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This study investigates the role of Enterprise Information Systems (EIS) in driving innovation within organizations. The research employs a mixed-method approach, combining survey-based structural analysis and in-depth organizational case studies to explore how different EIS capabilities influence organizational innovation. The study focuses on four key EIS capabilities: functional capabilities such as workforce management and customer value creation; technological capabilities including ERP systems and real-time analytics; dynamic capabilities, especially organizational learning; and collaborative innovation through external partnerships. The survey results reveal that EIS capabilities, particularly data analytics and integration, significantly enhance organizational agility, decision-making, and innovation outcomes. In-depth case studies provide detailed insights into how these capabilities are applied in real-world organizational settings, illustrating their impact on process and service innovation. The findings indicate that the effective integration of EIS across organizational functions, along with improved access to data, contributes to operational efficiency and innovation success. However, challenges such as integration issues, resistance to change, and lack of skilled personnel were also identified as barriers to successful EIS adoption. The study contributes to the literature by offering a comprehensive understanding of how EIS capabilities drive innovation and highlighting the importance of organizational culture and leadership in the adoption process. The research provides practical recommendations for organizations to leverage EIS for fostering innovation, such as focusing on EIS integration, overcoming organizational barriers, and ensuring leadership engagement. Finally, the study suggests future research directions, including the refinement of multi-method approaches and the need for longitudinal studies to better understand the long-term impact of EIS on innovation outcomes.

Mr. Ujang Cracker Factory, located in Pakiskembar Village, Pakis District, Malang Regency, is one of the UMKM that produces crackers. Most of the machines used in cracker processing at Mr. Ujang Cracker Factory still use a simple mechanical system. One of these machines is a cracker molding machine, where the speed is still adjusted manually by replacing the pulley. This study aims to recondition the cracker molding machine by adding a control panel in the form of a VSD inverter with the aim of facilitating the speed control process in operating the cracker molding machine. This study was conducted by analyzing the consistency of the influence of frequency and pulley diameter variations on the speed of the electric motor and mechanical movements in the cracker molding machine. The results of the study show that the frequency of the VSD inverter and the pulley diameter have a significant effect on the entire mechanism of the cracker printing machine. Based on the standard deviation value, the consistency of the pressing movement speed was obtained at a frequency of 40 Hz with a pulley diameter of 2 inches. From this study, it can be concluded that the overall frequency of the VSD inverter is the main parameter in determining the speed and stability of the cracker printing machine. Meanwhile, the variation in pulley diameter only serves as an additional mechanical adjustment to increase or decrease the output speed from the electric motor to the mechanical movement of the cracker printing machine.

Leaf springs serve as vehicle weight supports and vibration dampers from uneven roads. Reducing vehicle weight can support fuel consumption reduction. The use of composite materials allows for a reduction in leaf spring weight without reducing load capacity and stiffness. The purpose of this study was to find the composition of composite leaf springs with a polyurethane matrix that were resistant to tensile and flexural tests using e-glass, epoxy, and polyurethane materials. This study used an experimental method, in which specimens were tested using a tensile and flexural testing machine. The variations included polyurethane matrices of 10%, 20%, and 30%. The data was statistically analyzed using Excel to determine the significant effect of the variables. The results showed the effect of polyurethane variation on the composite. The tensile test showed that the greatest tensile stress was on the 30% polyurethane specimen at 1.574 N/mm² and the smallest was on the 10% specimen at 7.007 N/mm². In the flexural test, the greatest effect on flexural strength was observed in the 30% specimen at 14.36 MPa and the smallest in the 10% specimen at 25.82 MPa. Without the addition of polyurethane, the tensile stress was 39.678 N/mm² and the flexural strength was 157.09 MPa. Conclusion: The addition of polyurethane reduces the mechanical strength of composite leaf spring material without polyurethane addition.

