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This study applies the Mean Variance model, which aims to form an optimal portfolio composition in the health, property, and cyclical consumer sectors and combine the three sectors into one portfolio, then visualize its efficient frontier. This study analyzes the return profiles and compares the risks of each portfolio using alternative risk measures such as the Coefficient of Variation (CV), Value at Risk (VaR), and Conditional Value at Risk (CVaR). Daily closing price data for the three sectors listed on the Indonesia Stock Exchange (IDX) from March 2, 2020, to March 3, 2025, were used in this study. Stock selection was conducted using purposive sampling, followed by selecting seven stocks for optimization based on the lowest Coefficient of Variation (CV) value. Portfolio optimization analysis was conducted using the Python programming language with Visual Studio Code software. The findings of this study indicate that the combined portfolio incorporating the three sectors is the most efficient, with an expected return of 0.104%, standard deviation of 0.007, and alternative risk measures such as Coefficient of Variation (CV) 6.9328, Value at Risk (VaR) of -0.99%, and Conditional Value at Risk (CVaR) of -1.44%, which are lower than those of single-sector portfolios. Visualization of the efficient frontier curve confirms that the combined portfolio offers better results in terms of risk and return. The results of this study indicate that cross-sector diversification can significantly reduce risk and prevent significant losses.

Gastric disease is a common health problem that can disrupt daily activities if not properly treated. To aid the initial diagnosis process, this study developed a web-based expert system capable of diagnosing various types of gastric disease based on the symptoms experienced by the user. This system uses the Dempster-Shafer method to address uncertainty in decision-making by combining a number of pieces of evidence in the form of symptoms to determine the level of confidence in a disease. The system was developed using the PHP programming language and a MySQL database and designed for easy browser access. Testing demonstrated that the system was able to provide fairly accurate diagnostic results that closely approximated the results of consultations with medical professionals. This system is expected to become an initial solution for the public in quickly and independently recognizing symptoms of gastric disease.

The attendance recording system at PLN ULP Tanjungbalai still relies on manual, paper-based methods, resulting in delays in data recap, reduced efficiency, and a high potential for recording errors. This condition affects the accuracy of employee attendance information, which is essential for administrative activities and managerial decision-making. Based on these issues, this practical work aims to design and develop a web-based e-attendance application as a solution to enhance efficiency, processing speed, and the accuracy of attendance recapitulation. The system was developed using PHP as the programming language and MySQL as the database management system, following several stages including requirement analysis, system design using UML, and implementation of a web-based user interface. The application provides essential features such as user login, daily attendance recording, employee data management, attendance notes (permission, sickness, etc.), and automatic attendance report generation. The system is designed for two types of users—Admin and Employees—each with specific access rights. The implementation results indicate that the e-attendance application significantly improves the efficiency of attendance administration at PLN ULP Tanjungbalai. Data collection and recapitulation become faster, more structured, and less prone to errors, while also enabling administrators to monitor employee attendance in real time. Therefore, this web-based e-attendance application serves as an effective solution to support operational activities and enhance the quality of employee attendance management.

In this paper, we study the use of linear programming for the performance enhancement of fortified queues systems in which resources are unreliable in terms of variation and a case study on Marjan Hospital is considered. The quality management maturity level in the hospital was measured by an integrated inspection tool; senior management was found to be concerned for quality of service improvement and implementation of modern technology systems. Strengths and weaknesses in that activity are shown, and it is evidenced the need of boosting the quality of service activities and promoting the coordination between the different areas. From the findings, the study recommends the use of linear programming technique,Orgers should as well enhance proper training and development and Acquisition of modern day technology for effective performance improvement and quality of service. The study demonstrates that the adoption of linear programming techniques could be a viable solution to optimize resource allocation and enhance performance in the hospital's queue systems. Additionally, the research underscores the importance of investing in staff training and development programs, as well as the acquisition of state-of-the-art technology, to further improve service delivery and ensure sustainable quality improvement in the long term.

