Since 2019 Indonesia has had rapid development, especially in the digital industry, recorded at the 2020 World Economic Forum. Indonesia has 2,193 startup companies engaged in the digital field. It can also affect the ability of these companies to address existing or future digital problems. As is known, down or system failure in a server can cause losses in the company's economy. For a company the size of Facebook alone, it could suffer a loss of 99.75 million US Dollars. One of the causes of server failure is Overload Traffic and Request Cloud Environment caused by the large number of requests submitted to the server. Requests submitted to the server are recorded into 2 data, namely, CCU (Count Current User) and Traffic. In this study, the author uses the CDN and Private zone methods on Alibaba Cloud to share the server load so that there is no downtime or server failure caused by Overload Traffic and Request Cloud. It is hoped that this research can be helpful to networking engineers in overcoming Traffic Overload and Request Cloud, especially on Alibaba Cloud.

The use of technology and reliance on the internet has altered students' learning practices, especially how they approach mathematics. As a result, a novel method of teaching mathematics is required, particularly for geometric concepts that are challenging for children to grasp. For students to better comprehend geometric forms and volume formulas, this study intends to develop spatial learning applications incorporating augmented reality (AR). The method employed in this study is called the Multimedia Development Live Cycle (MDLC), and it includes the steps of ideation, design, material collecting, assembly, testing, and distribution. The results showed that this application succeeded in increasing students' understanding in the form of geometric shapes through the use of spatial learning applications with augmented reality. This was effective in increasing students' understanding of using 3D objects and interactions through applications made students more interested and motivated to learn mathematics.

Globalization makes all developments so fast, one of the factors that makes developments develop rapidly is technology. Technology was created to facilitate the work of everyone who needs it, one of them in large and small businesses. In the case of Ono Celluler Stores where they carry out several business activities using manual methods, these activities include recording sales, stock management, and employee management. Some of the activities currently implemented by Ono Celluler make doing business too long and ineffective. Apart from several problems that occur, Ono Celluler has a weakness in the introduction of Ono Celluler itself. This will affect what Ono Celluler is. The purpose of this research is to make an application that is able to solve problems that occur in Ono Celluler, this application will have a searching algorithm to make it easier for application users to find what products are available on Ono Celluler and features to help users. The Ono Celluler application will also have an information system to manage and monitor the products available at the Ono Celluler Store, besides that there will be a send mail feature to send formal emails from Ono Celluler. Research conducted using the waterfall method concluded that Ono Cellular's business processes can be carried out efficiently, difficulties in finding products are resolved properly using the searching algorithm. And employees can carry out business processes that are more organized and more formal using SMTP.

Emotional Text Detection is a technique in natural language processing that aims to identify the emotions contained in conversations or text messages. The LSTM (Long Short-Term Memory) method is one of the techniques used in natural language processing to model and predict sequential data. In this study, we propose the use of the LSTM method for emotion detection in conversation. The dataset used is a conversational dataset that contains positive, negative, and neutral emotions. We process datasets using data pre-processing techniques such as tokenization, data cleansing and one-hot encoding. Then, we train the LSTM model on the processed dataset and obtain evaluation results using accuracy metrics. The experimental results show that the LSTM model can be used to detect emotions in conversation with a good degree of accuracy. In addition, we also conducted an analysis on the prediction results of the model and showed that the LSTM model can correctly identify emotions. In conclusion, the LSTM method can be used to detect emotions in conversation with a good degree of accuracy. This method can be used to improve user experience in chat applications and increase the effectiveness of human and machine interactions.

The signature is a fully reliable proof of identity to explain the authenticity of a document, which becomes a serious problem that the acceptance of a signature as evidence of a person's recognition, in this case, is not accompanied by its identification, this causes great danger to the possibility of forgery and various other crimes related to signatures. The lack of experts and the lack of application of knowledge about this, and the development of crimes in this field, it is necessary to overcome using investigations based on science and technology as a tool for the prevention and prosecution of crimes, especially in the field of signature examination. The design of the expert system in this study is designed to assist signature examiners in anticipating the increasing crime of signature forgery, with restrictions on the dimensions and direction of the signature.

