Reviewerly/exHarmony huggingface dataset:
PENGEMBANGAN APLIKASI TEMPAT PENGOLAHAN SAMPAH BERBASIS ANDROID MENGGUNAKAN MODEL EXTREME PROGRAMMING DAN BLACK BOX TESTING

The closure of the TPA, which had been operating since 1990, forced Gunaksa Village to have its own TPST or Local Waste Processing Site (TOSS) as a waste processing site. The Klungkung regency government also requires each village to process household waste independently. This policy obliges Gunaksa Village to have its own (TOSS) as a waste processing site. According to Law No. 18 of 2008 concerning waste management, it is necessary to change the pattern of waste management which is based on reducing and handling waste. The output of this research is in the form of a local waste management application that can help TOSS in Gunaksa Village, Klungkung Regency which is expected to be able to integrate the management of each division and level so that it runs effectively and efficiently. This application is intended as a recording system in the management of waste banks. Research will be conducted using the methodextreme programming. The system will be designed using the Unified Modeling Language (UML). System testing will use the Black Box method. The results of the black box test state that the input and output of the Gunaksa Bank Garbage Application (GUNABANGSA) are appropriate.
SISTEM INFORMASI WARTA DESA (SIWADA) DENGAN MENGGUNAKAN SMS GATEWAY PADA DESA KLAMBIR LIMA KEBUN

The Village News Information System or SIWADA is an information system designed for use in Klambir Lima Kebun Village. SIWADA is used to spread important news and announcements in the village. The system is built based on a website by utilizing SMS Gateway technology. News or announcements from the village are delivered via broadcast messages to all resident numbers registered in the system. Announcements and broadcast news can be in the form of information such as the Covid-19 vaccine schedule, village meeting schedule, information on activities that involve residents and much other information that needs to be conveyed by the village to its residents. In this way, information will reach each villager more quickly. It also increases the truth of the information received by residents. The SIWADA development process is carried out using the Prototype model and UML methods as a design tool.
PERBANDINGAN METODE BALANCED SCORECARD DAN NAÏVE BAYES DALAM PREDIKSI DAN REKOMENDASI PADA PENILAIAN KINERJA GURU (STUDI KASUS : SMK YADIKA 12 DEPOK)

Teacher Performance Assessment guarantees a quality learning process at all levels of education. Educational supervision will be carried out with the aim to improve the quality of teaching / teacher so that the competitiveness of students studying at the school will increase towards a better direction. Supervision assessment is a class visit technique to obtain data about the actual situation regarding the ability and skills of teachers in teaching and mastery of class. To determine the teacher's performance, one approach can be done using the Balanced Scorecard approach and Naïve Bayes classification. The determination of teacher performance is then processed using Analytic Network Process-based modeling to improve teacher evaluation criteria that are still low. With the help of Super Decision software, a decision support system was created in determining teacher performance. The results of this study are the recommendations of permanent teachers in Junior High Schools, High Schools, and Vocational Schools Yadika 12 Depok based on performance to be objective and make more efficient decisions.
Vitamin-V: Virtual Environment and Tool-boxing for Trustworthy Development of RISC-V based Cloud Services

Vitamin-V is a 2023-2025 Horizon Europe project that aims to develop a complete RISC-V open-source software stack for cloud services with comparable performance to the cloud-dominant x86 counterpart and a powerful virtual execution environment for software development, validation, verification, and test that considers the relevant RISC-V ISA extensions for cloud deployment.
GETTING AROUND THE CHALLENGES OF LEARNING ACCOUNTING EDUCATION DURING THE COVID-19 PANDEMIC

This study aims to analyze the challenges faced by students in studying accounting during the Covid-19 pandemic and find solutions to overcome them. This research was conducted using qualitative and quantitative approaches through data collection through interviews, questionnaires and observation. The results of the study show that the Covid-19 pandemic has presented many challenges to the accounting learning process, including problems with unstable internet access, difficulties in adapting to online learning, and increased anxiety related to health and finances. Based on these findings, several solutions have been proposed, including increasing internet access, using different learning methods, and counseling support and financial assistance for students in need. This research is expected to contribute to the development of more effective learning strategies during the Covid-19 pandemic, particularly in the accounting discipline.&#x0D;
A Powerful Chrome Extension: Translation Program using Python, Website Analysis and Google Firebase Services

