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Research This investigate consumer sentiment analysis to halal products using social media data with utilise intelligence artificial intelligence (AI). With background behind increasing estimated market value of halal products reach USD 2.02 Trillion in 2024, understanding deep about opinion consumer become very important. Research This adopt approach quantitative, using secondary data from social media platforms such as Twitter, Instagram, and Facebook. Through Natural Language Processing techniques and algorithms learning machine, sentiment analysis is performed For identify pattern positive, negative and neutral in perception consumers. Research results show that 60% of the total 10,000 reviews had positive sentiment, with halal food products receiving the highest positive sentiment. Factors influencing consumer sentiment include product quality, price, and transparency of information. In addition, the study found that the use of AI in sentiment analysis provides advantages in efficiency and accuracy, and is able to capture nuances in consumer opinions that are not Possible done by manual analysis. From the analysis this, can concluded that the marketing strategy of halal products must focus on improving quality and providing clear information about halal certification. This study not only provides insight for halal industry players, but also enriches the literature related to AI, sentiment analysis, and sharia economics.

This research aims to compare the semantic phenomena of slang used by the Millennial generation and Gen Z on social media. The main focus of this research is to identify the types of slang that are often used by both generations, as well as understanding the meaning and reasons for the use of slang by the Millennial generation. The method used in this research is descriptive qualitative, with data obtained through journal reviews and analysis of documentation from social media such as Facebook, X (formerly known as Twitter), and Instagram. This research found that there are significant differences in the types of slang used by the Millennial and Gen Z generations, which are influenced by cultural and technological developments. In addition, this research reveals that the main reason the Millennial generation uses slang on social media is to strengthen social ties, show familiarity, and follow trends. The use of slang is also considered a way to create a unique and relevant digital identity in their social environment.

The aim of this research is to find out how criminal law regulates and recognizes the spread of hoaxes in the context of election campaigns and to find out how prevention efforts and legal education can be improved to reduce the spread of hoaxes during election campaigns. In this research, the researcher used a normative research method, namely a research method that aims to analyze, interpret and evaluate applicable law or legal principles by referring to theory, doctrine, statutory regulations, court decisions and other legal sources. Social media is the easiest place to share and get various information about the latest things that are currently being discussed and paid attention to by the public. However, as explained previously, not everyone can use social media well and wisely. This can be seen from the rise of hoax news spread on various social media platforms, be it Facebook, Instagram, WhatsApp, Twitter and so on.  

This research is motivated by the phenomenon that attracted the attention of netizens due to the raising of the Red and White Flag which was raised together with the flag of the Palestinian state which was spread through twitter social media. Many of the platform users commented that the incident was not in accordance with the laws and regulations in Indonesia.  In collecting data, this study used quantitative methods by examining the subject population of high school and university students with a survey approach. This study shows the subject's attention to the treatment of his country's identity, namely the Indonesian national flag as a student. The obligation to defend the country in the form of respect for the Indonesian national flag should be instilled in every soul of the young generation of the Indonesian nation. State defense is not only an obligation but also for the sake of maintaining the continuity of the Indonesian nation as a Pancasila human being.

The research was initiated in response to the increasing number of violations committed by media organizations, particularly those relating to violations of media ethics rules. Up to 30% of code of conduct violations are committed by online media. The Press Council said the number of news complaints reached more than 500 complaints throughout 2012, 98 of which were related to online media. As many as 76% of complaints related to violations of the Code of Ethics for Journalists. Technological advances along with the rapid development of social media have made it easier for people to disseminate information, ranging from writing, reporting, to disseminating information encountered in everyday life. In creating information, it is necessary to understand the journalistic code of ethics so that the content shared does not cause new conflicts in society. This research was conducted to examine how the Code of Journalistic Ethics is applied to the Twitter account TRIBUN LOTTO21GROUP as a citizen journalism media. This research is a descriptive qualitative research which means describing, presenting, explaining, or answering an existing problem in more detail

In the rapidly developing digital era, social media such as Twitter has become part of everyday life and facilitates the rapid dissemination of information, including information about criminals. This research aims to analyze public sentiment towards information about criminals spread on Twitter using the Naive Bayes algorithm. This algorithm was chosen because of its simplicity and effectiveness in text classification. Data was collected through a crawling process from Twitter, followed by a preprocessing stage to remove noise. The research results show that public sentiment towards information about criminals on Twitter is divided into three categories: positive, neutral and negative. After classification, it was found that neutral sentiment increased significantly to 63.4%, while positive and negative sentiment decreased to 10.5% and 26.1%. These findings indicate that people tend to be more careful in reacting to sensitive information. This research provides important insights for related parties in managing information about criminals on social media and can be a reference for developing further policies and strategies.

