Reviewerly/exHarmony huggingface dataset:
Sentiment Analysis of Jokowi’s Candidate Discourse in Three Periods using the Naïve Bayes Method

Approaching the 2024 presidential election many discourses develop among the public regarding the presidential election period which takes place every five years. One of the most widely discussed political discourses is the candidacy of President Jokowi for the third term of his leadership. This study aims to carry out a sentiment analysis of the public on the discourse. The sample data for sentiment analysis is taken from Twitter social media in the form of tweet status. The stages carried out by the researchers began with determining the research method through text mining and sentiment analysis using the Naive Bayes algorithm. The results of the research conducted revealed that there are still many positive sentiments compared to negative sentiments related to the discourse of Jokowi's candidacy in the three periods. Keywords: Sentiment Analysis, Naive Bayes, Twitter, Jokowi.
Usability Testing on ITTS MART Prototype

I nformation technology is currently growing very rapidly so that it can provide convenience to its users, one of which is the ease of accessing the internet, such as through cell phones. The rapid increase in internet users, especially through mobile phones, is caused by the hectic number of social media applications as virtual friendship applications. Apart from being a virtual friendship application, another benefit of social media is as a promotional media, one of which is the promotion of online shopping applications, so that the number of online shopping transactions in Indonesia also increases. Hydroponic and aquaponic activities at the Telkom Institute of Technology Surabaya are also developing and starting to enter the product harvest stage, so a platform is needed to sell these products. An online shopping platform was chosen, especially a mobile application, to sell ITTelkom Surabaya products so that consumers can shop anytime and anywhere. The online shopping application developed by ITtelkom Surabaya is called ITTS MART. Currently, ITTS MART is still in the prototype development stage and there is a need for usability testing using the WebQual Concept on the ITTS MART application. From the results of the study, it can be concluded that the six research variables, namely Trust, Informational Fit-To-Task, Web Appearance, Entertainment, Government Policy and Transaction Capability, show a significant difference between expectations and real experience or dissatisfaction when using the ITTS MART application. Only one variable that shows the value of the difference is not significant, namely Response Time, so it can be concluded that respondents are satisfied with the time to access the page on the ITTS MART application. Keywords: Usability, WebQual, Online Shopping, Application, Food Product .
Comparison of Ensemble Learning Method: Random Forest, Support Vector Machine, AdaBoost for Classification Human Development Index (HDI)

Classification in supervised learning is a way to find patterns in database that the classes are already known.In the classification of machine learning, there is a term called ensemble classifier.The workings of the ensemble classifier aimed to improve model accuracy and optimize classification performance.This study aims to analyze the comparison of algorithms that work with ensemble learning, including Random Forest, Support Vector Machine (SVM), and AdaBoost.The data used is the Human Development Index (HDI) of districts/cities in Indonesia.Other variables that are strongly related to human development are GRDP per capita, gross enrollment rate, net enrollment rate, labor force participation rate, unemployment rate, poverty rate, poverty depth, poverty severity, and average consumption per capita.The reason for using HDI is that apart from being an important macroeconomic variable in describing the condition of human resources in Indonesia, HDI already has an obvious classification according to the Badan Pusat Statistik (BPS) so that supervised learning can be applied.Comparison of model evaluation using accuracy, specificity, sensitivity, and kappa
Arduino-based Reverse Vending Machine Metal Medicine Packaging Exchange

As technology develops, the use of vending machines also develops. In addition to purchasing food and drinks, it can also be used to exchange medicine packaging for coins. To simplify the exchange process to make it more practical and not to spend a lot of time, a reverse vending machine was built for drug packaging containing metal as input. Collecting data using the method of observation and literature study. This type of research is prototyping because the results obtained are in the form of a prototype. This prototype used 3 buttons in main process. The first stage is pressing button 1 to detect metal, then pressing button 2 to weigh, and button 3 to release coins. The test results obtained from the Arduino-Based Reverse Vending Machine Metal Medicine Packaging Exchange indicate that the prototype is able to be used as a medium of exchange for drug packaging trash containing metal into a medium of exchange in money form. The prototype is able to provide a solution for reducing or managing medical trash which contains metal.
Improving Deep Echo State Network with Neuronal Similarity-based Iterative Pruning Merging Algorithm

