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Sign language recognition is one of the areas of image recognition and image processing technology that is developing rapidly in human-computer interaction. This technology really helps the deaf and speech impaired in communicating with non-disabled people. This research aims to examine the optimization of an object tracking system in sign language using the Gaussian Mixture Model (GMM) and Kalman Filter by including the Region of Interest (ROI). The proposed system consists of three main components, namely hand detection, object extraction, and classification. Hand detection is done using the Kalman Filter to track hand movements accurately. Next, Region of Interest (ROI) features, such as shape, direction and movement features, are extracted from the detected part of the hand. These features are fed into a Gaussian Mixture Model (GMM) classifier, which can recognize sign language based on the extracted features. With the combination of GMM and Kalman Filter in this research, it can increase accuracy in object tracking, reduce interference from the background, and ensure the tracking focus remains on important objects. The dataset used is in the form os SIBI alphabet symbols, namely A-Z with the amount of data for each class, namely 620 images. Based on the research result, model testing using GMM, Kalman Filter and ROI produces higher accuracy of 99%, while model testing using GMM and ROI produces accuracy of 90%.

The process of creating and verifying employee ID cards at BKPSDMD Jambi City was previously carried out manually, resulting in lengthy processing times, data entry errors, and a high risk of identity forgery. This study aims to design and implement a web-based employee ID card digitalization system integrated with QR Code technology to improve the efficiency, accuracy, and security of employee identity verification. The system was developed using the Waterfall methodology, consisting of requirements analysis, system design, implementation, testing, and maintenance. The application was built using Native PHP, MySQL, HTML, CSS, and JavaScript. Functional testing was conducted using Black Box Testing with 12 test scenarios, while usability evaluation employed the System Usability Scale (SUS) involving 20 respondents. The results indicate that all core system features functioned properly, achieving a 100% success rate on valid test scenarios. Furthermore, the usability evaluation produced an average SUS score of 71.75, which falls into the good and acceptable categories. The implementation successfully accelerated the ID card issuance process, improved data management accuracy, and enhanced identity verification security through QR Code integration directly connected to the employee database. Therefore, the developed system effectively supports digital transformation and improves the efficiency of employee identity management at BKPSDMD Jambi City.

Primary healthcare centers generate both medical and non-medical waste that may pose environmental and public health risks if not properly managed. This study aims to describe the waste management practices at Kesumadadi Public Health Center, Bekri Subdistrict, Central Lampung Regency, in 2025. This research employed a descriptive design conducted in May 2025 at the Kesumadadi Public Health Center. Data were collected through observation and interviews as primary data and secondary data from the health center. Data processing included editing, coding, tabulating, and cleaning, while data analysis was carried out using checklists and questionnaires. The results showed that the segregation of medical and non-medical solid waste was not fully in accordance with standards, waste transportation to temporary storage areas did not use trolleys and lacked designated routes, there was no wastewater treatment facility for liquid waste, and the use of personal protective equipment by staff was not optimal. Waste management practices at the Kesumadadi Public Health Center have not met the required standards, particularly in waste segregation, transportation, liquid waste treatment, and occupational safety, therefore improvements are needed to reduce environmental and health risks.

This study aims to analyze the environmental impact of waste generated by the gecko processing home industry based on environmental law regulations in Indonesia. In its processing activities such as lizards and snakes. These activities produce organic waste in the form of animal organs, blood, body fluids, and other waste in the materials that are later utilized as catfish feed. The research method used is qualitative with a normative juridical approach, statutory approach, and literature study. Data were obtained from laws and regulations , scientific journal, and environmental law literature. The results of the study indicate that the disposal of waste into rivers can increase Biological Oxyen Demand and Chemical Oxygen Demand (COD) levels, cause unpleassant odors, and reduce water quality and public health. The utilization of waste as catfish feed can reduce the amount of waste disposed of, however, it still requires hygienic processing to prevent biological risks. From the perspective of environmental law, the direc disposal of the waste into rivers is not in accordance with Law No. 32 of 2009 concerning Environmental Protection and Management and Government Regulation No. 22 of 2021 concerning the Implementation of Environmental Protection and Management. Therefore, better waste management is needed through proper waste treatment, increased awareness among business actors, and goverment supervision so that home industries can operate sustainably and in an environmentally friendly manner