Sang Pisang is a food and beverage business owned by President Jokowi's son, Kaesang Pangarep, together with a businessman from Makassar, Ansari Kadir. Sang Pisang was born in 2017 by serving products made from bananas. Sang Pisang just rebranded in November 2022 by presenting the latest concept, namely changing the outlet, logo, visuals, packaging design, and presenting several new menu variations, so there is a need for activities that can increase brand awareness. Sang Pisang carries out marketing implementation using marketing public relations to provide communication to its consumers that is educational and informative using social media and several offline activities. The purpose of this research is to find out how Sang Pisang implements marketing public relations in increasing brand awareness. The theory used in this research is Marketing Public Relations (Kotler and Keller, 2012). The approach used in conducting this research is a qualitative approach with descriptive methods, and data collection techniques through observation, interviews and documentation. The results of this research show that Sang Pisang's Marketing Public Relations is carried out with various strategies such as Publication using social media, events, press conferences and podcasts, Media Identity by making changes to the logo, visuals and outlets. , Marketing Public Relations Activity (Marketing Public Relations Activities) for online using social media such as Twitter, Tiktok, and Instagram while offline, namely by holding press conferences, events, Corporate Social Responsibility (CSR), and podcasts, Public-Services Activity ( Public Activity Services) by carrying out CSR such as Samtama activities, donations, and several other humanitarian assistance have succeeded in increasing Brand Awareness

The ease of use of E-commerce application features raises problems among students in the aspect of consumptive behavior. The main objective of this study is to assess the impact of using E-commerce on consumptive behavior among students in Indonesia. The method used in this research is quantitative research method. The scale in this study uses a Likert scale, which is a measurement method to measure the perceptions, attitudes, or opinions of individuals or groups about social events or phenomena. Data collection was carried out by distributing questionnaires using google forms through social media such as Whatsapp, Instagram, and Twitter. From the research data, 107 respondents were obtained from all students in Indonesia who used the E-commerce application, the majority of respondents were female with the age of 19 years. The results show that the ease of access to E-commerce affects consumptive behavior among students, especially because of the many promos and discounts that are easily obtained through the E-commerce application. In addition, this study also highlights the significant role of features such as shopping carts, promos and discounts, product searches and reviews in shaping the consumptive behavior of its users.

Twitter is one of the media used by the Indonesian people to express their opinions regarding the 2024 Presidential Election. However, there is no scientific calculation that can determine the tone of public opinion regarding the 2024 presidential election. In this study, sentiment analysis was carried out on the tweets of the Indonesian people related to the 2024 Presidential Election (Pilpres 2024). The purpose of this study is to find out the opinions of Indonesian Twitter users regarding the 2024 Presidential Election using Natural Language Processing (NLP) Technology and Long Short Term Memory (LSTM) algorithms. NLP techniques are used to understand natural language and extract meaning from tweet copy, and LSTM is used to analyze the accuracy and accuracy of classification. The data used in this study was 1,004 tweets with the topic "Presidential Election", this data researchers obtained through the process of crawling using the tweet harvest library. In this study, 53.2% had positive emotions, 3.5% had neutral emotions, and 43.3% had negative emotions. 78% accuracy, 67% precision, and 67% recall.

This research discusses the role of digital marketing and customer relationship management at PT. Indofood Sukses Makmur Tbk, a company mostly engaged in food and beverages that grows and originates from Indonesia. This research uses qualitative methods. The data collection method used in this study is a descriptive method which is a data collection technique via the internet. The results of the study concluded that digital marketing has a significant influence on customer relationship management strategies at PT. Indofood Sukses Makmur Tbk. Digital marketing plays a crucial role in expanding the company's market area and target customers, as can be seen from the use of various digital platforms to promote products, such as Instagram, Twitter, Tiktok, and Facebook. Therefore, digital marketing and CRM have an important role in developing strategies that can maintain the competitive advantage of PT. Indofood Sukses Makmur Tbk.

This research is motivated by the use of social media Twitter which attracts its users with informative and popular content. Twitter has succeeded in reaching users from various groups, from officials to the general public. The features in it allow for unlimited communication. This research focuses on analyzing the principles of jokes in tweets from the Twitter account @kaesangp. The principle of joking is a method that is intended to offend feelings by being friendly or in the form of a basis for making conclusions that are true and false; an intentional violation of the maxims of politeness; and disclosure of taboo things in a speech. In accordance with the focus of the research objectives, pragmatic theory is used and is related to the principle of jokes. This research use desciptive qualitative approach. The listening method and note-taking technique were used as data collection methods. As the end of the research objective, results were obtained in the form of utterances in tweets from the Twitter account @kaesangp which contained utterances with the principle of joking. The research results were obtained from the classification and decomposition based on the type of joking speech, including satire, banter and jokes. The benefit of this research is to find out the principles of jokes contained in the tweets of related Twitter accounts.

