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PT. Tirta Fresindo Jaya, specifically its Pasuruan plant as the producer of Pucuk Harum Tea beverage, requires a large supply of steam to support various production processes. This steam is used in the process of heating tea leaves, heating water through a heat exchanger, and heating chemicals and water in the cleaning in place (CIP) process. Steam pressure of 5 bar that is flowed to the process equipment will undergo condensation to produce condensate. To separate steam and condensate, steam traps are used, consisting of several types, namely mechanical, thermostatic, and thermodynamic. However, in operational practice, steam trap malfunctions often occur, either in the form of steam leaks that are wasted with condensate or failure to drain condensate from the system. This condition causes a decrease in the efficiency of the steam piping system and increases the workload of the boiler. As a result, fuel consumption and boiler feed water requirements become greater than ideal conditions. Therefore, this study aims to analyze the energy and operational losses caused by steam trap malfunctions, as well as evaluate their impact on boiler system performance and steam utilization efficiency at PT. Tirta Fresindo Jaya Pasuruan plant.      

The integration of Information and Communication Technology (ICT) and tools like Canva has revolutionized English Language Teaching (ELT) in Indonesia, shifting from traditional methods to interactive, student-centered approaches. This study aims to explore the benefits and challenges of incorporating these technologies into ELT practices. Employing a qualitative literature review methodology, the research analyzed over 20 empirical studies from 2020 to 2023 on Canva and ICT in Indonesian ELT, supplemented by global Computer-Assisted Language Learning (CALL) frameworks. Key findings reveal that ICT and Canva enhance student motivation, creativity, and communicative skills through multimodal and constructivist learning, while fostering authentic language exposure and collaboration. However, challenges include inadequate infrastructure, limited teacher training, digital inequities between urban and rural areas, ethical issues such as copyright infringement, and increased teacher workload. The implications underscore the need for systematic professional development, institutional support, curriculum alignment, and policies promoting equitable access to ensure transformative and sustainable technology integration in Indonesian ELT.  

This study seeks to investigate a consumer behavior model by evaluating the impact of interactive technology-driven digital innovation and perceived value on digital engagement, with customer behavior serving as a mediating variable within the retail sector in Jambi Province. A quantitative research design utilized a survey method with 150 retail consumers as participants. We used Structural Equation Modeling–Partial Least Squares (SEM-PLS) to look at both the measurement and structural models. The findings of the measurement model show that all indicators match the requirements for convergent validity. The outer loading values are all over 0.70, which means that the construct is reliable and valid. The evaluation of the structural model indicates that perceived value exerts a positive and significant influence on both consumer behavior and digital engagement. Also, how people act as consumers has a big effect on how they contact with and participate in digital media. This means that people who think retail services are more valuable are more likely to interact with and participate in digital media. Nevertheless, interactive technology-driven digital innovation does not exhibit a substantial direct impact on customer behavior or digital engagement. These findings suggest that value perception is more influential than technology innovation in determining consumer responses inside digital retail environments. This research enhances the body of knowledge regarding consumer behavior and digital marketing by highlighting the strategic significance of perceived value in augmenting consumer involvement within digital retail contexts.

The use of e-wallets is increasing in Indonesia, especially during the Covid-19 pandemic. The most popular digital wallets in Indonesia, such as Go-Pay, OVO, ShopeePay, Dana, and LinkAja, have adapted the mobile banking system, making it easy for users to download the app through the Play Store or App Store. According to Insight Asia, DANA is ranked third in terms of number of users after Gopay and OVO, with 221 respondents from major Indonesian cities. As an e-wallet platform created by PT Espay Debit Indonesi Koe Indonesia in 2018, DANA, as a local company, attracts people's interest and has become a popular choice. This study aims to identify the relationship and influence between Perceived Usefulness and Perceived Ease of Use on Decision to Use E-wallet, especially DANA, with Intention to Use E-wallet as an intervention variable. Through regression tests, the research findings show that Perceived Usefulness and Perceived Ease of Use have a positive and significant effect on Intention to Use DANA, and Intention to Use DANA has a significant effect on Decision to Use DANA. Intention to Use E-wallet mediates the relationship between Perceived Usefulness and Perceived Ease of Use with Decision to Use DANA. This result is obtained by looking at the results of statistical processing, where the p-value <0.005. These findings imply that the perceived usefulness and ease of use of the DANA application has the potential to encourage user interest in using e-wallets, which in turn can influence users' decisions to adopt DANA as an electronic payment method.