Background: The prevalence of Chronic Energy Deficiency (SEZ) of pregnant women nationally is still 16.9%, and anemia reaches 27.7%, so the development of local food-based Supplementary Feeding (PMT) is needed. Brownies with the substitution of red spinach as a source of iron and purple sweet potato flour as an energy source have the potential to be developed as an alternative to PMT. This study aims to determine the acceptability and nutritional content of red spinach brownies with the addition of purple sweet potato flour as an interlude food for pregnant women. Method: Design using the Complete Random Design (RAL) method. The formulation of making brownies consists of three treatments with a comparison between (red spinach pureee and purple sweet potato flour) as follows: F1 (50:50), F2 (60:40), and F3 (40:60). The acceptance test was conducted using a hedonic test of color, aroma, taste, and texture on 30 semi-trained panelists. Analysis of nutritional content includes moisture content (thermogravimetry), ash content (dry ashing), protein (Kjeldahl), fat (Soxhlet), carbohydrates (by difference), and Fe (Atomic Absorption Spectrophotometry). The data were analyzed using the Kruskal-Wallis test. Research Results: The acceptability test showed that there was no significant difference between the formulations. The F3 formulation with a ratio of 40% red spinach pureee and 60% purple sweet potato flour obtained the highest preference value and was determined as the best formulation. The nutritional content of the F3 formulation includes protein 10.447%, fat 8.047%, carbohydrates 1.5579%, Fe 0.0005%, moisture content 20.68%, and ash content 1.4875%. Conclusion: There was no significant effect of each formulation on the acceptability of Brownis Suggestion: It is hoped that the next researcher can improve product formulation and processing processes to maintain and increase iron (Fe) levels in brownies.

 The quality of digital system services in the ship clearance process is closely related to the work effectiveness of shipping agency companies. The advancement of port operational services is influenced by the system’s ability to provide convenience, speed, accuracy, and service integration for users. The system used in the ship clearance process must be able to meet user needs and support inter-agency coordination so that ship services can operate more effectively and efficiently. This study aims to analyze the performance level and the level of user importance regarding the implementation of the Single Submission Pengangkut System in the ship clearance process at PT Trans Cakrawala Perkasa. The research employed a descriptive quantitative approach with a sample of 30 respondents consisting of ship agents involved in the clearance process. Data were collected through questionnaires, observations, and literature studies. The data were analyzed using validity tests, reliability tests, conformity level analysis, and the Importance Performance Analysis (IPA) method. The results indicate that the SSM Pengangkut System has made a positive contribution to accelerating document processing, facilitating system usage, increasing work productivity, and supporting coordination among related agencies. Based on the IPA Cartesian diagram, one indicator was identified as a priority for improvement, while other indicators were categorized as maintain performance, low priority, and high performance with lower importance levels. Overall, the implementation of the Single Submission Pengangkut System has been running quite well; however, continuous evaluation and improvement are still needed to optimize the ship clearance process further.

This study aims to develop a sentiment classification method for YouTube user comments related to the game Love and Deepspace using the Naïve Bayes algorithm, focusing on improving the text data processing and understanding user perceptions. Comment data were collected through scraping from YouTube videos, followed by preprocessing including text cleaning, normalization, stopword removal, stemming, and translation into English. Initial labeling was conducted using TextBlob, then the data were randomly sampled for training the Naïve Bayes model. Evaluation involved comparing sentiment distributions and visualization using Word Cloud and bar charts. The Naïve Bayes model achieved an accuracy of 77.36% in sentiment classification. The sentiment distribution shows differences between TextBlob (positive: 1,011, neutral: 1,312, negative: 575) and Naïve Bayes (positive: 901, neutral: 1,627, negative: 370), with Naïve Bayes being more conservative. The Word Cloud visualization identifies dominant words such as "bang," "game," and "main," while the bar chart shows the largest proportion of neutral sentiment. Naïve Bayes is effective for sentiment classification on informal comment data, with significant differences from rule-based methods like TextBlob. This research contributes to the development of text data processing techniques and user perception analysis, as well as opening up optimization opportunities with other algorithms like SVM for better accuracy.

This community service activity aims to increase the business capacity of the wood ear mushroom food MSME through integrated mentoring on business legality and access to financing. The subject of the activity was the Brother Farm MSME in Kediri Regency, which initially ran its business informally without adequate legality and had limited access to formal financing. The method used was a participatory approach with activity stages including: initial observation and problem identification, mentoring in creating a Business Identification Number (NIB), mentoring in understanding halal certification, mentoring in processing Fresh Food of Plant Origin (PSAT) permits, and education on access to financing through the People's Business Credit (KUR) scheme. Data collection techniques were carried out through observation, interviews and documentation, while data analysis used a qualitative descriptive approach by comparing conditions before and after mentoring. The results of the activity showed that the MSME successfully obtained business legality in the form of a Business Identification Number and Fresh Food of Plant Origin permits and experienced an increase in understanding regarding halal product guarantees and access to formal financing. This integrated mentoring had a positive impact on increasing consumer confidence, expanding market opportunities, and business readiness in accessing capital. Thus, this activity is able to encourage business transformation towards a more formal, structured and sustainable condition (SDG 8 and SDG 12) thereby contributing to increasing the competitiveness of food MSMEs.

