with the highest accuracy achieved in the scenario using 30 seconds of audio duration with an accuracy value of 84%. In addition, experiments varying the number of convolution layers in the CNN model show that the selection of the model architecture plays an important role in classification performance. Overall, this research contributes to advancing the field of audio classification by providing insight into the optimal dataset duration and model architecture for wind instrument speech recognition using CNNs.