Accurate sales forecasting is essential for retail Micro, Small, and Medium Enterprises (MSMEs) to optimize operations and inventory planning in the digital economy. This study compares the forecasting accuracy between Artificial Intelligence (AI)-based methods (Random Forest, Decision Tree) and traditional techniques (Moving Average, Exponential Smoothing) using 3,600 transaction records from five retail MSMEs over three months. A quantitative experimental approach was employed to evaluate model performance under real-world conditions, including market fluctuations and seasonal anomalies. Evaluation metrics include Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE), and cross-validation techniques. The findings indicate that the Random Forest model achieves superior accuracy (MAPE = 8.5%) compared to traditional methods (MAPE = 15.2%). Explainable AI (XAI) using SHAP and LIME further enhances transparency and managerial trust. Although traditional methods offer faster computation and ease of interpretation, AI-based models show resilience against unpredictable sales patterns. This research recommends hybrid adoption strategies that balance predictive power with interpretability for MSMEs with limited technical capacity. The results contribute to the discourse on digital transformation and intelligent forecasting in the MSME sectors.

The increasing integration of Artificial Intelligence (AI) in e-commerce has transformed digital marketing strategies, particularly through personalized recommendation systems. However, this advancement has raised ethical concerns regarding data privacy, algorithmic transparency, and consumer autonomy. In Southeast Asia, where digital platforms rapidly expand, these concerns become more complex due to diverse regulatory landscapes and user expectations. This study aims to analyze and compare the transparency of AI-based recommendation systems across three major e-commerce platforms in the region: Shopee, Lazada, and Tokopedia. A qualitative comparative approach was employed using content analysis of official policy documents, including privacy policies and AI guidelines, sourced from each platform between January and March 2024. The analysis utilized LLM-assisted text mining and thematic coding to identify ethical indicators such as algorithmic transparency, user control, and policy readability. The results reveal significant variation in ethical practices: Shopee scored the highest in all dimensions, including algorithmic transparency (score: 9/10), user control (8/10), and policy readability (9/10). Lazada ranked moderately with scores of 6/10, 4/10, and 6/10 respectively, while Tokopedia scored lowest with 3/10 for transparency, 0/10 for user control, and 4/10 for readability. These disparities indicate that ethical communication and user empowerment remain uneven across platforms. This study contributes to the discourse on digital ethics by highlighting the need for regional standards in AI transparency and promoting user-centric ethical design. The findings provide valuable insights for policymakers, platform designers, and digital consumers navigating trust in algorithm-driven environments.

In recent years, retail investor participation in Southeast Asian capital markets has surged, contributing to increased market volatility and making sentiment analysis a critical factor in understanding price dynamics. This study investigates the relationship between social media sentiment and stock market fluctuations by focusing on Twitter data during periods of market volatility in Indonesia, Thailand, and Malaysia. The objective is to examine how collective investor emotions, as expressed through social media, correlate with daily stock index movements. Employing an exploratory quantitative approach, the study integrates Natural Language Processing (NLP) methods, both lexicon-based tools such as VADER and advanced transformer-based models like BERT and GPT, to classify over 150,000 tweets into positive, negative, and neutral sentiments. Sentiment scores were then aggregated and statistically tested using Pearson correlation with daily stock index returns, specifically the IDX Composite, SET Index, and FTSE Bursa Malaysia. The findings reveal a significant negative correlation between negative sentiment and market returns, particularly in the IDX Composite (r = -0.61, p < 0.05), indicating that pessimistic sentiment is associated with market downturns. Thailand’s SET Index and Malaysia’s FTSE Index showed moderate to weak negative correlations, with r = -0.43 and r = -0.27, respectively. These results highlight the sensitivity of emerging markets to emotionally driven retail behavior. The study concludes that AI-based sentiment analysis offers a valuable early warning tool for market volatility and can complement traditional financial indicators. It recommends developing AI-based sentiment dashboards and enhancing digital financial literacy to mitigate emotional reactivity among retail investors.

MP BARBER is an exclusive barbershop for men located in Kedemangan Village, Muaro Jambi Regency. Customers have complained about the queues at MP BARBER, reflecting the direct impact of an unsatisfactory experience where customers feel uncomfortable. This situation highlights the importance of queue management and efforts to improve service efficiency, to maintain customer satisfaction and minimize the potential loss of customers in the future. Therefore, the researcher offers the design of an Android-based reservation information system for MP BARBER. The research uses a qualitative approach, the prototype development method, system design using UML, and is assisted by Corel Draw. The system design uses Android Studio, Visual Studio Code, and XAMPP as the database. System testing is carried out using the blackbox method and feasibility testing through 8 respondents, including the owner, employees, and customers of MP BARBER.

The cosmetic industry in Indonesia continues to experience significant development along with the increasing awareness of the community, especially women, towards appearance. This change continues to grow also because the modern lifestyle today increasingly demands an attractive appearance as a form of self-confidence, both for daily and professional activities. This drives consumer interest in quality cosmetic products at affordable prices. In addition, awareness in choosing safe products to use according to skin needs is also increasing, this is in line with the education provided by cosmetic products through the marketing they use.