This study examines the implementation of the Coretax system in preparing electronic withholding tax slips (e-Bupot) and submitting Monthly Income Tax Article 21 (PPh 21) Returns at PT RSA. Coretax, launched by the Directorate General of Taxes (DGT) and officially implemented on January 1, 2025, is part of the government’s effort to modernize tax administration and improve taxpayer compliance. The research uses a qualitative descriptive method with a case study approach. Data were obtained through interviews with personnel responsible for PPh 21 administration, direct observation of e-Bupot preparation and monthly tax return filing through Coretax, and documentation review of tax reports and withholding slips. The analysis compares PT RSA’s practices with applicable tax regulations and identifies technical challenges during system use. The results show that PT RSA has complied with prevailing regulations, including the application of the Average Effective Rate (TER) and the utilization of Coretax for tax administration. However, technical constraints remain, particularly unstable internet connections and slow Coretax server performance during peak reporting periods, leading to data entry delays and upload failures. Therefore, improvements in system stability and performance are needed to support timely reporting and optimal tax compliance.

The rapid growth of social media has created new opportunities for Generation Z entrepreneurs to build business identity and brand image through digital content. One of the most popular platforms among this generation is TikTok, a short-form video platform characterized by high interactivity and strong viral potential. TikTok is not only used as an entertainment medium but also as a strategic tool for developing business personal branding. However, the utilization of TikTok by Generation Z entrepreneurs has not yet been optimal, particularly in implementing structured and consistent content marketing strategies. This study aims to analyze the use of TikTok and content marketing strategies in building personal branding among Generation Z entrepreneurs. The research employs a descriptive qualitative method with a literature review approach, examining various academic sources, research articles, and relevant reports related to digital marketing and social media. The findings indicate that effective personal branding on TikTok is strongly influenced by the ability to create creative, authentic, informative, and audience-relevant content. In addition, consistency in content uploads and the effective use of TikTok features contribute to increased audience engagement, consumer trust, and business reach. This study is expected to provide insights and practical references for Generation Z entrepreneurs in designing effective and sustainable digital branding strategies in the creative economy era.

The Information System registration module for the Regional Taxpayer Identification Number (NPWPD) was developed using the Laravel framework and implemented by the Taxpayer Identification Agency (BPPKAD) at Kediri City. The system was designed to digitize the NPWPD registration process, which was previously done manually. This traditional approach often led to long queues, extended processing times, and, at times, errors in data entry. The new system offers several key advantages, including an online registration form that allows taxpayers to upload required documents such as photos of ID cards, business locations, and other necessary paperwork. Data validation is performed by officers to ensure accuracy, and automatic notifications are sent to taxpayers, informing them of the status of their applications. The implementation of this system has had several positive impacts, such as significantly improving the efficiency of administrative processes, reducing the manual workload for officers, and increasing transparency and accountability in public services. Moreover, it has improved customer satisfaction by providing faster, more accurate, and more responsive services. This system supports the creation of a streamlined, user-friendly, and effective method for taxpayers to register for NPWPD online, enhancing the overall quality of public sector service delivery.

The rapid development of smartphone technology today creates challenges for consumers and manufacturers in determining an objective price range based on highly varied technical specifications. This study aims to implement the Random Forest algorithm in classifying smartphone price ranges into four main categories, namely low, mid-range, high, and flagship. The research method was carried out systematically through the stages of loading a dataset of 2,000 entries, exploratory data analysis (EDA) to ensure data integrity, and model training with a training and testing data split of 80:20. The results showed that the Random Forest model achieved a significant overall accuracy rate of 89%. Based on feature importance analysis, it was found that RAM capacity was the most dominant determining factor, contributing 47% to prediction accuracy, followed by battery power and screen resolution as supporting features. These findings have strategic implications for manufacturers to prioritize memory capacity upgrades in determining product pricing in the market, as well as providing guidance for consumers in assessing the fairness of a device's price based on its technical capabilities.

Overburden removal at Pit B did not meet the production targets for June and July 2025, which were set at 570,698.8 BCM and 400,986.56 BCM, respectively, while the actual production achieved was 507,071.66 BCM and 312,128.23 BCM. This study aims to determine the theoretical productivity of loading and hauling equipment and to identify the factors that hinder the achievement of production targets. The primary data used in this study include the cycle time of loading equipment, the cycle time of hauling equipment, bucket fill factor, and delay time. The secondary data required consist of swell factor, number of passes, bucket capacity, and available working time. The productivity of the loading equipment was 332.58 BCM/hour, while the hauling equipment achieved a productivity of 53.16 BCM/hour, with a match factor of 0.74. This indicates that the loading equipment experienced waiting time during loading operations due to the hauling equipment not operating optimally or at full capacity. The factors inhibiting the achievement of production targets include a narrow, waterlogged, and uneven working face; hard overburden material; a road grade of 16%, which exceeds the standard maximum of 12%; a curve road width of 15 m, which is less than the ideal minimum width of 19.95 m; undulating haul roads; narrow haul road width; and dusty road conditions.

