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The transition toward sustainable energy systems requires the transformation of renewable energy marketing strategies, particularly for waste-based energy. This study aims to analyze the effects of green marketing, stakeholder collaboration, and technological innovation on the marketing effectiveness of waste-based energy, with customer satisfaction as an intervening variable. A quantitative approach with a survey design was used. Data were collected from 300 respondents, comprising consumers and stakeholders at PT PLN (Persero) ’s waste-based energy processing units. Structural Equation Modeling (SEM) was used to analyze the data. The results indicate that green marketing, stakeholder collaboration, and technological innovation significantly influence customer satisfaction and the effectiveness of marketing. Furthermore, customer satisfaction significantly mediates the relationship between independent variables and marketing effectiveness. These findings emphasize the importance of integrating sustainable marketing strategies, multi-stakeholder synergy, and innovative technologies to enhance the competitiveness of waste-based energy products in the market. This study contributes to the theoretical development of renewable energy marketing models and provides practical implications for policymaking and green energy marketing strategies in Indonesia.

This research is motivated by the negative impacts of production activities at a manufacturing company engaged in rubber processing, specifically at PTPN VII Unit Pematang Kiwah Natar, South Lampung. The factory's operations directly impact the environment, generating noise pollution, air pollution, unpleasant odors, and liquid waste. This situation requires the company to implement Environmental Management Accounting (EMA) to balance business sustainability with social and environmental responsibility. This is in line with Law No. 40 of 2007 concerning Limited Liability Companies and PSAK 1 of 2021. The main objective of the study was to evaluate the suitability of the implementation of environmental management accounting at PTPN VII Uni ;t Pematang Kiwah Natar, South Lampung, based on the International Guidance Document IFAC 2005 and PSAK 1 of 2021. This study used a qualitative descriptive method. Primary and secondary data were collected through interviews, observation, and documentation. The research results show that the company has implemented environmental management accounting using PSAK 1 of 2021, where the company has fulfilled the identification, presentation, measurement, recognition, and disclosure stages using the 2022 sustainability report and the 2022 financial statements of PTPN VII. Furthermore, PTPN VII Unit Pematang Kiwah Natar, South Lampung, has classified environmental costs by allocating environmental costs based on the International Guidance Document IFAC 2005 and Ikhsan (2008). Therefore, PTPN VII Unit Pematang Kiwah Natar, South Lampung, has demonstrated its commitment to environmental regulatory compliance.

Inconsistent terminology across cybersecurity frameworks undermines global governance and interoperability. The National Institute of Standards and Technology Cybersecurity Framework (NIST CSF 2.0) and ISO/IEC 27001:2022 share similar objectives but diverge semantically in defining risk, control, and resilience. This semantic gap causes difficulties in compliance mapping and automated policy translation. Research Objectives: This study aims to analyze the semantic similarity and divergence between NIST and ISO/IEC 27000 terminologies, identify conceptual structures influencing interoperability, and propose an AI-assisted foundation for harmonizing cybersecurity language globally. Methodology: A mixed-method semantic comparative design integrates Natural Language Processing (NLP) and ontology mapping. Using the nist_glossary.csv dataset and ISO vocabularies, terms were normalized and analyzed via cosine similarity using sentence-transformer embeddings. Ontological alignment was visualized through the Semantic Threat Graph (STG) and validated by certified experts using Cohen’s Kappa reliability tests. Results: From 672 term pairs, results show 40.9% high semantic equivalence, 38.8% partial overlap, and 20.3% semantic divergence. Strongest alignment appears in “Protect” and “Identify” domains, while divergences occur in governance and recovery-related terms. Ontology mapping revealed three conceptual clusters—Risk Governance, Technical Safeguards, and Organizational Readiness. Conclusions: Findings confirm a 79.7% total semantic alignment, indicating strong potential for harmonizing global cybersecurity standards. The study contributes an empirical model combining computational linguistics and AI-based ontology mapping to establish semantic interoperability, enabling unified cybersecurity governance and AI-driven compliance automation. Keywords: Semantic Interoperability; Ontology Mapping; Cybersecurity Frameworks; Terminology Alignment; AI Harmonization