Pengolahan nilai akademik di sekolah dasar masih banyak dilakukan secara manual menggunakan buku nilai atau aplikasi sederhana seperti spreadsheet, sehingga menimbulkan ketidakefisienan, duplikasi data, dan tingginya risiko kesalahan pencatatan. Penelitian ini bertujuan untuk mengembangkan sistem pengolahan nilai akademik berbasis web dengan mengimplementasikan framework Laravel dan metode Agile. Penelitian ini menggunakan pendekatan mixed method, yaitu pengumpulan data kualitatif melalui observasi dan wawancara, serta evaluasi kuantitatif melalui pengujian sistem. Proses pengembangan sistem mengikuti tahapan Agile yang meliputi analisis kebutuhan, perancangan sistem, implementasi, dan pengujian secara iteratif. Sistem dibangun menggunakan bahasa pemrograman PHP dengan framework Laravel serta basis data MySQL. Hasil penelitian menunjukkan bahwa sistem yang dikembangkan mampu meningkatkan efisiensi, akurasi, dan kecepatan dalam pengolahan data akademik, khususnya pada proses input nilai, pengelolaan data, dan pembuatan laporan otomatis. Pengujian menggunakan black box testing menunjukkan bahwa seluruh fitur sistem berjalan dengan baik. Penelitian ini memberikan kontribusi berupa solusi yang terstruktur dan fleksibel dalam pengelolaan data akademik serta mendukung transformasi digital di bidang pendidikan.

This study analyzes the implementation of public service innovation through the E-TTSP application at the Investment and One-Stop Integrated Services Agency (DPMPTSP) of Banten Province. Using a descriptive qualitative method, data were collected through interviews, observation, and document analysis. The results show that this digital system has significantly improved service quality and efficiency. Processing time was reduced from 7–14 days to only 2–5 days, while bureaucratic procedures were simplified. The system also enhances transparency, accountability, and accessibility, allowing users to apply online without visiting the office. Consequently, the investment climate improved, marked by a 28% increase in permit applications and a 35% rise in investment value within two years. However, challenges remain, including uneven network infrastructure, low digital literacy, and limited human resource capacity. It is recommended to improve infrastructure, provide continuous training, and intensify socialization. In conclusion, E-TTSP has delivered tangible benefits, yet sustainable development is necessary to ensure equal and optimal services for all.

This study aims to describe the aesthetics of the performance form of the Lenggok Dance created by Ida Sulistyarini and Susiati, which has developed in Banyumas Regency. The Lenggok Dance is a creative dance work rooted in the local Banyumasan tradition and presents distinctive movement characteristics along with regional cultural values. This research uses Djelantik’s aesthetic theory with a qualitative method and a phenomenological approach. Data collection techniques include observation, interviews, and documentation. Data validity techniques employ triangulation of sources, techniques, and time. Data analysis is carried out by examining the aesthetic elements of the dance, which include form, content or substance, and presentation or performance contained in the show. The results of the study indicate that the aesthetics of the Lenggok Dance are reflected through the harmony between dynamic and flexible lenggeran movements and the rhythmic Banyumasan musical accompaniment, as well as visual support from makeup and costumes that strengthen the character of the dance. In addition, the Lenggok Dance contains aesthetic values that represent the cultural identity of Banyumas, particularly in the processing of movements and expressions that reflect flexibility, joy, and local wisdom. This study is expected to contribute to the development of dance studies, especially related to the aesthetics of regional creative dance, and to serve as a reference for the preservation and development of Banyumasan performing arts.

This study aimed to analyze the influence of capital structure, liquidity, activity, and dividend policy affect firm value in the food and baverage manufacturing sub-sector listed on the Indonesia Stock Exchange during 2022-2024. The research uses secondary data drawn from financial reports. From a population of 99 listed companies for the 2022-2024 period, purposive sampling yielded 19 companies as the study sample. A quantive approach was applied, using multiple linear regression for analysis. Data processing and analysis were conducted with Microsoft Excel 2022 and IBM SPSS version 27. The findings indicate the capital structure has a positive and statistically significant effect on firm value. While liquidity, activity, and dividend policy show no significant effect.  

