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This study focuses on analyzing the application of cloud computing as a supporting infrastructure for digital transformation in the implementation of Smart City at the Communication and Information Agency (Diskominfo) of Muara Enim Regency. In the era of digital transformation and accelerated urbanization, the need for smart city management based on information technology has become increasingly urgent. Cloud computing plays a strategic role in providing integrated, scalable, and efficient data services to support the effectiveness of public services and data-driven decision-making. This study aims to analyze the extent to which cloud computing has been implemented in the Muara Enim Diskominfo environment, identify the supporting and inhibiting factors of its implementation, and evaluate its contribution to the achievement of Smart City objectives. This study uses a comparative approach with data collection techniques through interviews, observation, and documentation studies. The results of the study show that the implementation of cloud computing at the Muara Enim Communication and Information Agency is still in the development stage, with positive achievements in data management efficiency and inter-unit collaboration, but facing obstacles in terms of system integration and human resources. This research contributes to strengthening academic understanding of cloud computing implementation strategies in the context of local government, as well as providing practical recommendations for policy makers to improve digital infrastructure readiness towards a sustainable Smart City.

The performance of investigators in resolving criminal cases is one of the key indicators of police effectiveness. However, the Semendawai Suku III Police Sector still faces challenges in monitoring case resolution due to the lack of an integrated reporting system and minimal documentation of investigators’ knowledge. This study aims to develop an interactive dashboard system based on Knowledge Management to assist in monitoring case resolution performance and support data- and knowledge-based decision-making processes. The research employs the Prototype method, involving several stages: needs analysis, system design, system development, testing, and refinement. The system was developed using the PHP programming language and MySQL database. The implementation results show that the dashboard can display data on criminal reports, case resolutions, and pending cases in an informative and integrated manner. In addition, the knowledge base feature functions as a medium for storing and sharing investigators’ experiences (lesson learned), allowing field knowledge to be reused by other officers when handling similar cases. Overall, the implementation of the interactive dashboard system based on Knowledge Management at the Semendawai Suku III Police Sector successfully improves work efficiency, strengthens the transparency of investigative performance, and builds a foundation for sustainable organizational learning within the police environment.

The development of digital technology has brought about significant transformations in the global entertainment industry, including in Indonesia. One manifestation of this change is evident in the presence of streaming platforms like Netflix, which have altered consumer consumption patterns for audio-visual content. This study aims to analyze how Netflix Indonesia utilizes Business Intelligence (BI) and Knowledge Management (KM) to maintain and increase customer loyalty. This research uses a qualitative descriptive method, collecting data from various scientific literature, industry reports, and relevant online sources. The results show that the implementation of BI enables Netflix to analyze user behavior, understand viewing preferences, and provide more personalized content recommendations. Meanwhile, KM plays a crucial role in internal knowledge management, content development, and service innovation. The synergy between BI and KM has been proven to support Netflix's strategy in improving user experience, retaining existing customers, and attracting new ones in the increasingly competitive Indonesian market.

This study presents the integration of a Large Language Model (LLM) Ollama with the OpenStreetMap (OSM) API within a Business Intelligence (BI) framework to develop an intelligent, location-based recommendation system. The system is designed to assist users in finding dining, leisure, and resting places through natural language interaction and contextual understanding. The LLM interprets user input semantically, transforms it into structured spatial queries, and retrieves relevant geospatial data from OSM. The data are then analyzed, categorized, and visualized using BI methods to enhance interpretability and decision-making. The system was implemented using Next.js, Leaflet.js, ensuring interactivity and scalability for web-based deployment. Technical evaluation focused on system accuracy, response time, and output consistency. Results demonstrate an average response time of 1.74 seconds, 80% accuracy, and 80% consistency, proving the model’s efficiency in producing relevant, context-aware recommendations. This integration highlights the potential of combining open geospatial data, local LLMs, and BI analytics to create intelligent, data-driven decision support systems applicable to tourism, urban planning, and spatial information management.

Palm oil is one of the plantation commodities that is growing rapidly in Indonesia, with a total sales area of ​​11,672,861 ha in 2016. Clearing land for oil palm plantations is often carried out by converting forest land into plantation land. This activity has the impact of deforestation and is a serious threat. For biodiversity in Indonesia, orangutans are no exception. Orangutans are one of the animals that, based on the Assessment Information issued by the IUCN (International Union for Conservation of Nature and Natural Resources), orangutans are expected to be converted to Critically Endangered status in 2016. In the context of protecting orangutan habitat in Indonesia. Clearing of land for oil palm plantations is based on the instruments regulated in Law Number 32 of 2009 concerning Environmental Protection and Management and within the principles regulated in Minister of Agriculture Regulation Number 19 of 2011 concerning guidelines for oil palm plantations

The application of Virtual Reality (VR) based on the Metaverse in education is an innovation that can enhance the quality of learning by providing a more interactive and immersive learning experience. This article discusses the development of VR-based learning integrated with the Metaverse using the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). Through the stages of analysis, design, development, implementation, and evaluation, VR and Metaverse-based learning can be tailored to students' needs, creating a more flexible and collaborative learning experience. The use of this technology allows students to learn independently or in groups, while improving practical skills and creativity. This study shows that by applying the ADDIE model, VR and Metaverse-based learning can be more effective in increasing student motivation and learning outcomes, addressing the challenges of education in the future.

