The PKK Women's Group in Sambirejo Village, Wonosalam District, Jombang Regency has the potential to produce briquettes from durian peel waste. This is supported by the large amount of waste waste that is wasted. The use of durian peel waste in Sambirejo Village has never been done before. The empowerment activity of the PKK Women's Group in Sambirejo Village aims to provide information, training and assistance regarding how to use durian peel waste into products that have a selling value and can reduce environmental waste. This activity received a positive response from the PKK Women's Movement and Village Apparatus in Sambirejo. From the results of this empowerment activity, the Sambirejo Village PKK Women's Group was able to process and utilize durian peel waste into a product that has a selling value.

Micro, Small and Medium Enterprises (MSME) are sectors that are influential in running the economy in the community. MSME are also expected to be able to contribute in creating employment opportunities for the surrounding community, so as to be able to reduce
poverty in an area. The existence of the Wolamgrezz MSME in Carangwulung village actually has the potential to become a large MSME in the Wonosalam District and even the entire Jombang Regency, because these UMKM raise the region's superior crops. Therefore, Wolamgrezz MSME must be fully supported in running their business, so that the existing potential can run optimally and can become the leading MSME in Jombang Regency. However, in carrying out its business, Wolamgrezz has several problems that arise in the field, such as obstacles to product promotion through digital e-commerce media and product marketing only by word of mouth, so that consumers who know Wolamgrezz's MSME products are very limited and only within the scope of Carangwulung village. Therefore, the branding and marketing of UMKM Wolamgrezz products must be carried out immediately and intensified so that they can attract consumers widely so that product sales can increase and income will also increase, and this can also affect the opening of new job vacancies.

Skin cancer has high incidence and fatality rates, making accurate and rapid detection crucial. This study developed a web-based skin cancer detection system using YOLOv8. The model detects seven types of skin cancer using a dataset of 17.366 annotated images. Methods included data collection, pre-processing, augmentation, model training, and performance evaluation using precision, recall, and mean Average Precision (mAP). Results show that the YOLOv8 model achieved a precision of 0.975 and a recall of 0.969. Evaluation with a confusion matrix demonstrated strong detection capabilities. A web interface was developed to allow users to upload images and view detection results in real-time. The YOLOv8-based skin cancer detection system provides accurate results and can be used as a tool for early diagnosis.