Reviewerly/exHarmony huggingface dataset:
Sentiment Analysis of The Tourist Destination Using Support Vector Machine Algorithm on Twitter Post

Sentiment analysis is an effective approach in identifying and analyzing user perceptions of digital applications such as social media to optimize the marketing of products and services in accordance with market demand. Social media nowadays has an enormous effect on decision-making. Social media allows users to be able to find out the reactions of other users to the information that is being hotly discussed. The problem is the large amount of data related to people's preferences for tourist attractions, especially on social media, so to process it manually requires time, energy, and even a lot of money. The algorithm used is the Support Vector Machine while the feature selection we use is Particle Swarm Optimization with Discrete Binary Particle. While particle swarms are patterned with optimizers so they are not able to stand alone, it must be followed by other algorithms that must carry out the learning process first. The accuracy value obtained as a benchmark in finding the best test example for sentiment classification problems. The outcome showed some improvement in the accuracy of 0.09006 from 0.87267 to 0.96273 after the implementation of the Particle Swarm Optimization. The conclusion showed that feature selection Particle Swarm Optimization was able to increase accuracy.
Twitter Sentiment Analysis with Maximum Entropy and Naive Bayes Using N -gram Approach

Finding out what people think and feel has always been common regarding social and political opinions, products, and services experiences. Due to the sheer amount of information on the internet, different machine learning algorithms are implemented to classify information better. The Maximum Entropy and Nave Bayes employing the n-grams approach will be assessed in this research study along with their accuracy, recall, f-1 score, precision, and time complexity. Instead of the customary product and service review, this study will investigate the opinions of Twitter users regarding the Death Penalty. In comparison to prior literature, the experiment's findings show improved accuracy. The findings reveal that Maximum Entropy with n-grams performs better when compared to Naïve Bayes with n-grams, with an average accuracy result of 92.67% in classifying the death penalty data. However, the Naïve Bayes using n-grams outperform Maximum Entropy regarding time complexity with an average of 69.83 milliseconds on an average input length of 97.98 Kb. The trade-off is when the basis is accuracy, the Maximum Entropy with n-grams is recommended. But regarding time complexity, the Naïve Bayes using n-gram is favored for smaller input length.
Software Metrics for Container-Based Applications: Systematic Literature Review

Containerization has become a popular approach in application development in applications development and deployment, many benefits we can get such as improved scalability, portability, and resource efficiency. Container-based applications, utilizing technologies like Docker and Kubernetes, have transformed the packaging, deployment, and management of software from the desktop environment to the cloud platform. In this context, software metrics approach plays a good role in evaluating the characteristics and performance of container-based applications, ensuring that developers and operators are on the same page. This article explores the importance of software metrics in optimizing the software lifecycle of container-based applications, addressing the unique challenges they present, and highlighting the potential benefits of leveraging metrics to improve performance and efficiency. Our finding Performance Metrics and Availability Metrics is the most metrics that the most measure by applications owner, relevant studies and industry practices, this study aims to provide insights and recommendations to effectively measure and optimize region-based software systems.
Implementation of Extreme Programming in Web Profile Development as an Effective Promotional Media

PT INOVASI AKSELERASI KREASINDO (IAK) is a service company that provides digital solutions, especially in designing and building websites. At this time, Client PT. IAK has a target to be able to become a Wedding Organizer (WO) that can reach all regions in Indonesia by embracing many vendors who are also spread out. With the current system conditions, it will be difficult for Client PT. IAK to realize that goal, because it still uses a conventional system so that the introduction of WO products is not efficient in terms of information dissemination in many regions, costs for promotion and time. The purpose of making a company profile website PT IAK so that potential customers and the wider community can find out information about the services and services provided by the company. The application design and development method use Extreme Programming (XP), which consists of the stages: Planning, Design, Coding, Testing, and Software Additions. This approach enables the realization of client satisfaction goals while accelerating the pace of the system's development process. As well as using Laravel as a Framework and black box testing that focuses on the functionality side, and testing is based on the user's point of view to find inconsistencies in the software. Based on the research results in the form of a web profile application (maritory-web), the author draws the conclusion that the design of web applications at this company can have an impact on the dissemination of information to potential customers so that the promotion process becomes easier and more effective.
Orthogonal Persistence a Breakthrough for Scaling and Seveloping an Application in Blockchain Scenario

