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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.

Global challenges such as climate change and land degradation demand the strengthening of the agricultural sector through the adoption of relevant technologies. Agricultural extension plays an important role in conveying information and technological innovations to farmers, with extension workers as facilitators, educators, and motivators in accelerating the implementation of agricultural technology packages. However, the rate of adoption of technology by farmers is still low, especially in Tana Toraja Regency, South Sulawesi. In addition, there is no comprehensive and results-based evaluation system for extension workers. This study aims to determine the level of farmers' understanding of agricultural technology packages introduced by agricultural extension workers in Batu Papan Village, Makale District, Tana Toraja Regency. The research uses a descriptive quantitative approach with the object of the study, namely Field Agricultural Extension Workers (PPL) active in Makale District as many as seven people and 139 assisted farmers from six farmer groups. Farmer samples were taken as much as 20% of the population or 30 respondents using census and purposive sampling techniques. Data collection was carried out through a questionnaire with a Likert scale to assess farmers' perception and level of understanding of the implementation of agricultural technology packages. The results showed that the level of farmers' understanding of the technology package introduced by extension workers was in the "very high" category with an index value of 82.6%. These findings show that extension workers have an effective role in increasing farmers' knowledge and involvement. Therefore, it is necessary to strengthen the support of extension facilities and infrastructure, such as technological teaching aids, audiovisual media, and field transportation, to support the optimization of the performance of agricultural extension workers in the region.

This study presents a Systematic Literature Review on Artificial Intelligence (AI) and Natural Language Processing (NLP) applications for customer support automation and digital service optimization. The review follows the PRISMA framework to ensure methodological rigor and transparency, focusing on literature published between 2020 and 2025 from the Scopus database. The findings reveal that AI-driven technologies, including Machine Learning, Deep Learning, and Large Language Models, have significantly improved efficiency, response time, and customer satisfaction in customer support and digital service. Common NLP applications include sentiment analysis, ticket classification, and automated response generation. Among these, hybrid and transformer-based models demonstrate superior accuracy and contextual understanding compared to traditional algorithms. However, several challenges persist, including data quality limitations, privacy and security concerns, algorithmic bias, and linguistic ambiguities such as sarcasm and negation. Moreover, issues related to trust and ethical adoption continue to influence user acceptance of AI systems. This review provides a comprehensive synthesis of current methodologies, trends, and research gaps, offering insights for future studies to develop explainable, secure, and human-centered AI systems that enhance the sustainability and transparency of digital customer support services.

Decision Support Systems (DSS) can become inaccurate when used with imprecise, incomplete, or dynamically changing data. Fuzzy logic techniques based on conventional methodologies may be strong at handling vagueness, but are unable to adapt their behavior in response to different data distributions on their own. This paper recommends the creation of an Adaptive Fuzzy Logic Integration Framework that dynamically updates membership functions and rule weights in response to data variation to enhance decision accuracy under uncertainty. The described framework combines Fuzzy Inference Systems (FIS) with learning-based parameter update concepts borrowed from adaptive optimisation. The model was simulated and executed on a hybrid algorithmic platform that included gradient-based parameter tuning and iterative feedback learning. Experimental tests were conducted on uncertainty-generated data sets to compare adaptive and conventional fuzzy models in terms of ISME (Root Mean Square Error), convergence stability, and decision accuracy. Previous results show that the adaptive model achieves a 21.4% increase in accuracy and a 28% improvement in convergence rate compared to non-adaptive fuzzy systems. Moreover, the model ensures stable performance even in the presence of random data perturbations, demonstrating its ability to handle uncertainty. This book incorporates a self-tuning fuzzy decision model that converts static inference structures to dynamic evolving decision engines. The outcomes establish a foundation for next-generation smart DSS for real-time optimization in uncertainty.

