In the current era of technological development, the application of conventional biotechnology can be seen in making tempeh, the manufacturing process of which uses fermented soybeans as raw materials with the help of microorganisms in the form of yeast. This tempe making training activity was held on April 20 2024 at Johar Market with a total of 29 participants. The method used in this training is to use the method of explaining the material and practicing directly. Based on the results of the training activities, there was an increase in participants' knowledge and abilities, this increase could be seen when the results of the questionnaire were distributed before and after the training was carried out. All participants know that tempeh is one of the foods most liked by the majority of Indonesian people. The speaker provided knowledge and experience regarding tempeh processing, when the participants already understood about tempeh processing, after that they carried out direct practice, up to the washing stage and entered the manufacturing stage. In this training, participants understand that tempeh has a fairly high source of vegetable protein and this training provides benefits and increases interest in opening up tempeh business opportunities.

The development rapidly growing of the Indonesian food and beverage industry increases the risk of business competition. To develop and overcome the food and beverage industry, Laoban Surabaya must have the advantage of being a kopitiam shop. The aim of this research is to cover all components that can influence customer satisfaction. Qualitative research uses interviews to collect data. The data analysis method used was data reduction and drawing conclusions, with eight respondents being owners and visitors to Laoban Surabaya. The research results show that product quality, price and service are three components that influence customer satisfaction. In terms of product quality, providing high quality food and drinks with unique flavors that can be enjoyed by everyone. In terms of price, affordable price offers start from IDR 10,000 to IDR 50,000. In terms of service quality, ensuring customer comfort, friendly and alert service, and fast service.
 

Indonesia, as a developing country, faces challenges in improving people's welfare through development that is not yet optimal. Under the leadership of President Joko Widodo, the government is focusing on significant infrastructure development in an effort to encourage economic growth and modernization. Using Harrod Domar's modernization theory, this research examines how investment in infrastructure can encourage Indonesia's economic growth. The method used is literature study, with analysis of literature related to infrastructure development and modernization theory. The results show that toll road construction has a positive impact on transportation efficiency, community mobility, and economic growth, although it also faces several challenges such as environmental impacts and community involvement. The construction of toll roads, especially through collaboration between the government and the private sector, is an example of the application of Harrod Domar's theory in the context of Indonesian modernization, showing that effective investment in infrastructure can increase productivity and community welfare.

The life of the people of Jember, which has long been inseparable from tobacco farming activities, sparked the birth of the idea of building a tobacco museum. This tobacco museum can be said to be a representation of how tobacco developed in the city of Jember. Several aspects contained in it also support the representation process. Starting from the beginning of the construction of the museum which was inspired by the habits of the people of Jember city, namely tobacco farming, the names of several agricultural tools were born from the language of the local community, even to the concept of the building which was interpreted as having similarities with one of the tools for tobacco production, namely the Atag warehouse. This research uses a representation theory perspective proposed by Stuart Hall. According to Hall, there are three approaches to the representation process consisting of reflective, intentional and constructionist approaches. The aim of this research is to find out how the representation process occurs in the tobacco museum. This type of research is qualitative research with an ethnographic approach. The results of the research show that there has been representation in the tobacco museum where the process involves various aspects contained in the museum itself.
 
 

Social life is inseperable from social interaction. This raises social problems in terms of cultural, religious, economic, educational, and politacal diversity. This research aims to reveal social criticism regarding socio-political problems correlated with Gillin and Gillin’s theory of social problems in novel 86 by Okky Madasari. The method used is descriptive qualitative method. The results of this study reveal three main issues of socio-political problems namely corruption, collusion, and nepotism. The most correlated influence is on economy, habits, and morals. However religion, education, and family issues are also related to these three elements. Economic problems are related to education, habits, religion, and family which have an impact on human behavior. The problem of habits is related to economics, education, morals, and religion which have an impact on the development of society. Moral issues are related to religion, habits, and education which have an impact on the character building of individuals or grups.

