This study aims to optimize the implementation of the K-Nearest Neighbors (K-NN) algorithm for medical image classification by focusing on selecting the optimal KKK parameter and applying dimensionality reduction techniques to improve accuracy and efficiency. The data used was sourced from public medical image repositories such as The Cancer Imaging Archive (TCIA) and Medical Image Analysis datasets, covering various diseases, including brain tumors, lung cancer, and kidney lesions. The research process involves data collection, data preprocessing, dimensionality reduction using Principal Component Analysis (PCA), applying the K-NN algorithm with Euclidean, Minkowski, and Cosine distance metrics, and performance evaluation using accuracy, precision, recall, and F1-score. Experimental results demonstrate that K=5with the Euclidean distance metric provides the best performance, achieving an accuracy of 90%. Additionally, PCA effectively reduces computational time by 30% without significantly compromising accuracy. This study proves that K-NN is an effective method for medical image classification. However, further research is needed to integrate K-NN with deep learning models to enhance performance and feature extraction capabilities.

Micro, Small, and Medium Enterprises (MSMEs) in Indonesia contribute 60% of regional income and absorb 97% of the workforce, yet many do not have a Business Identification Number (NIB). This activity aims to support government programs by improving capacity, access to capital, and business legality. The community service activity was conducted at the Market Day of SMK Nusantara, Ciputat, using the Participatory Action Research approach, involving 15 lecturers and students from STIE Ganesha. Results showed: 85% of participants were satisfied, but 40% faced difficulties using OSS, and 30% desired additional sessions. Participants' suggestions included follow-up programs, digital training, longer activity duration, and collaboration with financial institutions. Recommended follow-up includes continued assistance, digital literacy training, extended activity duration, and broader collaboration to strengthen the impact of the community service for business actors. 

Ekstraksi merupakan proses pemisahan senyawa aktif simplisia dengan menggunakan pelarut cair tertentu. Simplisia adalah bahan alami yang berasal dari alam dan belum mengalami proses pengolahan kecuali proses pengeringan. Proses pengeringan dilakukan untuk memperpanjang masa simpan dan mempermudah penggunaannya. Simplisia banyak digunakan sebagai bahan dasar ekstraksi. Ada beberapa metode dalam ekstraksi diantaranya adalah maserasi, sonikasi, dan sokletasi. Pada percobaan ekstraksi kulit buah naga, proses ekstraksi dimulai dengan menghancurkan kulit buah naga menjadi potongan kecil, kemudian direndam dalam pelarut untuk memisahkan senyawa senyawa yang diinginkan. Maserasi adalah proses merendam suatu simplisia dalam pelarut pada suhu kamar untuk mendapatkan ekstrak. Sonikasi adalah modifikasi dari metode maserasi yang menggunakan bantuan ultrasound (sinyal dengan frekuensi tinggi, 20 kHz), sedangkan sokletasi melibatkan pemanasan yang cukup pada suhu yang lebih tinggi. Pada kulit buah naga, senyawa senyawa yang dapat dihasilkan juga memiliki beberapa manfaat, diantaranya termasuk antioksidan yang tinggi dan khasiat anti - inflamasi. Dengan memanfaatkan teknik ekstraksi maserasi, sonikasi, dan sokletasi potensi senyawa senyawa bermanfaat dalam kulit buah naga dapat diekstraksi secara efisien untuk aplikasi yang beragam. Pada penelitian ini hasil nilai rendemen maserasi sebesar 16,29%; nilai rendemen sonikasi 3,74%; dan nilai rendemen sokletasi sebesar 29,54%. Adapun hasil uji fitokimia pada ekstrak kulit buah naga metode sokletasi terdapat senyawa metabolit dengan yaitu tanin.

This article discusses the implementation of sharia law in the Islamic economic system in Indonesia, focusing on the challenges and opportunities faced. This research uses the method of literature study and interviews with Islamic economic practitioners. The results show that although the regulation of Islamic economics is growing, there are still challenges in terms of public understanding, limited competent human resources, and competition with conventional economic systems. Therefore, a more effective strategy is needed in improving Islamic economic literacy, strengthening regulations, and developing Islamic financial institutions in order to contribute more to the national economy.