The last few decades have seen a remarkable development technological wise in order to provide understanding between people with different language backgrounds. This paper develops a Chrome Extension that scans texts on a website and discovers unfamiliar English words to its users, then translates those words and displays their meanings onto their computer screens. Using Python with Flask framework and Google Firebase as a backend means, this Chrome Extension can be downloaded on any Chrome Browser and provide definitions to difficult words on websites that users want to get translated. The extension is useful to those who are having a hard time understanding difficult English vocabulary. In the experiment, the application has shown to detect 95 to 98% of the difficult words users are struggling with, with the speed of 10 minutes for documents that have more than 2000 words. The results show that the application provides adequate predictions for most users. For this application, I took data reliability, usability, and web-scrapping into consideration. The extension required ample reliable data, user-friendly interface, and a stable Internet browser for usage.
Folklore, Analysis and Utilization of the Golden Cave and Silver Cave

The Gold Cave and Silver Cave are tourist attractions located in Durian IV Mbelang Village, STM Hulu District, Deli Serdang Regency, North Sumatra. Based on the data obtained, the gold cave and silver cave save a lot of historical history. Even these caves have their own uniqueness, namely there are silver and gold grains at several points on the cave walls. The historical story and the uniqueness of the cave became the basis for conducting a study to uncover the scientific truth of the gold and silver cave in history and laboratory testing of the authenticity of the gold and silver. This study uses qualitative methods to describe and describe existing phenomena, both natural and human engineered. This method consists of several stages of research interviews and observations using data analysis model Miles and Huberma techniques and observations of recordings and research notes so that every information can be recorded properly. The results showed several legend stories and cave naming if in a hermeneutic perspective the legend stories and the names of the caves were made for the preservation of the cave and increasing the tourism of the cave. Laboratory tests proved the presence of particles resembling gold (Titanium Nitride compounds, Ti2N) and silveccr (Nickel Iron Oxid compounds, NiFe2O4).
Effect of Cost Accounting Information Systems on Operational Cost Control

The purpose of this study was to determine the Operational Cost Accounting Information System on Internal Control of Operating Costs and how much influence the Operational Cost Accounting Information System has on Internal Control of Operational Costs at a consulting firm in Bandung. The research method used is descriptive analysis, while the data collection technique is by distributing questionnaires to 30 respondents. This study uses the Pearson Moment correlation data analysis technique and the coefficient of determination analysis technique using Excel and SPSS 25 For Windows Software in its operations.&#x0D; The regression equation research results show the positive influence of the Operational Cost Accounting Information System on the Internal Control of Operational Costs. This study obtained the results from the regression analysis, namely Y = a + bX Y = 16.888 + 0.567X, which means that if the value of X = 0, then Y = 16.888. So if X changes one unit, it will affect Y by 0.567. Therefore, the Operational Cost, Accounting Information System, influences the Internal Control of Operational Costs by 35.9%, while other factors affect as much as the remaining 64.1%. Thus, the researchers concluded that the Operational Cost accounting information system influenced the Internal Control of Operational Costs Case Study at a Consulting Firm in Bandung City.
Training on the Implementation of Online Learning System Applications for Teachers at SMAN 4 Palopo

Mastery of information technology is very important for a teacher in learning activities at school. One of the supporting factors for improving the quality of learning is mastering the skills of utilizing online learning system applications. The goal to be achieved in this activity is to transfer science and technology by conducting training activities on the application of online learning system applications for teachers at SMA Negeri 4 Palopo. The method of implementing training activities on the application of online learning system applications at SMA Negeri 4 Palopo is by applying lecture and practice methods. The stages are: teachers are given an understanding as well as an introduction to the online learning system application, provide training on the use of zoom, Classroom, and Quiziz applications to teachers, provide assistance for teachers in the context of implementing online learning system applications at school so that the learning process becomes quality. The results of the PKM program activities entitled "Training on the Application of Online Learning System Applications at SMA Negeri 4 Palopo" were able to improve teacher skills in using online learning system applications so as to improve the quality of learning at school. Based on the training program that has been carried out, it can be concluded that the implementation of the training went smoothly and received a positive response from the teacher as a very good trainee and has been skilled in using online learning system applications such as: Zoom, Classroom, and Quiziz.
Urban daily water demand forecasting

