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The advancement of information technology has driven higher education institutions to manage their digital presence professionally, particularly through quality website management as a representation of institutional identity. Preliminary observations of the Universitas Graha Karya (UGK) website (ugk.ac.id) identified several issues, including inconsistent page layouts, inactive hyperlinks, and irregularly updated content. This study aims to analyze the quality of the UGK website based on three WebQual 4.0 dimensions—usability, information quality, and service interaction quality—and to determine improvement priorities using Importance Performance Analysis (IPA). A descriptive quantitative approach was employed, with data collected through questionnaires distributed to 308 active students selected via purposive sampling using the Slovin formula at a 5% margin of error. Data analysis included validity testing, reliability testing, WebQual 4.0 analysis, gap analysis, and IPA Cartesian diagram mapping. Results indicate negative grand mean gap values across all dimensions, with service interaction quality recording the largest gap (-0.16), followed by information quality and usability (both -0.01). IPA mapping identified five indicators in Quadrant I as the main improvement priorities: ease of menu navigation (U2), relevance of academic information (IQ2), clarity of information language (IQ4), website access security (SI1), and ease of contacting administrators (SI4). The study concludes that UGK's website quality has not fully met user expectations and requires structured, user-oriented improvements.

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.

The term "breach of contract" in contract law refers to a breach of promise. Discussions of breach of contract, both in doctrine and jurisprudence, are usually associated with a statement of negligence by the debtor, where the debtor has failed to properly fulfill their contractual obligations, and the debtor is at fault. It must be acknowledged that a breach of contract, or breach of promise, already involves bad faith on the part of the party failing to fulfill their promise. The meaning of "breach of contract" in banking law relates to the occurrence of problem loans at banks, which cause the loan to become non-performing. This is usually due to the debtor or customer not paying by the previously agreed payment date. The existence of a breach of contract is inseparable from the existence of a credit agreement. Whether a debtor is in default cannot be determined simply because there are efforts to rescue loans that have entered a problematic stage. The beginning of a violation of an agreement or default due to someone not being paid, in meeting the credit rescue standards at the bank, usually efforts are made such as Rescheduling, Reconditioning, Restructuring, through this rescue, the debtor is given the opportunity to lose his business, so the concept of default in BW and the Banking Law must be measured through the performance given, in both regulations, then from there the concept of problem credit can be classified. This banking regulation can be said to be a default, the comparison of this concept is the discussion in this thesis.

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.

Education is the main driver of a nation's progress, which is not only related to intellectual intelligence, but also the formation of student character. Unfortunately, currently the world of education is facing serious problems, such as declining interest in learning and increasingly complex external factors in the digital era. This study aims to explore in depth the impact of learning motivation on student academic achievement, identifying obstacles that hinder this achievement. The method used in the current study is a literature study with a qualitative approach. Data were collected through theoretical studies and analysis of various relevant scientific sources, including research journals and textbooks, which were then combined to develop a comprehensive argument. The findings of this study indicate that learning motivation is the main factor that encourages student persistence and consistency in achieving the best learning. Academic success is defined as the result of a complex interaction between internal and external factors, where the existence of a supporting ecosystem such as good learning facilities, a supportive environment, and effective communication between lecturers and students plays a very important role. On the other hand, phenomena such as digital fatigue, low independence, and excessive workload are identified as significant barriers that can reduce academic performance. This analysis concludes that there is synergy in strengthening psychological aspects and creating an adaptable learning environment to maintain the stability of academic achievement amidst global demands.

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.

