The use of pesticides in the agricultural sector results in contamination of foodstuffs by pesticide residues, thus becoming a source of exposure to the body and resulting in health problems. The purpose of this study was to analyse the health risks due to the consumption of foodstuffs containing organophosphate residues in farmers. The design of this study was cross-sectional, employing the Environmental Health Risk Assessment (EHRA). The study population was farmers in the North Dempo District of Pagar Alam. A total of 117 farmers were sampled randomly. Environmental samples consisted of five red chilies and five tomatoes, which were selected purposively. Organophosphate residues were quantified using liquid Chromatography Tandem Mass Spectrometry. Body weight was measured using calibrated body scales. Activity pattern data were collected through interviews using a questionnaire. Data analysis was conducted using the  EHRA formulas. The results demonstrated the presence of Chlorpyriphos in red chillies  at a concentration of 3,05 mg/kg, while Profenofos was found at 0.0731 mg/kg and 0.0118 mg/kg.  The presence of Chlorpyriphos in tomatoes samples at a concentration of 0.4439 mg/kg, while Profenofos was found at 0.0112 mg/kg and 0.2043 mg/kg. The risk quotient  for consumption of red chillies containing Chlorpyriphos was found to be 0.0447, while that for Profenofos was 0.2476. The risk quotient for consumption of tomatoes containing Chlorpyriphos was found to be 0.0302, while that for Profenofos was 2.92. It can be concluded that respondents were at non-carcinogenic health risk due to consumption of tomatoes containing Profenofos.

 Background: Cow’s milk allergy is relatively common among Indonesian infantswho are not exclusively breastfed. Despite extensive hydrolyzed formula and aminoacid-based formula are the recommended nutrition for infants with moderate-tosevere illness, not all parents could provide those specialized formulas, presumablydue to the high cost, low availability and poor palatability. In that case, soy-basedinfant formula could be an alternative nutrition. However, it was unknown whetherIndonesian mothers were aware on that alternative nutrition. Objective: We therefore assessed the knowledge levels of mothers who participated in an online platform of PrimaKu on the usefulness of soy-based infant formula to support growthand development of children with cow’s milk allergy. Methods: The study subjectsappeared to have sufficient levels of knowledge on the usefulness of soy-based infant formula for children with cow’s milk allergy. Results: In addition, by increasing their knowledge on iron and fiber fortification in soy-based infant formula, e.g.,through regular academic presentations, mothers could be more selective in choosing alternative nutrition for children with cow’s milk allergy. Conclusion: Our studysuggested that Indonesian mothers who were active in the online platform of Primaku had sufficient levels of knowledge on the usefulness of soy-based protein formanaging children with cow’s milk allergy. 

The study focuses on addressing fatigue among healthcare workers in Emergency Room (ER), vital in delivering health services but prone to worker fatigue. Using objective measures like cardiovascular load (%CVL) and Bourdon Wiersma test, it evaluates physical and mental fatigue. Leveraging the System Engineering Initiative for Patient Safety 2.0 (SEIPS 2.0) model, it comprehensively analyzes factors affecting fatigue. Data collection includes surveys and statistical analysis through Structural Equation Modeling-Partial Least Squares (SEM-PLS). Results show all workers experience fatigue, with physical fatigue affected by age and gender, and mental fatigue influenced by workload. The outer model analysis confirms convergent and discriminant validity, and reliability of the constructs. The inner model analysis reveals the work system significantly affects fatigue, while the process does not. The study emphasizes the importance of addressing fatigue to improve worker well-being and enhance patient care in ER, providing actionable insights for healthcare organizations.

This study focuses on examining the impact of halal certification, product quality, and marketing strategy on the sales of Home Industry food products. A descriptive quantitative approach was adopted to analyze the relationship between variables. Data were collected through questionnaires distributed to 170 respondents who were food product business actors Home Industry in Sariwangi District, Tasikmalaya Regency, West Java Province. The collected data were analyzed using the Structural Equation Modeling method with a Partial Least Squares (PLS-SEM) approach. The results show that both halal certification and marketing strategy have a significant positive effect on sales of Home Industry food products. Meanwhile, product quality does not show a significant effect on sales. The study also indicates that halal certification has the strongest influence on sales compared to the other variables.

This study examines the impact of selling price, finished goods inventory management, and marketing strategy on sales turnover at Ayam Bakar Pak D Restaurant, Nginden Surabaya. Using quantitative methods and multiple linear regression analysis, the findings reveal that all three variables collectively influence sales turnover (F-value = 10.317, p = 0.000). However, partial analysis indicates only selling price (X1) has a significant positive effect (t = 4.591, p = 0.000), while finished goods inventory (X2)and marketing strategy (X3) show no significant impact. The regression equation derived is Y = 4.701 + 0.415X1 - 0.007X2 - 0.140X3 + e, emphasizing pricing strategy as a key driver of sales performance.