Abstract. Problem. The problem of building models and methods of forecasting the daily need for urban water is considered. Much more attention needs to be given to forecasting methods if utilities are to make decisions that reflect the level of uncertainty precisely in future daily demand forecasts. Daily water consumption, unlike annual and monthly water consumption, is much more highly dependent on chance. Goal. The main goal of this paper is to obtain enough accurate forecasts of daily urban water consumption. Method. An algorithm for calculating the urban daily water demand forecast based on the concept of same-type days of water demand for previous years has been suggested. Scientific novelty. The originality of the method lies in the fact that it does not use neural network models, but still makes it possible to obtain enough accurate forecasts of daily urban water needs. Results. The presented algorithm for calculating the urban daily water demand forecast has been implemented in the form of a software package and has been tested for many years in real-life conditions. The average absolute percentage error of the daily forecast of urban water demand for one month does not exceed 5%. Practical significance. The practical value of this work lies in the fact that the presented software complex for calculating the forecast of the city's daily water demand can be used in the information services of city utility companies to make operational and tactical decisions regarding the provision of water supply services to the population.
ESP Students’ Perceptions on the Use of Whatsapp Application as a Learning Tool

The development of technology provides a huge impact on the educational setting which increasing Mobile-Assisted Language Learning (MALL) usage especially in supporting ESP students. One of the mobile applications used in supporting language learning is WhatsApp Messenger. This study aimed to investigate ESP students’ perceptions on the use of WhatsApp in English language learning. The research approach was a descriptive quantitative approach while the design of this research was a survey. The participants were 22 male ESP students who followed the English class held by Helutrans Art-moving Company. For collecting the data, the researcher employed a questionnaire adapted from Mistar Embi (2016). The questionnaire consisted of three parts such as the attitude towards WhatsApp, the usefulness of WhatsApp and also the constraint in using WhatsApp. In analyzing the data, it applied descriptive statistics using SPSS version 26 in the form of frequencies, means, and standard deviations. The findings of the research revealed that the majority of the research participants had positive perceptions concerning the use of WhatsApp in the ESP setting. It implied that ESP students agreed for using WhatsApp on language learning was easy, useful and effective in increasing their motivation, interest, confidence, and their activeness. They also felt that using WhatsApp could increase their English skill such as listening, reading, writing and speaking.
The Study of Syntactic Error Review of Editorial News Titled Politics is Getting Hotter

The background of this research is the discovery of errors in the Indonesian language in online news writing. The most obvious error is at the syntax level. Therefore, this study aims to explain the form of language errors in the field of syntax contained in the online news portal Sindonews in the editorial news text entitled "Politics Getting Hot". This study uses a qualitative method with a descriptive approach. To obtain data, the observation technique was chosen as a data collection method. Furthermore, the data were analyzed using the distribution method. The results of the research regarding the analysis of language errors in the field of syntax contained in the editorial news include errors in coherence, borrowed words, sentence effectiveness, unity, and sentence logic that do not match. This study reinforces the paradigm that online news portals ignore the principles of Indonesian language syntax.
Sharing Lifelong Reinforcement Learning Knowledge via Modulating Masks

Lifelong learning agents aim to learn multiple tasks sequentially over a lifetime. This involves the ability to exploit previous knowledge when learning new tasks and to avoid forgetting. Modulating masks, a specific type of parameter isolation approach, have recently shown promise in both supervised and reinforcement learning. While lifelong learning algorithms have been investigated mainly within a single-agent approach, a question remains on how multiple agents can share lifelong learning knowledge with each other. We show that the parameter isolation mechanism used by modulating masks is particularly suitable for exchanging knowledge among agents in a distributed and decentralized system of lifelong learners. The key idea is that the isolation of specific task knowledge to specific masks allows agents to transfer only specific knowledge on-demand, resulting in robust and effective distributed lifelong learning. We assume fully distributed and asynchronous scenarios with dynamic agent numbers and connectivity. An on-demand communication protocol ensures agents query their peers for specific masks to be transferred and integrated into their policies when facing each task. Experiments indicate that on-demand mask communication is an effective way to implement distributed lifelong reinforcement learning and provides a lifelong learning benefit with respect to distributed RL baselines such as DD-PPO, IMPALA, and PPO+EWC. The system is particularly robust to connection drops and demonstrates rapid learning due to knowledge exchange.
Understanding how Differentially Private Generative Models Spend their Privacy Budget

Generative models trained with Differential Privacy (DP) are increasingly used to produce synthetic data while reducing privacy risks. Navigating their specific privacy-utility tradeoffs makes it challenging to determine which models would work best for specific settings/tasks. In this paper, we fill this gap in the context of tabular data by analyzing how DP generative models distribute privacy budgets across rows and columns, arguably the main source of utility degradation. We examine the main factors contributing to how privacy budgets are spent, including underlying modeling techniques, DP mechanisms, and data dimensionality. Our extensive evaluation of both graphical and deep generative models sheds light on the distinctive features that render them suitable for different settings and tasks. We show that graphical models distribute the privacy budget horizontally and thus cannot handle relatively wide datasets while the performance on the task they were optimized for monotonically increases with more data. Deep generative models spend their budget per iteration, so their behavior is less predictable with varying dataset dimensions but could perform better if trained on more features. Also, low levels of privacy ($\epsilon\geq100$) could help some models generalize, achieving better results than without applying DP.
NYU Library System Rec No 009486590 BMF Analytics

