Reviewerly/exHarmony huggingface dataset:
Performance Comparison of Different Feature Sets for Network Traffic Classification using Recursive Feature Elimination and One-Vs-Rest Random Forest Algorithms

Network traffic classification is an identification process of network applications like Yahoo, YouTube, Facebook, and Skype. Network traffic classification is required by network management to manage resources and to know different applications that can help network operators provide good Quality of Service, secure network, and monitor network. In this paper, we focused on the 7th layer of OSI model and using only TCP data. In recent years, there is much machine learning research to solve this problem either using supervised, unsupervised, or deep learning. Different feature sets are used to find the best performance for network traffic classification using Recursive Feature Elimination feature selections and One-Vs-Rest Random Forest classifiers. Six sets are compared: flow-based, session-based, time-based, packet-based, flow+ session-based, and packet+time-based. Furthermore, we have class imbalance problems in multiclass that make this difficult due to imbalance distribution, presence of outliers, and irrelevant features. Using this method, we can solve these problems. From the experiment, we get flow-based as the best feature set for network traffic classification with f1-score 0.81, GM 0.85, and model build time is 2634.987 s. Actually, we also can use packet-based, flow+session-based, and packet+time-based with a good classifier but need more time to model build.
Front-end Subsystem Design for Vehicle Registration Certificate Application with Image Encryption

Every citizen who owns a motorized vehicle is required to have a Vehicle Registration Certificate. Vehicle Registration Certificate must be extended every certain period and done at the Samsat office. However, the Vehicle Registration Certificate extension process often takes a very long time due to the large number of documents that must be processed and the long queues. Therefore, we need a solution so that the process of renewing the vehicle registration becomes easier and faster, one of which is by providing services on the mobile application. The purpose of this final project is to create an Android application for the extension of the Vehicle Registration Certificate. This application also includes an encryption method to secure various documents uploaded by users during the renewal process. Image encryption is implemented using the Henon and Arnold Map algorithms and document transmission is carried out through a secure communication channel to prevent data theft. Android application and decryption encryption algorithm are created using Visual Studio Code and Android Studio. This application has a main menu, namely “Form Filling” which functions to extend the Vehicle Registration Certificate. The user must fill in a bio and upload an image for successful registration. The code for image encryption is created using the Python programming language, but for application implementation the Dart programming language is used because the two programming languages interpret images in different ways. Henon's algorithm has better parameters than Arnold's, so that Henon provides a better security aspect.
The Shortest Path in the Ring Topology Using Genetic Algorithm

The shortest path in the ring topology is discussed in this paper using a genetic algorithm. The measurement parameters in the study are the shortest path and the computational time on the varying number of nodes. The measurement results of the genetic algorithm were compared with the results of the brute force and ant colony algorithms. The measurement of the shortest path using the genetic algorithm has an average difference of 23 when compared to the ant colony, while the brute force algorithm has the same value. The computational time of the genetic algorithm requires an additional time of about 1000–9000 milliseconds for each additional node which is better than the computational time when using the brute force algorithm but not as good as the computational time using the ant colony algorithm.
Development of Android Aplication for Online Training using Blended Learning System (Case Study of LPIKITB)

Blended learning is a learning system that combines offline learning with e-learning, in order to maintain two-way communications between the teacher and their students resulting in a more maximum outcome. LPIK ITB is an institution which focuses on innovation and entrepreneurship development in purpose of building a development culture for the country. One of LPIK ITB program is an incubation program which is an accompaniment program for start-up to develop further. The online training application is used to help said accompaniment program to become more maximized using blended-learning system which supported by direct messaging features that makes two-way communications during learning session possible. The application was examined using the black box testing with a value of 100 which means the application can function properly according to the scenario and testing with the mean opinion score (MOS) method with a test result of 3.87 which means it is included in the Enough group.
Website Usability Evaluation using Human Centered Design (HCD) Approach

As a result of the COVID-19 pandemic that is endemic throughout the world including Indonesia, which forces all activities to be done at home, including teaching and learning activities. This study aims to see the level of usability on an online college website and provide input based on human-centered design. The method used is the Usability testing criteria by Nielsen and the task to respond to the HCD approach, and consider the Quality Requirement tree for the academic websites. The results of the evaluation in this study indicate that the value of usability acceptance by users on the online college website is at 3.52, meaning that the online college website is quite user-friendly. The average value for usability testing, they are 3.4 for learnability, 3.4 for efficiency, and 3.52 for satisfaction, while memorability and error rate both get a value of 3.5.
E-Voting: Security, Threats and Prevention