Recently, a layer-stacked ESN model named deep echo state Network (DeepESN) has been established. As an interactional model of recurrent neural network and deep neural network, investigations of DeepESN are of significant importance in both areas. Optimizing the structure of neural networks remains a common task in artificial neural networks, and the question of how many neurons should be used in each layer of DeepESN must be stressed. In this paper, our aim is to solve the problem of choosing the optimized size of DeepESN. Inspired by the sensitive iterative pruning algorithm, a neuronal similarity-based iterative pruning merging algorithm (NS-IPMA) is proposed to iteratively prune or merge the most similar neurons in DeepESN. Two chaotic time series prediction tasks are applied to demonstrate the effectiveness of NS-IPMA. The results show that the DeepESN pruned by NS-IPMA outperforms unpruned DeepESN with the same network size, and NS-IPMA is a feasible and superior approach to improving the generalization performance of DeepESN.
Complete active space methods for NISQ devices: The importance of canonical orbital optimization for accuracy and noise resilience

To break the scaling of the number of qubits with the size of the basis set, one can divide the molecular space into active and inactive, also known as complete active space methods. Nevertheless, more than the active space selection is needed for accuracy and effectively describing quantum mechanical effects as correlation. This study highlights the importance of optimizing the active space orbitals to describe correlation and improve the Hartree-Fock energies. We will explore orbital optimization classically and through quantum computation and how, theoretically, a chemically inspired ansatz as the UCCSD compares with a classical full CI (FCI) description of the active space in weakly and strongly correlated molecules. Finally, we will explore the practical implementation of a quantum CASSCF where hardware-efficient circuits need to be used, and noise hinders its accuracy and convergence. Moreover, we explore canonical and non-canonical active orbitals and how those influence the convergence of the quantum CASSCF routine in the presence of noise.
How fear affects employees’ performance: A process model

The effect of emotions on employees’ attitudes, motivation, and workplace behaviors is an important and central topic in organizational behavior research. Therefore, the main purpose of this study is to develop and empirically test a model that explains how fear affects employees’ performance. The model was tested on a sample of 177 nurses working in different Jordanian hospitals. A questionnaire was developed to measure the main constructs of this study. The data was analyzed in SPSS using simple regression to test the main direct hypotheses. The model hypothesizes that fear has a positive effect on two psychological states: emotional exhaustion and perceived stress. Moreover, it hypothesizes that these two states will affect employees’ career choice regret, which, in turn, negatively affects employees’ performance. The results provided statistical support for all the proposed hypotheses. We concluded that excessive fear provokes emotional exhaustion and stress in frontline employees and that these two psychological states contribute to the development of career choice regret, which eventually affects employees’ performance. The findings of this study may enable managers to gain deeper insight into and a better understanding of the process by which fear influences employee performance. Finally, limitations and directions for future research are discussed.
Why Nations Prosper

Abstract This paper's main idea is that Synechi causes prosperity. I define "Synechi" as "nation political leader implemented and reinforced a series of free-market policy continuously without substantial reverse for at least 20 years." I use: (1) the difference-in-difference method, using West Germany, South Korea, Botswana as the treatment group and East Germany, North Korea, and Zimbabwe, as the control group, to mimic "natural experiment", (2) Direct Method of Agreement from data of 52 countries and (3) Method of Difference form data of 24 countries and (4) Joint Method of Agreement and Difference, from data of 66 countries. I use Maddison Project Database data in the long- run GDP per capita published in early 2018 and other data sources. This approach is novel since previous papers only show that the free-market correlates with prosperity. JEL Classification: F59 O10 O11 O20 O21 POO
Recalculating in big data

Abstract The available memory on a desktop or laptop computer can easily be exceeded by large datasets when performing analytics or training machine learning algorithms. In this paper we propose simple methods to recalculate and update the value of descriptive statistics (averages, variance, coefficients of skewness and kurtosis) after rescaling, adding or excluding some data. The coefficient of determination from regression analysis is also recalculated after deleting each sample observation. The objective is to avoid including all the observations (especially in big datasets) when those statistics are recalculated. For this, only its previous value updated by the changed observations is needed, saving time in the respective calculation.
Meningkatkan Keterampilan Mengungkapkan Monolog Descriptive Lisan Sederhana yang Berterima Menggunakan Sistem ICARE di MTs Muhammadiyah 2 Kalibening Banjarnegara