This research aims to determine the influence of e-commerce and accounting information systems (AIS) on entrepreneurial decision making among accounting students at the economics and business faculty, Nusa Nipa University, Maumere. The type of research used is quantitative research. This research data method uses primary data which means the respondents' answers to the questionnaire statements distributed and then measured using a Likert scale. The total sample was 38 accounting student respondents. The data collection technique is by distributing questionnaires using Google Forms which have been tested for validity and reliability, multiple linear regression analysis tests, hypothesis testing via the t test and f test, as well as the coefficient of determination (R2). In processing the data using SPSS version 23. Based on the research results, E-Commerce has a positive and significant effect on Decision Making for Entrepreneurship, the Accounting Information System has a positive and significant effect on Decision Making for Entrepreneurship, E-Commerce and the Accounting Information System together have a positive effect on Decision Making for Entrepreneurship.

Seren Village has abundant organic waste potential, particularly banana peel waste generated from banana-processing MSME activities and wood ash resulting from household firewood combustion. To date, this waste has not been optimally utilized and is often discarded, thereby posing potential environmental problems. This study aims to process banana peel waste and wood ash into an innovative, environmentally friendly shoe polish made from natural materials, while also enhancing the economic value and welfare of the community. The research employed a descriptive qualitative method with a case study approach. Data were collected through observation, interviews, and documentation involving the women’s Family Welfare Empowerment Group (PKK) of Seren Village as the target participants. The shoe polish production process includes drying and grinding banana peels, mixing them with a wood ash solution that functions as a natural coloring agent, adding supporting materials, and heating the mixture until a ready-to-use shoe polish is obtained. The results indicate that the shoe polish produced from banana peels and wood ash has a solid texture, is slightly coarse, non-glossy, and has a relatively fast drying time of approximately one minute. In addition, the product shows good resistance to water splashes and does not damage the surface of shoes. The use of natural ingredients makes this shoe polish safer for health. The utilization of this waste has the potential to support MSME development, reduce environmental pollution, and sustainably improve the welfare of the Seren Village community.

This study aims to analyze the role of local Micro, Small, and Medium Enterprises (MSMEs) in utilizing lemongrass (Cymbopogon citratus) as the main ingredient for mosquito repellent products and its contribution to improving the economy of the community in Timbang Jaya Village. Lemongrass contains essential oils that function as a natural insect repellent, making it a potential raw material for value-added products such as mosquito repellent sprays, aromatherapy candles, and herbal lotions. This research employed a descriptive qualitative method with data collected through interviews, observations, and literature studies. The findings indicate that local MSMEs play a significant role in the production process, product innovation, and marketing of lemongrass-based products. Besides generating additional income, this development also creates new job opportunities and supports the village’s economic independence. However, several challenges remain, including limited capital, lack of processing technology skills, and competition with chemical-based products. The recommended solutions include capacity building through training and mentoring, better access to funding, and strengthening digital marketing strategies. Therefore, the development of mosquito repellent products from lemongrass by MSMEs not only contributes to the community’s economic growth but also provides an environmentally friendly alternative beneficial for public health.

Information systems are an important element in the business world that helps businesses increase work efficiency and reduce human error. In practice, many businesses still produce financial reports manually. Manual preparation of financial reports is inefficient and tends to have a higher potential for delays, lateness, or errors in data entry. This makes the financial reports presented inaccurate and unreliable as a basis for making decisions. To address this problem, a community service program was implemented by designing an accounting system using Microsoft Access, which provides various features that can help users in data processing. The method carried out starts with observation, system design, and evaluation by the partner. The result of implementing this program is that the system designed in Microsoft Access successfully accelerated the work process for partners, making the preparation of financial reports more efficient and timely. The financial reports presented also became more accurate and reliable.      

As a manufacturing company engaged in the processing of copper and wire products, PT Tembaga Mulia Semanan, Tbk requires human resources with optimal performance to support the achievement of organizational goals. This study aims to examine the effect of work motivation and work environment on employee performance at PT Tembaga Mulia Semanan, Tbk. This research employed a quantitative approach with data collection conducted through questionnaire distribution. The research population consisted of all employees of the South Continuous Rod (SCR) Division, totaling 65 employees, with a sample of 42 respondents. The collected data were analyzed using multiple linear regression analysis with the assistance of SPSS software. The results of the t-test indicate that work motivation partially has a positive and significant effect on employee performance, as shown by a t-value of 4.265 which is greater than the t-table value of 2.022, with a significance level of 0.000 < 0.05. The work environment also partially has a positive and significant effect on employee performance, indicated by a t-value of 6.080 which is greater than the t-table value of 2.022 and a significance value of 0.000 < 0.05. Furthermore, the F-test results show that work motivation and work environment simultaneously have a positive and significant effect on employee performance. The coefficient of determination (R²) of 63.52% indicates that variations in employee performance can be explained by work motivation and work environment, while the remaining percentage is influenced by other factors outside this study.