Composite materials have the potential to be used as an alternative material for e-scooter frames due to their low weight and good mechanical strength. The mechanical properties of composite materials are strongly influenced by their constituent materials, particularly the fiber fraction. This study aims to analyze the effect of fiberglass composition variations on the tensile strength of composite materials as an alternative for e-scooter frames. The results show that increasing the fiberglass content leads to an improvement in the tensile strength of the composite material. The tensile strength increased by 51.52% when the fiberglass content was increased from 40% to 50%, while an increase of 19.5% was observed from 50% to 60%, indicating a decreasing rate of improvement. At higher fiberglass compositions, voids were observed due to imperfections in the manufacturing process, which affected the bonding between the fiber and the resin. In addition, increasing the fiberglass content resulted in a reduction in tensile strain from 1.1% at 40% fiberglass to 0.55% at 60% fiberglass, indicating that the material became stiffer and more brittle. These results indicate a trade-off between increased tensile strength and reduced ductility of the composite material.

The advancement of automotive technology has accelerated the adoption of renewable‑energy‑based electric vehicles, including the integration of solar panels on electric scooters. Indonesia’s tropical climate provides abundant solar energy potential; however, the limited surface area of scooters often restricts panel placement to the footrest section. This study aims to evaluate the impact of using a 10 mm clear acrylic cover on the performance of a 50 Wp monocrystalline solar panel in an electric scooter battery‑charging system. An experimental method was employed by comparing the panel’s performance under two conditions: without a cover and with the acrylic cover installed. Key parameters observed included voltage, current, and charging power, recorded using a data logger. Tests were conducted for 30 minutes under varying solar radiation intensities. The results indicate that the acrylic cover reduces the panel’s output power, from 55 W to 45 W at a solar radiation intensity of approximately 1100 W/m². These findings suggest that the use of an acrylic cover must be carefully considered to maintain optimal charging system performance.

User reviews on the Shopee e-commerce platform represent an important source of information for understanding consumer perceptions of products and services. Sentiment analysis is commonly applied to classify user opinions into positive, neutral, and negative sentiment categories based on textual data. This study aims to analyze the performance of the Long Short-Term Memory (LSTM) method in sentiment classification of Shopee user reviews. The dataset used in this study consists of Indonesian-language user reviews that have undergone preprocessing stages, including case folding, text cleaning, tokenization, and stopword removal. The LSTM model was trained using preprocessed text represented as word sequences. Model performance was evaluated using overall accuracy and class-wise classification results. The experimental results indicate that the LSTM method achieved an overall accuracy of 87.62%. In addition, the classification performance for the positive sentiment class reached 95.27%, the neutral class achieved 4.96%, and the negative class reached 74.26%. These results demonstrate that the LSTM method performs well in classifying sentiment in Shopee user reviews, particularly for positive sentiment. This study is expected to provide insights and references for the application of deep learning methods in sentiment analysis of Indonesian e-commerce review data.

This research aims to develop a multiclass flower image classification system using the Convolutional Neural Network (CNN) algorithm with the EfficientNet architecture. The main problem addressed is the difficulty of manual identification of flower species that share high visual similarity. The research stages include collecting 17,299 flower images across 19 classes, performing data preprocessing such as image resizing, pixel normalization, and augmentation, followed by model training using the EfficientNet transfer learning approach. The model was trained for 10 epochs with an 80:20 training-validation data split. The evaluation results show that the model achieved a validation accuracy of 98.05% with a loss value of 0.0968, and an average precision, recall, and F1-score of 0.98. The trained model was then implemented into a web-based application built using the Next.js framework, enabling users to upload flower images and obtain real-time classification results via the Hugging Face API. The system successfully identified flower species with a confidence level of 99.87%. These findings demonstrate that combining a modern CNN architecture with transfer learning provides efficient and highly accurate flower classification performance, which can be effectively implemented for educational and digital conservation purposes.

This study presents a comprehensive comparative analysis of four traditional machine learning algorithms Decision Tree, Random Forest, K-Nearest Neighbors, and Support Vector Machine for Android malware detection using the preprocessed TUANDROMD dataset comprising 4,465 instances and 241 features representing both static and dynamic application characteristics. Motivated by the limitations of conventional signature-based and hybrid detection methods, especially in managing imbalanced datasets and detecting emerging malware variants, the study employed SMOTE to ensure balanced training data and fair model evaluation. The dataset was divided into 80% training and 20% testing subsets, and models were assessed using key performance metrics including accuracy, precision, recall, F1-score, and ROC AUC. The findings revealed that the proposed Random Forest model outperformed the other classifiers, achieving an accuracy of 0.993, precision of 0.992, recall of 1.000, F1-score of 0.996, and a near-perfect ROC AUC of 0.9998 surpassing state-of-the-art approaches. These results affirm the superior predictive capability, consistency, and robustness of the Random Forest algorithm in Android malware detection. The study concludes that base models, when integrated with class-balancing techniques, provide reliable and efficient malware detection across imbalanced datasets. For future research, the study recommends exploring advanced hybrid or ensemble frameworks that integrate Random Forest with deep learning architectures or other meta-heuristic optimization techniques to further enhance detection accuracy, adaptability, and resilience against rapidly evolving Android malware threats.

