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The development of technology in the digital era has significantly altered consumer behavior, particularly for Generation Z, who are known as digital natives. This group possesses unique characteristics, highly relying on social media to seek product information before making purchasing decisions. This study aims to analyze digital marketing management strategies through social media in enhancing brand engagement and loyalty among Generation Z consumers, as well as to identify the key determinants of its success. The research method employed is descriptive qualitative, utilizing literature review as the data collection technique across prior scientific sources. The analysis reveals that the implementation of digital marketing strategies based on visual content and short-form videos on platforms such as TikTok and Instagram is proven to be highly effective in capturing the audience's attention rapidly. In addition to content format, collaboration with highly credible influencers and the application of authentic, responsive two-way communication serve as the main pillars in building emotional proximity and trust among young consumers. Operationally, this strategy offers cost efficiency and a broader market reach. The conclusion of this study emphasizes that the optimal integration between management information systems and interactive, adaptive communication approaches toward digital trends is the main key to winning the market and sustaining the long-term loyalty of Generation Z.

The digitalization of tax administration has become one of the Indonesian government's strategic initiatives to improve efficiency, transparency, and taxpayer compliance. However, the implementation of digital tax systems among Micro, Small, and Medium Enterprises (MSMEs), particularly distributor-sector MSMEs in Batam City, still faces various administrative and technical challenges. This study aims to examine the experiences, risk perceptions, and adaptation strategies of distributor MSME actors in responding to the digitalization of tax administration following the implementation of the Harmonization of Tax Regulations Law (UU HPP). The research employed a qualitative approach using a phenomenological method. Data were collected through in-depth interviews with seven distributor MSME owners in Batam City who had utilized digital tax systems such as e-Filing and Coretax. The findings indicate that most business actors still experience limitations in technical understanding, concerns regarding reporting errors, and difficulties adapting to changes in digital tax systems and regulations. To address these challenges, MSME actors developed several adaptation strategies, including the use of tax consultants, hybrid manual-digital bookkeeping systems, and informal assistance through the internet and business networks. This study highlights that the success of tax digitalization requires a more adaptive approach, stable systems, and policies that are aligned with the characteristics of local MSMEs.

This study aims to analyze the effect of cutting parameters on surface roughness in the turning process of AISI 1045 steel. The investigated parameters include cutting speed, feed rate, and depth of cut. A quantitative approach was employed using multiple linear regression analysis with SPSS software. The dataset consisted of 30 simulated experimental observations with varying cutting parameter conditions. Prior to regression analysis, classical assumption tests including normality, multicollinearity, and heteroscedasticity tests were conducted to ensure the validity of the model. The results indicated that all assumptions were satisfied. The findings reveal that simultaneously, all independent variables have a significant effect on surface roughness with a coefficient of determination of 82.1%. Partially, Feed rate and cutting speed significantly influence surface roughness, while depth of cut does not show a significant effect. Feed rate is identified as the most dominant variable affecting surface roughness, where an increase in Feed rate leads to higher roughness values. In contrast, increasing cutting speed tends to reduce surface roughness. This study highlights the importance of controlling cutting parameters, particularly Feed rate and cutting speed, to improve machining quality. The results provide practical implications for manufacturing industries in optimizing machining parameters to achieve better surface quality and process efficiency.

Digitalization in the fitness industry is increasingly essential to improve efficiency and service quality. However, many fitness centers still manage data manually, including KRESNA GYM, which faces challenges in member registration, workout scheduling, and facility information delivery. This study aims to design a web-based e-fitness application using the Laravel framework to support digital service management. The development follows the Waterfall model through stages of requirement analysis, design, implementation, testing, and evaluation. The application includes features such as a landing page, admin/member login and registration, management dashboards, workout schedules, equipment guides, and supplement listings. Black-box testing confirms that all features function as expected. This system simplifies administrative processes and enhances member experience, making it effective in supporting digital transformation at KRESNA GYM.

