The rapid growth of information technology has driven digital transformation in various sectors, including micro, small, and medium enterprises (MSMEs), the backbone of the Indonesian economy. In response to the challenges and opportunities of digitalization, the Surabaya City Government launched the Peken e-commerce platform on October 31, 2021. This platform aims to help MSMEs market their products online, expand market reach, and increase competitiveness. However, the use of digital systems also presents new challenges, particularly in terms of cybersecurity. Dependence on technology opens the door to various threats that can compromise data confidentiality, integrity, and availability. This study aims to analyze and evaluate information security risks on the Peken Surabaya website using a risk management approach based on the ISO/IEC 27005:2019 standard. The analysis method involves identifying information assets, recognizing potential threats, identifying vulnerabilities, and assessing risk levels based on the likelihood of occurrence and impact. To support the analysis, technical testing was also conducted using the Open Web Application Security Project Zed Attack Proxy (OWASP ZAP) tool. The research results indicate that most of the risks faced by Peken Surabaya are moderate to very high. These risks include Distributed Denial of Service (DDoS) attacks, user data leaks, and the lack of a two-factor authentication (2FA) system. Based on these findings, a risk management strategy was developed using the Risk Modification, Risk Sharing, Risk Retention, and Risk Avoidance approaches. Furthermore, this study recommends security controls based on ISO/IEC 27005 and OWASP Top 10 to enhance system protection. These findings emphasize the importance of implementing international standards-based risk management in maintaining the continuity and security of digital public services, particularly those supporting the MSME sector in the digital era.

This research is motivated by the low ability to write short stories in students, which is thought to be caused by the use of learning methods and media that are less varied and have not been able to stimulate students' imagination and creativity optimally. To overcome this problem, the application of innovative learning strategies is needed, one of which is the use of storyboard techniques. The purpose of this study was to determine the effect of storyboard techniques on the ability to write short stories of class X students of SMK Tritech Informatika Medan. The method used in this study is a quantitative method with a quasi-experimental design, specifically the Pretest-Posttest Control Group Design. The sample in this study amounted to 42 students who were divided into two groups, namely the experimental group who were given treatment using the storyboard technique and the control group who used conventional methods. Data collection techniques were carried out through observation, interviews, short story writing tests, and documentation. The data obtained were analyzed using normality tests, homogeneity tests, and t-tests (independent samples t-test). The results showed that there was a significant difference between the posttest scores of the experimental group and the control group. The experimental group experienced an average score increase of 18.81 points, while the control group only increased by 9.76 points. The t-test results showed a t-value of 2.677 and a significance level of p = 0.011 (p < 0.05), indicating that the storyboard technique had a significant effect on students' short story writing skills. Therefore, it can be concluded that the use of the storyboard technique is effective in improving students' creative writing skills. The implication of this finding is that the storyboard technique can be used as an alternative, creative and innovative learning strategy in writing instruction at the Vocational High School (SMK) level.

The current transformation of the workplace demands that organizations be more adaptive in understanding the factors that influence employee productivity, especially among the younger generation. Generation Z, as an age group that is starting to dominate the workforce, brings different characteristics and needs, including in terms of work-life balance and motivation. They tend to value time more, opportunities for self-development, and an inclusive work environment that supports a balance between professional and personal life. This study aims to determine the relationship between work-life balance and motivation on the performance of Generation Z employees in Klaten Regency. This study used a quantitative approach with a survey method. A total of 100 respondents were selected using a purposive sampling technique based on age and employment status criteria. The research instrument was a questionnaire using a five-point Likert scale, which included statements related to the dimensions of work-life balance, levels of work motivation (both intrinsic and extrinsic), and employee performance indicators. Data were analyzed using IBM SPSS version 25 software with correlation tests and multiple regression. The results showed that both work-life balance and motivation have a positive and significant relationship on employee performance. Among these two variables, motivation is the dominant factor influencing performance improvement. This suggests that while work-life balance is important, internal employee motivations such as passion, purpose, and a sense of belonging have a greater impact on job performance. The implications of these findings suggest that companies need to design human resource management strategies that are not only flexible but also responsive to the needs of the younger generation. Creating a work environment that supports work-life balance, provides recognition, and provides career opportunities.