The Impact of Development Trends and Policy Optimization of New Energy Vehicles (NEVs) on Consumer Usage Behavior in Guizhou explores the relationship between the evolving landscape of NEVs and consumer behavior in Guizhou, with a strong emphasis on environmental con-siderations. It argues that as consumers become more aware of environmental issues, their willingness to adopt NEVs increases, influenced by both government policies and social factors.   The study highlights how effective policy optimization—such as financial incentives and educational initiatives—can enhance the adoption of NEVs. Additionally, it underscores the role of social influence in shaping consumer at-titudes and behaviors toward sustainable transportation. By examining these dynamics within the context of Guizhou's natural environment, the research provides valuable insights into creating a more sustainable transportation framework that aligns with both consumer preferences and ecological goals, based on a sample of 390 consumers.

This study aims to analyse the design and optimization of digital marketing to increase the brand awareness of the IdRink MSME through the integration of a website and Instagram. The research employed a Research and Development (R&D) method using the Four-D model (Define, Design, Develop, Disseminate), combined with prototyping techniques and evaluation through blackbox testing. Data were collected through interviews, literature review, observation, Google Analytics, Instagram Insight, and A/B testing questionnaires administered to 100 respondents. The results show that the development of a WordPress-based website and a structured Instagram content plan significantly improved IdRink’s digital performance. Within one month, the audience growth rate increased by 256%, average post reach reached 216%, and website traffic recorded 298 users. Brand awareness measurement indicated brand recognition of 74% and brand recall of 79%, higher than the comparison brand in the local beverage category. These findings indicate that integrating a website and Instagram as a digital marketing strategy is effective in moving IdRink from the unaware-of-brand stage to recognition and recall, expanding market reach, strengthening customer engagement, and building a more professional brand image among young urban consumers. The study recommends maintaining content consistency and utilising digital analytics to support future marketing decision-making.

The advancement of digital technology has driven many service companies to transform toward faster, more efficient, and accurate systems. Himeji Express Banjarmasin, a company engaged in the field of goods delivery services, still faces challenges in data management and service processes that are mostly carried out manually. This condition leads to delays in shipment tracking, data entry errors, and limitations in report generation. To address these issues, a digital application was designed to optimize the delivery service processes at Himeji Express Banjarmasin. The application was developed using the Unified Modeling Language (UML) approach to model system requirements through use case, activity, sequence, and class diagrams. The implementation process utilized Sublime Text and XAMPP software, supported by an integrated database. The results show that the developed digital application can improve the effectiveness of managing customer, employee, pricing, cargo, and transaction data while generating automatic and real-time reports. This application enhances operational efficiency, transparency, and responsiveness to customer needs at Himeji Express.

A digital marketing mentoring program is an effective strategy for increasing the competitiveness of micro, small, and medium enterprises (MSMEs) in the digital economy era. The objective of this community service activity is to strengthen the marketing of the Permata Chips MSME through the utilization of social media, creative content production, and optimization of consistently scheduled online promotions. The methods used in implementing this program include training, direct mentoring, and content implementation to support online promotional activities. Results show a significant increase in promotional reach, more active customer interaction, improved brand perception, and increased transactions and repeat purchases. The implementation of digital marketing also provides benefits in the form of broader market expansion across regions and efficiency in the product offering process. This program is expected to become a model of capacity-based mentoring that can be replicated by other MSMEs, with implications for strengthening marketing accountability and the future sustainability of MSME businesses.

The selection process for prospective cadets at a maritime college is routinely carried out every year. In the current system, the processing and calculation of prospective cadet scores uses Microsoft Excel tools, but this takes a long time and can lead to errors in the calculation of scores and the recapitulation of selection results. In addition, unintegrated data can lead to data duplication, resulting in inaccurate selection results that can be detrimental to prospective cadets. A fast, precise, and accurate integrated decision support system is needed to support the selection process for prospective cadets. The author conducted a study on the prospective cadet admission system at UNIMAR AMNI Semarang using the Multi-Objective Optimization On The Basis Of Ratio Analysis (MOORA) method to assist in the selection of qualified prospective cadets who meet the established criteria. With this decision support system using the Multi-Objective Optimization On The Basis Of Ratio Analysis (MOORA) method, it can be used to solve the selection problem for prospective cadets because it has a short calculation time, is simple, transparent, and has high flexibility. This system will be built using the Codeigniter Framework and a MySQL database.