Education is used as a means of improving human resources. In increasing educational progress, a data management system is needed such as student, class, educator and education data, as well as recapitulation of school data reports for early childhood education levels. This Early Childhood Monitoring Information System was built for the process of monitoring Early Kindergarten (TK) reports to control student activities at school and make it easier to provide information on the development of children's activities that are reported in student activities, without having to use the old system by recording all student progress. manually because it is less efficient in its use and makes it easier for teachers to monitor students. The method used in system development is prototyping. The use of information systems makes it easier for teachers to input monitoring data and results of grades so that teacher users can easily monitor the progress of their students.  

Fraud in digital transactions has become a serious issue threatening the security and integrity of the fintech and e-commerce sectors. To address this problem, machine learning technology has emerged as an effective solution for automatically detecting anomalies and fraudulent transactions. This study aims to analyze the application of machine learning algorithms, specifically Support Vector Machine (SVM), Random Forest, and Ensemble Learning, in detecting fraud in digital transactions. The research adopts a quantitative approach with experimentation, testing the effectiveness of the three algorithms using a digital transaction dataset consisting of both fraudulent and non-fraudulent transactions. The results show that the Random Forest algorithm performs the best in terms of accuracy and recall, followed by Ensemble Learning, which enhances fraud detection performance by combining multiple prediction models. Meanwhile, SVM demonstrates satisfactory performance but is prone to overfitting issues when handling large and complex datasets. The study also finds that the problem of imbalanced data can affect model accuracy, and data balancing techniques such as oversampling are required to improve fraud detection performance. Overall, the findings suggest that machine learning, particularly Random Forest and Ensemble Learning algorithms, can be relied upon to improve fraud detection in digital transactions. However, challenges such as model interpretability and the need for periodic algorithm updates still need to be addressed to enhance the effectiveness of fraud prevention systems in countering the ever-evolving nature of fraud.

This study aims to analyze the implementation of Metaverse technology as a medium for socializing religious moderation at the Palembang Religious Education and Training Center. Using a qualitative approach, this research explores how Metaverse can facilitate the dissemination of religious moderation values and its potential in improving the understanding of balanced, tolerant, and inclusive religious practices among participants. Data was collected through interviews, observations, and document analysis. The research findings show that Metaverse offers a dynamic and immersive platform to deliver training and discussions on religious moderation, allowing participants to interact more deeply with the material presented. However, challenges such as limited access to technology and understanding of the virtual environment were also found. This research highlights the need for further adaptation and support to maximize the effectiveness of this technology in building religious moderation.

The web-based land transportation management system is a modern solution for managing transportation operations by utilizing web technology to facilitate monitoring, scheduling, and optimization of fleet usage. This study aims to analyze the strengths, weaknesses, opportunities, and threats in the implementation of a web-based land transportation management system using SWOT analysis. The results of this study are expected to serve as a guide for companies or transportation management agencies in designing and developing efficient and effective systems. Although there are several challenges, such as dependency on stable internet infrastructure and relatively high implementation costs, the potential benefits, such as increased operational efficiency, cost reduction, and improved customer service quality, make this system highly relevant and have strong prospects for application in the land transportation industry.

The Samsat Digital application is designed to improve efficiency and transparency in the management of motor vehicle taxes in South Sumatra. The main goal is to provide the best service to the public using information technology. The Samsat Digital application is an innovative solution that aims to make it easier for the public to access motor vehicle tax administration services. This application provides various features that allow users to make vehicle tax payments, check tax status, extend STNK, and search for information related to Samsat services online. Through mobile application-based technology, Samsat Digital seeks to reduce long queues at Samsat offices, increase time efficiency, and provide a more practical user experience. This system is equipped with secure authentication features, tax payment reminder notifications, and integration with various digital payment methods such as e-wallets, mobile banking, and credit cards.Keyword : Aplikasi Samsat Digital.

Lubuk Karet Village has great potential in rubber production. However, the rubber sales process is often faced with various obstacles, such as difficulty in determining the right price and lack of transparency in transactions. This study is an analytical study using a qualitative approach. The aim is to analyze and design a prototype of a rubber sales application. This study uses questionnaires and interviews as the main data to answer research questions. The output of this study is the identification of problems and concerns of farmers related to how to calculate market prices, difficulties in recording transaction history, and minimal transparency of information regarding selling prices in the wider market. Then the second finding is regarding the prototype design of a prospective rubber sales application which will later be further developed by researchers. From the results of the analysis in this study, it is hoped that there will be further development of the application with farmer data entry features, rubber price calculations, and transaction tracking. It is hoped that this application can provide convenience for farmers in selling their crops, increase farmers' income, and provide transparent information regarding market prices. In addition, this application can also be a promotional media for local rubber products.