This study aims to analyze the influence of work discipline, professionalism, and organizational culture on organizational commitment among employees in the Public Service Sector. Organizational commitment is an important factor that reflects employee loyalty and attachment to the institution, while the three independent variables are considered as internal factors that can strengthen this commitment. The method used in this study is associative quantitative with a multiple linear regression approach. Data were collected through distributing questionnaires to 46 respondents based on probability sampling techniques. Data processing and analysis in this study used SPSS software version 27. Based on the results of the study, it was found that there is a significant influence of work discipline on organizational commitment. In addition, professionalism has a significant effect on organizational commitment, organizational culture has a significant effect on organizational commitment. Based on simultaneous hypothesis testing, it is proven that work discipline, organizational culture, and professionalism jointly influence organizational commitment. While the amount of contribution is 54% to organizational commitment, while the remaining 46% of organizational commitment is influenced by other factors such as leadership style, motivation, competence, rewards, job satisfaction, and employee performance. Thus, this study confirms that to increase organizational commitment, government agencies need to strengthen a healthy work culture, enforce discipline, and encourage a professional attitude in the work environment.

This study aims to examine the influence of inventory intensity, executive compensation, and sales growth on tax avoidance in non-cyclical consumer sector companies listed on the Indonesia Stock Exchange (IDX). This type of research is quantitative research using secondary data during the period 2020–2024. The sampling method used was purposive sampling, and the sample obtained consisted of 7 companies with 35 observation data points. Data processing was carried out using the E-Views 12 statistical program. Based on the results of this study, inventory intensity, executive compensation, and sales growth simultaneously affect tax avoidance. Partially, only executive compensation has an effect on tax avoidance, while inventory intensity and sales growth have no effect on tax avoidance. This study contributes to the development of accounting and taxation literature, particularly regarding the factors influencing corporate tax avoidance practices in the non-cyclical consumer sector. The findings indicate that executive compensation plays an important role in influencing managerial decisions related to tax avoidance, whereas inventory intensity and sales growth do not significantly determine tax avoidance practices individually. Therefore, companies are expected to improve governance and transparency in executive compensation policies to minimize opportunistic actions related to tax management. In addition, future researchers are encouraged to expand the research variables and increase the number of samples in order to obtain more comprehensive results regarding the determinants of tax avoidance.

The evaluation of haul road geometry at PT Trubaindo Coal Mining was conducted to ensure that the haul road from the stockroom to the jetty meets applicable technical standards, thereby supporting the smoothness, safety, and efficiency of coal transportation activities. This study aims to analyze the conformity of haul road geometric parameters, including straight road width, curve width, curve radius, cross slope, longitudinal grade, and superelevation, based on the standards of AASHTO 7th Edition and Kepmen 1827 of 2018. The research method employed field measurements using a Terrestrial Laser Scanner (TLS), followed by data processing using Maptek and Surpac software. The obtained data were then compared with the applicable standards to determine the level of conformity of the haul road geometry. Based on field measurements, the average values obtained were 14.99 m for straight road width, 18.45 m for curve width, 0.22 m for cross slope, 6.97% for grade, 223.51 m for curve radius, and 1.40 m for superelevation. Furthermore, based on calculations and analysis referring to AASHTO 7th Edition and Kepmen 1827 of 2018, and considering the largest haulage equipment used (Volvo FMX 480), the ideal haul road geometry values were determined as follows: 13 m for straight road width, 17 m for curve width, 124 m for curve radius, 0.26 m for cross slope, 1 m for superelevation, and 6% for grade based on PT Trubaindo Coal Mining standards.

Indonesian culinary comments on social media platforms such as Instagram are characterized by informal spelling, regional language mixing, slang expressions, and emojis, posing substantial challenges for automated sentiment classification. While IndoBERT has demonstrated strong performance across Indonesian natural language processing tasks, the contribution of individual preprocessing components to fine-tuning performance on informal text remains underexplored, particularly in the culinary domain. This study addresses this gap by conducting a systematic preprocessing ablation study on IndoBERT-Base fine-tuning for Indonesian culinary sentiment classification, accompanied by a comparative evaluation against Naive Bayes with TF-IDF, SVM with TF-IDF, and BiLSTM as representative baselines. A dataset of 3,500 manually labeled Instagram culinary comments across three sentiment classes was used, with a stratified 80/10/10 split. Six preprocessing variants were evaluated under identical experimental conditions to isolate the contribution of each component. The results show that slang normalization is the most impactful single preprocessing step, yielding a macro F1-score gain of +0.0609 over the no-preprocessing baseline, while the full pipeline achieves an accuracy of 0.8800 and a macro F1-score of 0.8465. IndoBERT-Base with the full pipeline outperforms all baselines across all evaluation metrics. Per-class analysis reveals that the negative class achieves the lowest F1-score of 0.7600, with sarcastic expressions and Banjar regional vocabulary identified as primary sources of misclassification. These findings indicate that preprocessing decisions have a measurable and non-uniform effect on IndoBERT fine-tuning performance. In this study, slang normalization provides the most substantial individual contribution in bridging the vocabulary gap between informal user-generated text and the model’s pre-training distribution.