The high unemployment rate in Indonesia highlights the importance of enhancing work readiness among young people from an early educational stage. Work readiness is influenced by several factors, including learning motivation, communication skills, and parental support. This study aims to examine the relationship between learning motivation, communication skills, and parental support with work readiness among twelfth-grade students at SMAK Kasih Anugrah. This research employed a quantitative approach with a cross-sectional design. The population consisted of all 30 twelfth-grade students, and a saturated sampling technique was applied. Data were collected using structured questionnaires and analyzed through univariate and bivariate analysis using the Chi-Square test. The results indicate a significant relationship between learning motivation and work readiness (p-value = 0.021), communication skills and work readiness (p-value = 0.014), and parental support and work readiness (p-value = 0.005). These findings suggest that learning motivation, communication skills, and parental support play a crucial role in improving students’ readiness to enter the workforce. The results of this study are expected to provide practical implications for schools and parents in strengthening students’ preparation for the world of work

Intellectual Property Rights (IPR) are the result of human thought that have economic and social value and play a significant role in encouraging creativity, technological innovation, and sustainable national development. IPR protection not only aims to provide legal certainty for creators and rights holders, but also serves as a strategic instrument in strengthening the creative economy. However, low public awareness of the importance of IPR protection and the gap between legal norms and practices in the field result in frequent violations of intellectual works. This study uses a normative-juridical approach combined with a participatory-educational approach, in accordance with the characteristics of community service activities in the legal field. This approach aims to integrate normative legal analysis with legal education activities for the community, thereby producing both conceptual understanding and practical benefits. The results of the activities show a significant increase in public understanding of the relationship between constitutional principles and IPR protection in Indonesia. Through educational activities and legal dialogues, it was revealed that the integration between constitutional principles and the IPR legal system has not been optimal, not only due to limited regulations, but also weak public legal awareness and the application of substantive justice as mandated by the 1945 Constitution. These findings emphasize the importance of integrating constitutional values ​​in the IPR protection system.

The Community Service Program (PkM) focused on mentoring storytelling competitions was implemented as an effort to improve students' competence in the art of storytelling, while also supporting their preparation for the FLS3N event. The activity was designed through a series of training sessions that included understanding the concept of storytelling, examples of storytelling practices, hands-on practice, and periodic evaluations. During the mentoring process, students showed progress in terms of story mastery, intonation, expression, and confidence. The approach used encouraged active participation so that participants were able to improve their storytelling techniques based on the feedback provided. The results of this activity show that structured and continuous training can improve students' readiness to present stories in a more communicative and interesting manner in upcoming competitions.

Individuals with mental disabilities commonly experience difficulties in self-awareness and emotion regulation, which negatively affect social functioning and psychosocial well-being. These conditions were also observed among beneficiaries in the assisted community, who demonstrated limitations in recognizing emotions, expressing feelings, and engaging in social interactions. This community service program aimed to strengthen self-awareness and emotional regulation skills among individuals with mental disabilities through a psychosocial approach. The program employed activity-based psychoeducation using participatory and supportive methods, including emotional recognition training, self-reflection, positive emotional stimulation, and structured group support. The results indicated improvements in beneficiaries’ ability to identify and express basic emotions, increased self-confidence, enhanced emotional stability, and more active social participation. Qualitative observations revealed behavioral changes from passive tendencies to more responsive and cooperative involvement in group activities. These findings suggest that activity-based psychosocial interventions are effective in improving psychosocial well-being among individuals with mental disabilities.