None in this world, neither software nor hardware that is safe against the threat of attacks and security disturbances, including e-voting technology. There is no chance of tolerance for the slightest security flaws in e-voting technology because it involves public trust, cost and the sustainability of the implementation of e-voting. Several countries such as United States, Netherlands, Germany, United Kingdom and Norway canceled the implementation of general elections using e voting and even did not continue the project due to security factors that degrade public trust. In this paper, E-voting: Security, Threats and Prevention, we propose the results of the mapping of the security aspects needed, and the potential for attacks in each phase of e-voting in general continued with an analysis of their prevention. Hopefully, this paper will contribute to the development of e-voting technology especially in the security factor, and in general, provides an overview of the security needs of e-voting technology.
Vehicle Traffic Volume Counting in CCTV Video with YOLO Algorithm and Road HSV Color Model-based Segmentation System Development

Traffic congestion is a significant problem in developing countries. One viable solution is a Smart Traffic Light System which utilizes artificial intelligence to adapt light configuration to actual traffic condition in real time. To adapt properly, the system would need traffic density information. We propose a vehicle counting system with neural networks to calculate vehicle volume in traffic roads. In the proposed system, a vehicle is detected with YOLO (You Only Look Once), the state-of-the-art of neural network-based object detection algorithm. The model's performance can be improved with the extraction of RoI (Region of Interest), which is traffic roads. RoI extraction is implemented with HSV color model-based segmentation. Vehicle detection is followed by vehicle tracking and counting. Three tracking algorithms are experimented with the system: KCF (Kernelized Correlation Filter), CSRT (Channel and Spatial Reliability Tracking), and MOSSE (Minimum Output Sum of Squared Error). Vehicle counting is implemented in two methods: incremental or actual. A graphical user interface is developed to provide easy access to system configurations. The result reveals that the best system configuration in terms of accuracy while capable of running in real-time for CCTV recordings is YOLOv4 (608x608) with KCF tracker and RoI Extraction.
YOLOv3- Tiny's Weight Size Reduction using Pruning and Quantization

CNN has been widely applied to various technology fields, like real-time edge devices. One of the architecture detection objects based on CNN is YOLO, a real-time detection object with a high level of accuracy. Detection objects on the edge device itself are expected to have speed, accuracy, and less memory needed to carry out the detection process. In this paper, YOLOv3- Tiny will be pruned and quantized to reduce the size of the data from the weight without significant reduction of accuracy. Experimental results show that YOLOv3- Tiny weight data decreased up to 85.7% compared to the weight data before the pruning process, while in the quantization mode. Moreover, the iterative pruning method can reduce the weight up to 43%.
The Effects of Covid-19 on the Sentiments and Relationships of Universities Students

With the emergence of COVID-19 at the end of year 2019, movement restricting policies have been implemented worldwide to curb the spread of this disease. Most controls have been imposed to prohibit the operation of non-essential services, even including the closures of workplaces and schools. University students have been facing an even higher level of uncertainty as remote learning becomes the main medium of transferring knowledge. This research has identified the effects of COVID-19 on the sentiment and relationships of university students. The methods used in analysis will include sentiment analysis, topic modelling, and community detection on data collected from the Reddit social media platform for two universities located in different countries. Based on the obtained analysis results, it is determined that COVID-19 does have an impact on the sentiment and relationships between university students. The change of behaviors has some similarity that includes a higher range of sentiment expressed during the pandemic, and a social network structure of communities with similar sizes between universities. Some difference has also been noticed, where the changes in sentiment is expressed in different topics that is based on local events, and the change of structure for smaller communities during the pandemic. It is concluded that changes in the sentiment and relationships of the student community can be identified through the proposed methods, and therefore can be used as a guideline for local authorities and higher education institutions to take the measures to ensure the problems faced by students can be properly addressed.
The Quality of Analysis Women's Save-Loan Information System By Hybrid Method