New York University Library System Record No. 009486590 BMF Analytics
Real-Time Sign Language Recognition System for Hearing and Speech Impaired People

Abstract: People with hearing loss frequently use sign language to interact with their community and communicate with others because it is largely a visual form of communication. It requires the use of manual gestures, nonverbal facial clues, and body motions, unlike spoken language, to express thoughts and convey meaning. The goal of Sign Language Recognition (SLR) is to identify, interpret, and translate these signs into the appropriate speech or text. For those with speech and hearing impairments, sign language is an essential tool for communicating with others and exchanging ideas. This paper proposes a novel method for recognising individual alphabet signals in sign language so that words can be formed from them. This is accomplished through the application of a deep learning network, which can detect the signs and output the corresponding text. Additionally, the recognized individual characters can be sequentially utilized to form words, which can then be converted into voice output.
A Blockchain-based approach for Drug Traceability in Healthcare Supply Chain

Abstract: The blockchain typically described as a decentralized system in which transactional or ancient statistics are recorded, stored, and maintained throughout a peer-to-peer community of personal computers referred to as nodes. Counterfeit drugs are one consequence of such limitations within existing supply chains, which not only has serious adverse impact on human health but also causes severe economic loss to the healthcare industry. Blockchain technology has gained tremendous attention, with an escalating hobby in a plethora of several applications like safe and relaxed healthcare records management. Similarly, blockchain is reforming the traditional healthcare practices to an extra reliable means, in phrases of powerful prognosis and treatment through safe and cosy facts sharing using SHA Hash Generation Algorithm. Within the future, blockchain will be an era that can probably assist in personalized, authentic, and at ease healthcare by means of merging the entire actual-time scientific information of a patient’s fitness and offering it in an up to date cosy healthcare setup. In this paper, we evaluation each the present and modern day trends inside the subject of healthcare with the aid of imposing blockchain as a model. We also talk the packages of blockchain, at the side of the demanding situations confronted and destiny views. The proposed system executed blockchain implementation in distributed computing surroundings and it gives the automated restoration of invalid chain by using Consensus and Mining Algorithm. In this system, we present a Custom blockchain-based approach leveraging smart contracts and decentralized off-chain storage for efficient product traceability in the healthcare supply chain. The smart contract guarantees data provenance, eliminates the need for intermediaries and provides a secure, immutable history of transactions to all stakeholders. We present the system architecture and detailed algorithms that govern the working principles of our proposed solution. We perform testing and validation, and present cost and security analysis of the system to evaluate its effectiveness to enhance traceability within pharmaceutical supply chains.
ATM Based Face Recognitions System

Abstract: Automated Teller Machines are widely used nowadays by people. But it’s hard to carry their ATM card everywhere, people may forget to have their ATM card or forget their PIN number. The ATM card may get damaged and users can have a situation where they can’t get access to their money. In our proposal, use of biometrics for authentication instead of PIN and ATMcard is encouraged. Here, The Face ID is preferred to high priority, as the combination of these biometrics proved to be the best among the identification and verification techniques. The implementation of ATM machines comes with the issue of being accessed by illegitimate users with valid authentication code. The users are verified by comparing the image taken in front of the ATM machine, to the images which are present in the. If the user is legitimate the new image is used to train the model for further accuracy. This system uses open CV to process the image being obtained and Hear Cascade Classifier to detect the faces in the image. The face recognitions done using Local Binary Pattern.
Deep Learning Approach for Facial Expression Recognition

Abstract: In recent decades, facial expression recognition has emerged as a hot topic with significant implications in the realm of human-computer interaction. The simplest way for humans to express their emotions is through facial expressions. Non-verbal communication relies heavily on facial expression. This study outlines deep learning-based Facial Expression Recognition (FER) algorithm. The performance of the FER approach is compared based on the number of expressions detected and the difficulty of CNN algorithms. The FER2013, CK+ databases were used in testing the design. CNNs (Convolutional Neural Networks) have as of late gained fame in the field of profound learning because of its superb plan and capacity to convey clever outcomes without the requirement for manual feature extraction from raw information. The suggested algorithm achieves a higher rate of recognition on four datasets.