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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.

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 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.

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.

Technology-based information systems play an important role in financial management to enhance transparency. Financial transparency is a crucial factor for the sustainability of financial institutions and for building members’ trust. This study aims to analyze the implementation of a technology-based information system in financial management to improve transparency at the Credit Union Savings and Loan Cooperative Bahtera Sejahtera. This research employed a descriptive qualitative approach with data collection techniques including observation, interviews, and documentation. The results indicate that financial management at Credit Union Bahtera Sejahtera has been conducted online using the ESCETE application. Through this application, members are able to independently access financial data, while the financial reporting process is carried out transparently and can be accounted for. Furthermore, financial management is implemented through several stages, including planning and budgeting, recording and processing financial transactions, internal control, reporting and accountability, as well as the application of financial governance and compliance. The implementation of a technology-based information system has proven to enhance transparency, strengthen accountability, and support increased member trust in cooperative management.

This research aims to see the effect of Total Asset Turnover and Debt To Equity Ratio (DER) on Return On Assets (ROA) at PT Indofood Sukses Makmur Tbk which is listed on the BEI in 2010 - 2023. The data used in this research is data secondary in the form of the annual financial report of the company under study. This research uses quantitative data and the data source used is secondary data with an analysis method using multiple linear regression methods with data processing using SPSS v.25. The results of hypothesis testing (T Test) partially state that the Total Asset Turnover variable does not have a significant and positive influence on Return On Assets (ROA) and the Debt To Equity Ratio (DER) variable has a significant and negative influence on Return On Assets (ROA). Simultaneous F Test results of the Total Asset Turnover and Debt To Equity Ratio (DER) variables show a significant influence between Total Asset Turnover and Debt To Equity Ratio (DER) on Return On Assets (ROA).

Digital images often experience noise disturbances that can reduce visual quality and interfere with the image analysis process. One common type of noise is salt and pepper noise, especially in grayscale images, which is characterized by the random appearance of black and white dots. This study applied the Deep Convolutional Autoencoder (DCAE) method with a skip connection mechanism to eliminate salt and pepper noise in grayscale images measuring 256×256 pixels. The dataset used consists of 300 pairs of clean images and noisy images that have gone through the preprocessing stage, including normalization and data augmentation. The model was trained using an Adam optimizer with a Mean Squared Error (MSE) loss function and validated through a train-test split scheme to avoid overfitting. Model performance was evaluated using Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) metrics. The test results showed that the DCAE model with skip connections was able to effectively reduce noise while maintaining the main structure of the image based on the PSNR and SSIM values obtained, and showed better performance than conventional median filters. In addition, the model was successfully implemented into a Streamlit-based application to perform the image denoising process interactively, making it easier for users to experiment and visualize results in real-time.

Elsheskin is a local skincare brand from Yogyakarta, which is under the auspices of PT Elshe Estetika Nusantara. In October 2024, it was circulated that Elsheskin had overclaimed the content of skincare products, because the retinol content in Elsheskin's retinol rejuvenating night serum product was proven to be inconsistent with laboratory test results. This overclaim case has damaged Elsheskin's image. The purpose of this study is to measure Elsheskin's crisis communication in dealing with the case of overclaiming the content of skincare products, Elsheskin's image after conducting crisis communication and how much influence the crisis communication of the case of overclaiming the content of skincare products has on Elsheskin's image. The theory used is the crisis communication theory (Coombs, 2019) which consists of the pre-crisis stage, the crisis event stage and the post-crisis stage. This study also uses the Image theory (Boulding, 2007) which consists of knowledge, feelings, values ​​and beliefs. The method used in this study is a quantitative approach with a survey method and a simple random sampling technique by distributing paper questionnaires to 80 respondents selected according to the characteristics of the study. From the results of calculations and data processing using the SPSS 25 application, namely: a) Elsheskin has carried out crisis communication well in accordance with crisis communication theory. b) Elsheskin has succeeded in restoring its image due to the overclaim case. c) There is an influence of crisis communication in the case of overclaiming skincare product content on Elsheskin's image of 59.2%.