Arabic grammar (nahwu) instruction has long been dominated by rule-based approaches that emphasize memorization and formal analysis, often resulting in rigid learning structures and limited responsiveness to learners’ cognitive diversity. While such approaches play an important role in preserving grammatical accuracy, they frequently overlook individual learning trajectories, cognitive readiness, and adaptive instructional needs. In the era of artificial intelligence (AI), language education is increasingly shaped by adaptive learning systems that personalize content, pacing, and instructional strategies based on learners’ profiles. This study aims to reconceptualize Arabic grammar instruction by proposing a conceptual framework that integrates traditional nahwu principles with adaptive learning systems informed by AI. Using a qualitative conceptual analysis, this paper synthesizes classical Arabic grammar pedagogy, contemporary theories of adaptive learning, and recent developments in AI-supported language instruction. The proposed framework highlights key components, including learner profiling, cognitive-level alignment, hierarchical nahwu content structuring, and AI-assisted scaffolding mechanisms. The findings suggest that adaptive learning systems offer significant pedagogical potential to transform nahwu instruction from a static, rule-centered model into a flexible, learner-centered process. This reconceptualization is expected to enhance grammatical comprehension, reduce cognitive overload, and promote learner autonomy in Arabic language education, particularly in Islamic higher education contexts. The study concludes by discussing pedagogical implications and directions for future empirical research on AI-assisted Arabic grammar learning.

This research aims to improve the mathematics learning outcomes of Grade VII B students at SMP Darul Ulum 5 Rebalas through the implementation of Madurese language-based ethnomathematics. The study is motivated by the students' difficulties in understanding mathematical concepts delivered in formal Indonesian, as their daily communication relies on the specific Madurese dialect of Rebalas Village. This study employs the Classroom Action Research (CAR) method using the Kemmis and McTaggart model, conducted in two cycles. Each cycle consists of planning, action, observation, and reflection stages. The subjects of this research were 28 students from class VII B. The research instruments included test instruments in the form of group Student Worksheets (LKPD) and observation sheets for both teacher and student activities. The material focused on the topic of Lines and Angles. The results indicated an improvement in student learning outcomes from Cycle I to Cycle II. In Cycle I, the average group score was 80.2, which increased to 88 in Cycle II. Observations of student activities also showed a shift from passive participation in Cycle I to active and enthusiastic engagement in Cycle II. Furthermore, teacher observations showed significant improvement; initial issues regarding time management and excessive workloads were resolved, resulting in more enthusiastic and punctual teaching delivery. These findings demonstrate that the use of Madurese-based ethnomathematics helps students grasp mathematical terms more easily, increases discussion participation, and creates a more comfortable and interactive classroom atmosphere, thereby leading to improved learning outcomes.

In the contemporary digital marketplace, consumers increasingly face diverse product choices and brand communications. Understanding the mechanisms through which product quality and brand perception influence customer loyalty remains critical for competitive advantage. The mediating role of customer trust in this relationship has received limited empirical attention within Indonesian market contexts. This research analyzes the direct and indirect effects of product quality and brand perception on customer loyalty, with customer trust as a mediating variable, using Partial Least Squares Structural Equation Modeling (PLS-SEM) methodology on 103 respondents. A quantitative cross-sectional survey design was employed, collecting data via Likert-scale questionnaires (1-5) with 15 measurement items across four latent constructs: Product Quality (5 items), Brand Perception (4 items), Customer Trust (3 items), and Customer Loyalty (3 items). Data analysis utilized PLS-SEM via SmartPLS 3.0, including assessment of measurement model validity (outer model), structural relationships (inner model), and mediation effects through bootstrapping (5000 iterations). The outer model demonstrated adequate validity with 12 of 15 indicators loading above 0.7, and all constructs meeting composite reliability (CR > 0.7) and average variance extracted (AVE > 0.5) criteria. The inner model revealed that product quality significantly influenced customer trust (β = 0.624, p < 0.001), while brand perception showed no significant direct effect (β = 0.045, p = 0.767). Customer trust strongly predicted loyalty (β = 0.650, p < 0.001). Product quality demonstrated a significant indirect effect on loyalty through trust (β = 0.405, p < 0.001), indicating full mediation. The model explained 43.5% of trust variance and 42.2% of loyalty variance. Product quality emerged as the dominant antecedent of customer trust and loyalty, while brand perception did not significantly contribute. Trust served as the critical mechanism translating quality into loyalty. These findings suggest that companies should prioritize quality assurance and consistent delivery over brand marketing campaigns for sustainable loyalty development. The research contributes to mediation theory in consumer behavior and provides actionable strategic guidance for practitioners in emerging markets.

