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.

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.

Chicken Nuggets   is   a   processed   product   made   from   ground   meat   with   several   additional ingredients and moulded in various shapes. Innovatio in the use of breadfruit which has nutrients in the form of carbohydrates, fiber, protein, vitamins, and so on so that this food product has the potential to be of choice materials in chiken nugget product. Meanwhile,  Lampisang  Village,  Peukan Bada District,  Aceh Besar Regency,  as  a  location  for Community  Service  activity. The activities carried out were counseling and demontration on chicken nuggets with addition buah sukun. From this activity it can beconcluded that the implementation through community service processing chicken meat with addition buah sukun into nuggets, service participants can increase their knowledge and skills  in diversifikasi chicken meat. The implementation of the activity has been successful and has receiveda good response.

This research aims to analyze the efficiency of modern communication systems in transaction activities at Warkop Berkah, a micro-enterprise that has adopted digital technology. The main focus of the research is the implementation of modern communication systems, such as cashless payments via digital wallets, QR codes, and Point-of-Sale (POS) applications, which aim to improve operational efficiency, customer experience, and business competitiveness. This research also identifies various challenges faced in implementing this technology, including the need for employee training, implementation costs, and adaptation by customers who are still accustomed to conventional systems. The research results show that modern communication systems have a significant impact in increasing operational efficiency at Warkop Berkah. Transaction processes become faster, the risk of calculation errors is reduced, and financial transparency increases. In addition, this technology provides a better customer experience by offering convenience, security and comfort, especially for the younger generation who are more familiar with technology.  However, technology adoption also faces obstacles, such as dependence on stable internet connections, resistance from certain customers, and technical challenges in system maintenance. To overcome this challenge, the research recommends several strategies, including intensive training for employees, customer education, diversification of payment methods, and improving technological infrastructure. Real-time monitoring of transaction data is also proposed as a step to optimize operational performance and maximize customer experience. By implementing the right strategy, Warkop Berkah can utilize modern communication systems to support the sustainability and competitiveness of its business. This research contributes to understanding the importance of digitalization in micro and small businesses (MSMEs) in facing the challenges of the digital era. In addition, this study provides practical insights for micro business owners who want to adopt modern technology to increase efficiency and business growth amidst increasingly fierce competition.

E-sports is one of the techno-based sports that is generally held in the form of a video game tournament between several players which also has a fan base of millions of people.  E-sports has values in the form of sports, economic, social, achievement, and knowledge values like sports in general.  The parent organization of E-sport Indonesia itself is the Indonesian E-sport Executive Board (PBESI) chaired by Prof. Dr. Budi Gunawan, S.H., Si. This research aims to find out how the development of E-sport and what impact it has on economic growth in Pematangsiantar City.

This study examines the impact of relocating Indonesia's capital city from Jakarta to East Kalimantan on the local economy, workforce, and associated challenges. Using qualitative methods and descriptive analysis, the findings reveal positive effects such as increased investments and economic growth driven by new infrastructure and heightened economic activity in property, hospitality, and transportation sectors. However, challenges like rising property prices, gentrification, and social changes demand sustainable spatial planning and effective social impact management. Proposed mitigation strategies include thorough planning, social infrastructure development, local economic empowerment, and regular impact monitoring. The capital relocation has the potential to boost local economic growth if managed effectively.

Inheritance law in Indonesia has three directions, namely customary law, civil law and Islamic law. This journal article discusses one of the inheritance laws, namely customary inheritance law. The writing of this journal article aims to examine how the protection and process of obtaining inheritance rights for women in Balinese Hindu customary society, which adheres to the patrilineal system. The research method used is a normative legal research method with two approaches, namely a statutory approach and a conceptual approach. Data collection uses doctrinal which is by examining, analyzing and identifying knowledge contained in reading sources in the form of reference books, journals or previous research as research support. Based on the results of the study, it shows that under customary inheritance law, women are generally not entitled to inherit property, but only enjoy the inheritance of parents or husbands. However, they can obtain inheritance rights through grants, marital gifts (jiwa dana), or changing their status to male (sentana rajeg).

This research is about the implementation of Minister of Law and Human Rights Regulation No. 9 of 2017 in an effort to protect the position of notaries regarding TKM reporting. Reporting Suspicious Financial Transactions (TKM) is a new task that must be carried out by Notaries in accordance with the issuance of Permenkumham No. 9 of 2017 and the inclusion of Notaries as reporting parties in PP No. 43 of 2015. This Permenkumham was issued to support government programs in terms of preventing money laundering crimes. . This type of research is normative juridical with a statutory approach as well as an analytical approach. This research explains, However, this regulation does not explain further about what protections Notaries receive after reporting suspicious financial transactions themselves, as well as the obstacles experienced by Notaries in implementing Permenkumham No. 9 of 2017 in terms of reporting TKM.

This study analyzes the ambiguity regarding the obligation to mediate in resolving patent disputes according to the Patent Law, and its implications for the efficiency of the dispute resolution process. Although Article 153 and Article 154 of the Patent Law open up opportunities for dispute resolution through alternative mechanisms, the ambiguity regarding the obligation to mediate creates legal uncertainty that can hinder efficiency and increase dispute costs. Based on the Economic Analysis of Law approach, this study shows that the obligation to mediate can reduce social costs, accelerate the dispute resolution process, and increase overall economic efficiency. Mediation as an obligation can reduce the burden on the judicial system, minimize transaction costs, and create better legal and business stability. Therefore, this study encourages the implementation of the obligation to mediate in patent disputes to create a more efficient, fair, and profitable dispute resolution system for all parties involved.
 
 

This study explores the challenges experienced encountered among basketball players in tournament sports participation. The study employed a descriptive-exploratory case study approach. The researcher used semi-structured interviews and non-participatory observation to collect data from six basketball players who met the researcher's criteria. The finding’s revealed that the participants were challenged during tournament sports participation. The participants pointed out that during sports tournament participation, the participants revealed that some of their struggles were physical restraints, health conditions, such as injuries, not enough resting time, in-game pressure, and lack of communication. Results revealed that the presence of pressure, miscommunication of the team, and health conditions are their highly faced struggles during the game. The findings have proven that the challenges experienced by athletes undeniably affect their performance, which is also influenced by how they perceive situations in a competitive sports environment. This study highlights the importance of addressing both physical and mental health concerns to enhance player performance and team success in competitive sports environments.