The development of digital technology has encouraged the government to utilize social media as an effective means of public communication. The Ministry of Agriculture is one institution that actively uses Instagram to convey information, build a positive image, and interact with the public. This study aims to determine the Public Relations strategy in managing the Instagram social media account @kementerianpertanian. This study uses the Public Relations strategy theory from Cutlip and Center, which consists of four stages: problem identification, planning and programming, communication and action, and evaluation. The research method used is a descriptive qualitative approach, with data collection techniques through in-depth interviews and documentation of the Ministry of Agriculture's Public Relations team. The results show that the Ministry of Agriculture's Public Relations has implemented a planned communication strategy, starting from planning informative and educational content, utilizing Instagram features such as reels, stories, and live to increase interaction, to routine evaluation based on engagement data (likes, shares, comments, and saves). This strategy also adapts to social media trends and audience needs. Public Relations actively responds to user questions and comments to maintain two-way communication. However, challenges such as negative comments, limited resources, and changes in the Instagram algorithm are obstacles that still need to be overcome. Overall, the implemented strategy has successfully supported the improvement of the image and transparency of public information within the Ministry of Agriculture.

This research aims to design and implement a village MSME website as a centralized digital promotional medium to overcome the limitations of conventional marketing and expand the market reach of local products more effectively and sustainably. The system was developed using the waterfall method, encompassing requirements analysis, design, implementation, testing, and maintenance. The system was developed using the PHP programming language and the CodeIgniter framework based on the Model-View-Controller (MVC) architecture to ensure a structured, efficient, and maintainable development process. The implementation resulted in a responsive and user-friendly website equipped with key features such as an informative product catalog, village MSME profiles, and a content management system via an admin dashboard that allows MSMEs to update data independently and flexibly. Functional testing demonstrated that all features functioned well and reliably according to user needs. Therefore, this village MSME website can be concluded as an effective digital solution for increasing the visibility of local products, strengthening MSME competitiveness, and supporting village economic growth through sustainable and integrated online promotion.

Hijaiyah letters have varying shapes, and some of them are very similar, often causing errors in the manual character recognition process. This study aims to classify Hijaiyah letters based on digital images using the Convolutional Neural Network (CNN) method. This method was used in this study with a dataset consisting of 28 letter classes and a total of 4,480 images obtained from various public sources and private data. All images underwent a preprocessing stage that included labeling, resizing, normalization, and augmentation, then were divided into three parts, namely training data, validation data, and test data with a ratio of 70:20:10. The training process was carried out using the Python programming language with the help of the TensorFlow and Keras libraries on the Google Colab platform. The test results showed that the CNN model achieved an accuracy of 97.10%, with an average precision, recall, and F1-score of 0.97, respectively. Classification errors only occurred in letters that had similar shapes, such as Syin and Sin. Based on these results, the CNN method proved to be effective, efficient, and accurate in recognizing Hijaiyah letter image patterns, so it can be used as a basis for developing classification models with higher accuracy in the future.

This study discusses the design and development of an automatic safety system for a wood cutting machine using Arduino Uno, a PIR (Passive Infrared) sensor, and a servo motor as the main components. The system is designed to automatically stop the movement of the wood cutting machine when human motion is detected around the cutting area, thereby minimizing the risk of work-related accidents. The research method includes hardware design, microcontroller programming, and system response testing using two types of test objects: the human body and a wooden block. The results show that the system operates according to the programmed logic. When the PIR sensor detects human motion, the servo motor stops and the red LED lights up as a danger indicator. In contrast, when no human motion is detected, the servo motor continues to move normally and the green LED remains on as a safe indicator. The system’s average response time is 0.6 seconds, indicating a fast and accurate performance. Therefore, the designed system is considered effective and can serve as a prototype of a simple safety tool to enhance operator safety in wood cutting machines.