This study examines the performance of student administrative services in the Society 5.0 era at the Bureau of Academic Affairs, Student Affairs, and Planning of Gorontalo State University, focusing on scholarship services. It addresses the need for accessible, responsive, transparent, inclusive, and student-centered administrative services in higher education. A descriptive qualitative approach was employed through in-depth interviews, participatory observation, and document analysis. Informants included bureau leaders, scholarship and financial aid administrators, operational officers, and students receiving various scholarship schemes. Thematic analysis was conducted through data reduction, data display, and conclusion drawing, while validity was ensured through source triangulation, method triangulation, and member checking. The findings show that accessibility has improved through service counters, websites, social media, WhatsApp, online forms, SIMPEL BAKP, and coordination with faculties and study programs. However, information remains fragmented, digital standard operating procedures are not uniform, and disability-inclusive access is limited. Responsiveness is supported by direct and digital communication, but it lacks a dedicated complaint system, automatic notifications, selection-status dashboards, and real-time disbursement tracking. Service quality is perceived as fairly good because students experience professional, friendly, and fair treatment. Nevertheless, service documentation, procedural standardization, staff training, and humanistic technology integration need strengthening. The study concludes that scholarship administration should be transformed into a centralized, inclusive, responsive, transparent, and student-centered digital-humanistic service model.

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.

 Education in vocational high schools (SMKs) requires effective data management to improve students’ academic achievement and discipline. At SMK Islam Secang, students’ academic scores and attendance data have so far functioned merely as administrative archives, making it difficult to identify patterns of student performance. This study aims to classify students based on academic achievement and discipline by applying the K-Means Clustering algorithm using RapidMiner. The data used in this study consist of scores from six subjects and attendance records of 35 students from the Light Vehicle Engineering (TKR) department over two semesters. The data were obtained from original school records, compiled using Microsoft Excel, and processed in RapidMiner. The clustering process employed four clusters for academic achievement and two clusters for discipline, with Euclidean Distance used as the similarity measure. The results show that in the first semester, students were grouped into four academic achievement clusters: high achievement (6 students), moderate achievement (7 students), potentially problematic (14 students), and problematic (8 students). In the second semester, the distribution changed to high achievement (19 students), moderate achievement (14 students), potentially problematic (4 students), and problematic (1 student). Meanwhile, student discipline was divided into two clusters: disciplined (31 students) and undisciplined (4 students). These results demonstrate that K-Means Clustering is effective in mapping student conditions, revealing patterns in academic performance and attendance, and supporting educational evaluation, learning planning, and early detection of students who require academic or disciplinary intervention. Keywords: Data Mining, K-Means Clustering, Academic Achievement, Discipline, RapidMiner, Vocational High School (SMK)

Dividend policy is one of the key indicators used by investors to assess the stability and financial performance of banking companies. This study aims to analyze the effect of financial performance on the Dividend Payout Ratio in conventional banks in Indonesia during the 2021–2024 period. Financial performance is proxied by liquidity, Leverage, and profitability. This research employs a quantitative approach with an associative research design. The population consists of 43 conventional commercial banks listed on the Indonesia Stock Exchange up to 2024. The sampling technique uses purposive sampling, resulting in 24 conventional banks with a total of 96 panel data observations. The data used are secondary data obtained from the companies’ annual financial statements and analyzed using multiple linear regression. The results show that liquidity, proxied by Loan to Deposit Ratio (LDR), has a positive and significant effect on the Dividend Payout Ratio; Leverage, proxied by Debt to Asset Ratio (DAR), has a negative and significant effect on the Dividend Payout Ratio; and profitability, proxied by Return on Assets (ROA), has a positive and significant effect on the Dividend Payout Ratio. Furthermore, liquidity, Leverage, and profitability simultaneously have a significant effect on the Dividend Payout Ratio in conventional banks in Indonesia. This study indicates that the company’s financial performance is a key factor in determining dividend policy in the banking sector.

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%.

The digital transformation of Indonesia's political landscape has created space for the emergence of a new populist narrative based on vertical social mobility. This study aims to analyze the construction of the "Anak Kampung" identity used by Bahlil Lahadalia as an instrument of political branding on social media. Using netnography and a four-level Cyber ​​Media Analysis (AMS) tool, this study explores how past marginalized experiences—such as being a cake seller, a conductor, and a public transportation driver—are reconstructed into symbolic capital in the digital space. The results show that Bahlil carried out effective "impression management" through visual performativity and narratives of struggle, which succeeded in building affective loyalty among constituents across generations. However, this branding also faces challenges in the form of digital skepticism regarding academic integrity and controversial public policies. This study concludes that the success of political branding in the digital era depends heavily on actors' ability to navigate the logic of platform algorithms while maintaining a sense of authenticity.