This research aims to analyze the structure and identify various forms of linguistic errors found in students’ research reports. A qualitative approach with a descriptive method was employed, using documentation studies on three different students’ research reports as the primary data. The findings indicate discrepancies in the text structure, such as unsystematic composition of the introduction, methodology, results, discussion, and conclusion sections. Furthermore, various linguistic errors were identified, including spelling, punctuation, diction, ineffective sentence construction, and inconsistencies in citations and references. Other identified issues include content duplication, technical errors in word processing features, and lack of relevance in the theoretical review. The implications of this research emphasize the necessity of improving the quality of research report writing through strengthened academic writing curricula, structured mentoring, the use of reference management technology, and a disciplined scientific literacy culture. This study is expected to serve as an evaluation tool for students, lecturers, and study programs to enhance the standards of scientific writing in higher education.

The purpose of this study is to describe the marketing strategies and adaptability of “cakar bongkar” (second-hand clothing) traders in responding to market dynamics in Nabire City. This study employs a qualitative approach, as it is appropriate for addressing research problems that require an in-depth understanding of the socio-economic realities in Kalibobo Market and Karangtumaritis Market in Nabire City. The data used in this study consist of primary data as the main source and secondary data as supporting and relevant information. Data collection methods are carried out using the triangulation principle, namely through direct observation, in-depth interviews, and documentation. Informants are selected using snowball sampling and purposive sampling methods to obtain comprehensive and representative information. Data processing and analysis are conducted through the stages of data reduction, data presentation, and systematic conclusion drawing. The results of the study indicate that the informants apply five (5) marketing strategies in selling second-hand clothing (cakar bongkar), namely: (1) sourcing strategies, (2) pricing and promotion strategies, (3) word-of-mouth marketing strategies, (4) strategies for building social relationships with customers, and (5) product display strategies using prototype tables to attract consumer attention.

This study aims to analyze the influence of e-marketing and customer engagement on marketing performance. Analyze the influence of e-marketing and customer engagement, customer trust on marketing performance. The sample size was 78 respondents using SEM PLS for data processing. The findings of this study are that there is a significant positive influence between e-marketing on marketing performance; there is a significant positive influence between customer engagement on marketing performance; there is a significant positive influence between e-marketing on customer trust; there is a significant positive influence between customer engagement on customer trust; there is a significant positive influence between customer trust; on marketing performance

Measuring coal volume in the Stock ROM area played an important role in production control and mining evaluation. This research was conducted in the Stock ROM area at PT. Victor Dua Tiga Mega, where volume measurements were generally carried out using Total Station (TS) as the main method, howefer the use of Unmanned Aerial Vehicles (UAV) has begun to be implemented as a more efficient alternative. This study aims to compare the results of Stock ROM coal volume calculations using the Total Station and UAV methods. The research method was carried out by collecting data in the field, processing the digital Elevation Model (DEM), and calculating the volume using the Cut and Fill method. The results of the study the difference in volume between the two methods, where the UAV measurement results tend to be greater than those of the Total Station. The difference in Fine Coal volume was 724,15 m3 or 16,74% and Raw Coal volume of 9.335,98 m3 or 8,03%. Based on a comparison with weighing data, measurements using the Total Station provided results that were closer to the actual conditions in the field.

