This research aims to develop a strong visual identity as part of a brand strengthening strategy for Micro, Small and Medium Enterprises (MSMEs) in Cikelat Village. Cikelat Village is one of the rural MSME locations that faces challenges in terms of marketing and brand differentiation in the era of globalization and increasingly fierce competition. This research uses a qualitative approach with case studies as a methodology, involving MSME owners in the participatory visual identity design process. The research results showed that the measuring instrument used in this research was proven to be valid and reliable, with a calculated r value that was greater than the table r value, and a very high level of reliability based on the Cronbach's Alpha reliability coefficient. This shows that the measuring instrument is reliable in measuring the variables studied. The development of a visual identity is expected to provide significant benefits for Cikelat Village MSMEs, increasing brand impressions, building trust, and increasing sales and sustainable growth. This service also integrates a community empowerment approach with the aim of increasing the knowledge and skills of MSME owners, supporting the development of their businesses. The results of this research provide an important contribution in understanding the importance of developing visual identity in the context of empowering rural MSMEs and provide a basis for further action in supporting the growth of MSMEs in Cikelat Village.

Telang Flower Herbal Tea is a herbal drink produced from butterfly pea flowers (Clitoria ternatea), a plant that grows abundantly in tropical areas, including Indonesia. Butterfly pea flower, also known as butterfly pea flower or blue flower, has a distinctive blue color that gives this herbal tea its color and natural properties. This research is the result of collaboration between Nusa Putra Sukabumi University and Cikelat Village, in an effort to increase the attractiveness of telang flower herbal tea products. The product's visual identity is the main focus of this research, with the aim of creating a strong and attractive visual identity to increase consumer appeal. A strong visual identity can help these products be more easily recognized by consumers, create a positive image, and increase confidence in the product's quality. Visual identity design involves color selection, logo design, packaging design, and branding strategy, as well as active participation from the Cikelat Village community to ensure conformity with local values and culture. It is hoped that this research will provide benefits to the people of Cikelat Village, enrich students' educational experiences, and become a reference for other rural communities who are trying to increase the competitiveness of local products through designing effective visual identities.Keywords: Telang Flower, Visual Identity, Cikelat Village

Penyandang tunanetra menghadapi tantangan besar dalam mobilitas dan keselamatan saat beraktivitas, terutama di ruang publik yang kurang ramah disabilitas. Tongkat konvensional hanya mampu mendeteksi rintangan secara terbatas. Penelitian ini bertujuan untuk merancang dan mengimplementasikan tongkat pintar berbasis Internet of Things (IoT) dan algoritma deteksi objek real-time YOLO V3 guna meningkatkan mobilitas dan keamanan penyandang tunanetra. Sistem yang dikembangkan memanfaatkan sensor ultrasonik untuk deteksi rintangan di sisi kiri dan kanan pengguna, modul GPS untuk pelacakan lokasi secara real-time melalui web server, serta ESP32-CAM yang terintegrasi dengan YOLO V3 untuk mendeteksi objek seperti kendaraan, lubang, dan orang. Informasi disampaikan kepada pengguna melalui peringatan suara dari DFPlayer Mini dan ditampilkan juga pada LCD serta halaman web. Hasil pengujian menunjukkan bahwa sistem bekerja dengan akurat, dengan rata-rata error sensor sebesar 0,12% dan seluruh komponen berfungsi dengan baik. Pengujian usability terhadap 50 responden menunjukkan tingkat kepuasan pengguna sangat tinggi, dengan rata-rata persentase setuju di atas 85%. Penelitian ini membuktikan bahwa integrasi IoT dan computer vision mampu menciptakan alat bantu tunanetra yang cerdas, responsif, dan mudah digunakan.

This study addresses the gap in traditional project management education by developing a web-based learning platform for the Information Technology Project Management course. The platform integrates YOLO technology for real-time visual detection and Reinforcement Learning (RL) for automated decision-making. The development process adopted a Research and Development (R&D) approach using the ADDIE model, which consisted of five phases: Analysis, Design, Development, Implementation, and Evaluation. This research is significant as it offers a solution to the challenge of bridging the gap between theoretical knowledge and practical application in project management. The primary objective is to enhance students’ understanding of project dynamics and improve their decision-making skills through real-time project monitoring and data-driven recommendations. The development process adopted a Research and Development (R&D) approach using the ADDIE model, consisting of five phases: Analysis, Design, Development, Implementation, and Evaluation. Evaluation results demonstrated that the developed learning media achieved an average validity score of 87.7%, a practicality score of 85.7%, and an effectiveness score of 86.4%, confirming that the platform is valid, practical, and effective in improving student engagement and conceptual understanding of project management. The integration of YOLO and RL technologies proved effective in helping students comprehend project dynamics and support data-driven decision-making.

Kegiatan magang merupakan salah satu bentuk pembelajaran berbasis praktik yang memungkinkan mahasiswa untuk mengaplikasikan ilmu yang telah diperoleh di bangku kuliah ke dalam lingkungan kerja yang sebenarnya. Dalam kegiatan magang yang dilaksanakan di PT ANTAM UBPB Kalimantan Barat, mahasiswa ditempatkan di bagian Kesatuan ITC (Information Technology and Communication), yang memiliki tanggung jawab utama dalam pengelolaan dan pemeliharaan infrastruktur jaringan perusahaan. Mahasiswa terlibat langsung dalam aktivitas pendukung teknis sebagai IT Support, meliputi instalasi perangkat lunak, pemeliharaan perangkat komputer, pemulihan data, serta pengaturan koneksi jaringan Point to Point menggunakan perangkat Ubiquiti NanoStation. Melalui kegiatan ini, mahasiswa tidak hanya memperoleh pengalaman teknis, tetapi juga berkontribusi nyata dalam menjaga kestabilan operasional jaringan. Tulisan ini menyajikan hasil dari kegiatan magang tersebut sebagai bentuk pengabdian kepada masyarakat industri.

Project monitoring is an important element in project management that aims to ensure project implementation in accordance with the plan, schedule, budget, and objectives that have been set. The ineffectiveness of project monitoring can cause various problems, such as delays, cost overruns, inappropriate quality of results, and poor communication between stakeholders. To address these issues, technological advances such as YOLO (You Only Look Once) and Reinforcement Learning (RL) offer innovative solutions through real-time visual detection and data-driven automated decision making. This research aims to develop a web-based project monitoring system that integrates YOLO to detect activities in the field, such as workers and heavy equipment, and RL to provide optimal recommendations for resource management. The implementation of the system is expected to increase efficiency, reduce risk, and support more accurate decision making. Based on previous research, the adoption of AI technology in project monitoring is proven to reduce operational costs and increase productivity. This web-based system is designed to provide flexibility and accessibility, allowing users to monitor projects in real-time through an interactive interface. The expected outcome of this research is the creation of an effective technological solution to improving the efficiency of construction project management, as supported by the findings of previous research that shows the great potential of AI in the construction sector.