This study analyzes the maintenance process of the Roll Bending machine used in the wind tower production line at PT Kenertec Power System, Cilegon, Indonesia. The Roll Bending machine plays a crucial role in shaping steel plates into cylindrical shell components, which are later assembled into wind tower sections. The objective of this research is to identify maintenance patterns, types of failures, and improvement strategies to ensure machine reliability and operational efficiency. The research employed observation, interviews with maintenance personnel, and documentation review to collect relevant data. The findings show that the machine experienced multiple failures, mostly related to hydraulic system leaks, PLC programming errors, and component wear such as cylinders, seals, and gear pumps. A significant increase in corrective maintenance activities occurred between August 2023 and April 2024, particularly in February 2024, indicating the need for a more consistent predictive maintenance strategy. The implications of this study highlight that optimized maintenance scheduling and monitoring are essential to reduce downtime, avoid production delays, and maintain product quality. This research is expected to support maintenance decision-making and contribute to the improvement of industrial machine reliability in wind tower manufacturing operations.

Right now, the utilization of data and correspondence innovation fundamentally affects different business areas, including producing. One arising idea is e-business, otherwise called electronic business. This idea underlines data exchanging and paperless exchanges through different innovations like Electronic Trade of Data (EDI), email, electronic notice sheets, electronic assets move, and other organization based propels. An e-business data framework is a gadget, innovation, or system that uses equipment, programming, organizations, and human insight to interface, do exchanges, and complete different hierarchical exercises without being restricted by time or area. The utilization of e-business data frameworks is a significant instrument that associations use to further develop business activities at the nearby and worldwide level. Indonesia is one of the trailblazers in web-based business and internet business. Nonetheless, the potential presented by e-business haven't completely taken advantage of by business affiliations.

Rapid advances in Information Technology (IT) in the 21st century have significantly transformed educational practices, particularly in vocational high schools (SMK) specializing in Software Engineering (RPL). Traditional learning media, such as textbooks, static slides, and lectures, often fail to provide an interactive learning experience, limiting students’ engagement and reducing the effectiveness of knowledge retention. To overcome this challenge, this study focuses on developing and validating an interactive quiz application called VOCANETIC, designed as an innovative learning aid for SMK RPL students. The research uses a Research and Development (R&D) approach, emphasizing the stages of product development, expert validation, and feasibility assessment. VOCANETIC is developed using VB.NET in the Microsoft Visual Studio environment, and MySQL is employed for efficient data management and storage. The application features interactive quizzes, real-time feedback, and user-friendly interfaces to enhance student engagement and motivation. Based on evaluation and analysis by expert validators, VOCANETIC meets the “Proper” feasibility criteria, demonstrating usability, interactivity, and educational effectiveness. The results indicate that VOCANETIC is capable of supporting active learning, improving students’ understanding of software engineering concepts, and providing an effective platform for self-assessment and practice. In conclusion, the VOCANETIC application is proven to be a valid, reliable, and practical tool that can be implemented as an interactive learning medium in SMK RPL, offering an innovative approach to facilitate student learning and engagement in the digital era.                                                              

The development of information technology in the era of globalization continues to accelerate. This has brought significant changes in various fields, one of which is online business, namely e-commerce. This study aims to analyze competition and provide optimal strategies for Shopee and Tokopedia in addressing their dependence on subsidies and large-scale discounts, so that both platforms can remain competitive effectively without experiencing a decline in profit margins. The research method used is a quantitative approach with a survey research method. The data used is primary data analyzed using Game Theory with Pure Strategy, Mixed Strategy, and Linear Programming. The results show that Shopee obtained optimal strategies for Price (proportion 0.3568) and Product Completeness (proportion 0.6427). Meanwhile, Tokopedia obtained optimal strategies for Promotion (proportion 0.3568) and Product Completeness (proportion 0.6427). The implication of this study is that companies can use the optimal strategies obtained to overcome their dependence on subsidies and large-scale discounts, which result in declining profit margins for both platforms.

APIs (Application Programming Interfaces) have become a key component in the development of modern digital products and the transformation of cloud-based services. Its ability to provide structured access to data and enable cross-platform integration makes APIs at the core of the enterprise's digital architecture. However, the high level of API openness poses increasingly complex security challenges, including potential data exploitation, injection attacks, credential misuse, and exploitation of business logic loopholes. This article examines the strategic role of APIs in the digital ecosystem, analyzes the operational risks that arise from API exposure, and evaluates the effectiveness of basic defense mechanisms such as API Gateways and Web Application Firewalls (WAFs). The findings of the study show that while both solutions play an important role in controlling access, filtering, and mitigating attacks at the surface layer, they have not been able to provide comprehensive protection against modern API threats that are dynamic, distributed, and often exploit weaknesses at the application and business logic levels. Therefore, a more holistic, layered, and sustainable API security approach is needed, including anomalous behavior detection, API abuse protection, and real-time monitoring to maintain the integrity and reliability of digital services.  