Geographic Information Systems (GIS) based on ArcGIS are crucial tools for analyzing and visualizing the equitable distribution of Land and Building Tax (PBB) in Nabire Regency. This research aims to design a comprehensive spatial infographic that illustrates PBB distribution and assists the Nabire Regency Revenue Agency (Bapenda) in identifying potential areas for increased revenue. Through the processing of spatial and non-spatial data, the study reveals significant imbalances in PBB collection across different regions, with urban and economic centers showing higher achievements compared to peripheral areas. The resulting thematic maps and pie diagrams effectively visualize the proportion of PBB potential versus realization, highlighting areas with untapped tax potential. These findings underscore that geospatial visualization not only aids in making fair and equitable fiscal policies but also plays a strategic role in raising public awareness and participation in PBB payments, aligning with principles of fiscal justice and optimalization of Local Own-Source Revenue (PAD).

The proliferation of cloud infrastructures has intensified concerns regarding data security, integrity, identity and access management, and user privacy. Despite recent advances, existing solutions often lack comprehensive integration of privacy-preserving mechanisms, dynamic trust management, and cross-provider interoperability. This study proposes an AI-enabled, zero-trust, blockchain-fused identity management framework for secure, privacy-preserving multi-cloud environments. The framework integrates homomorphic encryption with differential privacy for aggregate-level protection and secure multi-party computation for collaborative data processing. The proposed system was validated in a simulated multi-cloud environment using CloudSim, Ethereum blockchain, and AWS EC2. Experimental results indicate homomorphic encryption latency of approximately 450ms per operation and statistically significant security improvements (t(128) = 12.47, p < 0.001), privacy (t(95) = 8.93, p < 0.001), and throughput (t(156) = 15.21, p < 0.001). The framework achieved differential privacy with ε = 0.1 while retaining 99.2% data utility, and demonstrated a 34% improvement in processing speed over conventional differential privacy approaches. In addition, the implementation was observed to be 2.3× faster than BGV-based configurations, with 45% lower memory consumption than CKKS and a 67% reduction in ciphertext size relative to baseline implementations. From an operational perspective, the framework shows a 23% reduction in security management costs, a 31% improvement in resource utilization efficiency, and an 18% decrease in compliance audit expenses. The model further indicates a 27% reduction in total cost of ownership (TCO) compared with multi-vendor security solutions, a projected return on investment (ROI) within 14 months, and an 89% reduction in security incident response costs under the evaluated conditions.

Fully Homomorphic Encryption (FHE) enables computation on encrypted data with end-to-end confidentiality; however, its practical adoption remains limited by substantial computational costs, including long encryption and decryption times, high memory consumption, and operational latency. Zero-Knowledge Proofs (ZKPs) complement FHE by enabling correctness verification without revealing sensitive information, although they do not support encrypted computation independently. This study integrates both techniques to enable encrypted computation with verifiably consistent results. A prototype system is implemented in Python using Microsoft SEAL for homomorphic encryption and PySNARK for Zero-Knowledge Proof verification. Experiments are conducted on standard consumer-grade hardware (Intel i5, 8 GB RAM, Ubuntu 22.04) using datasets ranging from 100 MB to 1 GB. The evaluation focuses on encryption and decryption time, homomorphic computation latency, memory usage, and proof generation overhead. Experimental results show that integrating ZKPs introduces a moderate and stable runtime overhead of approximately 15–20%, as analyzed in Section 4, while enabling verification without plaintext disclosure. Ciphertext expansion remains a notable limitation, with observed growth of approximately 30–40× relative to plaintext size, consistent with prior FHE implementations. Despite these overheads, the system demonstrates feasible scalability for datasets up to 1 GB on mid-level hardware. Overall, the results indicate that the integrated FHE+ZKP approach provides a practical balance between confidentiality, verifiability, and performance, supporting its applicability to privacy-preserving scenarios such as secure cloud computation, encrypted data analytics, and confidential data processing under realistic resource constraints.

Improper water management in rice cultivation can lead to water stress, which reduces productivity. Conventional monitoring has limitations on large-scale lands, necessitating more efficient remote sensing technologies. This study aims to develop a water stress identification system for rice plants in the late vegetative phase using multispectral drone imagery integrated with an Artificial neural network (ANN). The research method employs an experimental approach with six water availability levels in Karyamukti Village, Sumedang. Field reference data were obtained through soil moisture sensors converted into Available Water (AW) values. Image processing stages included orthomosaic reconstruction, leaf object segmentation, and transformation of vegetation indices (NDVI, NDRE, GNDVI, etc.) as model inputs. The results show that the ANN model with a four-hidden-layer architecture achieved training and validation accuracies of 94–95%. In the independent testing phase, the model produced an accuracy of 94.60% with an F1-Score of 93.33%. Spatial visualization of the prediction results indicates a consistent water condition distribution across rice plots. In conclusion, the integration of multispectral drones and ANN provides an accurate non-destructive solution for spatial monitoring of water availability in rice plants.

