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 system for detecting the credibility of information on social media X by classifying tweets as credible or non-credible. Additionally, it seeks to improve the accuracy of classification and prediction of information credibility using feature extraction methods, semantic features, feature expansion, and optimization.
Methods: The system is built using a deep learning approach with Long Short-Term Memory (LSTM), Term Frequency-Inverse Document Frequency (TF-IDF), Robustly optimized BERT Approach (RoBERTa), Global Vector (GloVe), and Particle Swarm Optimization (PSO). The dataset consists of 54,766 Indonesian tweets from social media X, focusing on the 2024 General Election and using several keywords such as ‘Pemilu 2024’, ‘Pilpres 2024’, ‘anies baswedan’, ‘Prabowo’, ‘#GanjarPranowo’, and ‘#debatCapres’.
Result: The results of this study show that the highest accuracy achieved is 89.09% using LSTM with an 80:20 data split, baseline unigram, RoBERTa, Top1 corpus IndoNews, and PSO of the LSTM model’s hyperparameters, resulting in a highly significant statistical improvement of 0.96% over the baseline model.
Novelty: This research contributes to information credibility classification research using RoBERTa to add semantic features and GloVe to expand features by utilizing a built corpus and finding similar words to connect with these expanded features. Additionally, PSO is applied to find the optimal hyperparameters, thereby improving the performance and accuracy of the LSTM classification model.

Obesity is a physical condition that is of great concern to Polri Personnel. Apart from having an excessive anthropometric impact, it can also result in less optimal physical condition performance. This research aims to find out how big is the relationship: 1) between dietary habit and the obesity condition of Polri personnel, 2) between physical fitness and the obesity condition of Polri personnel, 3) between stress and the obesity condition of Polri personnel, and, 4) among dietary habit, physical fitness, and stress on the obesity condition of Polri personnel. This research is a type of correlational research. This research was conducted with subjects totaling 584 Polri personnel. Instruments used in the research were dietary habit instrument using the Food Frequency Questionnaires for Adults, physical fitness instrument using the National Police Physical Fitness Test, and stress instrument using the Police E-Mental Application. Data analysis techniques in the research involved product moment  correlation test analysis, multiple correlation with the regression line equation, prerequisite test and hypothesis test as well as univariate and bivariate analysis. This research shows that: (1) there is a relationship between dietary habit and the obesity condition of Polri personnel with a p-value of 0,631 with significance value of 0,000, (2) there is a relationship between physical fitness and the obesity condition of Polri personnel with a p-value of 0,433 with significance value of 0,000, (3) there is a relationship between stress and the obesity condition of Polri personnel with a p-value of 0,429 with significance value of 0,000, (4) there is a relationship among dietary habit, physical fitness, and stress on the obesity condition of Polri personnel by obtaining an Fcount value of 13,143 and an Ftable value of 8,532 marked by an R value of 0,537 with a significance level of 0,000. Based on the research results above, it can be concluded that there is a fairly strong relationship among dietary habit, physical fitness, and stress on the obesity condition of Polri personnel, and it can be seen that dietary habit has the most significant influence compared to physical fitness and stress. Suggestion: Polri needs to adopt programs that encourage healthy dietary habit for the personnel, It is important for the Regional Police (Polda) physical fitness bureau to implement a comprehensive and sustainable physical fitness program, and for the Polda psychology bureau to provide programs or periodic checks that can help managing and reducing stress in the workplace.

Physical activity is vital for children to improve their motor skills and overall fitness. This study aimed to develop the Dance Intensive Nimble Activity (DINA), a physical activity model combining trending TikTok dances with short, high-intensity mini-games. The ADDIE model (Analyze, Design, Develop, Implement, Evaluate) guided the development. The study involved 68 children aged 9-10 years across Central Java and Yogyakarta schools, with data collected through observations, questionnaires, and documentation. Expert validation rated DINA as "Very Valid" (mean score 3.76/4), while children's responses showed high enthusiasm (mean score 3.60/4). DINA was easy to follow, engaging, and beneficial in enhancing motor skills, fitness, and cognitive function. The combination of fun music, simple moves, and ice-breaking elements made DINA enjoyable for children, promoting positive feelings and motivation. In conclusion, DINA is an effective and practical alternative physical activity model for children aged 9-10.