Accountability in preparing financial reports is a crucial instrument for the sustainability of business entities, because inaccurate financial data management can hinder decision-making and harm business performance in the future. For MSME actors in the PKK Tanggamus community, strengthening financial reporting competence is an urgent need so they can map expenditure structures, record income, calculate profit, and evaluate business development periodically. This community service activity aims to improve participants’ financial discipline, particularly in separating personal assets, business capital, and gross profit, while introducing accessible office technology. The training focused on optimizing LibreOffice Calc as an alternative to Microsoft Excel with similar functions for creating transaction tables, cost recapitulations, and simple financial reports. The activity method included material presentation, software demonstrations, report preparation practice, and interactive discussions based on participants’ business needs. Training results showed high enthusiasm, improved understanding, and readiness to use LibreOffice Calc as a more organized, transparent, and sustainable financial recording tool. Thus, this activity provides practical contributions to building an accountable financial administration culture for community-based MSMEs.

This study aimed to improve students’ speaking skills through animation-based learning in a first-grade EFL classroom at SMP Darul Amin. The study employed Classroom Action Research (CAR) consisting of two cycles, with each cycle including planning, action, observation, and reflection stages. The participants were 30 first-grade junior high school students. The instruments used in this study were observation sheets, speaking performance tests, and documentation. The findings revealed that animation-based learning successfully improved students’ speaking skills, classroom participation, confidence, and motivation during the learning process. The students’ average speaking score increased from 48.13 in the pre-action stage to 76.53 in Cycle I and further improved to 87.56 in Cycle II. In addition, the percentage of students achieving the Minimum Mastery Criterion (KKM) increased from 10% in the pre-action stage to 90% in Cycle II. Therefore, animation-based learning can be considered an effective learning media to improve students’ speaking skills in EFL classrooms.

This study investigates the performance of Internet of Things (IoT)-based monitoring systems using a mobile hotspot and IoT sensors for temperature and humidity data transmission. The research is based on the IoT concept, which enables electronic devices to communicate and exchange data through internet networks without direct human intervention. System performance was evaluated using standard Quality of Service (QoS) parameters, including throughput, packet loss, delay, and jitter. The experimental setup utilized a NodeMCU ESP32 microcontroller and a DHT22 sensor, with measurements conducted at various transmission distances through wireless communication media. The objective was to determine the reliability of hotspot connectivity and sensor communication in supporting IoT applications. The results indicate that the optimal performance was achieved at a distance of 20 meters using a 40-lambda variation. Furthermore, the communication signal between the ESP32 device and the mobile hotspot remained detectable up to a maximum distance of 32 meters. These findings demonstrate the effectiveness of the proposed IoT system for environmental monitoring applications within specific transmission ranges.

This research investigates the impact of authentic marketing and social media interactivity on market performance within the creative fashion sector, focusing on Yume Project in Bandung. Utilizing a quantitative approach with descriptive and verificative methods, data were collected from 100 respondents through purposive sampling. The results of multiple linear regression analysis (Y =5.751 + 0.422X1 + 0.390X2 ) demonstrate that both authentic marketing and social media interactivity significantly and positively influence market performance, both partially and simultaneously. The coefficient of determination (R2) of 0.596 indicates that these two variables explain 59.6% of the variance in market performance. This study underscores the necessity for local fashion brands to maintain transparency, honesty, and active digital engagement to thrive in hyper-competitive markets.

