Centella asiatica (L) urban is a plant that has the potential to be a source of immunomodulatory agents because it contains several groups of active compounds, asiaticoside, madecassoside, madecassic acid and asiatic acid, which can act as anti-allergic, anti-inflammatory, and immunomodulators. This study aims to review relevant literature to summarize the immunomodulatory effects produced by Centella asiatica (L.) urban. This study used a literature review design involving 4 experimental study articles published in the last 10 years in the electronic databases  PubMed and ScienceDirect. The results of this study showed that C. asiatica has been shown to provide immunomodulatory effects through various mechanisms, including as an anti-inflammatory by decreasing nitrite production, PGE2 and TNF-?, reducing NF-?? activation, and inhibiting pro-inflammatory mediators induced by IFN-? and TNF-?, including IL-6 and COX-2. C. asiatica can also act as an antioxidant that inhibits ROS production, stimulates GSH, and binds free radicals. In addition, C. asiatica can also play a role in the adaptive immune response.

Instilling moral values in elementary school students presents its own challenges in the era of globalization, especially with the emergence of Generation Z, who have distinctive characteristics. This study aims to analyze the strategies employed by teachers in teaching moral education at the elementary level. A descriptive qualitative approach was applied by reviewing relevant literature sources. The findings reveal that teachers play a crucial role as role models and mentors in embedding Pancasila values through active learning, integrating moral values into the curriculum, and utilizing contextual learning media such as folklore rooted in local wisdom. Challenges encountered include environmental influences, limited resources, and students’ low awareness of the importance of morals. This study highlights the need for collaboration among schools, families, and communities, as well as continuous teacher competency development, to foster students with noble character, ethics, and readiness to contribute positively to the nation.

Purpose: The study is conducted to determine the factors that affect sustainable development goals (SDGs) in Indonesia listed companies with a green accounting approach. Three independent variables (ESG disclosure, environmental performance, and green accounting) were empirically tested to determine their relationships with sustainable development goals (SDGs).
Method: The data set covers 16 companies that are consistently listed on the Jakarta Islamic Index (JII) during the period 2020 - 2024, data source was collected with purposive sampling technique, and hypotheses were tested using an ordinary least square regression random effect model.
Findings: The results showed that ESG disclosure, environmental performance, and green accounting simultaneously affect sustainable development goals. Partially, ESG disclosure and environmental performance have a significant positive effect on sustainable development goals, while green accounting has no effect on sustainable development goals.
Novelty: This study brings us to a different point of view, explaining that achieving sustainable development goals from a green accounting perspective. According to the findings, stakeholders can use it in making business decisions, both by companies and governments. Further research can add the variable of company value to see the investor’s perspective in contribute achieving sustainable development goals.

Facial recognition, a branch of image processing, is widely used in attendance systems to improve efficiency and security. This study develops an employee attendance monitoring system that integrates facial recognition using the Eigenface algorithm in OpenCV. The system records each individual's facial data alongside a password, enabling automated attendance tracking. Testing results indicate that with a database of 10 facial entries, the system achieved 100% accuracy in recognizing individuals. However, as the database expanded beyond 10 entries, accuracy declined to 80%, influenced by factors such as lighting variations, differences in facial structures, and increased data volume. This study employed a Research and Development (R&D) methodology, with expert validation yielding a score of 3.4, categorizing the system as "Highly Valid." User testing with 11 participants resulted in an overall score of 36, classifying the system as "Very Good (Valid)." The findings highlight the potential of facial recognition in improving attendance management while minimizing fraudulent entries. Future research should focus on optimizing recognition accuracy in larger databases through refined preprocessing techniques, image quality adjustments, and deep learning models.

The implementation of Artificial Intelligence-based Decision Support Systems (AI-DSS) in recruitment has significantly enhanced efficiency; however, concerns regarding algorithmic bias persist. Existing AI-DSS models primarily emphasize explicit data, often neglecting psychological and behavioral factors essential for fair recruitment. This study integrates Person-Job Fit and Person-Organization Fit theories into AI-DSS while employing adaptive learning techniques to mitigate bias. Using a mixed- methods approach with an explanatory sequential design, this research combines quantitative analysis (statistical comparisons of AI-DSS and traditional hiring methods, bias evaluation using fairness metrics) with qualitative insights (interviews with HR professionals and candidates). The findings indicate that AI-DSS improves selection efficiency and candidate performance yet remains susceptible to biases derived from historical data. Adaptive learning enhances fairness; however, ethical concerns about transparency and accountability persist. This research strengthens the AI recruitment debate by suggesting a comprehensive model that balances the operational efficiency, ethical needs, and fair practices. Explaining AI paradigms requires additional research to establish trust and flexibility for AI recruitment systems.