The purpose of this study was to determine the contribution of body mass index to the level of physical fitness of junior high school students in Medan City in 2023. This study used descriptive analytic method. The sample amounted to 23 people, obtained by purposive sample. To determine the correlation of body mass index to the level of physical fitness is sought using the product moment formula. This research uses body mass index test instruments and physical fitness tests carried out to find out data on research variables, namely body mass index data and student physical fitness tests. From the results of statistical analysis, the correlation coefficient between body mass index and physical fitness is rcount = 0.55. To find out how much the contribution of body mass index to the level of physical fitness is calculated with R = (0.55)2 x 100% = 30.25%. The contribution is 30.25%. Thus the hypothesis that states there is a contribution of body mass index to the level of physical fitness of junior high school students in Medan City in 2023 can be accepted in this study. This research opens insights into knowledge for teachers, especially physical education teachers so that this information can be applied in schools.

The change of Minister of Education is often followed by new policies that cause various reactions among the public, including students and educators. This study aims to understand public perceptions of the change of Minister of Education and its implications for curriculum policy. This research uses a descriptive qualitative approach with a questionnaire-based interview data collection method to educators and students. The results showed that most respondents had positive expectations of the new minister, especially regarding improving the quality of education and reducing the administrative burden on teachers. However, there were concerns about repeated curriculum changes. Respondents emphasized the importance of inclusive communication, strengthening the role of teachers and improving education infrastructure. Active stakeholder support is considered essential in realizing relevant, effective and sustainable education policies.

This study examines the main pests and diseases that attack cayenne pepper (Capsicum frutescens) plants grown in polybags. In Indonesia, this crop is in high demand for both household and industrial use. Nonetheless, farmers often face challenges from pest and disease attacks, including anthracnose, fusarium wilt and stem rot, leading to reduced yields. The methodology used was a literature review covering various sources related to cayenne pepper. Findings show that important diseases such as anthracnose can reduce yields by up to 80%, while pests such as fruit flies can cause chili fruits to drop prematurely before harvest. Effective pest and disease management is essential to increase the productivity of cayenne pepper cultivated in polybags.

This study examines the effectiveness of organic fertilizers in improving the quality and yield of cucumber (Cucumis sativus L.) plants through a comprehensive literature study. A systematic review was conducted on recent scientific publications that discuss various types of organic fertilizers, including chicken manure, bokashi, organic liquid fertilizer, and eco-enzyme. The research method used a literature study approach by analyzing articles from 2020-2024, focusing on the effectiveness of organic fertilizers in increasing the growth and productivity of cucumber plants.The results showed that organic fertilizers do not merely provide nutrients, but transform as agents of soil ecosystem regeneration. Each type of organic fertilizer has a unique mechanism in influencing plant growth, including increased microbiological activity, optimization of soil structure, and stimulation of the root system. Variations in plant responses depend on genotype, fertilizer composition and environmental conditions. The research resulted in practical recommendations for sustainable organic fertilization strategies, emphasizing the importance of a precision and holistic approach in cucumber crop nutrient management. The findings make a significant contribution in the development of sustainable agriculture.

This study aims to explore the root growth patterns of cucumber (Cucumis sativus L.) cultivated in a polybag system, and examine the implications for nutrient absorption efficiency and plant survival. The method used was a systematic literature review, with narrative analysis of recent studies in the last five years. Data were analyzed to identify the relationship between root architecture, growing medium, and nutrient absorption efficiency.  The results showed that the polybag system, with its limited root growing space, promoted adaptation of root growth patterns, including an increase in lateral root density and a reduction in primary root length. Coconut fiber- and vermiculite-based growing media were shown to increase nutrient absorption capacity by up to 30%, while inoculation of rhizosphere microorganisms, such as mycorrhiza, increased phosphorus use efficiency by up to 25%. In addition, optimal root zone temperature plays an important role in supporting root metabolic activities.  The conclusion of this study confirms that optimizing root growth patterns through growing media, temperature management, and utilization of microorganisms can significantly increase the productivity of cucumber plants. These findings provide a basis for developing more efficient and sustainable cultivation strategies in modern horticultural systems. 

This research examines how adherence to analytical standards influences the structure of sentences within texts. By analyzing the relationship between analytical compliance and sentence construction, the study aims to uncover the effects of adherence to linguistic, syntactic, and contextual norms on text cohesion and readability. The findings shed light on the importance of analytical conformity in shaping sentence structures and enhancing overall text quality and comprehension.