Blockchain technology has changed our perception of decentralized, secure data storage and administration. However, the scalability and development issues that blockchain-based applications confront remain substantial barriers to the broad use of blockchain technology. A novel concept called orthogonal persistence has emerged as a feasible alternative for improving the scalability and development of blockchain-based apps. This research looks towards orthogonal persistence as a possible breakthrough for scaling and growing blockchain systems. Data persistence in a blockchain environment is simplified by orthogonal persistence, making it easier for developers to maintain and grow the system. Orthogonal persistence has the potential to improve blockchain application efficiency and scalability while lowering design and maintenance costs. The study concludes that orthogonal persistence is a realistic technique for developing blockchain applications that may support innovation and success in this rapidly evolving technology industry.
Bibliometric Analysis of Trend in Metaverse Research

Metaverse is currently going to be a popular topic. This study aims to investigate the research trends in metaverse topics to provide a new point of view for future research direction. This study performed a bibliometric analysis systematic literature review by reviewing the specific term in the Scopus database. The data were obtained from publish or perish app and analyzed using the VOSviewer Software. This research article was limited from 2018 - 2022, and 119 were analyzed using the VOSViewer Software. The result shows that the metaverse topic is increasing very fast in 2022. The most popular term in the title and abstract combination are Experience, Study, Application, and Education, which indicates the opportunity for future research, trend, and topic that the public and researchers are interested in. Meanwhile, the keyword of a metaverse in education is still limited, which opens new opportunities to be discussed in the future.
Design and Development of Personalized Pregnancy Health Assistant Application

According to the Indonesian Ministry of Health, the number of maternal deaths increased from 4,221 deaths in 2019 to 4,627 in 2020. One of the factors supporting the high maternal mortality rate in Indonesia is due to the low level of knowledge of pregnant women about health conditions and solutions to health problems during pregnancy. Therefore, the main purpose of this paper is to propose a design of mobile and wearable applications that can help to reduce these problems. Using the iterative design thinking methodology, the output of this paper is a a personalized pregnancy health assistant application design that utilizes artificial intelligence and IoT technology.
The Evaluation of Trust Towards The Intention to Use of Blockchain-Based Crowdwork Systems (Case Study of Creative Industry)

Current crowdwork research still has issues related to trust. Workers and employers do not know each other, so problems related to trust will arise. This trust issue will influence the desire to use the crowdwork system. This study will evaluate trust in the intention to use blockchain-based crowdwork systems in creative industries. The methodology used is a quantitative approach (questionnaire) which is distributed to 200 respondents consisting of workers and employers. After that, testing the inner and outer models was carried out. The results obtained are technology, risk, and reputation which have the greatest impact on trust. The use of blockchain technology can minimize risks when using a crowdwork system, such as data that cannot be changed, data tracing can be done, and so on. The rating and review features are also important to be able to find out the user's reputation in the system.
Analysis and Design of Android-Based Mobile Tire Change Applications

This study aims to design an application for inputting digital tire change processes by storing tire change history and providing digital document reports according to company standard formats. Based on the current tire replacement process, one of the coal mining contractor companies has not been able to collect data optimally which hinders tire damage analysis and preparation of preventive strategies. For starters, the design of this application is focused on the big size off-the-road tire (OTR) replacement process. The research method begins with collecting data through literature studies, comparing it with similar applications, observing and interviewing informants in order to obtain the required information. The system design uses the Unified Modeling Language (UML). The application is designed by considering the eight golden rules, testing every function of the application, and evaluating the usability of the user experience using the Nielsen's model method. The test results for each function illustrate that the application successfully fulfills every task tested, meets the requirements for a productive, interactive and easy-to-understand application by users according to the eight golden rules. It can be concluded that the application can be an option for recording tire changes, storing and displaying tire replacement history, and providing reports in the form of digital documents according to company standards.
Analysis of the Use of E-Stickers in Chat Conversations for Higher Education Students

Online messaging applications are seeing an increase in popularity of e-stickers with vibrant and interesting sentiments, especially among students. These e-stickers were developed to allow people to communicate their feelings more obviously in online chat conversations. To find out why individuals nowadays want to utilize e-stickers in communication, research was done. It is necessary to respond to the following study question: “What variables drive individuals to use e-stickers in chat conversations?” The solution to this question might come from a few different hypotheses. By employing a survey to gather data from college students, this study assesses their sticker-using experiences. To collect information from our target participants, we use Google Forms. The association between each aspect that affects people's inclination to utilize e-stickers is also explained using a study model. We organized the data we gathered into tables to make it easier to read. Tables were made to show the results of Google Forms, composite reliability, average variance extracted (AVE), significance of the indicators, and SmartPLS application results. The conclusions we reached were based on the findings from the results and discussion, as well as their correlation with our hypotheses and what we had learned before conducting this research.
Evaluation of Indorelawan.org Website in User Experience Perspective using User Experience Questionnaire (UEQ)