During this time, the development of technology has progressed rapidly.  In this sense, many companies have followed this technological development and introduced it into the collection of inventory data of assets, goods, and their financial reports. To obtain accurate and precise data, an inventory data collection system is required. Manual accounting calculations mean that Depot Kayu Kusen Laris III often records inventory incorrectly, which affects the resulting financial reports. Therefore, this study aims to develop an inventory information system that will support accurate data collection at Kayu Kusen Laris III Depot. The conclusion of this study is that the inventory data information system is designed using Access and SQL database.

In  recent  years,  air  quality  has  become  an  increasingly  important  issue  in  various  cities  around  the  world.  Real-time  air  quality  monitoring  is  essential  for  identifying  pollution  problems  and  taking  appropriate  actions.  This  article  discusses  the  design  of  an  Internet  of  Things  (IoT)-based  air  quality  monitoring  system  using  the  prototype  method.  The  system  is  designed  to  monitor  air  quality  parameters  such  as  PM2.5,  PM10,  CO2,  and  temperature  in  real-time  and  present  the  data  to  users  through  a  web-based  application.

Students reading interest is a crucial factor in enhancing the quality of education. However, the lack of structured data makes it challenging to identify specific patterns of reading interest. This study aims to implement a data mining method using the Naive Bayes algorithm to analyze students' reading interest at SMP Negeri 2 Palembang's library. The data used includes book borrowing history, types of books, and library visit frequency over one semester. The analysis results indicate that the Naive Bayes method achieves an accuracy rate of 80% in classifying reading interest based on predetermined categories. These findings are expected to assist the school in designing more effective literacy programs.  

This research employs the Six Sigma method using the DMAIC cycle (Define, Measure, Analyze, Improve, Control) to enhance the quality of Shopee’s services. Among the variables examined, significant results were found in the areas of delivery accuracy and application reliability. Based on the survey conducted, customer dissatisfaction reached 20% in delivery and 25% in application reliability. Through analysis, the root causes were identified and addressed by optimizing logistics and application stability. This research demonstrates that Six Sigma is effective in improving customer satisfaction and the quality of Shopee’s services.  

The purpose of setting up SIMRS is to improve efficiency, effectiveness, professionalism, performance, and access and services in hospitals. In the preparation of this paper, data was collected through observation methods, interviews, literature studies, and the application of software development models using the waterfall method. The result is the design of a web-based patient registration information system using Laravel and MySQL as a database. Hospitals face several problems, including data redundancy in the input process and less than optimal data presentation, making it difficult to manipulate, change, and delete data. The author hopes that the development of a new information system can simplify and speed up the data input process. The information system designed is expected to make it easier for patients to register online as well as assist admins in the patient registration process, making it easier to make registration reports.    

Startups in Indonesia are growing very quickly which has an impact on the economy in Indonesia. High public enthusiasm is proven by Indonesia being one of the 5 countries with the highest number of startups in the world. There are several startups with good financial valuations that can be said to be unicoms or even decacorns. In this process, capital cannot be separated from the strategies taken by the Company. One alternative funding is to carry out an Initial Public Offering (IPO) on the Indonesia Stock Exchange (BEI). Until 2022, the startup that has carried out an IPO is PT. Goto Gojek Tokopedia conducted a Strength, Weakness, Opportunity, Threats (SWOT) analysis on the two companies to analyze the company's business strategy model. Method used in this research is a descriptive qualitative method and a data collection process by conducting literature studies from accredited scientific publication and digital news sources.    

The purpose of integrating artificial intelligence (AI) technology into campus smart parking management systems is to improve user comfort, safety, and efficiency. To control car traffic in real-time, the system combines technologies including computer vision, machine learning, and the Internet of Things (IoT). Automatic vehicle detection, license plate recognition, parking lot availability prediction, and ideal vehicle flow regulation are some of the key characteristics. The system can effectively recommend parking to users through a mobile app by using pattern analysis and historical data. The implementation results showed a 25% reduction in traffic in the university's parking area and a 30% increase in parking time efficiency. According to the findings of the study, applying AI technology in parking management can be a creative way to overcome the difficulties associated with facility management in higher education environments.

User satisfaction in information systems is a term used to describe how satisfied or dissatisfied users are when using a particular information system. User satisfaction includes how the information system meets the needs, expectations, and preferences of users in carrying out activities or achieving desired goals. User satisfaction is very important because it has a direct impact on the performance and success of information systems in organizations. The results of this study when viewed from Acceptability, Grade Scale and Adjective Rating are matched with the calculation of 50.5, namely the level of user acceptance is included in the marginal low category, the level of grade scale is included in the F category and the adjective rating is included in the ok-good category. According to the provisions of the conclusions that have been obtained, it can be concluded that users still experience difficulties when using SLiMS.