The development of information technology has brought about significant changes in the social, economic, and legal life of global society. On the one hand, digitalization creates efficiency and convenience in various activities, such as financial transactions, communications, and access to information. However, on the other hand, this progress has also given rise to a new form of crime known as cybercrime. Cybercrime differs from conventional crime in that it is committed through electronic systems that can cross national borders and involve a large number of victims. This crime encompasses various forms, such as data hacking, online fraud, and malware distribution. This research aims to examine the development of cybercrime as a form of modern crime in the digital era and to assess the response of Indonesian criminal law to these challenges. The method used is normative legal, with a statutory, conceptual, and case study approach. This research also examines existing regulations, such as Law Number 11 of 2008 concerning Electronic Information and Transactions (ITE) and Law Number 27 of 2022 concerning Personal Data Protection, in addressing cybercrime issues. The research results show that although Indonesia has several regulations related to cybercrime, their implementation still faces various obstacles. Some of the main obstacles include suboptimal law enforcement, limited technology and human resources, and low levels of public digital awareness. Therefore, regulatory reform, institutional capacity development, and increasing public digital literacy are essential. This is part of a national strategy to address cybercrime comprehensively and sustainably, in order to create a safer and more trustworthy digital environment.

This research was conducted from June to July 2025 in Binjai City, with the primary focus being analyzing the readiness of the Binjai City Regional Disaster Management Agency (BPBD) to implement a flood early warning system utilizing artificial intelligence (AI). The data collection process was conducted through a literature review, which involved reviewing various theories and previous research results regarding the application of AI and Internet of Things (IoT) technology in the context of disaster mitigation. Based on the results of the study, it was found that the use of technologies such as ultrasonic sensors, microcontrollers, fuzzy logic, and automatic notification systems can provide real-time warnings with a high level of accuracy and a fast response. This system enables early detection of rising river levels through automatic measurements, intelligent data processing, and sending notifications to authorities and affected communities within seconds. By integrating historical data and machine learning-based predictions, this system is also able to depict potential flooding before it occurs, providing a longer response time for evacuation. However, the readiness of the Binjai City BPBD still faces various challenges, such as limited digital infrastructure, the need for human resource training in the technology field, and inadequate budget allocation. Therefore, cross-sector collaboration and ongoing policy support are needed for optimal implementation of this system. The use of AI and IoT in early warning systems is not only technically relevant but also urgent in the face of increasing climate change and flood risks. A strategy involving cross-sector collaboration between government, academia, and the private sector is needed to develop an adaptive and sustainable early warning system.

The Cargo oil pump is one of the auxiliary units on board a ship, used to transfer cargo from one location to another during loading and unloading operations. On the MT?Pangrango vessel, an issue occurred with the cargo oil pump: its performance declined, resulting in slow suction during the unloading process. This problem hindered efficient cargo operations, as the pump was not functioning properly.This study aims to identify the contributing factors, impacts, and countermeasures for the decreased performance of the cargo oil pump. The research methodology applied in this thesis involved a descriptive approach combined with Miles and Huberman’s analytical method, with data validity tested via triangulation. Data collection techniques used to identify the problem included observation, interviews, documentation, and literature review.The results revealed that the pump’s shaft was worn due to excessive friction, and the ball bearing s exhibited wear and disintegration caused by lack of lubrication (grease). The recommended corrective actions were to add material to the shaft , perform realignment to correct any shaft misalignment, and implement routine maintenance—specifically, monthly grease lubrication. These measures, when properly applied, can significantly reduce the risk of Cargo oil pump damage.

Financial statements play an important role in providing relevant, reliable, and trustworthy financial information to stakeholders. Although auditors are responsible for ensuring the fairness of these statements, cases of undetected financial fraud still occur. This research seeks to empirically examine the effect of experience and time budget pressure on the auditor’s ability to detect fraud, with an understanding of red flags as a moderating variable. The research was conducted on auditors who work in Public Accounting Firms (PAFs) in Bali. The sample was determined using purposive sampling technique and 94 auditors were obtained as a sample. Data was collected through a survey method using a structured questionnaire distributed to respondents. The analytical methods used include multiple linear regression analysis and Moderated Regression Analysis (MRA). The results showed that experience has a positive effect, and time budget pressure has a negative effect on the auditor’s’ ability to detect fraud. Furthermore, red flags strengthen the effect of experience and time budget pressure on the auditor’s ability to detect fraud. The findings provide valuable insights for auditors to manage their work focus effectively and for public accounting firms to allocate audit time proportionally, ensuring optimal awareness of red flags even under high time pressure.