Smuggling of used clothes is a criminal act that is still a serious problem in Indonesia.This is certainly a concern from various parties, especially Customs and Excise as an agency that has duties and responsibilities in the field of Customs. Law Number 17 of 2006 concerning Amendments to Law Number 10 of 1995 gives authority for Customs and Excise to carry out their roles in accordance with the scope of duties and functions carried out. However, in practice in the field, cases of smuggling of used clothes continue to be found, one of which is in the Atambua City area This research uses an empirical juridical research method, which is a study that directly examines the phenomenon of smuggling used clothes that occurs in the field, as well as the role of Customs and Excise investigators and the obstacles of Customs and Excise investigators in eradicating the smuggling of used clothes by conducting an interview with the Head of the Atambua Customs and Excise Office, Head of the Atambua Customs and Excise Enforcement and Investigation Section, Atambua Customs and Excise Investigator Members and the public who are consumers and sellers of used clothes. The results of the study showed: (1) The role of Customs and Excise investigators in eradicating the crime of smuggling used clothes in the Atambua City area includes preventive measures, namely socializing to the public about the smuggling of used clothes and conducting patrols. (2) The obstacles experienced by Customs and Excise investigators in eradicating the crime of smuggling used clothes in the Atambua city area include the breadth of the surveillance area, accessibility, the high interest of the Atambua community in consuming used clothes, law enforcement factors where there are still law enforcement personnel involved in smuggling, facilities or facilities where the number of transportation and investigator members is still minimal, community factors where there is still a lack of sensitivity and community participation in eradicating the smuggling of used clothes in the Atambua city area.

Purpose: This study aims to analyze public sentiment towards the Indonesian Electoral Commission (KPU) performance and evaluate a modified Convolutional Neural Network (CNN) model effectiveness in sentiment analysis.
Methods: This research employs several methods to achieve its objectives. First, data collection was conducted using web crawling techniques to gather public opinions on the performance of the Indonesian Electoral Commission for the 2024 elections, with a specific focus on platform X. A total of 5,782 data points were collected and underwent preprocessing before sentiment analysis was performed. This study uses the CNN method due to its exceptional ability to recognize patterns and features in text data through its convolutional layers. CNN is highly effective in sentiment analysis tasks because of its ability to capture local context and spatial features from text data, which is crucial for understanding the nuances of sentiment in comments. The modified CNN model was then trained and evaluated using a labeled dataset, where each comment was classified into positive, negative, or neutral sentiment categories. Modifying the CNN model involved adjusting its architecture and parameters, as well as adding layers such as batch normalization and dropout to optimize its performance. The effectiveness of the modified CNN model was assessed based on metrics such as classification accuracy, precision, recall, and F1 score. Through this methodological approach, the research aims to gain insights into public sentiment towards the KPU performance in the 2024 elections and to evaluate the effectiveness of the modified CNN model in sentiment analysis.
Result: The research revealed several significant findings. Firstly, most comments expressed concerns regarding performance aspects of KPU’s, including transparency, fairness, and integrity. Neutral sentiment dominated the discourse, with approximately 23.66% of comments conveying dissatisfaction or skepticism towards KPU's handling of the elections. Additionally, sentiments expressed on social media platform X mirrored those found across other platforms, indicating a consistent perception of KPU performance among users. Furthermore, the evaluation of the modified CNN model demonstrated a substantial improvement in accuracy, achieving an impressive 93% accuracy rate compared to the pre-modification model's accuracy of 77%. These results suggest that the modifications made to the CNN model effectively enhanced its performance in sentiment analysis tasks related to KPU performance during the 2024 elections. These findings contribute to a deeper understanding of public sentiment toward KPU performance and underscore the importance of leveraging advanced technology, such as modified CNN models, for sentiment analysis.
Novelty: This study contributes novelty in several ways. Firstly, it provides insights into public sentiment towards the performance of the KPU during the 2024 General Elections, which is crucial for understanding the perception of democracy in Indonesia. Second, the study employs a mixed-methods approach, combining web crawling techniques for data collection and a modified CNN model for sentiment analysis, which offers a comprehensive and advanced methodology for analyzing sentiments on social media platforms. Thirdly, the evaluation of the modified CNN model demonstrates a significant improvement in accuracy, indicating the approach's efficacy in analyzing sentiments related to KPU performance. This study offers valuable contributions to academic research and practical applications in sentiment analysis, particularly in democratic processes and institutional performance evaluation.