The rapid development of network infrastructure demands high Quality of Service (QoS), especially in Metro Ethernet networks widely utilized by telecommunication service providers. A primary challenge is efficient bandwidth management to ensure network stability and performance. This research aims to optimize bandwidth management by implementing the Y.1731 method based on Ethernet Operations, Administration, and Maintenance (OAM) on Raisecom devices. The methodology employed is a quantitative experimental approach based on technical simulation within an Professional Network Emulator Tool Lab (PNET Lab), where real-time network performance measurements are conducted using the ITU-T Y.1731 protocol for key parameters such as delay, jitter, and packet loss on Raisecom devices (represented by Cisco routers). The expected outcomes include increased efficiency in bandwidth utilization through more adaptive allocation, comprehensive and accurate real-time network performance monitoring capabilities, validation of OAM functions on Raisecom devices, improved Quality of Service (QoS) and better Service Level Agreement (SLA) attainment, and the provision of technical recommendations for network management. The implementation of Y.1731 is anticipated to quickly detect and respond to service degradation, thereby providing a strong basis for decision-making in network management and contributing to the enhancement of service quality in Metro Ethernet networks through optimization based on proactive monitoring.

The demand for lightweight materials with high mechanical strength has driven the development of aluminum alloys, particularly Al-Mg-Si, through deformation processes such as cold rolling. This study aims to analyze the effect of varying degrees of cold rolling deformation on the grain aspect ratio and macrohardness of homogenized Al-Mg-Si alloys. Deformation was applied at three thickness reduction levels—5%, 10%, and 20%—followed by microstructural characterization using optical microscopy and macrohardness testing in accordance with ASTM E-18 standards. The results show that increasing deformation levels lead to elongated grain morphology, with the grain aspect ratio rising from 1.16 to 2.07 and macrohardness increasing from 46.64 HRE to 62 HRE. The emergence of slip lines and grain flattening indicates the occurrence of intense plastic deformation, while work hardening results from dislocation accumulation that impedes further slip motion. These findings confirm a strong correlation between microstructural evolution and mechanical property enhancement in cold-deformed Al-Mg-Si alloys. This research contributes to the optimization of cold rolling parameters to produce engineering materials with a desirable balance of strength, formability, and fatigue resistance for applications in the mining and heavy manufacturing industries.

Android continues to innovate, and biometric systems particularly fingerprint sensors must operate with high efficiency. However, the main challenge lies in the communication between hardware and software, which often causes high latency, excessive power consumption, and protocol incompatibility between components. As a result, authentication speed decreases and system stability is compromised, especially on mid- to low-range devices. This study explores various implementations of Android-based fingerprint systems, focusing on how sensor modules interact with the microcontroller or Trusted Execution Environment (TEE) and the operating system through a hardware-software co-design approach to evaluate integration efficiency across all layers. The analysis reveals that conventional protocols such as Bluetooth or serial connections still cause delays, while improvements in drivers and the Hardware Abstraction Layer (HAL) can significantly reduce latency. As a solution, the researchers propose a co-design optimization approach that utilizes data flow normalization within the HAL and adopts lightweight communication protocols to accelerate the verification process. Based on the test results, this approach successfully improves efficiency—authentication time is reduced by up to 35% and power consumption decreases by approximately 15%. Therefore, the efficiency of communication between hardware and software becomes a key factor in enhancing the performance and reliability of fingerprint systems on Android devices.

