Telkom AI Centre Makassar Becomes New Engine for Digital Innovation in Eastern Indonesia

PT Telkom Indonesia (Persero) Tbk (Telkom) is strengthening the development of the artificial intelligence (AI) ecosystem in eastern Indonesia by optimising the role of the AI Centre Makassar as a centre for innovation and digital talent development. This effort aims to foster the emergence of practical AI-based solutions and support the acceleration of equitable national digital transformation. During a working visit to the AI Centre Makassar some time ago, Telkom’s IT Digital Director Faizal Rochmad Djoemadi directly inspected the facilities and various innovations developed by local digital talents through exhibition sessions and project presentations. This activity also serves as a manifestation of Telkom’s commitment to providing exploration space for local innovators to develop capabilities and expand knowledge related to AI technology. In his speech, Telkom’s IT Digital Director Faizal Rochmad Djoemadi emphasised that AI is a strategic technology that must deliver real impacts for public services and industry. According to him, great innovations always require close collaboration between technology companies, developer communities, and educational institutions to accelerate adoption and produce an ecosystem that impacts societal welfare. “The utilisation of AI is not just about technology, but how that technology can provide real solutions to various problems in society and industry,” said Faizal. As part of strengthening this ecosystem, the AI Centre Makassar emerges through the implementation of the AI Connect pillar in Telkom’s strategic AI Centre of Excellence (AI CoE) initiative. This pillar is integrated with AI Campus, AI Playground, AI Hub, and AI Native in building a comprehensive AI ecosystem, from research collaboration, talent development, to the implementation of solutions in various sectors. Through these facilities, Telkom opens inclusive collaboration spaces for local digital talents to network, develop capabilities, and present innovations relevant to industry and societal needs. Some solutions presented include the use of machine learning for classifying the Indonesian Standard Industrial Classification (KBLI), an unsupervised learning-based school grouping model for operational education assistance recommendations, as well as the use of deep learning in endoscopic image analysis to support stomach disease identification.