Malware represents an evolving cybersecurity threat that demands more effective detection methods. Conventional signature-based detection systems have limitations in identifying new variants, driving the development of deep learning-based approaches. This research implements and evaluates four variants of the YOLOv11 algorithm (n, s, m, l) for malware classification based on visual image representation. The dataset consists of 22,056 malware and benign images, divided into 70% training, 15% validation, and 15% testing across 8 classes (adware, backdoor, benign, downloader, spyware, trojan, virus, worm). Each model was trained for 100 epochs with batch size 32 using Google Colab with GPU support. Results demonstrate that all variants achieve high accuracy (97.8%-98.1%) with YOLOv11m as the best performer (98.1%). YOLOv11n offers optimal balance between accuracy (97.9%) and efficiency (1.5M parameters, 0.3 ms/img inference) ideal for real-time applications. This research surpasses previous methods such as K-NN (97.18%) and hybrid CNN (96.55%) with superior inference speed (0.3-0.9 ms/img vs tens to hundreds of ms/img), proving the effectiveness of YOLOv11 for fast, accurate, and scalable malware detection.

The thesis supervision process in higher education institutions is still frequently conducted manually, which may lead to inefficiencies in recording supervision data. This study focuses on the development and implementation of a web-based thesis supervision attendance application designed to facilitate attendance documentation, supervision session administration, and systematic monitoring of thesis supervision history. The methodology applied in this study is the Waterfall model, which includes the phases of requirements analysis, system design, implementation, and testing. The application was developed using the Laravel framework and a MySQL database. The system design was modeled using Unified Modeling Language (UML), while the validation process was conducted through Black Box Testing techniques. The research findings indicate that the developed application is capable of performing real-time supervision attendance recording, managing supervision information, and generating attendance reports effectively and efficiently. It can be concluded that the web-based thesis supervision attendance application improves the efficiency and accuracy of supervision record management and supports a more effective thesis supervision monitoring process..

Batik motif classification has attracted growing attention in visual computing due to its role in cultural heritage preservation, textile informatics, museum documentation, and automated cataloging. Although many studies report high classification accuracy, robustness under real-world acquisition conditions remains insufficiently understood. Batik images are frequently affected by illumination variation, blur, folds, watermark overlays, wearable deformation, scale inconsistency, and background clutter, creating challenges that extend beyond conventional image-noise assumptions. Existing studies largely focus on improving classification performance, while the interactions among acquisition variability, feature representation, evaluation practice, and deployment constraints remain fragmented. This systematic literature review addresses this gap by synthesizing batik classification research through a robustness-aware perspective. Using query expansion, backward and forward citation chaining, relevance screening, and thematic coding, 116 candidate records were identified, resulting in 50 highly relevant studies for detailed analysis. The review reveals that robustness is shaped less by denoising alone than by the combined effects of acquisition conditions, representation design, evaluation realism, and deployment context. Handcrafted descriptors remain competitive for small datasets and structured motifs due to their data efficiency and interpretability, whereas deep learning models achieve the highest reported accuracy when supported by sufficient data diversity and realistic augmentation. Hybrid representations emerge as the most consistently balanced approach, combining local texture stability with higher-level abstraction across heterogeneous acquisition settings. The review further identifies recurring robustness failure patterns, including background dependency, illumination instability, motif-scale inconsistency, wearable deformation, and source-shift vulnerability. Based on these findings, a robustness-oriented research agenda is proposed, emphasizing cross-acquisition evaluation, representation-stability analysis, batik-specific robustness benchmarks, acquisition-aware augmentation, and deployable lightweight or hybrid architectures. The study contributes a domain-specific synthesis that reframes batik motif classification from an accuracy-centric task toward a robustness-aware visual recognition problem.

This study examines the transformation of financial management through the implementation of digital accounting in PPOB (Payment Point Online Bank) businesses, which still face manual recording problems such as input errors, delayed reconciliations, and data discrepancies. The research used a descriptive qualitative method with a case study approach involving PPOB agents in Sidoarjo. Data were collected through observation, interviews, and documentation. The findings show that digital accounting significantly improves operational efficiency through automated transaction recording, real-time data integration, and faster as well as more accurate reconciliation processes. In addition, features such as automatic validation, API integration, and audit trails help minimize recording errors and maintain data consistency. The implementation of digital accounting also supports transparency and improves the quality of financial information used in decision-making. Although challenges remain regarding agents’ technological understanding and infrastructure readiness, overall implementation has provided positive impacts on financial management effectiveness and business operations in PPOB services, making processes more efficient, accurate, and reliable.