The rapid development of the current digitalization era has encouraged an increase in e-commerce users  in Indonesia. This phenomenon also triggers impulse buying behavior  for consumers, especially for Shopee consumers. However, there are inconsistencies in the results of one study related  to the influence of hedonic shopping motivation and shopping lifestyle on impulse buying, so further analysis is needed by considering the role  of sales promotion as a moderation variable. The purpose of the study was to determine whether hedonic behavior had a significant impact on impulse purchases of shopee consumers in Denpasar. (2) To determine whether the shopping lifestyle has an impact on impulse purchases, especially shopee consumers in Denpasar. (3) To determine whether the promotion of consumer behavior moderates the relationship between hedonistic motivation and impulse purchases of shopee consumers in Denpasar City. (4) To determine whether sales promotion moderates the relationship between impulse purchases and shopping made by shopee consumers in Denpasar. This study uses a quantitative approach method using non-probability sampling techniques. The data analysis techniques used were multiple regression analysis and classical assumption tests. The results and conclusions resulting from this study show that: (1) Hedonic motivation to buy has a positive and significant impact on impulse purchases. (2) A shopping lifestyle that has a positive and significant impact on impulse buying (3) The relationship between impulse buying and hedonic motivation can be strengthened or moderated by sales promotions. (4) Sales promotions can strengthen or moderate the relationship between impulse purchases and shopping habits.

The scope of pretrial authority is regulated under Article 77 of the Indonesian Criminal Procedure Code (KUHAP), with an extension of authority introduced through the Constitutional Court Decision Number 21/PUU-XII/2014. The evidentiary process in pretrial proceedings is governed by Article 2 paragraphs (2) and (4) of the Supreme Court Regulation of the Republic of Indonesia Number 4 of 2016 concerning the Prohibition of Judicial Review of Pretrial Decisions. However, in practice, petitions for pretrial often address matters beyond this prescribed authority. Moreover, there remains a disparity in judicial reasoning across different judges, particularly with respect to the evaluation of evidence in the determination of a suspect.The legal issues examined in this study are: (1) whether the expansion of the pretrial authority’s scope has led to multiple interpretations among law enforcement officers, and (2) how the evidentiary process in pretrial proceedings aligns with the principle of legal certainty. This thesis employs normative legal research using statutory, conceptual, and case approaches. The findings of this thesis reveal that the expansion of pretrial authority has indeed created multiple interpretations among law enforcement officials, owing to inconsistencies in pretrial decisions that result from judicial discretion. Furthermore, the evidentiary process in pretrial proceedings ought to be limited to the formal aspects of investigative or prosecutorial actions. Nevertheless, certain pretrial rulings have considered the substance and quality of evidence, and even assessed the conduct of the suspect. Such practices undermine legal certainty for justice seekers. Therefore, the Supreme Court should issue more concrete regulations concerning the scope of pretrial and the evidentiary standards applicable in pretrial proceedings.

The coffee shop industry in Indonesia is experiencing rapid growth, including D'Kopikap as one of the businesses facing challenges in managing production and inventory. The main difficulty lies in the uncertainty in predicting the number of sales, which is influenced by various factors such as the type of day (weekdays, weekends, holidays, and promo days) and the time of sale. To overcome this problem, a sales prediction system using multiple linear regression algorithm was developed. System development is carried out using the Rapid Application Development (RAD) approach to accelerate the design and implementation process. The data used in this research is divided into two parts, namely training and test data of 80:20. The results showed that the sales prediction system created was able to provide sales forecasts that could be used to assist production planning and inventory management. Evaluation of the model shows the Root Mean Squared Error (RMSE) value of 22.48, Mean Absolute Percentage Error (MAPE) of 37.18%, and Coefficient of Determination (R²) of 72.26%. These results indicate that the model has good enough predictive ability to be used in operational activities. This research is expected to be the basis for the development of a better sales prediction system in the future.

Instagram is the second most used social media platform in Indonesia after WhatsApp social media which has a percentage of 90.9.7% of users. Meanwhile, Instagram has a percentage of 85.3% as of January 2024, namely with 139 million users. Kopi Good Day Indonesia uses Instagram as one of its digital marketing strategies. The purpose of this study was to determine the perception of followers of the Instagram account @gooddayid. This study uses a qualitative method with the subject being Generation Z in Semarang City. Based on the analysis that has been carried out by the researcher, it shows that the perception that is built on Instagram followers @gooddayid, Many factors influence perception, such as personal experiences of Instagram users with content, interest in coffee products, and the visual communication style displayed by the Kopi Good Day account. Kopi Good Day has become the first brand that comes to mind for the five informants when talking about instant coffee products that are suitable for accompanying relaxing time

The goal of this study was to find out how the Fix-up method affected the reading comprehension of class X students in SMAN 1 Harau District. Students' difficulties with reading comprehension while learning English are the impetus for this study. Reading scores for students are low. The majority of students did not achieve the KKM or Minimum Standard Score, as indicated by their daily reading tests. Vocabulary is lacking among students. Many students are still unable to comprehend the sentence's meaning when presented with advertisement text using common vocabulary, and they lack motivation to read. The researchers compared two classes using quantitative methods and a quasi-experimental research design in this study. This study's participants were students in class X at SMAN 1 Harau District, with X-E.7 serving as the control group with 30 students and X-E6 as the experimental group with 27 students. A reading test serves as the research instrument. On SPSS 26, an independent sample T-test was used to analyze the data. Students who were taught using the Fix-up strategy and students who were taught without using the Fix-up strategy achieved significantly different levels of reading comprehension. strategy. The fact that the p-value is lower than the alpha value (0.000 0.05) demonstrates this. It is possible to draw the conclusion based on these data that students' reading comprehension is significantly affected by the use of the fix-up strategy.