Reviewerly/exHarmony huggingface dataset:
A Static IDE Plugin to Detect Security Hotspot for Laravel Framework Based Web Application

Automatic detection of potential vulnerabilities is critical to promoting application security awareness. It should be performed at the earliest stages of the software development life cycle, the goal being to minimize risk, regardless of the progress of various vulnerability detection techniques in program code, both static and with deep learning, website application developers need to be assisted with notifications in real time, not waiting for the entire project to be completed directly from the IDE they use to stay focused. A common problem with vulnerability detection tools is annoying false-positive results and a lack of anticipation of new or unknown vulnerabilities. Therefore, in this work, we choose an approach to identify patterns and spots where there are potential vulnerabilities, termed security hotspots, so as not to detect vulnerabilities directly. We propose a rule-based plugin integrated into the IDE, which can detect eight security hotspots in the PHP web application program code based on the Laravel framework. We have implemented a proof-of-concept extension/plugin in the popular VSCode code editor (for this initial stage, only running on Windows OS), which is developed from PHP_CodeSniffer. Experiments on 10 Laravel-based projects presented an accuracy of 98.6% and an F1 score of 87.36%. When running, the extension takes 1 ms for the shortest number of tokens, 66 tokens, and 382 ms for the most extended tokens (4,051 tokens). The result shows that this plugin can help in code analysis on Laravel-based projects. Our approach can also effectively complement existing software security best practices.
Expert System Development Guidance in Essence Standard

An expert system is a computer system that can imitate the ability of an expert to make decisions and provide solutions and suggestions for a particular problem domain. This research shows the process of building detailed guidance for developing an expert system, particularly a rule-based expert system, to assist people who want to start developing one. Rule-based expert system uses rule to represent knowledge in its knowledge basis. Exploration and selection of expert system development methods were first conducted, followed by method evaluation to identify gaps in each method. The method evaluation generates a list of guidance requirements that are used as a basis for building the initial guidance. Essence was used to build the guidance as a notation to describe terminologies used in software development activity. The constructed guidance was evaluated with a case study by developing an expert system, followed by a qualitative analysis and evidence map analysis. The evidence map analysis tests the relevance of the elements or components defined in the guideline by showing the mapping between the parameters reviewed (guidance elements/components) and the facts that exist (evidence).
Interaction Design for Book Recommendation System to Improve User Satisfaction at EPerpusdikbud

In recent Years, many Indonesian libraries have adopted digital libraries. Interviews were conducted with users of 20 EPerpusdikbud (a digital library offered by the Indonesian Ministry of Education and Culture). The results show that readers are always shown pages from the same book. Users manually browse book categories to find books of interest and sort them according to their criteria. They suggest that the app can have a better search and recommendation system. This research proposed an interactive design to help users find and get relevant books suited to user preferences using a book recommender system. The research question is, “How can designing interactions in recommender systems increase user satisfaction?”. The recommendation interaction prototype built in this study uses recommendation goals based on user preferences, genres, and similar books, and the interaction design goals are search and browsing books. This goal is formed to achieve the research question. According to the usability testing in this research, the average task completion rate is 95%. In addition, the results of the user satisfaction questionnaire showed that participants were satisfied with the recommendation system. Compared to the existing EPerpusdikbud digital library, it was found that most of the participants agreed that it was easier to find books that matched their interests by using the proposed recommender system. This helps users save time and find books more efficiently.
Improving Cultural Objects Portal Application Usability Using User Usability Evaluation

The application of the prototype process model has been adopted and has undergone adjustments. Prototype emphasizes speed in development based on product prototype iterations to answer user needs. Iterations will be carried out based on an evaluation from the user. In this case, it is deemed necessary to have an evaluation method that can be used to confirm the evaluation basis. This study modifies the prototyping process model in 3 parts: simplifying the requirements definition stage, applying the medium fidelity principle to the application interface prototype design, and applying the System Usability Scale technique, performance efficiency, effectiveness, and heuristic at the evaluation step. This is based on the understanding that this evaluation can indirectly determine how well users receive the application. In order to implement the modified process model, this study uses a case study of smartphone application development for the needs of the Alunalun.info sub-project catalog of Indonesian cultural object information. This project is complex because many other independent sub-projects are also interrelated. The definition of functional requirements for the case study is based on questionnaires and interviews. The definitions obtained were translated into prototypes at medium fidelity based on team and user discussions. Based on this design, applications can be developed immediately. Applications are evaluated for feedback from users. The results of implementing the modification of the prototype model process have succeeded in helping a small Alunalun.info project team of 3–4 people produce the Alunalun.info catalog application.
Analysis and The Preliminary Design for Backend Technology of Disaster Management Information System