Village potential greatly influences the community's economy. Management of superior village products from various sectors will influence and provide beneficial impacts for the village itself. Kemlagi Village, Mojokerto Regency has various products in the tourism sub-sector based on culture/local wisdom, agriculture and livestock whose quality is not inferior to other potential villages. To increase the potential of the village area, it is necessary to increase the village branding of any potential sub-sectors that the village has. Therefore, it is carried out in several stages; field observations, interviews, documentation and data analysis related to village economic potential. With the result that the lack of public understanding of product marketing and promotion is the main obstacle in developing local potential. The community responded to this by providing suggestions and ideas to each other so that their village could develop. Apart from that, this activity also introduces the use of social media to help branding and promotion of villages and UMKM products in Kemlagi Village, Mojokerto Regency.

In the competitive world of business, identifying high-risk customers is critical to minimizing churn rates and increasing profitability. This research uses data mining techniques using the C4.5 decision tree algorithm to classify customers based on their churn risk. The research stages include data collection, cleaning, data processing, as well as dividing the data into training and testing sets. The implementation of this algorithm was carried out using RapidMiner software, which facilitates customer clustering and predicting behavior based on historical attributes. The evaluation results show the model has an accuracy of 74.59%, with precision and recall indicating the model's ability to identify high-risk customers. Thus, the Decision Tree C4.5 algorithm is proven to be effective in supporting decision making for customer churn risk mitigation strategies.

The rapid advancement of information and communication technology has transformed and opened business perspectives and operations, particularly in UMKM the photography industry. As the demand for online photography services continues to rise, it is crucial for service providers to develop efficient information systems to manage photo sales effectively. The research titled "Development of the POVSHOT Mobile Application for Online Photo Sales Using Flutter and MySQL" aims to facilitate online photo sales through the implementation of Flutter technology and a MySQL database. The findings indicate that the "POVSHOT" application successfully integrates features such as photo uploading, payment management, and user administration within a user-friendly interface. This study suggests that the use of mobile applications can enhance security in the photo sales process and provide a better experience for users. The implications of this research highlight that photography service providers can leverage mobile technology to expand their market reach and improve customer satisfaction through a more integrated and responsive system.

This study aims to analyze the implementation of interdisciplinary project-based remedial activities through infographic media in the Social Studies subject Phase E in class X MAN 2 Malang City after the implementation of the odd semester summative assessment. This study uses a descriptive qualitative method with data collection techniques through observation, interviews, and documentation. The results of the study indicate that this activity is effective in helping students understand the Social Studies material by exploring topics in depth using relevant data and sources. In addition, students are able to understand the functions and roles of geography, sociology, history, and economics in solving real problems, strengthening research and collaboration skills, and increasing learning motivation. Teachers and students also feel the efficiency of time and resources. However, this study identified several obstacles faced by students, including difficulties in dealing with less competent group members, challenges in using barcodes as references, finding the right infographic design, classifying topics in an interdisciplinary perspective, and dividing group tasks. This study recommends infographic design training, intensive guidance for group management, and more structured learning strategies in implementing an interdisciplinary approach.

The increasing unpredictability of climate change demands a system capable of automatically detecting rainfall and providing early warnings. This study aims to design and develop a rain detection system based on a water sensor and LED using an Arduino Uno microcontroller. The system operates by detecting water presence on the rain sensor and providing a visual indication through an LED. The research methodology follows a Research and Development (R&D) approach, including literature review, hardware and software design, implementation, and system testing. The test results indicate that the system can accurately detect rainfall and respond to weather changes in real-time. This system has the potential to be applied in various sectors, such as agriculture, transportation, and industry, to mitigate risks caused by sudden rain. Further development can integrate Internet of Things (IoT) technology for remote weather monitoring.