Construction project control requires careful planning to avoid delays and cost overruns. This study aims to evaluate the performance of the CBT Laboratory Building construction project at the Faculty of Medicine, Wahid Hasyim University, Semarang, in terms of cost and time using the Earned Value Analysis (EVA) method, and to analyze acceleration alternatives using the crashing method. The method used is a quantitative approach with a case study, based on project data such as the Budget Plan (RAB), S-curve, and work progress reports. The analysis was carried out using the Earned Value Analysis (EVA) method to assess project performance in terms of cost and time through indicators such as CV, SV, CPI, and SPI. Furthermore, an acceleration analysis was conducted using the crashing method to determine the optimal alternative for overcoming project delays by considering time and cost efficiency. The results of the Earned Value Analysis indicate that the project experienced delays and cost overruns, as shown by SPI < 1 and CPI < 1. The estimated project completion time increased to 227 days, longer than the initial plan of 217 days, while the estimated final cost reached RP 5,451,241,064.85, exceeding the initial budget. Acceleration efforts using the crashing method show that adding adding labor is more efficient than working hours (overtime), resulting in a project duration of 212 days with lower costs of RP 5,658,221,364.08. Thus, the Earned Value Analysis method is effective for evaluating project performance, while crashing can be a solution for acceleration by considering time and cost efficiency.

This study aims to analyze the implementation of good governance principles in digital population administration services in Medan Marelan Subdistrict from the perspective of Administrative Law. The background of this research is based on the importance of digital transformation in public services through the Electronic-Based Government System (SPBE) to enhance transparency, accountability, effectiveness, and efficiency. However, in practice, several obstacles are still encountered, such as limited infrastructure, network disruptions, and limited human resources. This research employs an empirical legal research method with both empirical and statutory approaches. Data were collected through field research, including interviews with subdistrict officials and the community, as well as library research involving laws, regulations, and relevant literature. The data were analyzed qualitatively to examine the conformity between the implementation of services and the principles of good governance and general principles of good administration (AUPB). The results show that the implementation of good governance principles in digital population services in Medan Marelan Subdistrict has not been fully optimal. This is indicated by challenges in information transparency, system effectiveness, and limitations in human resources and infrastructure. Nevertheless, digital services have provided convenience for the community in accessing population administration services. In conclusion, improvements in human resources quality, technological infrastructure, and the strengthening of supervision and evaluation mechanisms are necessary to achieve public services that align with good governance principles.

Poor soil quality and inefficient nutrient utilization remain major constraints in tomato (Solanum lycopersicum L.) cultivation, often resulting in reduced plant growth, lower productivity, and suboptimal fruit quality. This study aims to evaluate the growth performance of rose tomatoes through the integration of open-field cultivation and hydroponic planting systems. The research methods included land preparation using the Pythagorean technique to ensure proper spacing and planting layout, the application of organic fertilizers to improve soil fertility, and the transition to a hydroponic drip irrigation system using rockwool as the growing medium during weeks 1 to 7 of plant development. Plant growth parameters, including plant height, leaf development, stem vigor, and overall plant health, were observed throughout the cultivation period. The results indicated that the combination of appropriate soil management practices and precise nutrient delivery in the hydroponic system significantly enhanced nutrient uptake and supported healthy plant growth. Furthermore, the drip irrigation system helped optimize water use efficiency while reducing nutrient losses. This integrated cultivation approach demonstrated its potential as an effective solution for maintaining crop quality and productivity, particularly in areas with limited land resources. Overall, the findings suggest that integrated management practices can provide a practical, efficient, and sustainable strategy for farmers seeking to improve horticultural production in modern agricultural systems.

The consistent decline in cucumber production in Indonesia indicates limitations in conventional cultivation systems, particularly due to land scarcity and inefficient resource management. This condition has encouraged the development of hydroponic systems as a more controlled and productive cultivation alternative. This study aims to critically analyze the key factors determining the success of hydroponic cucumber cultivation and to identify the most influential management aspects in improving yield. The method employed is a literature review, examining various recent studies related to hydroponic systems, nutrient management, growing media, and environmental factors. The results show that the advantages of hydroponics lie not only in land and water efficiency but also in the ability to precisely control growth variables. However, optimal productivity highly depends on the proper integration of nutrient management, particularly the regulation of pH, electrical conductivity (EC), and nutrient balance, as well as the control of environmental factors such as temperature, humidity, and light intensity. Inaccuracy in a single component can significantly reduce plant performance, even when other factors are optimal. Therefore, an integrated approach combining nutrient and environmental management simultaneously is essential to enhance hydroponic cucumber productivity. This study confirms that hydroponics has strong potential as a strategic solution to support sustainable agriculture amid land limitations in Indonesia.