This study was motivated by the lack of standardized and objective assessment instruments for the teaching of the Syofyani Minang Payung Dance at the junior high school level, resulting in an assessment process that remains largely subjective and fails to measure psychomotor, affective, and cultural aspects in a balanced manner. This study aims to design and test the validity and reliability of a performance assessment rubric for the Syofyani Minang Payung Dance in cultural arts education at SMP Negeri 1 Bukittinggi. The research method used is a mixed-methods approach with a sequential explanatory design. The research subjects consisted of three dance instructors serving as expert judges, one cultural arts teacher, and 33 junior high school students. The research instrument was a performance-based assessment rubric covering five competency indicators: basic movement techniques; alignment with musical rhythm and dynamics; expression and character interpretation; mastery of payung props and movement safety; and accuracy of floor patterns and group synchronization. Quantitative data analysis was conducted using IBM SPSS Statistics through the Corrected Item-Total Correlation validity test and Cronbach’s Alpha reliability test, while qualitative data was analyzed using descriptive-interpretive methods. The research results show that all indicators have validity scores above 0.30 and are therefore considered valid, and the Cronbach’s Alpha reliability score is above 0.70, indicating good internal consistency of the instrument. Furthermore, the interview results indicate that the rubric is considered relevant, clear, and aligned with the learning characteristics of Syofyani’s Minang Payung Dance at the junior high school level. Consequently, the developed assessment rubric is deemed suitable for use as an objective, standardized, and contextually appropriate assessment instrument for dance education rooted in local culture.

The growth of information technology has driven changes in consumer behavior, one of which is through e-commerce platforms such as Shopee. This phenomenon has generated a large number of customer reviews, including those for local cosmetic products such as Wardah. These reviews serve as an important source of information for understanding customer perceptions and satisfaction levels. However, manual analysis of large and linguistically diverse datasets is inefficient and potentially subjective. This study aims to implement the multi-category Naive Bayes algorithm to classify the sentiment of Wardah product reviews on Shopee into three categories: positive, negative, and neutral. The data were collected using a web scraping technique and processed through a series of preprocessing stages including case folding, tokenization, stopword removal, stemming, and text cleaning. Subsequently, term weighting was performed using the TF-IDF method prior to classification. Model performance was evaluated using a confusion matrix as well as accuracy, precision, and recall metrics. The results indicate that the multi-category Naive Bayes algorithm achieved an accuracy of 86.00%, a precision of 86.63%, and a recall of 98.24%. This approach can assist business practitioners in objectively understanding customer opinions and support decision-making in business strategy and product development.

The development of social media, especially TWITTER, has become one of the main means for people to express opinions and criticism on various issues, including the performance of law in Indonesia. This study aims to analyze public sentiment towards the performance of law based on TWITTER user comments using the Naïve Bayes algorithm. The research data consists of 1004 comments collected from several videos related to legal topics. The analysis process includes the stages of data crawling, pre- processing (text cleaning, normalization, and tokenization), labeling sentiment into positive, negative, and neutral, and testing the Naïve Bayes model. The results show that the Naïve Bayes algorithm is able to classify sentiment with an accuracy level of 93.73%. The distribution of sentiment from 1004 comments shows that the majority of public opinion is (negative/positive/neutral), which indicates that public perception of the performance of law is still (critical/positive). These findings are expected to be input for related parties to understand public opinion and improve the quality of legal performance in

This study discusses a student concentration detection system using Convolutional Neural Network (CNN) with the MobileNetV2 architecture. The dataset was adapted from Classroom Student Behaviors and mapped into four concentration categories: highly focused, focused, less focused, and unfocused. The system was tested with a 720p webcam and produced real-time detection data. The evaluation results show an overall accuracy of 75.85%, with the highest precision achieved in the focused class (0.9859) and the highest recall in the highly focused (0.9739) and unfocused (0.9811) classes. The confusion matrix indicates that the focused class was detected most consistently, while highly focused and unfocused classes were often misclassified as focused, resulting in lower precision. In real-time testing, the system operated at an average of 7 FPS and worked optimally when students faced the camera directly with sufficient lighting, but its performance decreased significantly at face angles greater than 45°. User evaluation shows that 75% of students rated the detection results as accurate/very accurate with an average satisfaction score of 3.6 out of 5, and 75% felt assisted in recognizing their concentration level. From the teachers’ perspective, most stated that the results were consistent with classroom observations, and all expressed willingness to reuse the system.