Financial administration plays a crucial role in village-level governance, requiring transparency, accountability, and efficiency in the use of public funds. Currently, the Hameli Ate Village Office still relies on manual methods to manage its financial administration, including recording cash receipts and expenditures using notebooks and simple spreadsheets. This approach presents various issues, such as the risk of data loss, calculation errors, delays in report preparation, and difficulties in tracking and collecting financial transaction data. This study aims to develop a web-based financial administration information system to assist village officials in managing financial data more effectively, efficiently, and in an integrated manner. The methods applied include observation, interviews, and document collection to understand system requirements, while the system development process is implemented using the Waterfall model, which consists of the stages of analysis, design, implementation, testing, and maintenance. The system was built using the PHP programming language and a MySQL database and is designed to generate financial reports automatically and in real time. The testing results show that the system can handle income and expenditure data more quickly, accurately, and in a user-friendly manner. With the implementation of this information system, the financial administration process at the Hameli Ate Village Office becomes more transparent, accountable, and facilitates data-driven decision-making.

Administrative services for civil servants (ASN) play a crucial role in ensuring the rights and obligations of government employees. One of these services is the submission process for the Wife Card (KARIS) and Husband Card (KARSU), which serve as official proof of marital status for civil servants. At the BKPSDM of Sumba Barat Daya, the current submission process for KARIS and KARSU is still carried out manually by filling out paper forms and attaching physical documents. This manual method is time-consuming, prone to data errors, and complicates the monitoring process. Therefore, this study aims to develop a digital information system to simplify the submission, verification, and issuance process of KARIS and KARSU online. This research applies a Research and Development (R&D) approach using the Waterfall model, consisting of requirement analysis, system design, implementation, testing, and evaluation stages. The system is developed using the Python (Streamlit) programming framework and a SQLite3 database, designed to be easily accessible to both ASN users and BKPSDM officers through local networks or the internet. The results show that the developed system successfully reduces processing time by up to 60%, improves data accuracy by 90%, and significantly decreases the use of physical documents. The implementation of this digital information system makes the KARIS and KARSU administrative service more efficient, transparent, and accountable, supporting the ongoing digital transformation within the local government of Sumba Barat Daya Regency.

MP3 audio files are often used in a variety of fields, but they are prone to security risks such as eavesdropping and illegal access. This study proposes a super encryption method by combining the algorithms of Rivest Shamir Adleman (RSA) and ElGamal to improve the protection of audio data. RSA was chosen for its efficiency and ease of implementation, while ElGamal offers a high level of security through discrete logarithmic complexity. The combination of the two is expected to address the weaknesses of each algorithm and strengthen file security. The system is developed using the Python programming language with the Visual Studio Code environment. The encryption process is done in layers: MP3 files are first encrypted with RSA, and then the results are encrypted again with ElGamal. The decryption is done in reverse order. Tests are conducted with various MP3 file sizes to measure the effectiveness and performance of the system. The results show that this method is able to secure audio files so that they cannot be accessed without the private keys of both algorithms. Although processing times are increased compared to single encryption, the level of security obtained is much higher. This approach can be an effective solution for protecting digital audio data, particularly MP3 format, and could potentially be applied to a wide range of other data types that require a high level of security.