Oil palm plantations constitute a leading subsector that plays a strategic role in regional economic development, particularly in Nagan Raya Regency, which is predominantly based on the agricultural sector. This study aims to analyze the role of the oil palm plantation subsector in promoting regional economic development using the Economic Base Theory as an analytical approach. A descriptive qualitative method with a literature study was employed. The data used consist of longitudinal secondary data for the period 2019–2024, sourced from official publications of Statistics Indonesia, regional development planning documents, and relevant scientific articles. The results show that the agricultural sector, dominated by the oil palm plantation subsector, makes a large and relatively stable contribution to the Gross Regional Domestic Product (GRDP) of Nagan Raya Regency, thereby qualifying it as a basic sector. This subsector also plays an important role in employment absorption, particularly in rural areas. However, the substantial economic contribution and labor absorption have not been fully accompanied by equitable improvements in community welfare, as indicated by the relatively slow decline in poverty rates. This condition suggests that the economic multiplier effect of the oil palm plantation subsector has not yet been optimal due to limited downstream activities and low value-added processing at the regional level. The study concludes that strengthening downstream industries and intersectoral linkages is necessary to ensure that the role of oil palm plantations can more effectively support inclusive and sustainable regional economic development.

This study aims to analyze the effectiveness of bulk cement loading processes on the operational performance of vessels agented by PT. Pelayaran Multi Jaya Samudera Belawan. Bulk cement loading is a complex logistical activity at specialized port terminals that requires intensive coordination between the vessel, agency, and terminal to comply with international safety standards such as the IMSBC Code. The research method used was descriptive qualitative, with data collection techniques including direct field observations, interviews with the company's operational staff, and documentation studies conducted during the internship period. The research findings indicate that loading effectiveness is significantly influenced by the readiness of cargo handling equipment, such as pneumatic or conveyor systems, as well as the timeliness of agency administration in processing ship documents. Although the process generally runs well, obstacles were identified in the form of technical malfunctions of loading equipment and weather factors that frequently hinder operational speed. The conclusion of this research emphasizes that enhancing technical supervision and strengthening communication between the agent and port terminal authorities are crucial to minimizing vessel dwelling time, thereby optimizing operational performance and cost efficiency for ship owners.

This study aims to examine the effect of work motivation and work environment on employee performance at Wijaya Kusuma School, North Jakarta, both partially and simultaneously. This research employed a quantitative approach using a survey method. The population consisted of all employees of Wijaya Kusuma School, North Jakarta, with a total sample of 87 respondents selected using a saturated sampling technique. Data were collected through questionnaires that had been tested for validity and reliability. The data analysis techniques included instrument testing, classical assumption tests, and hypothesis testing using multiple linear regression analysis, F-test, t-test, and coefficient of determination. Data processing and analysis were conducted using SPSS version 25. The results indicate that work motivation has a positive and significant effect on employee performance. In addition, the work environment also has a positive and significant effect on employee performance. Simultaneously, work motivation and work environment significantly influence employee performance at Wijaya Kusuma School, North Jakarta. These findings suggest that improving employee motivation and creating a supportive and conducive work environment are essential strategies for enhancing employee performance in educational institutions.  

Strategies to increase the income of self -help palm oil farmers can help farmers to increase production yields. This study aims to formulate and obtain strategies in an effort to increase the income of oil palm farmers. This research was conducted in Kalis District, Kapuas Hulu Regency. This study was carried out from April 5 to May 524. This study used a descriptive quantitative method with case study methods and identified internal factors (strengths and weaknesses) and external (opportunities and threats) used for the strategy to increase the income of oil palm farmers in the sub -district dull. The variables used in this study were obtained from indicators of strengths, weaknesses, opportunities and threats. Based on the results of the research results of the collection, processing and analysis of the main internal factors, it is found that the main strength factor of farmers is the status of land ownership and land area owned by farmers with a weight score of 0.41. As for the main weakness of self -help farmers is inadequate access to infrastructure with a weight score of 0.18 and the total score of the IFE matrix is ​​2.51. For data analysis of the main external factors, it is found that the main opportunity factor of farmers is oil palm can be a term investment for farmers with a weight score of 0.41. As for the main threat of self -help farmers is a long queue at the Palm Oil Mill (PKS) with a weight score of 0.18 and the total score of the IFE matrix is ​​2.62. The results of processing internal and external data of farmers using the IE matrix show that the position of farmers is in quadrant I, the suitable strategy is an aggressive strategy that can support the growth of oil palm farming.

