This study aims to examine the influence of knowledge and awareness on safety riding behavior among online motorcycle taxi drivers. Considering the rapid growth of online transportation and the increasing risk of accidents, understanding the factors that affect driver behavior is crucial. This literature review analyzes 15 relevant studies. The researcher conducted a series of studies involving various sources such as books, Google Scholar, Mendeley, PubMed, ScienceDirect, focusing on open access and full paper articles in Indonesian or English. The analysis shows a significant relationship between drivers’ knowledge and awareness of safety riding practices and their compliance with safe driving behavior. Higher levels of knowledge and awareness correlate with increased adherence to traffic regulations, proper use of safety equipment, and better understanding of potential road hazards. These findings emphasize the importance of continuous safety training programs and policy interventions to improve the safety and welfare of online motorcycle drivers.
 
 

This study aims to determine the influence of Digital Marketing, Taste and Promotion variables on Purchasing Decisions at Mi Ayam and Bakso 45 Burengan. This type of research is quantitative research. The data for this study were obtained through questionnaires, interviews, and literature studies. The analysis techniques used were Validity Test, Reliability Test, Classical Assumption Test, Multiple Linear Regression Analysis, t-test, F-test and Determination Coefficient Test. The results of the t-test of the digital marketing, taste and promotion variables had a significant partial effect on purchasing decisions with sig <0.05. The results of the F test can be concluded that digital marketing, taste and promotion have a simultaneous and significant effect on Purchasing Decisions at Mi Ayam and Bakso 45 Burengan with sig. <0.05.

The phenomenon of climate change has a very pronounced impact on Semarang City, especially in Tambakrejo Village with increased risk of disasters such as flooding and tidal floods. Various efforts in reducing the risk of climate change have been carried out through the Climate Village Program (ProKlim) with the aim of increasing community participation in waste management. Currently, inorganic waste management has been carried out by the Berkah Jaya Waste Bank but it is not optimal, while for organic waste management it still does not exist. The purpose of the service activity is to make household waste management more organized so that it supports the Climate Village Program. Activity methods through counseling, training, technical guidance, field practice, equipment facilitation and program development. The results of activities in the form of increasing partners' understanding and skills in waste management with several activities including socialization of household-based waste management, increasing community capacity in processing organic waste, facilitating facilities and infrastructure for organizing waste processing sites and developing waste bank savings programs. Another result is an increase in sales of inorganic waste from the Berkah Jaya Waste Bank, where from waste management it can buy waste from residents amounting to Rp.2,749,350, - with sales of Rp.3,376,200, - during February - June. The conclusion of this activity is that there is an increase in organic and inorganic waste management in target partners.

Handwritten digit recognition is one of the key challenges in the field of digital image processing and artificial intelligence, with significant potential in various applications such as automatic form input systems, handwritten data correction, and attendance systems based on handwriting. This study aims to develop a web-based information system capable of automatically recognizing handwritten digits using the K-Nearest Neighbors (KNN) classification method. The system is designed through several main stages, including image preprocessing (conversion to grayscale, thresholding, and image size normalization), feature extraction using the zoning technique, and classification using the KNN algorithm. This research utilizes the MNIST dataset, which contains thousands of handwritten digit images ranging from 0 to 9. The system is developed using the Google Colab platform, supported by Python libraries such as OpenCV, NumPy, and Scikit-learn. Test results show that the system can achieve an accuracy of over 90% at certain K values, indicating that the KNN method is quite effective and efficient in recognizing handwritten digit patterns. This system is expected to be applicable for various digitization needs of handwritten numbers in education, administration, and information technology sectors

