It is hoped that breastfeeding can help achieve SDGs goal 3, target 2, namely efforts to reduce the neonatal mortality rate to at least 12 per 1000 live births in all countries by 2030 and stop unnecessary deaths of newborns and toddlers. Encouraging healthy breastfeeding is so important that it can prevent more than 820,000 deaths of children under five every year. Oxytocin massage has been shown to increase the sensation of relaxation, improve sleep quality and comfort, reduce pain and tension, and help increase prolactin and oxytocin levels, which in turn increases breast milk production.The research design uses the Pre Experimental Design method, namely in the form of a One Group pretest and posttest design without a control group. This research used purposive sampling, with a total sample of 22 respondents. Univariate and bivariate data analysis.
The results of this study showed that the value before the oxytocin massage was a mean of 16.14 and after the oxytocin massage the mean was 27.73. The conclusion of this research shows that the results of the experimental test have a significant value with a p value = 0.000 <0.05. This proves that there is a significant difference in breast milk production between before and after oxytocin massage. It is recommended that midwives at the Afisya clinic use this research as input in efforts to increase breast milk production in post partum mothers.

spam is posting unsolicited messages or advertising on social media, particularly Twitter. These messages are normally designed to sell specific products and services or links. In this research, we developed a fuzzy control system to detect Arabic spam tweets based on deep learning with a large language model. Initially, we performed text cleaning and further transformed text into vectors with the help of AraGpt and AraBert. Subsequently, we employed a multi-layer perceptron network model in feature extraction of essential features. Finally, we adopted the fuzzy logic control system for classifying spam tweets using features filtered from deep networks. Employing the proposed Fuzzy logic control system provided nearly a 100% comparative to only utilizing the deep neural networks, which yielded an almost 99% throughput for both large language models Aragpt and Arabert, with a 100% F1 score for the Aragpt model and 99% for Arabert model respectively.

Analysis of the preliminary research phase as the basis for developing a biology practicum guide based on a scientific approach. The purpose of this study was to describe the initial research stage data obtained as a basis for developing teaching and learning materials based on research results that will be made in the future. The development model applied in this study is the Plomp model, which has reached the initial data investigation stage. Instruments for collecting data include interviews, observations, and questionnaires. The results of the student needs questionnaire revealed that students agreed that it was necessary to develop a practicum guide based on a scientific approach with a percentage of 94.73%. The teaching materials that have been used in learning are less effective so that students are less able to understand the subject matter. So it can be concluded that it is necessary to develop teaching materials for practicum guides based on a scientific approach on the material of the circulatory system and respiratory system in class XI SMAN 15 Pekanbaru.

The World Trade Organization, hereinafter referred to as the WTO, is an international organization part of the Economic and Social Council as an important component in international trade. In carrying out international trade activities, a legal instrument is needed to ensure the sustainability of trade and facilitate the resolution of disputes that will be experienced by the international community. The trade dispute between Indonesia and Brazil was caused by Indonesia's policy of stopping chicken meat imports from Brazil since 2009, causing Brazil to suffer huge losses because it could not export chicken meat to Indonesia. From the chicken meat import policy in Indonesia, Brazil demanded that Indonesia had carried out trade protection which violated various WTO rules. Indonesia's defeat in the DSB-WTO Panel was due to the many Indonesian policies that violated the WTO agreement and the inability of Indonesian representative diplomacy to resolve the dispute.

Advances in information and internet technologies have significantly transformed the business environment, including the financial sector. The COVID-19 pandemic has further accelerated this digital adoption, expanding the e-commerce industry and highlighting the necessity for secure online transactions. Credit Card Fraud Detection (CCFD) stands critical as the prevalence of fraudulent activities continues to rise with the increasing volume of online transactions. Traditional methods for detecting fraud, such as rule-based systems and basic machine learning models, tend to fail to keep pace with fraudsters' evolving tactics. This study proposes a novel ensemble deep learning-based approach that combines Convolutional Neural Networks (CNN), Gated Recurrent Units (GRU), and Multilayer Perceptron (MLP) with the Synthetic Minority Oversampling Technique and Edited Nearest Neighbors (SMOTE-ENN) to address class imbalance and improve detection accuracy. The methodology integrates CNN for feature extraction, GRU for sequential transaction analysis, and Multilayer Perceptron (MLP) as a meta-learner in a stacking framework. By leveraging SMOTE-ENN, the proposed approach enhances data balance and prevents overfitting. With synthetic data, the robustness and accuracy of the model have been improved, particularly in scenarios where fraudulent examples are scarce. The experiments conducted on real-world credit card transaction datasets have established that our approach outperforms existing methods, achieving higher metrics performance.