The massive adoption of Internet of Things (IoT) devices is expanding the cyberattacks surface, particularly by the Mirai botnet, which exploits the dynamic characteristics of data traffic. This research proposes a Mirai detection approach based on a Recurrent Neural Network (RNN) optimized using Bayesian Optimization to improve prediction accuracy on sequential data. Unlike previous studies, this research utilizes the latest CIC IoT-DIAD 2024 dataset and applies probabilistic optimization to the hyperparameter space, including RNN units, dropout, and learning rate. The experiment was conducted on 201,021 valid data points, with dimensionality reduction using PCA as the optimal point to represent essential features without redundancy. The results show a significant increase in accuracy from 97.95% to 99.69%, accompanied by an 84% decrease in False Negatives, an 86% decrease in False Positives, and an AUC value of 0.9999. These findings confirm that integrating RNN and Bayesian Optimization not only improves numerical performance but also strengthens the reliability of the intrusion detection system for modern IoT ecosystems with controlled computational loads.

This study aims to design the User Interface (UI) and User Experience (UX) on the VINIX Showcase Website as a personal branding platform and digital Skill Passport for participants of the VINIX Seven Aurum Program using the Design Thinking method. The background of this research is the absence of an integrated digital platform that can systematically and easily document and display participants' skills, projects, certificates, and professional identity. The design process is carried out through five stages of Design Thinking, namely Empathize, Define, Ideate, Prototype, and Test, starting with exploring user needs, formulating problems, developing solution ideas, creating Prototypes, and Usability Testing. The results of the study consist of the UI/UX design of the VINIX Showcase Website, which includes registration and Login features, user Dashboard, Skill Passport, project upload, public Showcase, and automatic CV generation feature. Testing using the Usability Testing method showed that the resulting design has a good level of ease of use and comfort and is acceptable to users. This research is expected to be an effective digital solution in supporting personal branding, skills documentation, and improving the professionalism of VINIX Seven Aurum Program participants.

The rapid development of the Internet of Vehicles (IoV) has introduced new security challenges, particularly in protecting Controller Area Network (CAN Bus) communications from cyberattacks such as Denial of Service (DoS) and spoofing attacks. This study proposes the implementation of the Extreme Gradient Boosting (XGBoost) algorithm combined with Information Gain feature selection to improve intrusion detection performance in IoV environments. The CICIoV2024 dataset, which represents both benign and malicious traffic, is used as the primary data source. The research process includes data integration, preprocessing, feature selection, data splitting, and model training using a 5-fold cross-validation approach. Experimental results demonstrate that the proposed model achieves outstanding performance, with accuracy, precision, recall, and F1-score exceeding 99.99%, and an Area Under Curve (AUC) value approaching 1.00. Furthermore, Information Gain successfully identifies the most influential CAN payload features, enhancing model efficiency without sacrificing accuracy. These findings confirm that the combination of Information Gain and XGBoost is highly effective for developing a fast, accurate, and efficient intrusion detection system in IoV networks.

The increasing demand for interactive web applications has encouraged the adoption of server-driven approaches such as Livewire as an alternative to building Single Page Applications (SPAs) without complex client-side JavaScript. However, the performance implications of this approach compared to conventional methods remain insufficiently explored. This study presents an empirical comparison between Laravel Blade with AJAX and Livewire in an academic attendance system scenario. Performance evaluation was conducted using k6 on the same web server, complemented by manual browser-based testing to observe actual communication patterns. The results indicate that Livewire exhibits approximately 2.7× higher average response time and up to 6× greater bandwidth consumption than Laravel Blade, primarily due to its snapshot mechanism and state synchronization process. Conversely, Livewire demonstrates better stability, reflected by lower maximum response times and a 0% error rate. These findings highlight a clear trade-off between resource efficiency and development convenience, where Livewire favors stability and developer productivity, while Laravel Blade provides superior efficiency in terms of latency and bandwidth usage.

