Indonesia’s waste management system struggles to keep pace with rapid population growth and urbanization, resulting in inefficient waste collection, environmental degradation, and low recycling rates. The country predominantly relies on open dumping and landfilling, which contribute significantly to pollution and greenhouse gas emissions. This study explores the transformative role of Artificial Intelligence (AI) and the Internet of Things (IoT) in waste management, focusing on smart waste collection, automated sorting, real-time monitoring, and predictive analytics. AI-driven waste classification enhances recycling efficiency, while IoT-enabled smart bins optimize collection routes, reducing operational costs and landfill dependency. Despite these advantages, challenges such as high implementation costs, digital infrastructure limitations, and data privacy concerns hinder widespread adoption. This study highlights that policy support, investment in digital infrastructure, and stakeholder collaboration are crucial for successful implementation. By leveraging AI and IoT, Indonesia can significantly improve waste management efficiency, minimize environmental impact, and advance circular economy initiatives. The findings suggest that, with the right policies and investments, AI-driven waste management can drive sustainability, reduce waste mismanagement, and promote resource optimization, making it a vital strategy for future urban development in Indonesia.
 

Bali Province is a world-renowned tourism destination that significantly contributes to the Gross Regional Domestic Product (GRDP) of the region. However, the COVID-19 pandemic led to a severe economic downturn, causing negative economic growth. This study aims to examine the simultaneous and partial effects of tourist visits, local revenue (PAD), and investment on the GRDP of Bali Province. The research utilizes secondary data from nine regencies/cities in Bali over a six-year period (2018–2023). Data analysis is conducted using panel data regression with the Eviews 12 software. The results indicate that tourist visits, PAD, and investment collectively influence the GRDP of Bali Province. Partially, tourist visits and PAD have a positive and significant impact on GRDP, while investment has a negative but insignificant effect. The findings suggest that optimizing tourism potential, improving infrastructure, maximizing the potential of each region to increase local revenue, and exploring investment opportunities beyond the tourism sector—while supporting both domestic and foreign investment are essential to boosting Bali’s GRDP.

This article presents a comparative constitutional law study of the President's executive power. The article confidently interprets the President's executive power based on the 1945 Constitution. It does so by referring to the unitary executive theory developed in the United States by unitarians based on the Constitution of the United States. Unitary executive means that the President, as Chief Executive, holds all executive power. The study's central point is presidentialism, a system of government shared by the United States and Indonesia. This article has two purposes. First, it corrects the foundational flaw of the unitary executive theory developed by unitarians because they do not specifically claim presidentialism as the underlying principle of their theory. Second, it makes the unitary executive theory applicable to Indonesia.

Target nasional tahun 2024 Indonesia terbebas dari BABS atau dengan status ODF. Sanitasi sehat dan aman akan meningkatkan kesehatan dan kesejahteraan masyarakat. Tingkat ekonomi dan pendidikan yang rendah menjadikan perubahan kebiasaan BABS menuju ODF bukanlah hal yang mudah. Atas dasar Perda Surabaya No. No. 2 Tahun 2014 tentang Penyelenggaraan Ketertiban Umum dan Ketentraman Masyarakat, maka tahun 2023 Surabaya telah mampu mencapai target 100%. Oleh karen itu dalam penelitian ini akan menganalisis kebijakan Surabaya dalam mendukung target ODF 100% serta strategi Surabaya agar dapat mempertahankan status ODF saat ini. Dengan menggunkan metode sosio legal dapat disimpulkan bahwa Surabaya telah menerbitkan Peraturan Walikota untuk melakukan percepatan pembangunan jamban dengan mengabaikan syarat legalitas kepemilikan lahan. Sedangkan strategi dalam mempertahankan status ODF adalah dengan adanya kebijakan dan aplikasi sedot tinja dengan biaya yang murah serta keterlibatan aktif masyarakat untuk tetap melakukan kebiasaan baik dalam hal sanitasi berkelanjutan.
 

One of the infectious diseases that is a problem in the world is Pulmonary TB with the main symptoms of shortness of breath, chest pain when coughing and breathing due to airway obstruction. If not treated, it can cause death, so it needs treatment, one of which is with effective coughing exercises. The activity begins with measuring the respiratory rate, then effective coughing exercise therapy. Education is carried out to relieve the respiratory tract by expelling sputum for Pulmonary TB sufferers and in collaboration with local village officials. The method used in this activity is counseling on effective coughing exercises from a team of nursing lecturers and nursing students during Field Learning Practices of 32 respondents. The results obtained from respondents before being given education were 32 people with a high respiratory rate> 25x / minute and after education there was a change in the normal range of 23-25x / minute as many as 26 people and 6 others with a high respiratory rate> 25x / minute. The output of the PkM that has been implemented is expected to increase the respiratory rate after effective coughing exercises are applied in the community.