This study aims to examine and review the impact of language learning through text-based methods on the cognitive abilities of elementary school students. The research approach used is a qualitative study with the main instrument being the researcher, and supporting instruments including observation, interviews, and documentation of student learning outcomes at the elementary school level. Research data was obtained from various library sources, such as books, scientific articles, national and international journals, and other relevant scientific works related to text-based learning and student cognitive development. The results of the study indicate that the implementation of Indonesian language learning with text-based methods has a diverse impact on students. Differences in learning outcomes are not only influenced by the strategies and learning processes implemented by teachers, but are also closely related to students' cognitive abilities in understanding, interpreting, and processing information from Indonesian texts. Thus, text-based methods need to be adapted to the characteristics and levels of students' cognitive abilities so that learning objectives can be optimally achieved.

The digital era has fundamentally revolutionized human interaction and information processing, particularly for Generation Z as digital natives. This research aims to identify the characteristics of digital information consumed by Generation Z and evaluate their long-term memory (LTM) capacity in the digital age. Using a Systematic Literature Review (SLR) method with a qualitative approach, 15 relevant studies published between 2021 and 2026 were analyzed from databases such as Scopus, Google Scholar, and ScienceDirect. The findings indicate that digital information characteristics—which are often "bite-sized," visual, and rapidly consumed—tend to encourage shallow encoding and digital amnesia. However, the study also found a dual impact: while high cognitive load and constant multitasking can hinder memory consolidation, structured digital use and interactive learning modules can significantly enhance memory retention. These results imply that optimal cognitive function in the digital era highly depends on digital literacy and effective information management strategies to balance technological use with natural cognitive sharpness.

Sea Surface Temperature (SST) is an important parameter in oceanographic studies because it influences climate dynamics, ocean circulation, and marine ecosystems. Continuous monitoring of SST in open sea areas requires a reliable system capable of operating autonomously. This study develops a solar-powered ocean buoy designed to measure sea surface temperature while simultaneously evaluating the performance of a solar panel as the main energy source. The system uses a DS18B20 sensor to measure SST and an INA219 sensor to monitor the voltage, current, and power of the solar panel, while an ESP32 microcontroller functions as the central data processing unit. The results show that sea surface temperature tends to remain relatively stable with small daily variations, whereas the temperature and performance of the solar panel exhibit larger fluctuations due to direct exposure to solar radiation and changing weather conditions. Solar panel performance also shows significant variations in current and power depending on the intensity of sunlight. To analyze the influence of SST variations on solar panel performance, a statistical analysis using Analysis of Variance (ANOVA) was conducted. The ANOVA results, based on the calculated F-value and the significance value (p-value) at a confidence level of α = 0.05, indicate that SST variations have a significant effect on solar panel performance, demonstrating that the proposed solar-powered buoy system can operate autonomously and has potential for long-term SST monitoring in offshore areas.

This study examines the effectiveness of Assemblr Augmented Reality (AR) in improving English vocabulary mastery among deaf students in an inclusive classroom setting. The research was conducted at SD N 2 Bengkala using a quantitative pre-experimental design with a one-group pre-test and post-test approach. The participants were Grade 5 deaf students selected through purposive sampling. Data were collected using a researcher-developed vocabulary test consisting of 15 items, which was validated through expert judgment and demonstrated high reliability (Cronbach’s Alpha = 0.815). Descriptive statistical analysis revealed a substantial improvement in students’ vocabulary scores, with the mean increasing from 45.00 in the pre-test to 76.50 in the post-test. The minimum score improved from 40 to 73, and the maximum score increased from 50 to 80. Inferential analysis using the Wilcoxon Signed-Rank Test showed a significance value of 0.180, indicating no statistical significance due to the small sample size. However, the observed improvement indicates strong practical significance. The findings suggest that Assemblr AR enhances vocabulary learning by providing visual and interactive learning experiences that support deaf students’ cognitive processing. This study highlights the potential of AR technology as an effective instructional medium in inclusive education environments.