Purpose: The objective of this study is to assess the usability of the Baraya Travel application, highlighting areas for enhancement to improve the online ticket booking experience for users. By concentrating on the Baraya Travel app as the research subject, the study intends to offer valuable insights for its developers. It emphasizes user feedback and recommendations to improve interface navigation, application speed, and the addition of new features, ultimately increasing convenience and ease of use. This study aims to provide an extensive examination of the app's performance, identifying precise areas where improvements can be made.
Methods: Using the Usability Testing methodology, particularly emphasizing the System Usability Scale (SUS), this study employs a quantitative research strategy. Surveys were administered to 409 Baraya Travel application users to gather primary data concerning usability aspects including user interface navigation, application responsiveness, and user convenience. The statistical analysis utilized both descriptive statistics, encompassing measures of central tendency and variability, to summarize the data, and potentially inferential tests like correlation analysis or t-tests, to investigate relationships and disparities between variables. The selection of statistical analysis aimed to offer a thorough interpretation of the data and extract meaningful insights into the usability of the Baraya Travel application. Furthermore, the utilization of the SUS evaluation metric provided a standardized measure to evaluate usability and facilitate comparisons across studies, ensuring consistency and reliability throughout the evaluation process.
Result: The examination of the SUS questionnaire indicated that users of the Baraya Travel application provided an average score of 75.26. This score suggests that the application demonstrates a commendable level of usability, earning a "Good" rating and a Letter Grade of "B". Nonetheless, there remains potential for enhancement to reach the desired standard of perfection. Users offered invaluable feedback and suggestions, highlighting the necessity for enhanced user interface navigation, improved application speed, and the implementation of additional features to augment convenience and user-friendliness.
Novelty: This research provides valuable insights for Baraya Travel application developers, emphasizing areas for improvement based on user feedback and suggestions. It contributes to the progression of online ticket booking systems, with the goal of enriching the overall travel experience for users. Highlighting the significance of user-friendly interfaces, efficient application performance, and convenient features is crucial for enhancing user satisfaction and fostering loyalty. Subsequent research endeavors could explore further factors influencing user satisfaction and loyalty in the context of digital travel applications.

Purpose: This research aims to develop a classification model using histogram-based gradient boosting to identify relevant contextual tweets about disasters. This model can then be used for subsequent data cleaning stages.
Methods: This study uses a semi-supervised approach to develop a classification model using histogram-based gradient boosting. The model is trained to identify and remove irrelevant tweets that are related to disasters and gathered from Twitter. Optimization techniques, such as the AdaBoost classifier, calibrated classifier, and self-training classifier, are used to enhance the model's performance. The goal is to accurately recognize and categorize relevant tweets for additional data analysis and decision-making.
Result: The classification model that has been developed has achieved a high F1-score of 93.07%, which indicates its effectiveness in filtering disaster-related tweets that are relevant. This highlights the potential of the model to enable more precise aid distribution and faster decision-making in disaster response efforts. The successful implementation of the model also demonstrates its usefulness in utilizing social media data to enhance disaster management practices.
Novelty: This research contributes to the analysis of social media through machine learning algorithms. By utilizing social media, specifically Twitter, as a valuable resource for disaster response efforts, this study tackles challenges related to data collection and analysis in disaster management. The classification of relevant tweets into different types of natural disasters offers opportunities to enhance stakeholder decision-making processes in disaster scenarios.

Purpose: This study aims to improve brain tumor detection by integrating Fuzzy Logic with K-folds validation to enhance classification accuracy and robustness. The research addresses the challenge of distinguishing between normal and abnormal brain MRI images.
Methods: This study utilized a public dataset from Kaggle comprising 2,660 MRI images, initially categorized into four classes: Glioma, Meningioma, Pituitary, and No Tumor. For the study, Glioma, Meningioma, and Pituitary were combined into one abnormal label, resulting in two classes: Normal and Abnormal. The methodology involved pre-processing the images, applying Fuzzy Logic with K-folds validation (K=3), and evaluating the model’s performance using single prediction tests.
Result: The proposed approach achieved an exceptional accuracy of 99.88% during the K-folds validation process. The model demonstrated strong performance across all test samples, accurately classifying both normal and abnormal cases, with true positive results in single prediction tests.
Novelty: This study introduces a novel combination of Fuzzy Logic with K-folds validation, demonstrating a significant improvement in classification accuracy compared to existing methods. The integration of these techniques offers a robust framework for brain tumor detection, enhancing diagnostic precision and addressing the challenge of distinguishing between various tumor types in MRI images.

Purpose: This research compared the accuracy level of six algorithms based on the ROC method and the Confusion Matrix evaluation on data regarding public sentiments towards electric cars.
Methods: Data collection was conducted for data sourced from TikTok. Next, the data underwent text preprocessing (data cleaning and case folding) and text processing (stemming, tokenizing, stopword removal, word frequency, word relation, TF-IDF, scoring, and labeling). Modeling was then conducted using supervised (labeled) algorithms consisting of the Support Vector Machine (SVM), Decision Tree, Naive Bayes, Random Forest, K-Neighbor, and Logistic Regression. Finally, an evaluation was conducted (confusion matrix and ROC).
Result: The results revealed that the Decision Tree algorithm with the Confusion Matrix and ROC evaluation obtained the highest result of 87%. The algorithm with the lowest result is KNN, which has an accuracy of 56%. The classification result for the neutral sentiment has a percentage of 57.1%, followed by negative sentiment at 26.8% and positive sentiment at 16.1%. The KNN algorithm is suitable for large and low-dimensional data, SVM is suitable for data with many features and clear separation between classes, and Naive Bayes is efficient for large datasets with many low-quality features. Additionally, the Random Forest algorithm could overcome overfitting and unbalanced data. Logistic regression is also suitable for linear data without assuming a certain distribution. The Decision Tree algorithm is good for complex data as it provides a visual explanation of predictions. In this study, the Decision Tree algorithm obtained high results because it has the best characteristics and is a linear technique.
Novelty: This study found that based on the ROC method and the Confusion Matrix evaluation conducted, the Decision Tree algorithm is more accurate than the other algorithms studied.