English translation. The rapid advancement of technology encourages more diverse interactions in languages, one of which is followed by the emergence of various social media. The following research aims to discuss linguistic interactions regarding locutionary speech acts in Pragmatics. Unlike previous studies, this data was taken from utterances that discussed Indonesian language material uploaded by a Twitter user. Starting from discussing UTBK questions, PBM, language issues, to updates regarding the EYD (Edition V) which is implemented in Indonesia. This study aims to determine the intent and form of locutionary speech acts in Fauzan Al-Rasyid's Twitter account uploads regarding this linguistic material. This article applies a research method with a pragmatic and descriptive qualitative approach that uses techniques of reading, observing, and documenting the data to be collected. Documentation techniques are used to collect data, reduce data, display data, and verify the data taken so that all data is neatly arranged and properly recorded. The results of this study, the researcher found 15 speech data where all the data were in the form of locutionary speech acts. The 15 data have the intention of conveying information and giving confirmation from speakers to speech partners related to language. Then, in presenting the data, the writer uses formal and informal presentation. This research is expected to provide an understanding of locutionary speech acts and can be used as a basis and reference or reference by other researchers who wish to conduct similar research in order to improve their problem-solving skills or as an effort to improve their analytical skills .    

The development of information technology in the form of social media has experienced tremendous progress throughout the world. This development has an impact on changes in social behavior. Social behavior is defined as individual behavior in relation to society, or among members of society in the context of how they communicate between its members. The use of YouTube, Facebook, blogging, WhatsApp and Twitter for learning purposes by creating groups based on certain interests to hold discussions is very widespread in society. As a result of the very rapid development of social media, social behavior patterns have changed, which has gradually led to the integration of social media applications in various types of learning and learning activities. In fact, overall it can be said that this change is a change in the education system which covers all components    

Indonesia's golden opportunity to take part in a world-class soccer competition at the U-20 World Cup competition was wiped out, as FIFA gave the decision to revoke Indonesia's status as host of the U-20 World Cup. Indonesian netizens who felt disappointed expressed their opinions and trended on social media Twitter. This research focuses on sentiment analysis of tweets using a combination of FastText embeddings method for word vectorization and using LSTM type RNN algorithm for sentiment classification. The dataset used totals 9,645 data consisting of 4,141 positive data and 5,504 negative data taken from March 29, 2023 to April 05, 2023. The test results on the LSTM model provide the best performance with an accuracy value of 74.92%, precision 74.74%, recall 74.92%, and f1-score 74.78%. The conclusion of this research is that the majority of datasets have negative sentiments, which means that people are more likely to give negative opinions than to provide support to Indonesian football which is experiencing problems. It is hoped that with this conclusion in the future people will better control their opinions and provide positive opinions when Indonesia is experiencing problems.

This research aims to find out the parents' strategies in educating and developing children from early childhood to adulthood and the role of parents in balancing work and family or work life balance in daily life. The results of this study indicate that parents have several obstacles and factors in implementing the concept of work life balance, but have one strategy, namely authoritative parenting. Patterns that are combined between Authoritarian Parenting and Pessimistic Parenting. This can be seen from the 2 dimensions given, namely the Control and Warmth Dimensions, this process must also be carried out consistently and responsibly so that it is well implemented. The research uses qualitative methods with descriptive research types. With secondary data sources through national and international journal articles and using other sources such as online media, social media (youtube, instagram, facebook, and twitter). From the results mentioned, it can be concluded that work and personal life as well as the role of parents in educating children are the most important things in order to create a golden generation, where generations are able to provide polite attitudes, carry out responsibilities for work and personal life, and the most important thing is that children are able to become people who carry out all their activities in the social environment properly

This study explores the role of sentiment analysis as a predictive tool for understanding and forecasting product launch success in the digital market. Sentiment analysis involves the classification of consumer sentiment expressed on social media platforms such as Twitter and Instagram, and it can significantly impact businesses by predicting consumer behavior and product performance. The research highlights the relationship between social media sentiment and product success, demonstrating that positive sentiment is strongly correlated with higher sales and consumer engagement, while negative sentiment can lead to declines. Machine learning models, including Support Vector Machines (SVM) and Random Forest, were employed to classify sentiment from large volumes of social media data and correlate it with product performance indicators such as sales volume and consumer interaction. The study found that sentiment analysis models were highly effective in predicting product success, with positive sentiment generally driving product profitability and negative sentiment posing a potential threat to brand reputation. Moreover, the analysis showed that social media sentiment provides real-time insights into consumer perceptions, enabling businesses to quickly adjust marketing strategies and product development plans. These findings underscore the importance of integrating sentiment analysis into product launch evaluations and strategic decision-making. Future research should explore the integration of sentiment analysis with other predictive market models and investigate the effects of fake reviews and post-purchase consumer behaviors on product success.

