This research focuses on the development of an Android-based vegetable detection application by utilizing digital image processing technology and data communication through Application Programming Interface (API). This application is designed to make it easier for users to visually recognize different types of vegetables using the device's camera. The detection process is carried out by sending the image to a cloud server, where the image analysis process is carried out to identify the type of vegetable, displaying its name, characteristics, and benefits. The app's implementation includes an intuitive and user-friendly user interface, with key features such as login, registration, and an interactive dashboard. The dashboard displays user information, location, ambient temperature, vegetable detection history, and direct access to the camera for real-time detection processes. The utilization of cloud computing technology not only keeps application performance lightweight and responsive, but also enables high processing efficiency and data scalability. This allows the application to continue to evolve according to the increasing number of users and incoming data. Image processing is done with machine learning algorithms that are trained to recognize the shape, color, and texture of different types of local vegetables. In addition, this system is also equipped with a periodic data update feature to be able to adjust to the development of new vegetable classifications. The test results show that the app is able to recognize different types of vegetables with a high level of accuracy, as well as provide additional relevant information quickly and accurately. Tests are carried out on a variety of lighting and background conditions to ensure the reliability of the system. The success of the development of this application reflects the integration of modern technology in supporting the digital agriculture sector.

PT Unilever Indonesia’s strategic application is examined through the Balanced Scorecard framework, focusing on four key perspectives: financial, customer, internal business processes, and learning and growth. The analysis reveals that while the company demonstrates strong financial performance, such as high ROI and ROE, challenges like declining annual profits and increasing liabilities signal the need for improved cost management and risk mitigation. Unilever's strategy emphasizes innovation and customer relationships, leveraging Total Quality Management (TQM) and continuous product enhancements. However, internal issues such as employee work culture, inadequate facilities, and employee satisfaction remain significant obstacles to organizational performance. The findings suggest a need for stronger employee engagement and workplace improvements, alongside enhanced financial sustainability strategies. Future research could explore how external factors, such as shifting market trends and government regulations, influence Unilever’s strategic decisions and overall success.

Exclusive breastfeeding plays a crucial role in reducing neonatal mortality rates, preventing growth disorders, and enhancing immunological resilience. However, adherence to exclusive breastfeeding practices remains below the targeted level. This study aims to analyze the relationship between maternal characteristics, knowledge, and family support with the success of exclusive breastfeeding in infants. A cross-sectional design was used, conducted at the UPTD Sawang Health Center, South Aceh Regency, during February–March 2025. The population consisted of all mothers with infants aged 7–12 months visiting the health center, totaling 120 individuals. A sample of 97 respondents was selected using purposive sampling. Data were collected through a structured questionnaire, followed by data processing that included response completeness checks, variable coding, and data entry. Data analysis comprised univariate analysis to present the frequency distribution of maternal characteristics and knowledge, and bivariate analysis using the Chi-Square (χ²) test with a significance level of α=0.05 to test the hypotheses. The results showed that maternal employment was significantly associated with the success of exclusive breastfeeding (p < 0.001), whereas maternal education (p = 0.566), income (p = 0.915), maternal knowledge (p = 0.351), and family support (p = 0.252) were not significantly related. In conclusion, maternal employment has a significant relationship with exclusive breastfeeding success

Cafes in Jember Regency continue to grow significantly amid increasingly fierce competition among businesses and the rise of MSMEs in the digital era. The culinary industry, particularly the café sector in Jember Regency, has seen significant growth, presenting promising opportunities for café owners and a substantial market. Numerous cafés are spread across various neighborhoods in Jember Regency. This study focuses on how social media can be utilized for customer engagement and promotion. Additionally, entrepreneurial motivation is examined as a factor that can enhance the influence of these elements on business success. To explore the relationships among these factors, data was gathered through questionnaires and analyzed using multiple linear regression techniques. A quantitative survey approach was used to collect information from 100 cafe owners in Jember. The findings showed that social media significantly and positively influenced motivation and company success. In addition, motivation was found to be an intervening variable that strengthens the impact of these elements on cafe business success.

Technological developments and globalization encourage people to develop in the transaction process. Now, conventional technology is starting to be abandoned and switched to a digitalization system, thus strengthening the balance of trade on an international scale. As one of the global e-wallets, PayPal offers convenience in cross-border transactions, but there are not many studies that specifically evaluate the level of satisfaction of Indonesian users in the application of this service. This research focuses on analyzing the level of satisfaction of using PayPal in Indonesia in cross-border transactions and examining technology acceptance factors with the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) method. Data were collected through distributing questionnaires to active PayPal users in Indonesia and analyzed quantitatively using structural regression methods (SEM/PLS). The results showed that perceived ease of use, usefulness, and trust have a significant influence on user satisfaction. In addition, UTAUT 2 variables such as performance expectations, effort expectations, social influence, and hedonic value also contribute to forming positive perceptions of using PayPal. The findings are expected to contribute to the development of an international digital payment system that is more responsive to the needs of users in Indonesia.

