In today's digital age, social media stands as a dynamic arena where individuals freely express their thoughts and opinions, from succinct tweets on Twitter to expansive narratives on platforms like Facebook and Instagram. However, amidst this vast sea of user-generated content, a glaring void persists a definitive rating system capable of distilling the nuanced sentiments embedded within these diverse commentaries. This study thus emerges as a pioneering endeavor, poised to bridge this crucial gap in sentiment analysis. Leveraging the transformative potential of the Word2vec methodology in the preprocessing phase, researchers embark on a comprehensive journey to classify comments on a meticulous 1-5 rating scale, thereby unraveling the multifaceted spectrum of sentiments encapsulated within them. Complementing this groundbreaking approach, the Random Forest classification model is harnessed to bolster the analytical prowess of the study. The resultant accuracy score of 60.4% stands as a testament to the study's significant strides towards achieving a deeper understanding of comment sentiment in the realm of social media. However, this is merely the inception of a promising trajectory; the study's findings hold the promise of not only refining sentiment analysis techniques but also revolutionizing diverse sectors, from market research to product development. With this study, the narrative of sentiment analysis transcends the confines of academia, beckoning forth a new era of nuanced comprehension and meaningful engagement within the sphere of social media commentary. As the study concludes, it leaves behind a compelling call to action, inviting further exploration and innovation in this dynamic field.

Information technology plays a crucial role in enhancing company performance and driving business growth. Maintaining good customer relationships is essential, and Customer Relationship Management focuses on building customer commitment. Sales Force Automation systems automate sales processes and manage customer interactions. PT. Maju Jaya Kreasindo, a furniture company in East Jakarta, aims to automate its sales force and centralize operational information through a web-based Sales Force Automation system using Electronic Customer Relationship Management. The research adopts the "Prototyping" method, offering a shorter development duration and flexible implementation. Visual Studio Code and Xampp, along with PHP and MySQL, are utilized as development tools. The result is a Sales Force Automation system based on Electronic Customer Relationship Management that assists PT. Maju Jaya Kreasindo in automating its sales force. The design successfully automates tasks, supported by Electronic Customer Relationships and the prototyping method. The Sales Force Automation system passed the functionality evaluation, achieving high user acceptance test scores, and indicating its effectiveness in meeting user requirements.

Information technology plays a crucial role in enhancing company performance and driving business growth. Maintaining good customer relationships is essential, and Customer Relationship Management focuses on building customer commitment. Sales Force Automation systems automate sales processes and manage customer interactions. PT. Maju Jaya Kreasindo, a furniture company in East Jakarta, aims to automate its sales force and centralize operational information through a web-based Sales Force Automation system using Electronic Customer Relationship Management. The research adopts the "Prototyping" method, offering a shorter development duration and flexible implementation. Visual Studio Code and Xampp, along with PHP and MySQL, are utilized as development tools. The result is a Sales Force Automation system based on Electronic Customer Relationship Management that assists PT. Maju Jaya Kreasindo in automating its sales force. The design successfully automates tasks, supported by Electronic Customer Relationships and the prototyping method. The Sales Force Automation system passed the functionality evaluation, achieving high user acceptance test scores, and indicating its effectiveness in meeting user requirements.

Universities in Indonesia are working hard to improve the graduation rates of their students as it is considered a measure of success and quality in terms of accreditation. This study focuses on analyzing the effectiveness of machine learning algorithms, regression, Support Vector Machine (SVM) Decision Tree and ensemble learning, with AdaBoost wether the Computer Science students will graduate on time or not. The data used for this analysis consists of student records from 2015 to 2019. Includes 14 variables. To understand the relationships between these variables a two-dimensional visualization called a Heatmap was employed. The research findings indicate that the Support Vector Machine (SVM) and AdaBoost Decision Tree (DT) algorithm performs better than the other algorithms. The Decision Tree and AdaBoost (DT) model achieved an F1- score of 0,76 and 0,82. This research contributes towards enhancing education management by facilitating decision making to ensure timely graduation, for student

The company, which is engaged in information technology services and solutions, is facing several issues. The first problem is the absence of Standard Operating Procedures (SOPs) for documenting IT risks. Additionally, there have been instances of system downtime on the local servers, affecting both company and client data. Furthermore, data loss has occurred for employee records, financial data, inventory data, and purchasing data from the on-premises company server. To assess the capability level of the company's IT governance, the COBIT 2019 framework was implemented, focusing on operational and security areas. An approach was undertaken to enhance services and operations within the company. The results of the capability level measurement for process objective APO12 indicated that it has reached level 2, with a target capability level of level 3. On the other hand, process DSS01 successfully achieved level 3, meeting its target capability level, while process DSS02 reached level 2 with a target capability of level 3. This suggests that there is a 1-level gap in the APO12 and DSS02 processes. The recommendation given to the company is to concentrate on risk management, finding a balance between the costs and benefits of managing IT-related risks. Moreover, it is advised to minimize disruptions by resolving user incidents promptly.