This research aims to describe the implementation of digital transformation in marketing strategies among micro, small, and medium enterprises (MSMEs) in the culinary sector, using Nomnom Kitchen in Bandarlampung City as a case study. Employing a qualitative approach with data collection techniques including interviews, observations, and documentation, the research explores the firsthand experiences of business actors in transitioning from conventional to digital marketing. The findings reveal that MSME actors face complex dynamics throughout the digitalization process, involving internal challenges such as limited human resources and digital content management, as well as external opportunities like expanded market reach. Digital transformation emerges as a strategic tool that enhances promotional efficiency, strengthens customer engagement, and fosters a business model that is more responsive to technological advances. The study highlights the importance of digital training and the enhancement of entrepreneurial capacity to optimize the digital potential of MSMEs.

Digital devices support early childhood learning; however, excessive use may hinder social-emotional development, making supervision and wise use by parents and teachers crucial. This study aims to understand the positive and negative impacts of digital device use in learning on young children's social and emotional behavior. A correlational quantitative method was used by distributing survey instruments to 100 respondents. The results support four hypotheses about device use and children's social-emotional development. Excessive device use negatively affects social interaction skills (coefficient -0.45; P = 0.002) and emotional regulation (coefficient -0.50; P = 0.003). In contrast, supervised device use positively influences empathy and communication skills (coefficient 0.60; P = 0.000). Children guided by parents or teachers show better social-emotional development than those without supervision (coefficient 0.55; P = 0.000). All hypotheses are supported, emphasizing the importance of supervised device use.

Breast cancer is the most prevalent cancer among women worldwide, requiring early and accurate diagnosis to reduce mortality. This study proposes a hybrid classification pipeline that integrates Hybrid Statistical Feature Selection (HSFS) with unsupervised LSTM-guided feature extraction for breast cancer detection using the Wisconsin Diagnostic Breast Cancer (WDBC) dataset. Initially, 20 features were selected using HSFS based on Mutual Information, Chi-square, and Pearson Correlation. To address class imbalance, the training set was balanced using the Synthetic Minority Over-sampling Technique (SMOTE). Subsequently, an LSTM encoder extracted non-linear latent features from the selected features. A fusion strategy was applied by concatenating the statistical and latent features, followed by re-selection of the top 30 features. The final classification was performed using a Support Vector Machine (SVM) with RBF kernel and evaluated using 5-fold cross-validation and a held-out test set. Experimental results showed that the proposed method achieved an average training accuracy of 98.13%, F1-score of 98.13%, and AUC-ROC of 99.55%. On the held-out test set, the model reached an accuracy of 99.30%, precision of 100%, and F1-score of 99.05%, with an AUC-ROC of 0.9973. The proposed pipeline demonstrates improved generalization and interpretability compared to existing methods such as LightGBM-PSO, DHH-GRU, and ensemble deep networks. These results highlight the effectiveness of combining statistical selection and LSTM-based latent feature encoding in a balanced classification framework.

This study aims to analyze the level of understanding of the division concept among third-grade elementary school students. Understanding division is a fundamental component in mathematics learning, serving as a basis for more complex numerical operations in higher grades. The research employed a descriptive qualitative method involving 5 students from an elementary school in. Data were collected through diagnostic tests, interviews, and observations. The findings revealed that most students still struggle to grasp the concept of division, particularly in understanding it as a grouping process and as repeated subtraction. Factors influencing students' comprehension include limited use of varied teaching methods, insufficient application of concrete learning media, and differences in students' learning styles. These findings are expected to serve as a reference for teachers in designing more effective and contextual learning strategies to enhance students’ understanding of the division concept at the elementary level.

SMEs are the backbone of the local economy and require contextualized and adaptive leadership and human capital management strategies. This article aims to describe the indigenous values-based leadership model implemented in Aglaia Shoes Cleaning-a shoe-care SME in Malang City-and how it contributes to strengthening human capital. The service activities were carried out through a participatory and educative approach, including soft skills training, structuring work structures, and preparing simple SOPs based on local cultural values such as mutual cooperation, responsibility, and perseverance. The results of the activities show that a leadership approach that integrates indigenous values can create a more collaborative work environment, increase productivity, and foster loyalty and a sense of ownership in the work team. Strengthening human capital does not only occur through increasing technical capacity, but also through instilling local values and work ethics. This model has the potential to be replicated in other MSMEs with similar characteristics to encourage local culture-based business sustainability.