The 2024 General Election in Indonesia marked a significant shift in the landscape of political communication from conventional media to the digital sphere. Political campaigns conducted through social media and online platforms have opened new opportunities for persuasive effectiveness but also introduced serious challenges in terms of communication ethics, particularly in advertising. This study aims to analyze digital political campaign practices during the 2024 election through the lens of the Indonesian Advertising Ethics Code (Etika Pariwara Indonesia/EPI), which serves as a self-regulatory standard in the advertising industry. This research employs a qualitative approach using a case study method, supported by documentation analysis, digital observation, and literature review. The findings reveal that many digital political advertisements violate key EPI principles, including honesty, transparency, and social responsibility. The most prominent violations include negative campaigning, the use of religious symbols to construct candidate images, and undisclosed endorsements by political influencers. Weaknesses in digital monitoring systems exacerbate these issues, allowing unethical content to spread massively and uncontrollably. This study concludes that the implementation of EPI in digital political campaigns remains weak and requires a more adaptive, collaborative, and technology-based monitoring approach to safeguard democratic integrity in the digital communication era.

This study aims to examine the effect of digital literacy on entrepreneurial decisions among students of Universitas Negeri Jakarta participating in the 2023 Student Entrepreneurial Program (PMW), with self-efficacy as a mediating variable. A quantitative approach was employed using a survey method. A total of 136 respondents were selected from 206 students in the TOP 50 PMW business teams through purposive sampling. Data were collected using a questionnaire and analyzed using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) method with SmartPLS 4.0 software. The results show; (1) that digital literacy has a positive and significant effect on self-efficacy; (2) digital literacy has a positive and significant effect on entrepreneurial decisions; (3) self-efficacy has a positive and significant effect on entrepreneurial decisions; (4) and digital literacy indirectly affects entrepreneurial decisions through self-efficacy. These findings highlight the crucial role of self-efficacy in strengthening the influence of digital literacy on entrepreneurial decisions. Therefore, it is essential for higher education institutions to foster students' digital literacy and confidence to support entrepreneurial development in the digital era.

This study analyzes the performance of the Logistic Regression algorithm in facial image classification using a combination of color and shape features. These features are used to extract key information to distinguish individuals. Logistic Regression was chosen for its simplicity and ability to produce probabilities, despite the availability of more complex algorithms. The dataset includes variations in facial expressions and lighting conditions. The results show that combining color and shape features improves classification accuracy to 80%, with a recall of 88% and a precision of 75.86%. However, the algorithm shows limitations when dealing with high-complexity data. This study contributes to the development of more efficient facial recognition systems and offers insights into the strengths and limitations of Logistic Regression in image classification tasks.

The evolution of computer architecture has given rise to two main approaches: RISC (Reduced Instruction Set Computer) and CISC (Complex Instruction Set Computer). These architectures differ significantly in terms of instruction design, efficiency, and performance. This study aims to analyze the performance and efficiency of RISC and CISC in the context of computer architecture organization. The methodology includes a literature review, comparative analysis, and performance evaluation based on parameters such as processing speed, power consumption, and design complexity. The results indicate that RISC tends to be more efficient in terms of power consumption and execution speed for simple instructions, while CISC excels in handling complex instructions with fewer lines of code. The findings of this study can serve as a reference for the development of modern computer architectures that balance performance and efficiency.

Law Number 1 Year 2023 on the Criminal Code (KUHP) is a form of national criminal law reform that recognises the existence of customary criminal law. However, it has not been regulated in detail how the implementation and position of customary criminal law as a reason for criminal prosecution, and there are fundamental differences between the two concepts of the legal system. The problems in this research are how the position between customary criminal law and national criminal law in the new Criminal Code, how the legal certainty of the regulation of customary criminal law in the new Criminal Code, and how the challenges in enforcing customary criminal law using the current criminal justice system in Indonesia. This research uses normative juridical method with regulatory and conceptual approaches. The results show that the applicability of customary criminal law is limited to the area where the law lives and applies to customary criminal acts committed in the area where the law lives. The position of customary criminal law can be valid as a reason for criminal prosecution if the customary law that is still alive in the community has been stipulated in the form of Regional Regulations, and customary offences that are similar to offences in the New Criminal Code will be ruled out, and the classification of customary sanctions as additional sanctions, positioning customary penalties to be complementary or secondary, because additional sanctions can only be imposed together with the main sanctions. Legal certainty towards the regulation of customary criminal law is highly dependent on the formulation of the elements of each offence of customary criminal law stipulated in regional regulations. The current criminal justice system in Indonesia (KUHAP) cannot realise the objectives of customary criminal law. The objectives, characteristics, and procedures in the concept of customary law are contrary to those in the criminal justice system. Restorative Justice can be utilised as an alternative to the settlement of customary criminal cases when the New Criminal Code comes into effect.