Penelitian ini berfokus pada penerapan metode Exploratory Data Analysis (EDA) untuk menganalisis dataset publik tentang lemak tubuh. Masalah yang diidentifikasi adalah pentingnya memahami pola distribusi dan hubungan antar variabel dalam dataset lemak tubuh. Penelitian ini memanfaatkan dataset lemak tubuh yang mencakup berbagai pengukuran lingkar tubuh pria, seperti berat badan, tinggi badan, dan persentase lemak tubuh. Solusi yang ditawarkan melibatkan serangkaian langkah EDA, termasuk pembersihan data, analisis univariat dan multivariat, serta visualisasi data menggunakan grafik seperti histogram, scatter plot, dan heatmap. Penanganan outlier dan rekayasa fitur seperti Body Mass Index (BMI) dilakukan untuk meningkatkan kualitas data dan menghasilkan wawasan baru tentang distribusi lemak tubuh. Hasil penelitian menunjukkan hubungan kuat antara persentase lemak tubuh dengan variabel seperti berat badan, lingkar perut, dan kepadatan tubuh. Sebagian besar individu dalam dataset berada dalam kategori BMI normal, dengan perbedaan distribusi ukuran tubuh berdasarkan kategori BMI. Hasil dari penelitian ini adalah dengan menggunakan EDA yang menyeluruh, yang mencakup analisis univariat dan multivariat, pola dan hubungan antara persentase lemak tubuh dan variabel lain seperti berat badan, tinggi badan, usia, dan lingkar tubuh telah ditemukan. Penelitian ini merekomendasikan pengembangan model prediktif berbasis machine learning dengan menggunakan dataset lemak tubuh.

Background: One of the factors that can affect treatment adherence in patients with type 2 diabetes mellitus is glycemic results, if glycemic control is poor then the implementation of treatment compliance can be a motivation for glycemic control. Purpose: This study aims to determine the relationship between treatment adherence and its impact on glycemic control in patients with type 2 diabetes mellitus in the Klatak Health Center working area in 2024. Methods: This study used a cross sectional design with purposive sampling and a sample size of 35 respondents. Data collection using the MTAQDM questionnaire (modified treatment adherence questionnaire in DM patients) and observation sheets and then analyzed using the spearmen rank test. Results: All patients (100%) were in the adherence category following treatment adherence activities and almost all patients (97%) were in the diabetic category. Based on the results of the analysis obtained a P-value of 0.628 (p>0.05) which means that there is no relationship between treatment adherence and the impact of glycemic control, with a correlation of 0.085 which shows a correlation with very weak strength. Conclusion: Respondents who adhere to treatment adherence do not affect their glycemic control and adhere to treatment but HbA1c is not controlled, because many factors can affect it.

The problems faced in this study include (1) How does the quality of nurse services affect patient satisfaction in the Inpatient Room of the Regional Public Service Agency of the Banjar City General Hospital? (2) How do paramedic facilities affect patient satisfaction in the Inpatient Room of the Regional Public Service Agency of Banjar City General Hospital? (3) How does the quality of nurse services and paramedic facilities affect patient satisfaction in the Inpatient Room of the Regional Public Service Agency of Banjar City General Hospital? This study aims to study, know, and analyze (1) The effect of nurse service quality on patient satisfaction in the Inpatient Room of the Regional Public Service Agency of Banjar City General Hospital. (2) The effect of paramedic facilities on patient satisfaction in the Inpatient Room of the Regional Public Service Agency of Banjar City General Hospital. (3) The effect of the quality of nurse services and paramedic facilities on patient satisfaction in the Inpatient Room of the Regional Public Service Agency of the Banjar City General Hospital.The method used in this study is an explanatory survey, while the data analysis techniques, namely validity tests, reliability tests, descriptive statistics, Inferential Statistical Analysis with Multiple Regression. The results of the study inform that (1) The quality of nurse services has a positive effect on patient satisfaction in the Inpatient Room of the Regional Public Service Agency of the Banjar City General Hospital. This means that if the quality of service is improved, then patient satisfaction in the Inpatient Room of the Regional Public Service Agency of the Banjar City General Hospital will also increase. (2) Paramedic facilities have a positive effect on patient satisfaction in the Inpatient Room of the Regional Public Service Agency of the Banjar City General Hospital. This means that if paramedic facilities are improved, patient satisfaction in the Inpatient Room of the Regional Public Service Agency of the Banjar City General Hospital will also increase. (3) The quality of nurse services and paramedic facilities has a positive effect on patient satisfaction in the Inpatient Room of the Regional Public Service Agency of Banjar City General Hospital. This means that if the quality of nurse services and paramedic facilities is improved, patient satisfaction in the Inpatient Room of the Regional Public Service Agency of the Banjar City General Hospital will also increase.