This study aims to determine the quality of the women's savings and loan information system that is currently running at the UPK V Koto Kampung Dalam office. The use of the women's savings and loan information system is carried out directly by involving the borrower group by coming directly. The information system was built using a desktop-based programming language. So it has a relatively long waiting time for the community to make savings and loans at the UPK. To avoid this, it is necessary to measure the quality of the information system in order to develop the system. The system analysis process is carried out using the IPA (Important Performance Analysis) method which involves several stages such as service performance and satisfaction levels and PIECES. The analysis process involves 55 respondents, where the measurement results get a percentage of quality with results that are not good, sufficient, good and very good. From the measurement results, it has an impact on women's savings and loans because the community understands and knows the quality of system services based on the information system used. This study was built using descriptive quantitative methods that provide results in the form of information.
Evaluation Methodologies of Recommendation System: An Experimental Approach

Information overload is a common issue faced by internet users due to the huge amount of freely available content. A single search could return millions of results and it is not feasible for a user to go through each of it to find the information relevant to his/her needs. It a tedious and time-consuming task. To address this, recommendation systems have been introduced. It is a tool that provides suggestions to users based on the user&#x2019;s preference of a particular item or predicted using the ratings gathered via feedback from previous users with similar taste. The emergence of various types of recommendation system has raised the question of how these systems can be evaluated in a standardized and effective manner. It is important for researchers to quantitatively compare the performance of new recommender against the existing ones to establish that the proposed solution is indeed an improvement to the current one. There is a need for researchers as well as academics to be able to compare between two different systems and establish which the better one is based on a clearly defined numerical value. Based on this numerical value, researchers will be able to decide whether the new system requires further fine tuning. Repeated evaluation can be made after each fine tuning to determine the margin of improvement that has been made. This article will propose a methodology to perform such an evaluation of recommendation systems regardless of the domain in which the recommendation system has been used.
Systematic Literature Review on Organizational Cyber Security Deficiency in Mitigating Mobile Device Risk

The use of mobile devices by employees to access organizational Information Systems (IS) is common nowadays, and it can be seen from the trend to the formalization of Bring Your Own Device (BYOD) and remote working settings. However, allowing IS resources to be accessed by mobile devices that enable work flexibility across time, location, and network also increased the cybersecurity risk and vulnerabilities towards organizational resources, including network, system, and data. Therefore, this paper presents a systematic literature review on this context to explore the cybersecurity deficiency and mitigating techniques proposed for mobile device risk mitigation in organizational IS. Following the Systematic Literature Review protocol, 31 research articles are selected and reviewed using Thematic Analysis. Three themes were set to classify the output presented by the selected articles according to the context of Security Control, Cybersecurity Pillars, and Information System Management (ISM). This thematic analysis has successfully integrated various terms and narratives. Through analysis, nine security controls have been identified, with the most frequent concern being on Cybersecurity systems and Mobile Device profiling. The authors also discovered that deficiency in the Process factor is mostly discussed compared to the People and Technology factor, which also called for improvement in the ISM Planning phase. This study is beneficial in understanding the organizational cybersecurity deficiency in mitigating the risk of mobile devices and providing a reference for the significant security control in the context of the discussed environment.
Control System and Letter Disposition Management Using the Chronological Filing System Method Mobile Web Based

The development of information technology demands to always follow its development, as well as agencies will carry out administrative modernization such as mail filing information systems. The implementation of the letter filing and disposition system at Putra Indonesia University aims to make the implementation of mail data processing and archiving run more effectively and efficiently where previously it was done using a ledger and in the disposition of letters it took a long time to handle and make decisions on letters. This improvement in computing services is important to meet the needs of all parties involved in accessing up to date correspondence information. The Mail Filing Information System is designed using one of the mail archiving management methods, namely the Chronological Filling System. Chronological Filling System is an archive storage system that is organized by time such as year, month and date of the letter. Thus, management of disposition and filing of letters can be arranged and recorded in a complete and secure manner and it is easy to view the history of existing letters.
Thyroid Cancer Classification using Transfer Learning

The growth of artificial intelligence has been successfully reached remarkable findings in all fields including of medical cases. The powerful performance of artificial intelligence successfully became a second opinion to assist the medical personnel in making diagnosis decision. In the thyroid cancer cases, the growth of artificial intelligence offered valuable benefit since thyroid examination procedures highly depended on the medical personnel skills and experiences. One of the popular findings was that the implementation of transfer learning to find the best network for the targeted problem. In this study, we conducted experiment to develop a classification method for classifying thyroid cancer using transfer learning method. Our experiment was performed in the thyroid public dataset consisting of 348 thyroid ultrasound images divided into two classes (benign and malignant). In this study, we performed DenseNet121 and NasNetLarge as the best networks according to previous similar studies. According to our experiment, NasNetLarge obtained better accuracy than DenseNet121 by 8% of improvement. This result indicated that NasNetLarge was a powerful CNN for classifying the thyroid cancer.
Combination of C 4.5 Algorithm and Profile Matching for Determining University Students Graduation