Artificial intelligence (AI) has developed rapidly in recent years, making judgments and executing tasks in ways comparable to decisions made by the human brain. These technological advances allow AI to replace or complement human work in various fields, but they also raise complex legal questions regarding accountability for the actions it performs. This study employs a normative juridical research methodology, which emphasizes the analysis of laws and regulations, concepts, principles, and legal theories, using literature as the primary data source. The findings show that AI, despite its advanced capabilities, remains a legal object rather than a legal subject. In accordance with Government Regulation No. 71 of 2019 on the Implementation of Electronic Systems and Transactions in Indonesia, AI cannot be considered a legal entity with independent rights and obligations. Consequently, AI cannot be held legally accountable for its actions, as it operates under human creation, programming, and direction. Responsibility for any consequences arising from the use of AI lies with the individuals or institutions that develop, operate, and control it. This study highlights the importance of establishing a clear legal framework to regulate AI applications, ensuring that technological innovation aligns with legal certainty and accountability. It concludes that while AI may imitate human decision-making, it lacks autonomy in the legal sense and therefore cannot bear responsibility under positive law.

Rice production remains a strategic component in supporting local food security, yet its performance is strongly influenced by the heterogeneity of farmers' characteristics. This study aims to describe the characteristics of rice farmers in Tonra District and analyze their implications for the formulation of agricultural extension programs. Using a descriptive quantitative approach with 100 respondents selected proportionally from eleven villages, the research examines key variables including land size, seed use, fertilizer application, age, education level, and farming experience. The findings reveal clear variations in productivity among farmers, where higher production is generally associated with larger landholding, optimal input use, productive age groups, higher educational attainment, and moderate farming experience. These patterns highlight how farmers' demographic and agronomic characteristics shape their management capacity and adoption of recommended practices. The study emphasizes that extension programs must be designed based on farmers’ actual profiles to enhance relevance and effectiveness. Tailored strategies—such as visual communication for low-education groups, mechanization support for senior farmers, and input-use optimization training—are necessary to improve productivity outcomes. The results provide an important basis for developing more targeted, responsive, and sustainable agricultural extension programming at the district level.

Waste management remains a major challenge, particularly due to the lack of public awareness and habits in sorting waste from its source. Innovative technology-based solutions are needed to support more effective waste management systems. This study aims to design and develop an Internet of Things (IoT)-based smart trash bin capable of automatically sorting metal and non-metal waste. The system utilizes an ESP32 microcontroller as the main controller, an LJ12A3-4-Z/BY sensor to detect metal materials, an E18 sensor to detect non-metal materials, and an ultrasonic sensor to monitor bin capacity. The waste separation mechanism is operated by a servo motor controlled by the system, while the Blynk application is integrated for real-time monitoring and full-capacity notifications sent directly to the user’s smartphone. The research stages included hardware design, microcontroller programming, IoT platform integration, and functionality testing to ensure system performance and reliability. The results showed that the smart trash bin operated as expected, successfully identifying and separating metal and non-metal waste automatically, while also sending real-time notifications to the user when the bin approached full capacity. The implementation of this technology has the potential to modernize waste management processes, improve the efficiency of waste sorting, and reduce dependency on manual labor. Furthermore, this research opens opportunities for future development by integrating additional sensors and cloud-based data management systems to support smart city initiatives and sustainable waste management practices.

Manual post-harvest paddy stirring requires significant time and labor and often results in uneven mixing, which can affect grain quality. To address this issue, this study designed and implemented a prototype of an Internet of Things (IoT)-based paddy stirring robot to simplify the process and improve efficiency. The system utilizes an ESP32 microcontroller as the main controller, DC motors as the stirring mechanism, and an IoT module for wireless connectivity to a mobile application. The research stages included hardware design, control system programming, IoT platform integration, and performance testing. Testing was conducted to evaluate response time, mixing uniformity, and power consumption. The results showed that the system could be operated remotely via a local Wi-Fi network with an average delay of less than 1 second, enabling real-time control. The prototype successfully stirred 0.3 kg of paddy with a mixing uniformity rate of 92% and an average power consumption of 12 watts. The application of IoT in the paddy stirring mechanism significantly improved time efficiency, reduced manual labor requirements, and maintained grain quality compared to traditional methods. These findings indicate the potential for further development into a large-scale automated paddy processing system with integrated humidity and temperature sensors for real-time quality monitoring, supporting the modernization of post-harvest processing through digital technology.