Disaster management information system are essential for handling emergencies and saving lives through swift responses and coordination. This study aims to analyse and design an efficient backend technology for such apps. Research methods involve literature review, interviews, and observation with stakeholders. Load balancing is found effective for optimizing disaster management, efficiently distributing workloads and ensuring high system availability. The analysis identifies functional and non-functional requirements, examining technologies like API, WebSocket, Caching, and Relational Database. The design section creates a 3-tier architecture with caching for enhanced performance and scalability. Integration with Mobile Cognitive Radio Base Station (MCRBS) ensures emergency communication in affected areas.
Designing an Energy Tracker and Smart Home Solutions Using Design Thinking Methodology

As energy consumption rises, finding ways to reduce energy usage in homes is crucial. This paper presents a case study using design thinking to create a daily energy tracker that helps users reduce energy consumption. We conduct user research, define the problem, brainstorm solutions (mobile app, smart thermostat, smart plug, physical tracker), and test prototypes. A mobile app that tracks energy usage in real-time and offers personalized tips emerges as the most promising solution. We develop and launch the app, partnering with an energy company. This case study showcases the effectiveness of design thinking in creating a user-centered solution for reducing energy consumption.
The Effectiveness of Free Online Learning

Nowadays, the usage of web courses for learning activities is very popular among students. Through online learning, students don't have to go to school to learn. Especially during the COVID-19 pandemic, online learning activities have increased significantly. Therefore, this study aims to determine the factors that influence students to use web courses as learning tools and the effectiveness of online learning. An online questionnaire is used to gather data from respondents of different ages and education levels. Structural equation modeling (SEM) was performed to assess the study hypotheses. The results show that academic achievement (AA) is influenced by web course information adoption (IA) as a learning tool. Information adoption (IA) is influenced by information usefulness (IU). Source credibility (SC) and information quality (IQ) both influence information usefulness (IU), while information language (IL) does not. Information quality (IQ) is influenced by intrinsic, contextual, and accessibility information quality. This study adds to the literature by empirically testing and theorizing the effects of free websites as a learning tool on the academic achievement of Indonesian students who are studying in bilingual surroundings. This research shows that Indonesian High School and University student feel helped with the development and use of free online learning websites or software that is available in Indonesia so they are able to use it to develop their soft skills, even help them reach academic goals.
Device Scheduling and Bandwidth Allocation for Federated Learning over Wireless Networks

Federated Learning (FL) has been widely used to train shared machine learning models while addressing the privacy concerns. When deployed in wireless networks, bandwidth resources limitation is a key issue, thereby necessitating device scheduling and bandwidth allocation. It is challenging to carry out device scheduling due to the large combinatorial search space. Besides, the heterogeneous computing capabilities and uncertain channel states of wireless devices complicate the design of a bandwidth allocation method. In this paper, we propose a joint device scheduling and bandwidth allocation framework for implementing FL in wireless networks. Specifically, deep reinforcement learning (DRL) is employed to conduct device scheduling. To this end, the state space, action space, and reward function of DRL are carefully defined for a typical FL system. Long short-term memory (LSTM) is adopted as the DRL agent to analyze the sequential input data. Given the scheduled devices of each global iteration, the proposed bandwidth allocation method aims to minimize the weighted sum of the time delay and energy consumption. Numerical experiments on both independent and identically distributed (IID) and non-IID datasets demonstrate that the proposed framework enables FL to reach the desired accuracy with low time delay and energy consumption.
An Analysis of Multiple-Object Tracking Using the Global Nearest Neighbor Method: A Case Study of Ground-Controlled Interception (GCI) Radar

GCI Radar plays a vital role in guiding interceptor aircraft to intercept unauthorized aircraft attempting to enter Indonesian airspace without permission. The operation of GCI Radar necessitates the implementation of an efficient multiple object tracking method to accurately determine the location of detected targets. The chosen multiple-object tracking method must exhibit a high level of accuracy and speed to effectively meet the demanding requirements of GCI Radar. The Global Nearest Neighbor (GNN) method has emerged as a prominent approach extensively employed in multiple-object tracking. Renowned for its computational efficiency, the GNN method proves particularly suitable for online tracking applications. The experiments conducted in this study demonstrate that the GNN method, with customized parameters, is capable of tracking high-speed objects within a speed range of 13.3 m/s to 531.9 m/s. It effectively performs track management and handles data with a time interval of 6 seconds. However, the method still created some false alarm and remained sensitive to noise. Overall, the findings of this research indicate that the GNN method is suitable for application as a multiple-object tracking technique in GCI Radar, as it aligns well with the characteristics of GCI Radar data.
Unlocking User Satisfaction: Evaluating Stress Levels of Financial Technology Users in Indonesia Through Sentiment Analysis