The Merdeka Learning Campus Merdeka Program, also known as MBKM, is an activity that provides students with the opportunity to learn outside the classroom, one of which is teaching assistance. This paper aims to describe the activities conducted by students of Universitas Bina Darma Palembang in community service by implementing learning through the viewing technique in the Indonesian language subject for 11th grade students in the Merdeka curriculum. Through learning with the viewing technique, it is expected that students will be able to answer, summarize, and understand the intrinsic and extrinsic elements of the short story Tukang Cukur by Budi Darma. This Community Service (PkM) activity was conducted in the form of learning, counseling, and training. The PkM activity took place at SMA Arinda Palembang with 20 students. The method used in this activity was qualitative descriptive with data collection techniques of observation, note-taking, and documentation. After conducting learning on the short story Tukang Cukur by Budi Darma with the viewing technique in the 11th grade IPA class at SMA Arinda Palembang, positive results were observed. The majority of students were able to understand the content of the story, answer questions correctly, and improve their critical thinking skills, as well as their appreciation for literary works.

Informasi biaya merupakan informasi penting bagi pelaku usaha untuk penentuan harga jual ataupun untuk menentukan target laba. Penelitian ini bertujuan untuk mengeksplorasi mengenai perhitungan biaya pada jasa pemain pengganti game online dalam menentukan harga jual jasa. Penelitian ini berfokus pada perhitungan biaya serta metode yang digunakan untuk penentuan harga jual jasa. Metode penelitian yang digunakan dalam penelitian ini adalah wawancara secara langsung kepada pemilik layanan penyedia jasa pemain pengganti game online dengan mengambil 3 (tiga) genre diantaranya adalah MOBA, RPG, dan FPS. Hasil wawancara menunjukan bahwa metode yang digunakan untuk menghitung biaya masih tergolong sederhana dan belum ada perhitungan khusus. Harga jual jasa yang ditawarkan kepada konsumen lebih berpatokan pada harga pasar yang berlaku dan perhitungan biaya merupakan pertimbangan minor.

This abstract discusses the importance of preventing corruption through effective implementation of the law, especially in relation to stakeholders. Corruption is a serious threat to public trust and the stability of government and private institutions. Strict and fair application of the law is very necessary to create a transparent and accountable environment. By implementing clear rules and heavy sanctions, acts of corruption can be minimized. Active participation of stakeholders, including government, civil society and the private sector, is also very necessary in monitoring and supporting efforts to prevent corruption. This will create good governance and strengthen public trust in institutions.

In the community of Langkuru Village, Pureman District, Alor Regency, there are often illegitimate children who cause problems because they become a topic of discussion in the community. The process of resolving illegitimate children can be carried out with national law or through customary law as is done by the community of Langkuru Village, East Nusa Tenggara (NTT). The settlement of illegitimate children according to customary law in Langkuru Village, Pureman District, Alor Regency, East Nusa Tenggara, is usually resolved in the Customary Warehouse (langwah) because the Customary Warehouse (langwah) is a place of peace for customary problems and never has to get a court decision because basically the residents of Langkuru Village can resolve it by mutual agreement, either a joint agreement with the family or a joint agreement according to custom. The position of illegitimate children in the distribution of inheritance in Langkuru Village remains the same as the distribution of inheritance against legitimate because it adheres to the matrilineal customary system. This type of research uses an empirical legal research type with a sociological legal approach and primary data sources and secondary data are then analyzed descriptively qualitatively.

This study aims to analyze the importance of professional laws and codes of ethics for members of the National Police of the Republic of Indonesia (Polri). The National Police professional code of ethics is a code of conduct that must be followed by every member of the National Police in carrying out their duties and responsibilities. This study examines the legal aspects that govern the code of ethics, as well as evaluating the challenges and its implementation in police practice. Data was collected through literature studies, analysis of laws and regulations, and in-depth interviews with members of the National Police. The results of the study show that effective enforcement of the code of ethics can strengthen integrity, professionalism, and public trust in the National Police. However, several challenges are still faced in the implementation of the code of ethics, such as the lack of socialization and strict supervision. This research provides recommendations to increase awareness and compliance of members of the National Police with the code of ethics, as well as strengthen its enforcement mechanism to strengthen.

Marriage is often pursued with the expectation of finding enduring happiness and fulfillment. However, the reality of marital life can deviate from these aspirations. This study investigates the crucial role of marital commitment in shaping marital satisfaction among couples in Bali. Employing survey techniques, data was collected through questionnaires, utilizing a scale likert to measure both commitment and satisfaction levels. The results highlight a significant positive correlation between marital commitment and marital satisfaction. Specifically, higher levels of commitment are associated with increased marital satisfaction, while lower levels of commitment correspond to diminished satisfaction. Pearson product moment parametric correlation analysis substantiates these findings, revealing a correlation coefficient of r = 0.848 and p = 0.000 (p < 0.05). This study underscores the importance of marital commitment in fostering marital satisfaction, offering valuable insights for couples and practitioners alike.