Development in the field of education requires universities to keep improving their standard and quality. A university's quality is reflected by, among others, its graduated students as a quality university has their students graduated on time. The development of technology, especially the decision support system, can help the university to determine the root of factors affecting its students' graduation. New insights could be obtained from the existing data on graduated students, which is useful for the university to understand the factors affecting students' graduation Implementation of the C 4.5 algorithm to obtain decision tree and rules, as well as the use of profile matching could be useful for sorting students' rank from the highest score to determine the students' graduation. In the Faculty of Computer Engineering and Science Universitas Dharmawangsa, root of students&#x2019; graduation was the students' thesis writing duration.
Increasing Competitive and Marketing Technology Skills for Small Medium Micro Business in Padang City with Customer Relationship Management (CRM) Concept

Padang is one of the big cities in Indonesia which has various kinds of economic potential that can be developed. One of these potentials is Micro, Small, and Medium Enterprises. Micro, Small, and Medium Enterprises in Padang City have an important contribution to supporting the economy. The main driver of the economy in Padang or Indonesia so far is the Micro, Small, and Medium Enterprises sector. This happened in line with developments in the tourism sector, where Padang became the main destination for people when traveling to West Sumatra. The increase in tourist destinations in Padang City has a direct impact on economic growth itself so that Micro, Small, and Medium Enterprises have sprung up, be it fashion, culinary, or art. More and more Micro, Small, and Medium Enterprises of course also provide business competition where Micro, Small, and Medium Enterprises must be able to market their products so that they are in great demand. For Micro, Small, and Medium Enterprises, of course, it takes extra time and energy to market their products to be able to compete in the market. This is the basis for building technology to increase competitiveness and digital skills in marketing MSMEs in the city of Padang with the concept of maintaining consumer relations with MSME actors. So that the growth in the number of Micro, Small, and Medium Enterprises not only increases but also lasts a long time or can compete by applying the customer relation management method by determining the products to be marketed using the C4.5 algorithm calculation. based on research that has been done several factors play a role in increasing digital marketing ranging from location, product prices, social media promotions, e-commerce marketing, product quality, product types, and popularity.
Development and Validity of the Responsive Web for Assessing English Speaking and Listening

We have designed and created a responsive web for English speaking and listening assessment where the students can practice online and the lecturers have access to assess the students' work. This website was designed and developed to content the students' and lecturers' needs especially during the online learning engagement based on the previous research held in the Computer Science faculty of UPI YPTK Padang. The website was designed using Visual Studio Code for making the website, MySql for saving (database), PHP, SQL, Laravel, and Javascript are used for the programming language. The website was featured with the login page for both lecturer and students, a menu page that consists of listening practice, listening quizzes, speaking practice, speaking recording, and an uploading video button. Based on the questionnaire given to the expert and English lecturers, the validity percentage value of the responsive web got 95% validity for content eligibility, language components, presentation component, and graphical component. Thus, the responsive web can be used as a valid media for speaking and listening assessment media with few revisions.
Systematic Literature Review Knowledge Reuse in Software Development

Knowledge reuse is important to increase efficiency and effectiveness to minimize possible risks, useless activities, and poor project performance in the software development process. Thus, this study aims to find barriers and impacts of knowledge reuse and how to build knowledge reuse mechanisms in software development using a systematic literature review. The systematic literature review involves several stages from defining research questions, determining the database and keyword, searching process, selection based on title and abstract, selection based on research content, and quality assessment. Based on the systematic literature review stages carried out, several results were found to answer research problems. The result shows that the barriers are lack of documentation, knowledge bias, people factor, and high complexity. The research also found that knowledge integration, ease of decision-making process, and knowledge standardization were the impact of using knowledge reuse. For knowledge reuse mechanisms it recommends categorizing data or knowledge, use versioning mechanisms, agile approach, tools utilization, the importance of maturity level and effective communication, and importance of knowledge capture. Knowledge reuse shows a lot of impacts, but it is a complex process, therefore performing certain mechanisms can aid the knowledge reuse process. Furthermore, future research can observe other software development methodologies and compare each methodology for knowledge reuse processes.