Chili pepper (Capsicum annuum L.) is recognized as one of the horticultural commodities with significant economic value and an important contribution to food security in Indonesia. However, conventional cultivation practices still face various challenges, including limited land availability, climate uncertainty, and disturbances from plant pests and diseases. These conditions highlight the need for the implementation of innovative technologies to improve production efficiency while maintaining yield stability. One approach that has been increasingly developed is the hydroponic system, a cultivation technique that does not rely on soil as a growing medium but instead utilizes nutrient solutions as the primary source of essential elements. This article aims to examine various aspects of hydroponic chili cultivation, including the roles and benefits of the plant, different types of hydroponic systems, abiotic and biotic stress factors, and cultivation management strategies. Based on the review conducted, hydroponic systems, when supported by optimal nutrient management and environmental conditions, are capable of enhancing both the yield and quality of chili plants. Therefore, the development of hydroponic-based chili cultivation is considered to have promising prospects as a solution to support sustainable agriculture in the future.

Postharvest handling of leafy vegetables, such as kale (Brassica oleracea var. acephala), is crucial for maintaining product quality and market value. This study aims to review the application of sorting and grading processes in improving the quality of horticultural products. The method used is a literature review of scientific journals and relevant references related to postharvest handling of vegetables. The findings indicate that sorting functions to separate damaged and unmarketable products based on physical condition, while grading classifies products into quality categories based on size, shape, and visual appearance. These processes contribute to reducing postharvest losses, improving product uniformity, and increasing market value. Furthermore, proper sorting and grading support quality control and enhance efficiency in distribution and marketing systems. Therefore, sorting and grading are essential components of postharvest management to ensure product quality and market competitiveness.

Abstract: Detecting chili leaf diseases remains challenging due to the non-uniform manifestation of symptoms, local discoloration, small lesion regions, and visual similarity between disease patterns and natural leaf background variations. Although YOLO-based detectors provide favorable computational efficiency, lightweight variants often struggle to distinguish subtle lesion characteristics, while conventional attention mechanisms such as CBAM primarily rely on global feature aggregation and may overlook regional activation variability. To address these limitations, this study proposes a YOLOv9s-based detection framework integrated with a Region-Dispersion Channel Spatial Attention (RDCSA) module. The proposed module incorporates regional dispersion statistics, namely mean, standard deviation, and range, as channel descriptors to capture inter-region feature variability before applying spatial attention refinement. Experiments were conducted on the COLD dataset containing 532 original images from five chili leaf condition categories using a split-before-augmentation protocol to ensure objective evaluation. RDCSA was integrated at the P5 feature level and evaluated through attention placement analysis, component-wise ablation, sensitivity analysis, stability assessment, and comparison with modern attention mechanisms. The proposed YOLOv9s + RDCSA model achieved an mAP@50 of 0.894, mAP@50–95 of 0.773, precision of 0.858, recall of 0.861, and an F1-score of 0.859 with only a marginal increase in model parameters. The results suggest that regional dispersion-based attention improves feature discrimination while preserving computational efficiency, particularly for disease symptoms characterized by heterogeneous spatial patterns. Nevertheless, performance remains influenced by visually ambiguous symptom categories, indicating that further validation across multiple datasets and field conditions is required. Overall, the proposed RDCSA module enhances detection capability without substantially increasing computational overhead, making it a promising attention mechanism for lightweight plant disease detection systems.

The development of information technology has encouraged the transformation of government administration toward digital-based governance, including correspondence management systems. Digital correspondence governance plays an important role in improving administrative effectiveness, bureaucratic efficiency, and the quality of public services. However, the implementation of digital correspondence systems in local government institutions still faces several challenges, including limited system integration, inadequate human resource capacity, and unstandardized electronic archive management. This study aims to analyze and construct a digital correspondence governance model in realizing administrative effectiveness at Dinas Komunikasi, Informatika, Statistik dan Persandian Kabupaten Gowa. This study employed a qualitative approach with a descriptive research type. Data collection techniques were conducted through observation, in-depth interviews, and documentation. Research informants were selected using purposive sampling techniques, while data analysis employed the interactive model of Miles, Huberman, and Saldaña through data condensation, data display, and conclusion drawing. The results indicate that the implementation of digital correspondence governance has improved the speed of document disposition, administrative efficiency, accessibility of documents, and organizational work coordination. However, the implementation has not been fully optimal due to constraints in system integration, human resource capacity, and digital archive management. This study produced a digital correspondence governance model emphasizing the strengthening of information technology, enhancement of employee competence, integration of administrative systems, and development of a digital work culture. It is recommended that government institutions strengthen the integration of digital correspondence systems, improve employee competencies, and establish sustainable electronic archive management standards.