The growth of coffee shop businesses in Semarang has accelerated in line with the rising coffee consumption trend among younger generations. In this context, employees play a crucial role in ensuring service quality. However, job dissatisfaction triggered by work-related stress and excessive service load remains a significant challenge. This study aims to examine the influence of occupational strain, service load, reward fairness, supervisory support, and work-life balance on job satisfaction among coffee shop employees in Semarang. A quantitative approach was used through a survey method, utilizing a questionnaire distributed via Google Form. A total of 100 respondents from various coffee shops in Semarang were selected using a census technique. The results revealed that occupational strain and service load have a negative and significant effect on job satisfaction. Meanwhile, reward fairness, supervisory support, and work-life balance have a positive and significant impact on job satisfaction. These findings offer valuable insights for coffee shop owners in developing effective human resource strategies that promote employee wellbeing and maintain high service quality.

The enactment of Law Number 1 of 2023 concerning the Criminal Code brought fundamental changes to the regulation of the crime of adultery in Indonesia. The expansion of the scope of criminalization, including regulations regarding extramarital relationships, has given rise to debate regarding its compliance with the principles of the formation of laws and regulations and its impact on criminal law enforcement. This study aims to analyze the provisions of the adultery article in the new Criminal Code from the perspective of the principles of the formation of laws and regulations and assess its implications for the effectiveness of the criminal justice system. This study uses a normative legal research method with a legislative and conceptual approach. Legal materials were obtained through literature studies and analyzed qualitatively and juridically. The results show that the regulation of the crime of adultery in the new Criminal Code has a clear normative purpose, but still leaves issues regarding the clarity of formulation, legal certainty, and potential human rights violations. Furthermore, the application of the adultery article has the potential to create obstacles in law enforcement practices, particularly related to evidence, caseload, and the legitimacy of the criminal justice system. Therefore, further evaluation is needed to ensure that these regulations align with the principles of sound legislative development and ensure legal justice.

Overburden stripping operations in the coal mining industry require optimal performance of loading and hauling equipment to achieve production efficiency. This study aims to evaluate the performance of loading and hauling equipment using the Match Factor method in overburden stripping operations at PT Bumi Artlantis Raya. The results indicate that the equipment combination achieved a Match Factor of 0.85, reflecting moderate compatibility with a potential efficiency improvement of 15%. The actual productivity of Excavator 4002 reached 137.02 bcm/hour (91.35% of the 150 bcm/hour target), while Excavator 4004 exceeded the target with a productivity of 195.73 bcm/hour (130.49% of the target). In contrast, dump truck productivity remained relatively low (Mercedes dump truck: 35.58 bcm/hour; Hino dump truck: 35.40 bcm/hour), primarily due to waiting time during loading and disposal activities. Statistical analysis reveals a strong negative correlation between cycle time and productivity (R² = 0.9929). The optimal cycle time to achieve a Match Factor of 0.80 is 969 seconds, corresponding to an optimal hauling distance of 5.38–6.725 km. Although mechanical availability and physical availability were high (94–100%), the use of availability and effective utilization were relatively low due to an imbalance between loading and hauling equipment. This study concludes that improving equipment coordination, increasing bucket fill factor, enhancing haul road conditions, and implementing preventive maintenance are essential to achieving more optimal operational efficiency in overburden stripping activities.

Waste from used Polypropylene (PP) and High Impact Polystyrene (HIPS) plastic is problematic in its management. The purpose of this research is to obtain the fatigue life of a mixture of used PP and HIPS plastics in its pure plastic. The research method is through the stages of mixing pure PP and 50% volume of used PP, pure HIPS and 50% volume of used HIPS, injection molding of R.R. Moore standard fatigue test specimens for pure PP, pure HIPS, pure PP + used PP, and pure HIPS + used HIPS, checking the straightness and smoothness of the molded specimen surface, fatigue testing with increasing serial loads, analysis of the bending stress curve (S) against fatigue life (N). The results showed that mixing used PP and used HIPS in pure plastic affected the fatigue life at the test speed (n)=2100 rpm for recycled PP was 9.84% shorter than pure PP, and at n=1600 rpm for recycled PP it was 9.32% shorter than pure PP, while at n=2100 rpm for recycled HIPS it was 4.45% shorter than pure HIPS, and at n=1600 rpm for recycled HIPS is 4.77% shorter than pure HIPS, while the fatigue life of pure PP is 1627704 cycles and the fatigue life of pure HIPS is 1291636 cycles or the fatigue life of pure HIPS is 20.65% shorter than pure PP, the implication of which is that the addition of used PP and used HIPS reduces the fatigue life to 9.84% for PP and 4.45% for HIPS.