Cooperatives have developed from time to time, in providing services, credit cooperatives certainly have certain requirements as prospective customers to receive loans. Cooperatives need to check whether interested parties will receive loans. Loans to customers are the main source of income for cooperatives. In data mining, there are several classification algorithms that can be used for credit analysis, including the Random Forest and the C4.5 Algorithm. Data on prospective customers received from cooperatives as a condition for applying for credit is processed using Random Forest data mining and C4.5 Algorithm to support credit analysis in order to obtain accurate information on whether the prospect who applies for credit is feasible or not, this study was conducted to classify loans to prospective customers. cooperative customers using the Random Forest method and the C4.5 Algorithm which is optimized by Random Oversampling because the dataset is in an unbalanced condition. In testing the C4.5 Algorithm which is optimized with Random Oversampling, it gets an accuracy of 78.03%, where the accuracy increases by 7.89% from the previous 70.14%. Meanwhile, Random Forest with Random Oversampling has an accuracy value of 87.12%, an increase of 23.69% from the previous Random Forest test of 63.43

Software Defined WAN or better known as SDWAN has now become a technology that is hype and has a lot of interest, in addition to simplifying SDWAN operations, it can also reduce operational costs, especially links. Researchers will make it within the scope of the PoC Lab (Proof of Concept) so that later the results from this PoC can show the expected results, namely being able to improve the security of connections between branches and the results achieved by devices between branches whose connections are successful using SD-WAN with traffic and data that already encrypted with IPSEC and also other features by the Cisco SDWAN

The progress of an agency or company can be seen from how to use computer technology as a tool in solving problems. This is very supportive in the operation of an agency or company, both small, medium and large companies in increasingly fierce business competition. In this case the application in question is the Cashier Application System at the Indonesian Employee Cooperative, RSCM Central Jakarta, which is located at Jln. Diponegoro no. 71 Central Jakarta. This cashier and report application was built based on needs analysis from KPRI RSCM. This application was built using the JAVA programming language (Desktop) using Netbeans as its IDE, and using the MySql database. The methodology used by the researcher is the Agile software development method. The data collection methods used in this study were closed interviews, observation, and review of decisions from stakeholders so that the data obtained were able to accommodate the needs and initiation of the application to be built. This application is tested using blackbox as a test of application functionality.

Many of courses that have been taken makes it difficult for students to determine one area to focus on in determining the theme of the final project. The case study of this research is the Informatics Study Program at the Adisutjipto Aerospace Technology Institute, Yogyakarta. For this reason, a chatbot with a decision support system was made using the simple additive weighting (SAW) method which adds up the weights of the performance of each object that is different and has the same opportunity on all the criteria it has. This method requires the process of normalizing the decision matrix (X) to a scale that can be compared with all existing alternative ratings. The number of observation scores is the sum of the scores of each observation statement multiplied by the weight of the score according to the Likert scale. The maximum score is the maximum score on the Likert scale multiplied by the number of questions, so 5 x 9 = 45. The expected score is the maximum score multiplied by the number of respondents, so 45 x 30 = 1,200. Based on the feasibility test of the chatbot system for the final project recommendation using this method, it succeeded in calculating the feasibility of an application of 1074 (89.5%) with the formula for calculating the percentage of eligibility which was tested by 30 students of the 2017 class of Informatic Study Program, Adisutjipto Aerospace Technology Institute.

Information security is an important thing that must be considered for every individual and agency, because if information can accessed by unauthorized people then accuracy of the information can be doubted, becoming misleading information and even various problems will be found. Such problems can be malware attacks, exploits, or database injections. In this study, the mechanism of risk assessment methods was carried out on the website information system of greenschool high school. As the name implies XSS or stands for Cross Site Scripting is one form of interference in the form of Code Injection Attack or code injection attack. Where attackers or outsiders insert malicious code that is usually in the form of Javascript. This’s because the main purpose of using XSS is to retrieve important data and send a program that can damage the user but as if the cause is from the web itself. Web security solutions from hacker interference or attacks can be done by means of self-test, namely testing conducted on the web legally with activities such as hackers. Therefore, an analysis of the vulnerability of system that refers to the standardization of open web application security project (OWASP) security with combination of several security tools.