PT. Bukit Baiduri Energi (BBE) is a coal mining company that utilizes hauling roads as the main infrastructure for material transportation. This study focuses on a 1.7 km road segment selected as the object of technical evaluation. The objective of this research is to analyze the effect of road geometry improvements on hauling time efficiency and equipment productivity. The method employed includes direct field measurements and calculations of operational parameters such as travel time, cycle time, and productivity. The results indicate that improvements in road grade reduced travel time from 10.13 minutes to 9.86 minutes. This reduction was followed by a decrease in cycle time from 16.29 minutes to 16.22 minutes. In addition, productivity increased from 65.4 bcm/hour to 66.69 bcm/hour. Also, improvements in curve radius and superelevation were implemented on the hauling road. These improvements resulted in a further decrease in travel time from 9.86 minutes to 8.6 minutes. Consequently, the cycle time also decreased from 16.22 minutes to 16.18 minutes. The productivity of hauling equipment increased from 66.69 bcm/hour to 67.02 bcm/hour. Overall, the evaluation of road geometry provided a positive contribution to operational performance. The productivity of overburden removal increased from 65.4 bcm/hour to 67.02 bcm/hour, representing an improvement of 2.48%.

Magelang City faces the challenge of limited land availability, with a total area of only 18.58 km2 and a high population density. Consequently, telecommunications infrastructure development requires a precise strategy. This study aims to analyze the business model and investment feasibility of Pole and Greenfield type telecommunication towers in Magelang City. Using a descriptive quantitative approach, this research processes secondary data from PT Dayamitra Telekomunikasi Indonesia by applying feasibility analysis based on Life Cycle Costing (LCC), Net Present Value (NPV), Internal Rate of Return (IRR), Break-Even Point (BEP), Payback Period (PP), and Benefit-Cost Ratio (BCR). The results indicate significant differences in cost structures; Pole towers proved to be more efficient, requiring an initial capital outlay of only 28.8% of the total capital required for Greenfield towers. Greenfield towers generated an NPV of Rp13.07 billion with an IRR of 20%, while Pole towers generated an NPV of Rp2.46 billion with a higher IRR of 23%. Pole towers have proven to offer a faster return on investment and better operational cost efficiency, making them the most strategic option to support network densification and the implementation of 5G technology in urban areas with spatial constraints like Magelang City.

Gorontalo Province possesses significant mineral resource potential, particularly gold, silver, and copper, positioning the mining sector as a key driver of regional economic growth. However, a shortage of skilled local labor and the scarcity of vocational educational institutions in the mining field severely hamper human resource development in this sector. This study aims to design a Mining Polytechnic Campus in Gorontalo by applying sustainable architecture principles, encompassing energy efficiency, environmentally friendly materials, sound wastewater management, and user comfort. The research approach involves literature studies, field observations, interviews with relevant stakeholders, and quantitative data analysis regarding resource potential, the number of senior high school students, and educational space requirements. The design results emphasize site arrangement, building mass configuration, utility systems, and interior and exterior spaces that support academic, social, and community activities. The application of sustainable architecture principles is expected to create a campus that not only meets the needs of mining vocational education but also contributes to environmental conservation and sustainable regional development.

This research aims to analyze the implications of the transition in lease accounting standards to PSAK 73 on tax efficiency levels and net income structures within the retail industry, focusing on PT Mitra Adiperkasa Tbk as case studies. Employing a descriptive quantitative method, this research compares financial statement data from the 2017-2024 period to evaluate shifts before and after the regulation's enforcement. The results reveal that the implementation of PSAK 73 successfully improved corporate tax efficiency, characterized by a decrease in the Effective Tax Rate (ETR) below the statutory corporate tax rate. This was achieved by leveraging temporary differences that resulted in the recognition of deferred tax assets, providing a strategic advantage in the form of tax deferral. On the other hand, the application of this standard caused significant pressure on net profit during the initial transition phase due to the front-loading expense pattern derived from right-of-use asset depreciation and lease liability interest.