Bening's Clinic is a company in the field of beauty and health services that has experienced rapid growth since its establishment in Jambi in 2017, including opening a branch in Padang. This study aims to analyze the influence of Customer Relationship Management (CRM) and Service Quality on Customer Loyalty, as well as the role of Customer Satisfaction as a mediating variable at Bening's Clinic Padang. The method used is a quantitative approach with survey techniques on customers who have used clinic services. The results of the study show that CRM and Service Quality do not have a significant direct effect on Customer Loyalty. However, both have a positive and significant influence on Customer Satisfaction. Furthermore, Customer Satisfaction has been proven to have a significant effect on Customer Loyalty and is able to mediate the influence of CRM and Service Quality on Customer Loyalty. These findings affirm the importance of the role of customer satisfaction as a bridge to increase customer loyalty through relationship management and service quality. In conclusion, the strategy to increase customer loyalty at Bening's Clinic Padang will be more effective if it is focused on increasing customer satisfaction first through strengthening CRM and improving service quality.
 

This study aims to identify the effectiveness of the heptagon fraud model in detecting fraudulent financial reporting within consumer goods sector companies listed on the Indonesia Stock Exchange (IDX). A quantitative research approach is employed, utilizing secondary data sourced from IDX-listed companies. The research population comprises consumer goods manufacturing firms listed on the IDX between 2019 and 2023. Based on specific selection criteria, 41 companies were chosen as the study sample. The data analysis involves various techniques, including descriptive statistics, the Overall Model Fit Test, the Hosmer and Lemeshow goodness-of-fit test, the coefficient of determination (Nagelkerke’s R-square), the Omnibus Test of Model Coefficients (F-test), and the Wald Chi-Squared Test (WALD). The findings reveal that the pressure has a significant positive impact on financial statement fraud. Meanwhile, arrogance is found to have a significant negative impact on the occurrence of financial statement fraud. In contrast, other factors, opportunity, rationalization, capability, ignorance, and greed do not exhibit a significant influence on fraudulent financial reporting.

Phubbing behavior, a combination of the words "phone" and "snubbing," refers to a social phenomenon in which individuals focus more on their smartphones than interacting directly with the people around them. This behavior is increasingly widespread among students along with the rapid development of communication technology. This research aims to provide a general overview of phubbing behavior in students, identify the factors that influence it, as well as its impact on social relationships and the quality of communication between individuals. Literature studies conducted show that phubbing can be triggered by various factors, such as social media addiction, boredom in social interactions, low self-control, and the influence of social conformity. The impacts include a decrease in the quality of social relationships, communication disorders, and reduced academic productivity. Solutions that can be provided are based on analysis of several cases, such as increasing awareness through education and strengthening self-control, creating gadget-free zones, as well as developing empathy and social involvement in students. This research is expected to provide insight for academics and practitioners in overcoming phubbing problems in higher education environments.

Gout is an inflammatory arthritis caused by the accumulation of uric acid crystals. Dietary adherence is one of the managements of gout. The purpose of this study is to determine the influence of peer group therapy on the dietary adherence of gout sufferers in Mentor Village, Sumberasih District, Probolinggo Regency. This study uses a one-group pre-post test design (pre-experiment) research design. The total population was 36 respondents with gout, the sample studied was 33 respondents with gout using the Purposive Sampling technique, In accordance with the inclusion criteria willing to be a respondent, Permanent Resident of Mentor Village, Patients who have gout, Gout level value above seven point zero for men and Women more than six point zero Exclusion criteria Patients with comorbidities that interfere with the research (kidney, janttung, lung and so on), Patients do not participate in the entire activity or resign.Peer group therapy was carried out four times in 14 days. Statistical Test for dietary adherence using the Wilcoxon Test. The results of the study Before peer group therap was coalited, the Gout Diet Compliance value was moderate,  24 respondents (72.7%),while the after tritmen value of goud diet compliance of  31 respondents (93.9%), The results of the Wilcoxon statistical test,obtained p value = 0.000. This shows that Peer Group therapy affects dietary adherence of gout patients. Peer Group Therapy is a program that can be applied to gout patients who have low dietary adherence. Nurses are expected to be able to use Peer Group Therapy as a health promotion program. 

This research discusses the role of humanistic teaching strategies in enhancing students' learning motivation in Islamic Religious Education (PAI). Humanistic teaching strategies focus on the holistic development of students, addressing cognitive, emotional, and spiritual aspects. Through this approach, students are given opportunities to relate learning material to their personal experiences, which in turn increases their engagement and intrinsic motivation to learn. This research uses the library research method to collect and analyze various literatures related to humanistic teaching, learning motivation, and its implementation in PAI. The findings of this study indicate that the application of humanistic strategies in PAI teaching can create a more inclusive environment, improve positive interactions between teachers and students, and encourage students to learn more meaningfully and with greater motivation.