 Road infrastructure development is an important factor in supporting community mobility and equitable regional development. However, road construction data management in Palembang City still faces various problems, such as scattered data, lack of integration, and not yet presented in a map-based visual form. This study aims to implement a Geographic Information System (GIS) as a medium for location mapping and presenting road construction data information in Sematang Borang and Kalidoni Districts, Palembang City. The methods used include field observation, road construction data collection and verification, GPS coordinate point retrieval, spatial and non-spatial data processing, and the development of a GIS system based on interactive digital maps. The results of the study indicate that the system is able to present road construction information in a structured, accurate, and easily accessible manner. This GIS helps improve the efficiency of the monitoring process, data management, and preparation of road construction reports at the Palembang City Public Works and Housing Agency. Thus, the application of GIS can be a supporting solution in decision-making and encourage the digitalization of road infrastructure data management.

This article aims to analyze the implementation of tax planning by CV. Sukses Mitra Sejahtera in reducing Corporate Income Tax liabilities. The research employs communication and observation methods, with data collected through interviews, company documentation, literature study, and online information searching. The collected data were then analyzed using a qualitative descriptive approach, focusing on the processing of commercial and fiscal financial reports. The findings indicate that the company has not fully implemented tax planning optimally. However, the existing tax planning strategy has shown positive results, with a tax burden saving of IDR 3,994,865 or approximately 5.05% of the total income tax payable. These results demonstrate that, although not fully effective, tax planning can significantly contribute to reducing the company's tax burden. Therefore, tax planning proves to be an essential tool in enhancing the efficiency of tax liabilities, which can help companies achieve better and more sustainable financial management. This study provides valuable insights for other companies in implementing tax planning to maximize their tax savings.

The decline in service quality observed in 2023, such as frequent malfunctions of queue management machines and slow credit processing, indicates that the implementation of Total Quality Management (TQM) at PT Bank Pembangunan Daerah Sulawesi Tenggara, Wakatobi Branch, has not been fully optimized. These issues are particularly evident in aspects of continuous improvement, employee education and training, long-term management commitment, and employee involvement and empowerment. Therefore, this study aims to analyze the effect of Total Quality Management implementation on employee performance at PT BPD Sultra Wakatobi Branch. This research was conducted from February to August 2024 in Wangi-Wangi Regency. The study employed a quantitative research design using a census approach, in which all 40 employees were included as respondents. The data used in this study consisted of primary data collected through questionnaires and secondary data obtained from company documents. Descriptive analysis and Structural Equation Modeling–Partial Least Squares (SEM-PLS) were applied to examine the relationship between TQM and employee performance. The results reveal that long-term management commitment as well as employee involvement and empowerment have a significant effect on employee performance. In contrast, continuous improvement and education and training do not show a significant influence, indicating the need for further evaluation and improvement to strengthen the future implementation of Total Quality Management and enhance organizational performance.

The rapid advancement of Information and Communication Technology (ICT) has accelerated the digital transformation of public services, including land administration. However, public complaint services at the Land Office of Southwest Sumba Regency still encounter challenges such as unstructured complaint procedures, manual data processing, risk of data loss, and limited public access to clear information. These issues highlight the need for an innovative and accessible complaint information system. This study aims to design and implement a chatbot-based public complaint service information system to enhance accessibility, transparency, and service effectiveness. A qualitative research method with a system development approach was applied. Data were obtained through interviews, observations, and documentation. The system was developed using a rule-based approach with a Finite State Machine (FSM) algorithm and implemented through the Typebot.io platform. The findings indicate that the chatbot provides structured, consistent, and user-friendly information, reduces manual workload, and improves public readiness before submitting complaints directly, while supporting future integration and system enhancement.