A lot of organizations now provide online services to assist their customers in the digital age. This includes websites that facilitate volunteering, such as Indorelawan.org. Nevertheless, despite the huge number of online platforms, it is not always simple and comfortable for people to use them. Users may experience issues with unclear information and unattractive website design. This user dissatisfaction tends to be caused by a user experience that is unsuitable for usage on the website. This paper aims to enhance the user experience (UX) on the Indorelawan website with the purpose of attracting and obtaining a larger number of volunteers in indonesia. In this research we will identify problems and barriers experienced by users when using the website, as well as to devise strategies and necessary improvements to enhance the UX. This study used the instrument User Experience Questionnaire (UEQ) survey for evaluate the website Indorelawan.org's user experience (UX). UEQ is a mechanism used to determine and evaluate whether Indorelawan.org meets user expectations in terms of UX. Using UEQ responses from users of Indorelawan.org, it was determined that the platform fulfilled users' needs and expectations in every category. The analysis result is classified into 5 categories, with Indorelawan.org placing highest in the attractiveness category. But the novelty category on the indorelawan.org website is lacking and needs to be improved. Overall, indorelawan.org website has a good User Experience and it can help user feel at ease when utilizing the website.
Utilization of Wokwi Simulation Application in Supporting Internet of Things Learning (IoT)

This research examined the development of Internet of Things (IoT) learning materials using the Wokwi simulation application as a solution for students who have difficulty purchasing hardware for practicum. IoT allows objects to send data over the internet without the assistance of humans or computers. The survey results on 27 respondents revealed that students responded positively to the Wokwi application, with a total index of 83.2% and a very agree interval score. In the practical part of the POSI (Portable Operating System Interface) class, the Wokwi application can assist students in learning IoT well.
Performance and Security Comparison of Json Web Tokens (JWT) and Platform Agnostic Security Tokens (PASETO) on RESTful APIs

This research aims to compare the performance and security between Json Web Token (JWT) and Platform Agnostic Security Tokens (PASETO) on RESTful API. Performance is measured through the parameters of token generation time, token size, and token transfer time, while security is measured through the top three API OWASP 2019 vulnerabilities and testing CSRE attacks on tokens. The results from 50 samples show that the average token generation time of JWT is 0.5068 ms and PASETO is 2.4044 ms. The average transfer time of JWT tokens is 95.4604 ms and PASETO 190.4344 ms. The T-test results confirm the significant difference between token generation time and token transfer time in JWT and PASETO. In addition, the number of PASETO tokens generated is also greater at 320 tokens compared to JWT at 186 tokens. In security testing, JWT tokens are proven safe from OWASP 2019 API attacks, such as Broken Object Level Authorization and Excessive Data Exposure, but are not safe from Broken User Authentication attacks. PASETO tokens were shown to be safe from all three attacks. However, neither JWT nor PASETO tokens are safe from CSRE Cookie attacks. The result can be concluded that PASETO has a longer token generation time and transfer time compared to JWT. However, PASETO shows a higher level of security compared to JWT, as it can protect against the top three attacks of the OWASP 2019 API.
Mobile Forensic Imaging Prototype with Data Integrity

Although it is a useful tool in criminal investigations, digital evidence is easily altered. This might result in misinterpretation, deletions, or privacy violations. To protect digital evidence, it is important to ensure its integrity, authentication, and non-repudiation. This can be done using hash functions, digital signatures, and traceability functions. However, in Indonesia, the storage of digital evidence integrity data relies on handwriting, which is vulnerable to tampering. A prototype of mobile forensic imaging tools that can help protect the reliability of digital evidence is shown in this study. The prototype uses a more secure SHA-256 hash function, an ED25519 digital signature, and a traceability function. An RFID tag automatically stores and secures the digital evidence’s integrity data. The prototype also offers entity authentication to prevent hash value forgery. The Raspberry Pi single-board computer is the platform for the prototype. These procedures are carried out automatically by the system, which promotes accuracy and consistency.
A Modified Zero-Knowledge Scheme from Bilinear Pairing for Securing Multiple Secret Values