Korean pop culture, or K-Pop, has become a global phenomenon that influences many aspects of the lives of teenagers around the world. This research aims to understand how teenagers' lifestyles are influenced by Korean pop culture through television programs. Qualitative research methods were used to explore teenagers' experiences and perceptions of consuming Korean pop culture via television. Research findings show that teenagers often adopt lifestyles promoted by the K-Pop celebrities they see on television screens. They follow fashion trends, hairstyles and even diets inspired by Korean television programs. The results of this research provide deeper insight into the impact of Korean pop culture on teenagers and its implications for local cultural identity.

development of sharia economics in Indonesia, sharia financial institutions, especially Baitul Maal Wat Tamwil, have the main goal of being able to help and alleviate problems, especially the problem of limited capital based on Sharia principles. Because many entrepreneurs have limited business capital. Therefore, with this research, entrepreneurs who need it will have information about the financing mechanism with a Mudharabah agreement, for those who have limited business capital. BMT UGT Nusantara has several financing products, one of which is the mudharabah contract. Mudharabah financing is an agreement where the shohibul maal provides funds to the mudharib with the profits divided according to the profit sharing and nibah agreed at the beginning of the contract. The mudharabah financing mechanism at BMT UGT Nusantara Kepanjen requires members to fulfill the requirements, then the BMT will carry out analysis and observations to ensure the eligibility of the recipient of the financing, if it has been approved they will inform you of the disbursement of funds and carry out an agreement. When the contract is executed, BMT and the customer enter into an agreement on the division of the ratio and margin. This research uses qualitative methods, with field research and interviews with BMT staff as a means of obtaining information

Purpose: The presence of a two-month lag in Hotel Room Occupancy Rate (TPK) data necessitates an alternative method to accommodate adjustments in the economic circumstances of the tourism industry. In this context, TPK is connected to the influx of tourists, making the data a valuable resource for assessing the tourism potential of a particular area. The information can be used to make informed decisions when considering investments in the local tourism industry. Therefore, this research aimed to formulate predictions for future trends using now-forecasting. The variables of Google Trends Index (IGT) and online traveler reviews considered were obtained from big data.
Methods: This research used machine learning methods with Random Forest, LSTM, and CNN-BiLSTM-Attention models in determining the best model. Meanwhile, the datasets were acquired from diverse secondary data sources. Hotel Occupancy Rooms Rate was derived from BPS-Statistics Indonesia, while additional data were collected through web scraping from online travel agency websites such as Tripadvisor.com, IGT with keywords “IKN”, “hotel”, and “banjir”. For the sentiment variable from online reviews, lag effects of one, two, and three months were analyzed to determine the correlation with TPK. The highest correlation was selected for inclusion in the prediction model across all machine learning methods.
Result: The results showed that the use of IGT and online traveler reviews increased the precision of forecasting models. The best model of hotel TPK nowcasting was Random Forest Regression with the lowest MAPE value and accuracy of 5.37% and 94.63%, respectively.
Novelty: The proposed method showed great potential in improving the prediction of hotel TPK by leveraging new technology and extensive data sources. The correlation with TPK decreases with an increasing time lag of sentiment. Therefore, the sentiment of reviews in the current month has the highest correlation with TPK, compared to the previous one, two, or three months.