The limitation of physical memory (RAM) is a primary constraint hindering optimal performance in modern operating systems, especially when running large applications or performing intensive multitasking, often resulting in crashes and high latency. This research aims to quantitatively analyze the effectiveness of Virtual Memory (VM) implementation as a solution to this RAM constraint on the Windows 10 operating system, focusing on VM’s impact on CPU performance, GPU performance, and multitasking response. The methodology employed is a controlled experiment using industry-standard benchmarks: Cinebench R20 (CPU), Unigine Heaven (GPU), and response time measurements in intensive multitasking scenarios. Experimental results demonstrate that VM activation improves CPU/GPU performance by up to 5% and accelerates multitasking response time by up to 15%, confirming VM's effectiveness in mitigating memory bottlenecks. Nevertheless, this study also identifies potential performance overhead stemming from excessive paging and swapping processes, which trigger the phenomenon of Thrashing. Therefore, the research recommends a dual optimization strategy to achieve maximum and stable performance: software optimization via the Least Recently Used (LRU) algorithm to suppress page faults, supported by hardware optimization including the use of an SSD for the swap file and increased RAM capacity.

This study aims to analyze and determine the optimal production capacity at Sekar Arum MSMEs to achieve maximum profit using the Linear Programming (LP) graphical approach. The research employed a quantitative method with a descriptive approach. The data used included primary data from interviews and observations, and secondary data from production and raw material records. The analysis was conducted by formulating a mathematical LP model consisting of an objective function and constraint functions based on the limited resources available to the enterprise. Data processing was carried out using POM-QM for Windows version 5 with the graphical method to identify the optimal solution point. The results indicate that the optimal production combination is 2 kilograms of red ginger and 3 kilograms of tamarind turmeric, yielding a maximum profit of Rp4,600,000 per production cycle. The implementation of Linear Programming proved effective in assisting MSME owners in making efficient production decisions, thereby enhancing profitability and the sustainable use of resources.

The Hospital Management Information Sistem (SIMRS) is a key component in the digital transformation of healthcare services, aiming to enhance efficiency and service quality. This study evaluates the implementation of SIMRS at Mutiara Bunda Mother and Child Hospital and explores the challenges and opportunities for improvement. A qualitative case study approach was employed, with data collected through in-depth interviews, observations, and document reviews involving five key informants, including the medical records head, medical service manager, registration officers, and IT staff. The results show that the SIMRS covers registration, procedure input, laboratory, and pharmacy functions. However, issues such as delayed data entry by medical staff, limited equipment, lack of integration across service units, and absence of written user guidelines and regular training persist. The study concludes that although the SIMRS is in use at RSIA Mutiara Bunda, sistem optimization, staff capacity building, and stronger managerial support are crucial to fully realize its potential in improving service quality.

This Community Service Program (PKM) was implemented in Siantar Martoba, Pematangsiantar City, with the aim of enhancing the local economy through empowering farmer groups in optimizing backyard land. The program is a collaboration between Universitas Murni Teguh PSDKU Pematangsiantar, Politeknik Bisnis Indonesia, and the Food Security and Agriculture Office of Pematangsiantar City, attended by 15 farmers on July 4, 2025. The resource person, Henry Dunan Pardede, S.P., M.M., provided training on cultivating high-value crops such as California Papaya and Caplak Chili. The activities consisted of preparation, training, field assistance, and distribution of seedlings. The results showed an improvement in skills, entrepreneurial motivation, and more productive use of backyard land. This program also contributed to the achievement of SDGs point 1 (No Poverty), point 2 (Zero Hunger), and point 8 (Decent Work and Economic Growth) by strengthening the local economy based on agricultural potential. With a community-based approach, this program successfully increased food security, household income, and the sustainability of agricultural practices, while demonstrating the effectiveness of empowerment that can be extended to other areas facing similar challenges.