Face spoofing detection is critical for biometric security systems to prevent unauthorized access. This study proposes a deep learning-based approach integrating FaceNet and DenseNet201 to enhance face spoofing detection performance. FaceNet generates identity-based embeddings, ensuring robust facial feature representation, while DenseNet201 extracts complementary texture-based features. These features are fused using the Concatenate function to form a more comprehensive representation for im-proved classification. The proposed method is evaluated on two widely used face spoofing datasets, NUAA Photograph Imposter and LCC-FASD, achieving 100% accuracy on NUAA and 99% on LCC-FASD. Ablation studies reveal that data augmentation does not always enhance performance, particularly on high-complexity datasets such as LCC-FASD, where augmentation increases the False Rejection Rate (FRR). Conversely, DenseNet201 benefits more from augmentation, while the proposed method performs best without augmentation. Comparative analysis with previous studies further confirms the superiority of the proposed approach in reducing error rates, particularly Half Total Error Rate (HTER), False Acceptance Rate (FAR), and FRR. These findings indicate that combining identity-based embeddings and texture-based feature extraction significantly improves spoofing detection and enhances model robustness across different attack scenarios. This study advances biometric security by introducing an efficient feature fusion strategy that strengthens deep learning-based spoof detection. Future research may explore further optimization strategies and evaluate the approach on more diverse datasets to enhance generalization.

The procedures for cargo ship clearance in and out at Weda Port, Central Halmahera, managed by PT Pelayaran Bahtera Diserindo, play a vital role in ensuring efficient port operations and regulatory compliance. The clearance-in process consists of several steps that cargo ships must complete before entering the port, including document verification, health inspections, and adherence to security protocols. On the other hand, the clearance-out process involves procedures that must be completed before a ship departs, such as submitting shipping documents and undergoing cargo inspections. This study aims to examine these procedures, identify the challenges faced, and propose recommendations to enhance the efficiency and effectiveness of clearance processes at Weda Port. By utilizing the latest data and statistics, this research also emphasizes the significant role of PT Pelayaran Bahtera Diserindo in facilitating logistics operations in North Maluku. The findings are expected to provide a comprehensive understanding of the existing procedures and their impact on Indonesia's maritime industry.

The results of observations and research on November 06 2023 are about students' learning motivation in learning Indonesian using pantun board media. The research method used is a descriptive quantitative method and uses nominal questionnaire data which only contains simultaneous results and facts from the truth produced by the researcher. From the results of this research, the student data obtained was 23 (twenty three) students and it was found that 3 (three) of the 23 (twenty three) students in class IV of SD Negeri 101744 Klambir Village had low motivation and interest in learning in particular learning. Indonesian language. The aim of this research is to describe students' learning motivation in learning Indonesian in class IV. The method used in this research is descriptive quantitative research. Meanwhile, data collection techniques include observation, interviews, questionnaires and documentation. This process is carried out by collecting data directly at the research location. Next, the data analysis process was carried out on a nominal scale only. This research uses source triangulation techniques. From the results of data analysis, it is known that students' learning motivation in learning Indonesian in class IV of SD Negeri 101744 Klambir Village is still low, as can be seen from the low interest of students in learning Indonesian both in class and at home, as evidenced also by the results of the assessment of the distributed questionnaire data, which shows that some class IV students got grades that were less than expected, and this was due to several factors, namely 1). Self factor 2). Environmental factors 3). Family factors. The impact of the causes of low student learning motivation internally is due to a lack of motivation in their enthusiasm for learning and externally due to 1). Teacher performance 2). Infrastructure 3). Surrounding environment.

This article aims to provide an explanation of creative methods for inclusive education, especially for students at the Sukoharjo State Special Elementary School who prioritize motor skills and the ability to interact with other people. Data was collected through interviews and observations, and qualitative methods were used to compile this article. Literature review is the basis of process analysis. The findings from this study indicate that educators have the potential to enhance the utilization of educational resources, objectives, tools, techniques, assessments, and learning atmospheres through the implementation of innovative teaching methods. Diverse instructional approaches, ranging from remedial and deductive to inductive and heuristic techniques, can be employed to accommodate elementary-level students with special needs. Collaborative learning, behavior modification, and other methods are also beneficial. Moreover, it is suggested that teachers explore alternative learning aids like puzzles to cater to the unique needs of these students.

This research aims to identify students with special needs (PDBK) with emotional barriers (tunalaras) in elementary schools. Tunalas is a disorder in managing emotions and behavior that has an impact on students' social interactions and learning processes. The method used in this research is descriptive quantitative, with data collection techniques through observation, interviews and documentation. The research results showed that of the 846 students, 11 students (1.30%) were identified as experiencing emotional obstacles. The main characteristics of students with hearing impairments include difficulties in controlling emotions, a tendency to act aggressively, and difficulties in building social relationships. Therefore, a more adaptive and emotional support-based learning approach is needed to help them participate more effectively in inclusive education. By understanding the characteristics of students with disabilities, schools can develop more appropriate learning strategies to improve their academic and social development.