In the current era of rapid technological advancements, the financial sector has experienced significant transformations, greatly influencing the daily lives of individuals. Particularly, Financial Technology (Fintech) services have gained substantial popularity among users. In Indonesia, one prominent Fintech service is the peer-to-peer (P2P) lending platform, commonly referred to as Online Loans. This study focuses on analyzing user complaints and responses concerning a widely used P2P lending service provided by XYZ Company. To achieve this, an appropriate method for processing complaint data and user responses, namely Sentiment Analysis, is employed. Sentiment Analysis is a valuable approach for extracting insights on opinions, attitudes, and emotions towards specific objects. Specifically, this analysis aims to measure customer satisfaction by assessing the stress levels associated with the use of the XYZ Company P2P lending fintech service, considering various technostress aspects. The Naïve Bayes algorithm is employed as the methodology for sentiment analysis. The main objective of this research is to provide a comprehensive understanding of user sentiments towards the XYZ Company P2P lending fintech service, considering different dimensions of technostress such as overload, complexity, insecurity, uncertainly.
Unveiling the Power of ChatGPT: Transforming Face Detection with AI and AR

The goal of the current research is to develop a novel face identification system utilizing the Streamlit Python Library, with a particular emphasis on identifying and modifying human faces. The suggested solution makes use of ChatGPT, a powerful advanced communication model, to construct the fundamental program structure and assist in debugging potential coding problems. The method replaces the recognized human faces with other images by using a photo layer, delivering a distinctive and engaging experience. This prototype's main objective is to explore ChatGPT's potential and improve learning while the program is being developed. To identify and calculate the number of human faces in a given image or video stream, the system uses face identification algorithms. A configurable image layer is then used to replace each recognized face.
Development of Biometric Face Recognition System for Digital Learning Authentication

The current security system offers several options such as the use of PIN, Password, and ID Card. However, the available systems do not guarantee the security of the inputted data. This problem can be addressed by leveraging biometric technology and machine learning algorithms. One example of biometric technology that can be used as a data security system is Face Recognition. This system works by detecting and recognizing faces, making it suitable for implementing as a security authentication in schools in Indonesia that use digital learning media in the learning process. The aim of this research is to develop a Biometric Face Recognition System for Digital Learning Authentication that provides a high level of security. The research methodology used is the 4D development model, which consists of four stages: define, design, develop, and disseminate. In summary, this research resulted in the development of a Biometric Face Recognition System for Digital Learning Authentication, which was achieved through face identification based on testing the differences in distance and various facial positions, with an accuracy testing result of 83.33%.
Development of an Intelligent Carbon Emission Monitoring Methodology to Support Carbon Trading with A Design Thinking Approach: A Case Study in PT Paiton Energy

The Ministry of Energy and Mineral Resources of Indonesia announced that carbon trading in the first phase would be implemented in 2023, starting with coal-fired power plants. PT Paiton Energy is one of the coal-fired power plants obliged to participate in the carbon trading mechanism according to government regulations. Currently, PT Paiton Energy utilizes Continuous Emission Monitoring Systems (CEMS) for carbon emission calculations. However, PT Paiton Energy has not yet adopted a decision support system for carbon trading in the implementing carbon trading scheme. Additionally, the power plant has not developed an emission monitoring system that can predict emissions for future periods and provide efforts for carbon emission optimization. Based on these circumstances, this research focuses on developing a methodology using the design thinking approach to develop a carbon emission prediction model, a carbon emission optimization model, and a decision-making system for carbon trading. The design thinking approach is employed to ensure that the developed system aligns with the needs and expectations of stakeholders and to generate innovative and effective solutions for optimizing carbon emissions. The result of this research is the development of a methodology capable of designing a carbon emission monitoring system for carbon emission optimization in support of carbon trading using a design thinking approach. This outcome was achieved through a process aligned with the design thinking method. By employing this method, the research output can focus on user needs through an empathetic approach, enabling immediate implementation by PT Paiton Energy in constructing a monitoring system capable of carbon emission prediction and optimization.
Development of Sundanese Stemmer Based on Morphophonemics