Indomaret Semuli Raya is a company that competes in the industrial world. In the industrial world, the quality of products marketed is an important indicator for Indomaret Semuli Raya to be able to stand during intense competition from other companies. Product quality is certainly the thing that attracts consumers. In dealing with problems that occur in the company, it must make the right decision in determining the product strategy to be sold, to get the right decision, sufficient item data is needed to be analyzed. This research raises the issue of whether or not goods are worth selling in the category of damaged goods at Indomaret Semuli Raya in the period from February to March 2023. Data mining is used in this study, specifically the C4.5 Algorithm Method. The author chose the C4.5 Algorithm method because it can be used to determine whether or not damaged goods are unfit for sale. Algorithm C4.5 will determine damaged goods based on the attributes that become the standard for the eligibility of goods. The attributes referred to in this study are Overweight, Brackage, Sell by, and Moisture and temperature. The aftereffects of manual computations by means of Microsoft Succeed utilizing the C4.5 Calculation have a precision of 90.00% then demonstrated by the RapidMiner application with an exactness of 90.00%.

Fake news has proliferated on the internet in recent decades. More people than ever before are creating and sharing knowledge because of social networks, many of which have no connection to reality. This has led to the rapid dissemination of false information used for various political and business objectives. Finding reliable news sources has become more difficult due to online newspapers. In this work, we gathered news articles of Hindi text from various news sources. Techniques for pre-processing, feature extraction, classification, and prediction are all extensively covered. A “Fake news detection system” has been developed in this project. Various Hindi news articles have been collected from multiple sources to help diversify the dataset and train the model better. The project first pre-processes the dataset and uses the pre-trained Bert model for feature extraction. Then, the data is classified from the dataset and prediction processes are employed on the dataset. Various machine learning algorithms and deep learning models like Naïve Bayes, Long Short-Term Memory, Logistic Regression have been employed in previous works for the purpose of detecting fake news. Pre-processing steps include data cleaning, stop words removal, tokenizing, stemming. The testing and training of the dataset include using the BERT for sequence classification model. The model is trained and tested against the validation dataset

The paper intends to discuss the status of data mining applications in the normal and critical healthcare system of Bangladesh. The paper also focuses on the data mining strategies and processes in the current healthcare system in Bangladesh. This is a secondary source-based review paper. The methodology chosen for the study is a literature review and document analysis. The literature review was done through the analysis of book chapters, research-based articles, review-based journal articles, organizational reports, and conference papers. The key findings of the study indicate that as Bangladesh is not a developed country and is a developing one, the country’s healthcare system is not up to the required standard, and the application of data mining techniques is very limited and in most cases, it is at the policy level. The implementation and practice of data-mining techniques is available in internationally recognized organizations and institutions. In these circumstances, the country’s healthcare policymakers and administrators should employ experts in data mining in healthcare services and facilities and standard technologies should be included in their administering the data mining in healthcare facilities. Besides, data mining should be incorporated with other related concepts and strategies to make the highest outcomes in health care systems.

The development of video games is very fast according to data obtained by ESA in 2021, about 226 million people on American played video games and in Indonesia 105 million people play video games and this will continue to increase, it is predicted that in 2025 video players gaming in Indonesia will reach 127 million people, this causes the need for game content continues to increase while for making game content it is not something that cheap, one way to reduce costs in making content in the game is to implement procedural content generation, procedural content generation is one way of creating content game automatically by using an algorithm. This research aims to design and build a virtual reality horror game using use cellular automata algorithm, cellular automata algorithm in research This research is used for map making, besides that this research also aims to measure the level of player satisfaction with the game that has been made. Game created using the Unity 3D game engine and the C# programming language. After game has been successfully built, will measure the level of satisfaction through cakes. questionnaire using GUESS-18, based on tests that have been carried out with GUESS-18, the results obtained are 77.1 percent, which can be concluded that the level of player satisfaction is categorized as good.

Investments made by business organizations in the field of Technology and Information are a form of investment that is not measurable when the return on investment will be achieved if it is not accompanied by an appropriate IT investment utilization strategy. PT XYZ Insurance has implemented digital transformation in several of the company's operational activities. The Procurement Division at PT BNI Life Insurance has used the e-procurement system since 2019. The Procurement Division of PT XYZ Life Insurance in implementing the e-procurement system will try to be evaluated using the VAL IT 2.0 method. The implementation of VAL IT is one of the frameworks that can be used to conduct an information technology governance management audit or IT Governance. The VAL IT 2.0 Framework analysis used in this study's conclusion to determine the state of the e-procurement system's implementation as part of operational technology management at the company PT XYZ Life Insurance yielded results showing that the highest average GAP Maturity Level is found in the Portfolio Management domain analysis at 1.11, which is different from the level or value 5 of the expected maturity level. PT XYZ Life Insurance must identify all potential e-procurement programs that could be part of the company's IT investment portfolio and prioritize e-procurement programs based on their alignment with strategic objectives, potential value, and risk considerations.