This Community Service (PkM) activity was implemented in the form of an entrepreneurship seminar. This seminar strategically raised the theme "Changing the Mindset Shift from Follower to Owner", with the crucial aim of facilitating a paradigm shift in participants from mere passive consumers or followers to active and empowered business owners (owners). The implementation of PkM is based on the reality of the high unemployment rate among educated people and the urgency of global economic challenges that demand mental transformation and strengthening of practical skills. The main target group of this activity included students of entrepreneurship study programs from various universities in East Java as well as representatives of Micro, Small, and Medium Enterprises (MSMEs) operating in the Gresik area, ensuring the relevance of the material to academic and practical needs. This seminar featured two credible expert speakers in the field of entrepreneurship. The implementation method focused on interactive delivery of material, followed by a focused discussion session to maximize knowledge absorption. The results achieved showed a significant increase in understanding among participants, not only regarding the importance of instilling an entrepreneurial mindset but also mastery of practical aspects of business, including digital marketing implementation strategies and concrete steps in starting or developing a business unit. Through this intervention, PkM is expected to be able to provide a real contribution to accelerating the creation of new, innovative entrepreneurs and strengthening the sustainable entrepreneurial ecosystem in East Java

Stevens–Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are rare, life-threatening mucocutaneous reactions characterized by extensive epidermal necrolysis and mucosal involvement. The entities represent a clinical continuum distinguished by the extent of epidermal detachment (SJS <10% body surface area [BSA], SJS/TEN overlap 10–30%, TEN >30%). Most cases are drug-induced, making early culprit-drug withdrawal and structured supportive care the cornerstones of management. Immunopathogenesis is primarily mediated by drug-specific cytotoxic T cells and NK cells through granulysin, Fas–Fas ligand, and perforin/granzyme pathways, with emerging roles of necroptosis and candidate biomarkers such as RIP3 and galectin-7. Diagnosis relies on timely recognition of the characteristic painful erythematous/targetoid lesions, Nikolsky/Asboe–Hansen signs, multi-site mucositis, accurate BSA assessment, and early severity scoring (e.g., SCORTEN) to guide referral and monitoring. Systemic immunomodulators (corticosteroids, cyclosporine, IVIg, anti-TNF agents) have variable evidence; thus, individualized selection and early multidisciplinary care particularly ophthalmologic involvement are essential to reduce acute mortality and long-term sequelae.

The rapid development of artificial intelligence (AI) in the medical field has become an important part of the learning process and health services. Preparing medical students as future healthcare professionals to understand, use, and implement AI responsibly is a crucial aspect. This level of readiness can vary depending on their knowledge, abilities, perceptions, and ethics in using AI. This study aims to determine the readiness of young medical students in the Surabaya area in using artificial intelligence based on these four domains, and to compare scores between first-year professional students and undergraduate students. This study used a quantitative descriptive design with a cross-sectional approach. The instrument used was the Medical Artificial Intelligence Scale for Medical Students questionnaire, which consists of four domains: knowledge, abilities, perceptions, and ethics. The study sample was first-year and second-year professional students of the Faculty of Medicine, Ciputra University. Data analysis was performed using descriptive statistics including mean values, standard deviations, and frequency distributions for each domain. The results showed that the total readiness scores for DM1 (89.95 ± 11.84) and DM2 (88.38 ± 8.85) showed a positive picture, with minimal mean differences. The knowledge and skills domain showed almost uniform values ​​between the two groups, while the ethics domain had the highest stability with a very small mean difference. These findings indicate that the readiness of professional students at the Faculty of Medicine, Ciputra University, towards the use of AI shows a positive and relatively even picture at all levels.  

General practitioners play a crucial role in the delivery of healthcare services in public hospitals, where limited organizational resources and high service demands often place significant pressure on medical personnel. These conditions may disturb work–life balance, increase the risk of burnout syndrome, and ultimately lead to higher turnover intention. This study aimed to analyze the effect of work–life balance on turnover intention, with burnout syndrome acting as an intervening variable among general practitioners at RSUD Balaraja. An observational analytic design with a cross-sectional approach was applied, involving all 40 general practitioners working in the emergency department and inpatient units through a total sampling technique. Data were collected using standardized instruments, namely the Work–Life Balance Scale, Maslach Burnout Inventory, and the Intention to Quit Questionnaire. Data analysis was conducted using Spearman correlation and Structural Equation Modeling–Partial Least Squares (SEM-PLS). The results revealed a significant relationship between work–life balance and burnout syndrome, as well as between work–life balance and turnover intention. Burnout syndrome was also significantly associated with turnover intention. Further analysis showed that work–life balance had both direct and indirect effects on turnover intention, with burnout syndrome partially mediating this relationship. In conclusion, work–life balance and burnout syndrome are important determinants of turnover intention among general practitioners. Therefore, hospital management should prioritize strategies such as workload regulation, enhanced organizational support, and burnout prevention to retain medical staff and maintain the quality of healthcare services in public hospitals.