This study aims to integrate Prophetic guidance (Sunnah of the Prophet Muhammad into the development of a Maqāṣid-Based Budgeting Framework, focusing on the balance between efficiency and social responsibility in Islamic financial management. Using a qualitative thematic approach to relevant hadiths on trust (amānah), professionalism (itqān), prohibition of extravagance (isrāf), and distributive justice, the study reveals that efficiency in Islam extends beyond cost reduction toward the optimization of maslahah ‘āmmah (public welfare). Meanwhile, social responsibility serves as an ethical foundation ensuring fairness, transparency, and accountability in fiscal decision-making. The integration of Prophetic values with theories of Islamic Fiscal Management and Public Finance Efficiency enhances the conceptual strength of Islamic budgeting as a model of balanced financial governance. Thus, budgeting in the maqāṣid and Prophetic perspective is not merely a technical instrument but also a spiritual and social tool for achieving just, efficient, and ethically grounded financial management.

The digital transformation era requires university students to develop digital literacy competencies that not only support academic activities but also serve as essential capital for entering the workforce and pursuing entrepreneurship. One relevant professional platform to enhance career readiness is LinkedIn, which serves as a medium for both personal branding and professional networking. This community service aimed to improve students’ digital literacy and career readiness through mentoring sessions on LinkedIn account optimization. The program involved the students from the English Education (TBI) and Physics Education (TFS) study programs at the Faculty of Tarbiyah and Teacher Training, UIN Palangka Raya, comprising prospective teachers and professionals across various disciplines. The implementation was carried out through tutorials and direct mentoring in two sessions, covering account creation, developing professional headlines and summaries, adding skills and experiences, and uploading simple portfolios. The results indicated that all participants successfully created or improved their LinkedIn profiles, actively engaged in the activities, and demonstrated a greater awareness of the importance of a professional digital identity, which can be seen from the students’ participation, the quality of the profiles produced, and their commitment to continuously developing their LinkedIn accounts. The program highlights LinkedIn’s strategic role in strengthening digital literacy and career readiness among university students in the global era.

This study is a literature review aimed at examining in depth the concepts, characteristics, learning difficulties, and applications of quadratic functions in secondary mathematics education. The research employs a qualitative approach by analyzing ten articles published between 2019 and 2025 from both national and international journals. The findings indicate that the quadratic function is a fundamental topic in the mathematics curriculum, playing a crucial role in developing higher-order mathematical thinking skills such as analysis, synthesis, and problem-solving. It also serves as a foundation for understanding more advanced topics such as calculus, analytic geometry, and optimization. However, various studies have found that students continue to face significant learning difficulties, including misconceptions related to the shape of the parabola graph, understanding the discriminant value, and connecting algebraic forms to real-world contexts. To address these issues, research suggests that technology-assisted learning—particularly through interactive software such as GeoGebra—has proven effective in enhancing conceptual understanding, motivation, and student engagement. Therefore, this review highlights the importance of strengthening conceptual understanding, applying contextual learning approaches, and integrating digital technology as innovative strategies for teaching quadratic functions at the secondary education level.

This study aims to analyze the investment policies in Semarang City, focusing on Regional Regulation Number 9 of 2014 and its execution by the Investment and One-Stop Integrated Services Office (DPMPTSP). Using a descriptive qualitative approach, this research applies the policy implementation theory by Edward III, examining four variables: communication, resources, disposition, and bureaucratic structure. The results show that despite significant efforts to promote investment, the policy implementation still faces various challenges. These include suboptimal communication between agencies, limited human resources (HR) capacity, and misalignment between regional regulations and newer national policies, such as the Omnibus Law and the Online Single Submission (OSS) system. Although Semarang City has great investment potential supported by adequate infrastructure, the realized investment has yet to meet the set targets. Therefore, this study recommends an optimization strategy that includes simplifying licensing procedures, enhancing the capacity of apparatus, harmonizing regulations across government levels, and integrating technology to improve transparency and ease of investment.