In the era of globalization, technology is developing rapidly, especially in the field of communication media, making the world feel more connected. Internet media, as a rapidly developing communication medium, has penetrated into various levels of society, becoming a necessity in daily activities. Social media networks such as Twitter, Facebook, SMS, BBM, Line, and WhatsApp (WA) have become the main means of delivering various information services. Through this social media network, public communication becomes easier and faster, creating a high level of usage among the public. WhatsApp (WA), as a popular social media service, is used effectively to share information both privately and publicly, not only by teenagers but also by adults. One of them is a WA group which is formed based on needs. For example, the Independent Student Exchange 3 (PMM3) group. Research on code mixing in the use of Indonesian on WhatsApp social media is based on Applied Sociolinguistic Theory.

In facing the increasing awareness of environmental impact, electric vehicles have become a primary focus in the global automotive industry. With the advancement of technology and the growing need for eco-friendly solutions, the evaluation of public sentiment towards electric vehicles becomes highly relevant. This research aims to analyze opinions expressed on Twitter regarding the use of electric vehicles using the Long Short Term Memory (LSTM) classification method. Utilizing a dataset of 30,000 entries, this study applies the LSTM algorithm to classify sentiment in tweets. Four different scenarios are tested, involving combinations of Continuous Bag of Words (CBOW) and Skip-Gram feature extraction methods, as well as data split percentages of 80:20 and 70:30. The research results demonstrate high accuracy levels across all scenarios, ranging from 85.16% to 85.9%. These findings indicate the effectiveness of sentiment analysis in gauging public perspectives on the use of electric vehicles. This study makes a significant contribution to understanding public sentiment related to electric vehicles based on Twitter data while highlighting the application of sentiment analysis techniques in the context of electric vehicle usage.

Childfree terjadi pada individu atau pasangan yang secara sukarela memilih untuk tidak memiliki anak. Fenomena Childfree semakin menarik perhatian masyarakat modern dan mempengaruhi keputusan hidup banyak individu. Data yang digunakan diperoleh dengan melakukan crawling data pada sosial media twitter. Dalam analisis sentimen kali ini menggunakan metode naïve bayes, data akan diflasifikasikan menjadi dua hasil, yaitu sentimen negatif dan positif. Setelah itu, data tersebut akan dinilai menggunakan pengujian dengan confusion matrix untuk mengukur akurasi, recall, dan precision. Hasil pengujian dengan Rapidminer menunjukan tingkat akurasi naive bayes yang tinggi sebesar 96%, untuk sentimen positif menghasilkan nilai precision 84,13%, dan nilai recall 100%. Sedangkan untuk sentimen negatif menunjukkan nilai precision 94,92%, dan recall 100%. Hasil klasifikasi tersebut menghasilkan 254 tweet negatif, dan 74 tweet positif. Analisis sentimen menggunakan metode Naïve Bayes dapat memberikan wawasan yang berharga tentang pandangan dan sentimen masyarakat terhadap Childfree. Hasil penelitian ini penting untuk memahami dan menghargai keragaman pandangan terkait topik ini. Implikasi penelitian ini dapat digunakan untuk pengambilan keputusan yang lebih baik dalam konteks sosial, budaya, dan kebijakan yang berkaitan dengan keputusan Childfree.

The Digital Era has transformed the way humans interact and communicate through the development of information technology and social networks. Social media platforms such as Facebook, Instagram, and Twitter have reshaped the landscape of social interactions, enabling individuals to connect with people worldwide quickly and efficiently. This article conducts an in-depth analysis of the significant influence of social networks on social interactions in the digital era. Social networks facilitate the exchange of information, collaboration, and getting to know each other in various forms, ranging from text to visual and audiovisual content. In this context, there are two key elements in social interactions: social contact and communication. The Uses and Gratifications theory highlight the active role of social media users in choosing and utilizing these platforms to fulfill their needs for entertainment, information, personal identity, and social integration. Despite the convenience they offer, the use of social networks also presents significant challenges, such as privacy issues and social media addiction. It is crucial for individuals to develop a healthy self-awareness regarding their social media usage. Additionally, technology companies and policymakers must prioritize protecting users' privacy and creating an online environment that is healthy, safe, and inclusive for everyone. This analysis not only discusses negative impacts such as privacy and data security but also demonstrates the potential of social networks as powerful tools for building bridges between cultures, ideas, and people worldwide. Therefore, collaboration between society, governments, and corporations is essential in creating a positive and healthy online environment for all users.