Excessive alcohol consumption, including traditional alcoholic beverages such as Cap Tikus  (alcohol content ±45%) from North Sulawesi, can induce liver damage characterized by steatosis, inflammation, and necrosis. Leilem leaf (Clerodendrum minahassae) extract, rich in phenolic and flavonoid compounds, has potential hepatoprotective effects due to its antioxidant properties. To evaluate the effect of leilem leaf extract on the histopathological features of the liver in Wistar rats (Rattus norvegicus) induced by Cap Tikus alcoholic beverage. This experimental study used a post-test only control group design with 24 male Wistar rats divided into four groups: normal control, negative control (Cap Tikus 2.16 mL/day), treatment I (leilem extract 150 mg/kgBW + Cap Tikus), and treatment II (leilem extract 300 mg/kgBW + Cap Tikus). Treatments were administered orally for 14 days. Liver tissue was processed for histopathological examination using hematoxylin-eosin staining and observed under a light microscope. The negative control group showed significant steatosis and inflammatory cell infiltration. Treatment groups exhibited reduced steatosis and inflammation, along with increased hepatocyte regeneration. The higher dose (300 mg/kgBW) demonstrated greater hepatoprotective effects and more prominent regeneration compared to the lower dose (150 mg/kgBW). No necrosis or fibrosis was observed in any group. Leilem leaf extract exerts a hepatoprotective effect by suppressing inflammatory responses and enhancing hepatocyte regeneration in Wistar rats induced with Cap Tikus. The highest protective efficacy was observed with leilem leaf extract at 300 mg/kgBW.

This qualitative inquiry examines the deliberate operational timing adopted by street vendors selling martabak, a popular Indonesian snack, exploring why nocturnal hours are strategically favored over daytime. The research methodology combined in-depth interviews with ten vendors operating in urban centers like Jakarta and Bandung with a consumer survey of one hundred respondents. Analysis of the collected data identifies a dual strategic foundation. From a demand perspective, night-time aligns with consumer psychology, fostering a leisurely atmosphere conducive to social snacking and impulsive purchases. On the supply side, vendors benefit from diminished direct competition, reduced operational overheads, and tapping into peak demand for evening treats. This synergy effectively cements martabak’s market identity as a beloved night-time culinary ritual linked to socialization. Consequently, the study posits that this chrono-marketing approach represents a savvy adaptation to local socio-economic rhythms. The insights derived provide a framework for micro-entrepreneurs to optimize service timing, aligning business operations with ingrained cultural consumption cycles to enhance sustainability and customer loyalty.  

With financial inclusion acting as a moderator, the goal of this study is to examine how financial technology use and financial literacy impact microbusiness performance. Microbusinesses in Bandar Lampung City's food and beverage industry serve as the research subjects. This study employs a quantitative approach, using questionnaires to collect primary data from microenterprises. Purposeful sampling was used to choose 203 microbusinesses that met the research criteria. SPSS was utilized to analyze the data using multiple linear regression and Moderated Regression Analysis (MRA). The study's conclusions imply that the use of financial technology has an effect on microenterprises' performance. Additionally, it has been shown that financial literacy affects microenterprise performance. The findings show that key components in increasing microbusiness performance are the use of financial technology and the entrepreneur's capacity to supervise and make financial decisions. However, the test results indicate that financial inclusion cannot boost the impact of financial technology and financial expertise on microbusiness performance. This implies that the influence of financial technology and financial knowledge on business success is not necessarily enhanced by having access to financial services. It also shows that a key factor in increasing the success of microbusinesses is the characteristics of the entrepreneur. The research's objectives are to assist important stakeholders in creating plans for microenterprise growth, as well as to assist microenterprise actors in improving their financial literacy and utilizing financial technology to its fullest.