Hotel booking cancellations pose significant challenges to the hospitality industry, affecting revenue management, demand forecasting, and operational efficiency. This study explores the application of machine learning techniques to predict hotel booking cancellations, leveraging structured data derived from hotel management systems. Various classification algorithms, including Random Forest, XGBoost, and LightGBM were evaluated to identify the most effective predictive model. The findings reveal that XGBoost model outperforms other models, achieving F2-score of 0.7897. Key influencing factors include deposit type, total number of special requests, and marketing segment. The results underscore the potential of predictive modeling in optimizing hotel revenue strategies by enabling proactive measures such as dynamic pricing, targeted customer engagement, and improved overbooking policies. This study contributes to the ongoing advancements in data-driven decision-making within the hospitality industry, offering insights into how machine learning can mitigate financial risks associated with booking cancellations.

Customer churn is a major challenge in e-commerce, directly affecting revenue and profit. This study aims to develop a machine learning model using XGBoost to predict churn probability. To handle class imbalance, SMOTE was applied as a resampling method, and hyperparameter tuning was performed to enhance performance. The model was evaluated using the F2-score, prioritizing recall while maintaining precision. The results show that the XGBoost model with SMOTE achieves strong performance, with an F2-score of 0.849 on the tuned test data. This model can help businesses identify at-risk customers early, enabling proactive retention strategies.

Cryptocurrency in Indonesia has begun to develop and is starting to be widely used by businessmen in Indonesia. This is a phenomenon given the need for accounting treatment for cryptocurrency transactions. This research seeks to explore and test cryptocurrency and blockchain technology with the approach and review of PSAK in Indonesia and focuses on accounting treatment for cryptocurrencies in Indonesia. The purpose of this study is to conduct an accounting study for cryptocurrencies based on PSAK that applies in Indonesia. The study used a review literature model to figure out accounting for cryptocurrencies.

Background: Para-sport provides a new meaning of life for people with disabilities giving them the opportunity to compete nationally and globally, the achievements obtained will have a positive impact on the quality of life, social and economic. To achieve all of this requires biomechanical analysis such as ground reaction force to the specific needs of para-athletes. Objective: To determine the changes in ground reaction force (GRF) in para-athletes with various impairments. Methods: Following PRISMA guidelines, studies from 2015 to 2025 were analyzed in Scopus, PubMed, Springer, and Google Scholar. The eligible study examined para-athletes with a focus on the variable ground reaction force. Results: the 87 articles obtained 8 articles met the inclusion criteria. The participants was 97 (12.88 ± 6.97). Quality assessment (6.75 ± 0.7). This review identified significant differences in GRF between para-athletes and healthy athletes, especially in those with uTFA. Asymmetry in vertical and anterior-posterior GRFs is observed between affected and unaffected limbs in athletes with uTFA. Conclusions: This review emphasizes the importance of understanding GRF patterns in para-athletes to improve training methods, prosthetic design, and injury prevention strategies. These findings highlight the need for individualized programs that consider the unique biomechanical challenges of para-athletes.

Background Problems: Finswimming face high psychological stress due to demands, competition, risk of injury, and challenging aquatic environments. Basic psychological needs and the ability to manage emotions are crucial factors in supporting athletes' mental well-being. Research Objectives: This study aims to explore the relationship between the fulfillment of basic psychological needs and emotions of finswimming athletes. Methods: The method used is quantitative descriptive using Basic Needs Satisfaction in Sport Scale (BNSSS) and Sport Emotion Questionnaire (SEQ). Subjects involving 30 finswimming athletes at the Shark Aquatic Club. Results: The results of the study showed a significant positive relationship between the fulfillment of basic psychological needs and the emotions of finswimming athletes. Data analysis revealed that when athletes' basic psychological needs are well met, they tend to be better able to manage emotions effectively. This indicates that increasing the fulfillment of psychological needs is related to increasing the ability to control emotions. Conclusion: This study concludes that there is a significant positive relationship between the fulfillment of basic psychological needs and the ability to manage emotions of finswimming athletes. This means that fulfilling psychological needs supports better emotions during the training phase. This study suggests paying more attention to meeting athletes' basic psychological needs in training programs to optimize athletes' mental well-being and performance.

This study aims to describe and analyze: Governance Capacity of the Jombang Regency Regional Government in the Implementation of the Upper Secondary Education Policy and Factors Inhibiting the Capacity of the Governance Capacity of the Jombang Regency Regional Government in the Implementation of the Upper Secondary Education Policy. The research is a qualitative descriptive analysis. The data analysis technique uses a technique developed by McNabb (2002), namely Grouping the data according to key constructs, identifying bases for interpretation, developing generalizations from the data, Testing Alternative interpretations and Forming and/or refining generalizable theory from case study. The results of the study show that there are 4 (four) factors that affect the Governance Capacity of the Jombang Regency Regional Government in the Implementation of the Upper Secondary Education Policy. First: The communication pattern carried out by the Jombang Education Office is ineffective so that the aspirations and problems that arise cannot be accommodated properly. Second: Resources & Funding, namely the implementer (policy implementer) of the resource aspect shows that Human Resources at the Jombang Regency Education and Culture Office is supported by 266 employees. Third: Implementer Attitude (Dispositions). show a positive attitude and sufficient willingness to carry out a good secondary education program. Fourth: The bureaucratic structure is quite clear, namely the Jombang Regency Education Office, the school and the Board of Education/community leaders, but the bureaucratic procedures are still long. The factors that hinder the implementation of education policies in Jombang Regency are factors that come from within are the existence of facilities and infrastructure, the motivation of teachers and students. Then the factor that comes from outside is the school's accessibility to a variety of sources, both resources and funds

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. 

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.

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.