Streetboba & Gildak Kediri outlet is a restaurant that serves a variety of Korean food menus and various kinds of drinks with boba and jelly toppings that are sold at low prices that suit the student's budget. This restaurant is located in East Java province which is precisely on Jalan Yos Sudarso No.43, Kediri City. With technological advances that continue to grow to affect various aspects, especially in the business and industrial world. Sentiment analysis is a technology that extracts or manages text to be expressed using text that can also be classified into positive and negative polarity. Consumer reviews are a form of communication that occurs in the sales process, the stage where potential buyers receive an explanation of the product posted and buyers receive reviews that explain the advantages or disadvantages of purchasing the product. In this study, sentiment analysis was conducted based on consumer opinions regarding social media accounts. The study aimed to use social media data to assess the service, cleanliness and quality of products offered by categorizing companies as having positive and negative reviews. To classify sentiment, the Naive Bayes method is used, which combines survey data collection methods, questionnaires, and observation data.

Introduction: Datafication still plagues Indonesian journalists, especially local ones, skewing news validity and neutrality. Indonesian journalists from 13 local media were surveyed and interviewed for this study. This study relied on several studies that suggest journalists may deliver more accurate, objective, and unbiased news by expanding their datafication capacity. As digital technology advances and social media spreads misinformation, it becomes critical.

Methods: Mixed-methods experimentation and triangulation. Indonesia has 13 native media representing its diversity. Using regional media, this study can illustrate data journalism literacy levels in different locations, including those with differing technology and education. We chose material based on data journalism approaches including data visualization, infographics, and data-driven reporting. This ensures study-relevant respondents.

Findings: Indonesian media's poor data literacy has a big impact. Data-driven journalism in local media is poor due to data analysis incompetence. Access and chances for journalists to develop data skills are major issues. Clearly, formal training is needed. Another factor is local media's focus on reporting speed over data analysis. Lack of technology and institutional support hinders local journalist data literacy projects.

Originality: Previous studies on Indonesian journalists' datafication knowledge and abilities are scarce and fragmented. Despite data journalism's growing popularity in newsrooms and academic status, comprehensive study is needed to define it.

Introduction: This study explored the role of mass media in enhancing tsunami preparedness among young adults on the southern coast of Central Java, a region highly vulnerability to tectonic events. Mass media, with its extensive reach and persuasive influence, played a significant role in disaster communication, shaping public awareness and preparedness.
Methods: Guided by Elaboration Likelihood Model (ELM) and neuroscience perspectives, the research examined how cognitive and emotional responses to disaster information influenced preparedness behaviors. A survey was conducted with 175 respondents aged 18-24 from Calaca, a high-risk tsunami zone. Among these, 91 respondents had prior disaster experience, with 60.38% relying on mass media as their primary source of emergency information.
Findings: The survey results showed that 74.9% of respondents indicated readiness for disaster preparedness. The study integrated the ELM framework with cognitive neuroscience, emphasizing modification to critical element such as ability to process information and the nature of cognitive processing. These adaptations supported more effective, persuasive disaster communication.
Originality: The finding underscored the potential of mass media as powerful stimulus, shaping cognitive responses and preparedness behavior. This research contributed to understanding the interplay between disaster communication, cognitive processes, and behavioral outcomes, offering insights for designing targeted interventions to enhance preparedness.