The spread of hoax news in digital media is a serious problem because it can affect public opinion and social stability. This study aims to classify hoax news using the Support Vector Machine (SVM) algorithm. The dataset used is a hoax clarification dataset from the Ministry of Communication and Digital (Komdigi) of the Republic of Indonesia, totaling 1,872 data. The research process includes data collection, text pre-processing, feature extraction using TF-IDF, and classification using the SVM algorithm. Implementation was carried out using Google Colaboratory (Google Colab). Test results show that the SVM algorithm is able to provide good performance in classifying hoax news based on its topic with satisfactory accuracy, precision, recall, and F1-score values.

This study is motivated by the importance of systematic evaluation in ensuring the quality and effectiveness of the implementation of educational programs, particularly the Al-Qur'an Halaqah Program as a means of developing the ability to read and memorize the Al-Qur'an and shaping the religious character of female students. This study aims to identify the gap between the established standards and the actual implementation of the program using the Discrepancy Evaluation Model (DEM). The approach used is qualitative evaluative with five stages of evaluation, namely design, installation, process, product, and comparison. Data was obtained through interviews, observations, and documentation studies, then analyzed through the stages of data collection, processing, presentation, and conclusion drawing using triangulation techniques. The results showed that the design and installation stages met the standards, while in the process stage, a gap was found in the consistency of female student attendance. In the product stage, the success rate reached 93.48%, but there was still an imbalance in memorization achievement. The implication is that the program should be continued with strengthened attendance monitoring and individual mentoring strategies to improve the equity of outcomes and the sustainability of the program.

Cassava is one of the strategic agricultural commodities in Indonesia, contributing significantly to national production, particularly in several major producing provinces. In addition to the challenge of declining harvested areas, cassava processing activities also generate agricultural waste that poses environmental risks. In Purwasari Village, Dramaga Subdistrict, Bogor Regency, household-scale cassava processing industries produce solid waste in the form of cassava peels, which are not optimally managed and are commonly discarded in the surrounding environment. This cassava waste has the potential to cause environmental pollution, unpleasant odours, and negative impacts on public health. One sustainable alternative for managing this cassava waste is the use of cassava peels as a raw material for composting. This study aimed to identify problems associated with cassava peel waste and to assess members of the Taruna Tani Millennial Farmer Group's interest in compost production using cassava peels. The research was conducted from December 2024 to June 2025 using a community-based assistance approach. Data was collected through interviews and questionnaires involving 20 respondents. The results showed that the main problems associated with cassava peel waste include waste accumulation, limited processing facilities, and low community awareness. Farmers’ interest in cassava peel composting was generally categorized as high, with an average score of 77%, although several indicators remained at a moderate level. Extension activities and hands-on demonstrations were proven to enhance farmers’ understanding, interest, and participation. With sustained educational support and adequate facilities, the use of cassava peel compost has strong potential to promote environmentally friendly, sustainable agricultural waste management.

This study examines the utilization of Aloe vera as a herbal medicine by the community of Sobawagoli Village, Indonesia. The research aims to document local knowledge related to the processing, application, and perceived benefits of Aloe vera in traditional healthcare practices. A qualitative descriptive approach with a case study design was employed. Data were collected through direct field observations, in-depth interviews with community members, and documentation of preparation methods. The findings reveal that Aloe vera is widely used for both internal and external treatments, including digestive disorders, internal heat, hypertension, burns, skin inflammation, and natural skin and hair care. The plant is processed through simple methods such as boiling, blending, and direct topical application, reflecting the accessibility and practicality of herbal medicine in rural settings. Community perceptions toward Aloe vera are highly positive, viewing it as a safe, effective, and culturally embedded alternative to chemical medicines. These practices are supported by empirical experiences and align with recent scientific studies highlighting the therapeutic properties of Aloe vera. The study underscores the importance of preserving indigenous herbal knowledge and integrating it with modern health education to promote sustainable, community-based healthcare systems.