Zero-knowledge proof is a tool in cryptography that ensures the privacy of the users. In general, zero-knowledge (ZK) proves that a user (called the prover) knows one secret value to another (called the verifier) without revealing the secret value itself. This proof is used, for instance, in password verification or authentication process. The concept of ZK has been implemented in various fileds, including secure multi-party computation and blockchain technology. ZK proof could use pairing as the interactive function, through which the prover and verifier play their roles. ZK proof usually protects one secret, meaning the prover only certifies their knowledge of one single secret value. In this paper, we proposed a zero-knowledge scheme using a bilinear map which could help a user prove their knowledge related to multiple secret values to others. We also show that this scheme satisfies completeness and soundness properties, implying the proposed scheme is a proof of knowledge.
Communication Efficient on Symmetric and Asymmetric Encrypted Anonymous Federated Learning

The rise of privacy concerns and the emergence of privacy and data protection laws push companies to reassess their practices if utilizing traditional machine learning. The collection and processing of users’ private data on the central server may violate the regulation if not appropriately handled. Federated learning comes as a solution where there is no need to upload users’ data to the server. Still, it enables robust learning by collaboratively training on each client’s devices and aggregating the model gradient updates. Federated learning enhanced with proxy as a bridge and encrypted model parameters will boost anonymity, privacy, and data protection guarantee against malicious attacks such as the membership inference attack. However, encrypted data costs more to the clients’ communication and data size by more than twice the initial size. Our paper tries to address these concerns. Throughout our experiments, we found that it is possible to achieve the same level of communication cost as if it was not encrypted. Aside from the experiment analysis on this subject, we also recommend a safe and secure way to implement communication efficiently in an anonymous encrypted federated learning setup as our contribution.
Secure Self Payment and Monitoring Service Laundry using RFID with SHA-3 and AES 128

Automation converts work processes, procedures, or equipment into automated rather than human-controlled operations. Automation of payment methods is now known as emoney. Researchers use e-money to carry out independent services and monitor services at the laundry. The use of e-money in this laundry has threats from card cloning and hacking in the storage process of the database. This research offers a solution for self-service payments for safe laundry services by applying the SHA-3 and AES 128 algorithms. This study implements the top-up system to fill in balances and the client system to reduce balances and activate the washing machine. This study uses the waterfall-based SDLC methodology with two test results. First, user security in transactions is evidenced by limited access to authorized card users with authentication on numbers other than UID to avoid the threat of cloning on UID numbers. The second test proves that the data is stored securely in the database so unauthorized parties cannot read it.
Text-based File Security with Signcryption Using AA<sub>β</sub> and DSA Algorithms

The swift development of the current digital era is directly proportional to the emergence of several security issues in digital data transmission, especially in data confidentiality and authentication. The modernisation of this way of communication method must be given more attention to the security system because of its increasing popularity. In this case, users can overcome it by using various encryption method approaches, one of many ways that can be done is signcryption. Signcryption is a scheme that combines encryption and digital signatures. Where the encryption process provides confidentiality while the signature offers authenticity. Signcryption itself is utilized in providing solutions to the security problems mentioned earlier by combining a relatively new public key algorithm called $AA_{\beta}$ with DSA, which is the standard in digital signatures, in the hope that this combination of algorithms could provide integrity, confidentiality, and authentication. The final result of this research is that signcryption with $AA_{\beta}$ and DSA algorithms has been successfully carried out by producing an execution time of 1.189 seconds on the signcryption process of the smallest file size of 1 KB and resistant to brute force attacks.
Comparison of Meet-in-the-middle Attacks on 2-DES and 2-AES with Four Scenarios

The Data Encryption Standard (DES) is a symmetric key encryption algorithm developed in the early 1970s by IBM. The 2-DES algorithm is a DES algorithm that is encrypted two times. However, the 2-DES algorithm is theoretically vulnerable to meet-in-the-middle attacks. In this research, a Meet-in-the-middle attack is carried out on the 2-DES algorithm with the sample of 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">20</sup> and ensures the key used is in that range. Apart from 2-DES, an attack was also carried out on 2-AES as a comparison. The attack is conducted on both algorithms using four encryption modes: ECB, CBC, CFB, and OFB. The attacks were carried out in four scenarios that are encryption-encryption, encryption-decryption, decryption-encryption, and decryption-decryption. The attack results show that the MITM attack are successfully recovered the secret keys used on both algorithms for all modes and all scenarios. The consuming time of the attacks observed on both algorithms do not show that the scenario affects the consuming time on each algorithm. On the other hand, the encryption mode OFB and CFB need longer time than other modes on DES, but has no effect on AES for all scenarios.