The Stemming Process is used to get the base word by removing the word affixes. The purpose of this study is to improve the algorithm in previous research by incorporating the Stemming Process into a morphophonemic approach for language processing based on rules (Rule Based) which is named AM Sundanese Stemmer (AMS). The AM Sundanese stemmer algorithm will utilize morpheme information to perform stemming on Sundanese words and analyze the phonemes in a word to identify the morphemes therein contained. The experimental process was carried out with 11,885 existing data and a sample of 546 words were taken to be stemmed. The test was carried out by comparing the algorithms of Nazief and Adriani, UG 18 and AMS. The test results showed that the AMS Algorithm was better than the Nazief Andriani Algorithm and the UG18 Algorithm with a high F-1 score of 87.52% and the comparison of the execution time of the AMS Stemmer Algorithm was 0.041403 seconds faster than the Nazief Andriani and UG 18 Algorithms.
Social Media Sentiment Analysis for Local Water Company Customers Using a Support Vector Machine Algorithm

The United Nations under the WMO predicts that more than 5 billion people will experience a water crisis in 2050. PDAM is responsible for managing drinking water, which is one of the government's efforts to prevent a water crisis in Indonesia. However, only 17.96% of all household heads in Indonesia use PDAM. PDAM uses Facebook and Instagram accounts to interact and convey information to its users. In this study an analysis of the sentiments of PDAM users regarding the services provided will be carried out. The information used came from online scraping of PDAM social media accounts. The algorithm used is Support Vector Machine with the words TF-IDF and SMOTE as weighted as imbalanced data handling. After experimenting with the best holdout modelling method, the ratio of 70:30 on balanced data with negative label data has a precision value of 0.95, recall of 0.99 and f1-score of 0.97. Meanwhile, data with a positive label has a precision value of 0.90, a recall of 0.62 and an fl-score of 0.73. The accuracy value is 95% and has an AUC value of 0.927. The results of the analysis show that many PDAM users have complaints related to water services that often fail, payments, leaks, cloudy water, and meter records.
Eye Tracking in Usability Evaluation of User Experience on Enrichment Apps Web for Internship Program at XYZ University

Internship activities are one of the activities of students to prepare themselves to enter the world of work. To support these activities, The university develops web applications where students can report their activities and lectures can supervise them. The XYZ University enrichment apps web is a website for making reports related to activities during the period consisting of daily, monthly, and final reports along with the tasks given by XYZ University while working in the company carried out by internship students. The enrichment apps web has several menu tabs with functions and objectives for internship students and companies. However, the enrichment web still needs to improve regarding user experience for internship students. The author gets information about the problem through social media that reviews the enrichment apps web. This study aims to determine the level of User Experience of Student Interns in accessing the XYZ University enrichment apps web and analyze features for the needs of XYZ University student interns. The research method used is the usability evaluation method, consisting of usability testing, SUS questionnaire, quantitative questionnaire, Eye-Tracking, and Think-Aloud Interview. The sample of this research is 10 internship students who studied at XYZ University with Effectiveness (91%), Efficiency (89.6%), and Satisfaction (53%), then the final result is 78%.
Central Bank Digital Currency (CBDC) Information Technology System Design : A Literature Review

Disruption in information technology is reaching in many industries including banking & financial sectors. Central Bank Digital Currency (CBDC) is another level of disruptions within financial currency comes as an official digital currency backed by the government of a country. This paper mainly focused within CBDC system design from the perspective of information technology (IT) aspect based on its literature review. The study showed that academic references are still lacking in the aspect of CBDC system design and even more from IT perspective. The lack of framework, methodology, or an architecture references of CBDC system design are reflected by the number of variance and trials that has been done for a CBDC around the world while lacking to the performance evaluation and verification method. The result of this study is expected to be an initial reference for the future development and research of CBDC system design with the focus in the information technology perspective.
A Smart Campus Framework in Developing Countries: Systematic Literature Approach

This study aims to conduct a systematic literature analysis of the recent research papers on the framework of smart campuses in developing countries. We were using Publish or Perish v8 software to conduct the systematic literature analysis. We were using specific keywords such as ‘SMART CAMPUS” and ‘DEVELOPING COUNTRIES from the Scopus database. We got 26 papers, ranging from 2015–2023. After several analyses, we were using 16 papers as the basis of this systematic literature review. Through descriptive analysis, we try to respond to these two research questions: 1) The framework of smart campuses in developing countries, and 2) The challenges in utilizing smart campuses in developing countries. The framework of smart campuses that we used consists of 5 indicators: smart society, smart economy, smart environment, smart governance, and smart technology. Based on the analysis, most smart campuses in development focus their activities on smart society and smart governance. While the challenges come from the lack of expertise, lack of facilities, and uncertain economic condition. Several strategies are needed to support the smart campus in developing countries” higher education.