This community service activity aims to improve the knowledge and skills of homestay and family inn managers in marketing and branding management in the region Pagaralam City. The background of this activity is the importance of the role of homestays and family lodging in supporting local tourism, as well as the problems faced by managers in terms of marketing and branding. The method of implementing this activity includes a needs survey, preparation of training materials, training implementation, and follow-up in the form of mentoring and evaluation. The training was attended by 50 participants with a high level of attendance and activity. The results of the pre-test and post-test evaluations showed an average increase of 89 percent in participants' understanding. Feedback from participants also showed that this training was very useful and relevant. After the training, participants began to implement changes in their marketing and branding strategies, which had an impact on increasing the number of guests and the quality of photos of lodging products. The interpretation of the results showed that this training was effective in improving the knowledge and skills of the participants, as well as having a positive impact on their efforts. The conclusion of this activity is that marketing and branding management training has succeeded in increasing the capacity of homestay and family inn managers in developing their businesses. This activity also contributes positively to the development of local tourism.

Umah Lokal Coffee Roastery is a business engaged in the production and marketing of coffee beans. This study aims to optimize the production combination to maximize profits using the Linear Programming method. This method enables the company to determine the optimal production quantity for each type of product, namely Telek Beans, Barong Beans, Jauk Beans, Gerbera, and Daisy. The analysis results indicate that the optimal production combination includes producing 128 units of Telek Beans, 155 units of Jauk Beans, 85 units of Gerbera, and 189 units of Daisy, while the production of Barong Beans is discontinued. Implementing this strategy has the potential to increase profits by Rp1,124,417 or 6.4%. This research contributes to the development of more efficient production strategies in dealing with resource constraints.
 

Purpose: The cardiovascular system is a vital system responsible for the distribution of oxygen and nutrients throughout the body. The complexity of interactions between the heart and blood vessels often presents challenges in monitoring and analyzing health conditions. The research proposes the development of a Human Digital Twin (HDT) for the cardiovascular system through application of two different modelling approaches geometric modeling and physic-based modeling. Through this model physical conditions can be represented and real time data integrated to offer insights into the dynamics of the cardiovascular system.
Methods: This model development is based on two major components: a geometric modeling and a physic-based modeling. The geometric model is done in 3D to show the structure of the heart in detail, while the physical-based model is tabulated with different measurable physical parameters in the cardiovascular system, such as blood pressure and flow rate. This information is integrated into the Five Dimension Digital Twin model, including physical, virtual, data, connection, and service dimensions for the accurate simulation of cardiovascular conditions.
Result: Results confirm that the Five-Dimensional Digital Twin (DT) could give further development to how the dynamics of the cardiovascular system behave, possibly in real-time updates on conditions and a supply of data that is far more detailed in view of analyzing risk and further representation of specific cardiovascular disorders while providing personalized medical support.
Novelty: The Five-Dimensional Human Digital Twin Model (HDTM) developed in this research introduces novel innovations in the monitoring and simulation of the cardiovascular system through the application of geometric and physic-based modeling techniques. This approach offers a higher level of detail, compared to previous models, and added value for the advancement of health technology by integrating real time data into the simulations. This model serves not only as an advanced analytical tool but also as a reference for further research on DT technology in the medical field.

Purpose: This research aims to improve the accuracy of sentiment analysis on PLN Mobile app reviews by overcoming the challenge of data imbalance. This goal is important to provide a better understanding of user opinions and support PT PLN (Persero) in improving mobile application services.
Methods: This research uses the Random Forest algorithm combined with Synthetic Minority Over-sampling Technique (SMOTE) to handle imbalanced data. Data is collected through web scraping reviews from the Google Play Store, followed by preprocessing processes such as data cleaning, stopword removal, tokenization, and stemming. Feature extraction is performed using the Bag of Words (BoW) method, and the data is tested with four sharing schemes.
Result: The results showed that the 90%-10% sharing scheme gave the best performance with an accuracy of 81% and an average precision and recall of 0.79. This finding confirms that the larger the proportion of training data, the better the model performs sentiment classification.
Novelty: This research's novelty lies in combining SMOTE with BoW and Random Forest to overcome data imbalance. This approach is a significant reference for future sentiment analysis research. It provides practical insights that PT PLN (Persero) can use to improve the quality of its application services.