The transition of children from early childhood education to elementary school (SD) is a critical phase in their psychological and academic development. During this phase, children face significant challenges, including changes to a more structured learning environment and increasing academic demands. At SDN 055991 in Langkat Regency, this phenomenon is reflected in the difficulties experienced by some students, particularly with basic skills such as reading, writing, and arithmetic, as well as with socializing with peers. These difficulties can impact children's long-term academic and social development. This study aims to identify the key factors influencing children's learning readiness during this transition period, utilizing artificial intelligence (AI) technology. Specifically, this study uses Artificial Neural Networks (ANN) and Decision Trees as tools to analyze the data obtained. The use of this data-driven approach allows for a more in-depth analysis of the complex patterns and relationships between various variables that influence children's learning readiness, such as family factors, social environment, and students' basic skills. This study also references various previous studies demonstrating the effectiveness of backpropagation and Deep Learning algorithms in the context of education and student performance prediction. This approach is expected to provide more precise solutions for understanding children's learning readiness and provide a more accurate picture of the factors contributing to difficulties experienced by students in the transition to elementary school. The results of this study are expected to provide relevant recommendations for parents, educators, and education policymakers to support children's learning readiness and strengthen basic education policies that are adaptive to the needs of students in this digital era.

This study explores the semantic fields of love and loss in Lord Huron’s song "The Night We Met," using a lexical semantics framework. Song lyrics, known for their emotional depth, serve as a rich source for analyzing affective meaning, particularly through word selection and repetition. The primary research question addresses how semantic fields are constructed within minimalist lyrical compositions to convey complex emotional states. In this analysis, a qualitative descriptive method is applied to examine the song's lexical items and group them into thematic semantic fields. The study finds that the song uses a concise set of lexemes connected to themes of memory, temporal disorientation, grief, and love. These thematic fields intertwine, interacting to depict a narrative that encapsulates unresolved emotional pain. Love and loss are not presented in isolation but are embedded in a broader emotional context, where words evoke both the sweetness of past affection and the sorrow of its absence. The overlap of these semantic fields reflects the internal conflict experienced by the narrator, torn between cherished memories and the painful realization of loss. The study concludes that despite the song’s brevity, the lyrics effectively evoke profound emotional responses through a meticulous choice of words and thematic consistency. The semantic fields constructed within the song illustrate how even minimal language can convey intense emotional content, providing valuable linguistic insight into the function of lyricism in popular music. The research demonstrates the ability of short, poignant lyrics to engage listeners emotionally, revealing how lyricists use limited language to encapsulate complex feelings of love and loss.

This research is motivated by the phenomenon of stock price fluctuations in manufacturing companies, which reflect market instability, both internal and external to the company. These volatile stock price changes create uncertainty for investors, particularly when financial performance indicators such as Return on Assets (ROA), Current Ratio (CR), and Net Profit Margin (NPM) show varying results across companies and time periods. Strong financial performance is usually a positive signal for investors, but inconsistencies in these indicators raise doubts in investment decision-making. The purpose of this study is to analyze the effect of ROA, CR, and NPM on stock prices in manufacturing companies listed on the Indonesia Stock Exchange (IDX) from 2021 to 2024. This study uses a quantitative approach with a causal research type, where the data used are secondary data obtained from the companies' annual financial reports. The sampling technique used was purposive sampling, with certain criteria, resulting in a sample of 85 companies. With an observation period of four years, a total of 340 observations were analyzed. The analysis was conducted using multiple linear regression with the help of SPSS version 30 software. The results of the analysis indicate that, partially, ROA and CR have a significant influence on stock prices. This means that increasing the efficiency of asset use and the company's ability to meet short-term obligations are important factors considered by investors. However, NPM does not have a significant influence partially on stock prices. Nevertheless, all three variables simultaneously have a significant influence on stock prices. This finding has important implications for company management, namely that increasing asset efficiency and optimal liquidity management can strengthen a company's attractiveness to investors by improving credible financial performance.