The key output of the teaching process is the material provided by the students themselves,therefore it is important to conduct research. The methodology used in this investigation is aclass of investigative action. Methods of data collection using interviews, tests, observation,and documentation. Data validation using triangulation. Data analysis methods used in thisresearch include quantitative analysis, especially reduction analysis, presentation, andconclusion or verification analysis. The results of this study indicate that: (1) teaching Englishuses the ICARE system to teach one continuous monologue that is descriptive in nature andincludes four learning objectives: Introduce (Introduce), Connect (Connect), Apply (Apply),Reflect (Reflect), and Expand (Expand). (2) The results of Section I show that there are 16 or43% of participants who have completed the course and 27 or 67% who have not; the overallparticipation rate was 68. In Part II,
IMPLEMENTASI MEDIA JAMBOARD PADA MATA KULIAH BAHASA INDONESIA DI MASA PANDEMI DI UNIVERSITAS BATTUTA (STUDI KASUS PROGRAM STUDI PENDIDIKAN GURU SEKOLAH DASAR)

This study will explore the Google Jamboard learning method during covid-19 during online learning, showing that the perception of students and lecturers regarding the most effective application when online learning is using Google Jamboard?. The purpose of this study is to see learning media that can support student success based on the teaching and learning process as an effective form of activity in order to achieve the desired goals, it is hoped that learning media will become a mediator which is one of the tools in the teaching and learning process. The expected result after the implementation of this research is to increase the knowledge and understanding of students and lecturers in Indonesian language courses. This study will look at the effect of using Google Jamboard on the effectiveness of the learning process in Indonesian language courses in the elementary school teacher education study program at Battuta University. After the results of this study, in the future, students and lecturers during online learning, lecturers will certainly find it easier to provide Indonesian language course material to students by using Google Jamboard.
TREN RISET TANAMAN OBAT DI INDONESIA DARI TAHUN 2011-2021: ANALISIS BIBLIOMETRIK MENGGUNAKAN VOSVIEWER

&lt;p class="abstrak"&gt;This study aims to determine the development of research on medicinal plant domains in Indonesia in Scopus indexed journals or proceedings from 2011-2021. Data was collected using the Publish or Perish application with search keywords related to medicinal plants in Indonesia, namely Indonesian medicinal plants and Indonesian herbal plants. The data storing in the form of Microsoft Excel 2013 and RIS. Microsoft Excel 2013 was used to analyze the development of the number of publications, the productivity of the authors, and the top most widely used articles for citations. The VOSViewer application version 1.6.17 using to analyze the relationship between research topics, trends, and the most frequently researched research topics. The results of this study show that the highest publication occurred in 2021, 177 publications (20.30%), while the lowest publication occurred in 2011 with 21 publications (2.41%). The 5 most productive researchers in publishing articles in 2011-2021 are Elya, B, who produced 14 published articles; Coal, who produced 13 published articles; Nisyawati and Silalahi, M produced 10 published articles; and Subositi, D produced 9 published articles. In this study, the topic that was most cited was Indonesia. Network visualization is divided into 4 clusters. The latest topics based on data from articles in this study, namely plants, traditional medicine, and medicinal plants, were the most published in 2017-2019. The most published topic was Indonesia, followed by topics such as medicine, analysis, and areas.&lt;/p&gt;
Was Fairness in IR Discussed by Cooper and Robertson in the 1970's?

I discuss fairness in Information Retrieval (IR) through the eyes of Cooper and Robertson's probability ranking principle. I argue that unfair rankings may arise from blindly applying the principle without checking whether its preconditions are met. Following this argument, unfair rankings originate from the application of learning-to-rank approaches in cases where they should not be applied according to the probability ranking principle. I use two examples to show that fairer rankings may also be more relevant than rankings that are based on the probability ranking principle.
"Become a Guardian of Al Wasl"

At the time of writing (2021--22), "Become a Guardian of Al Wasl" represented the world's largest interactive experience. Designing, producing and deploying an immersive interactive experience at the monumental scale of the Al Wasl Plaza 360° projection surface necessitated the research, prototyping and testing of proposed solutions, including systems architecture, to meet the scope and specifications of the project. Four problem spaces emerged during development; real-time rendering, projection-mapping, redundancy, and content synchronisation. In addition, budget constraints, Covid-19, and remote deployment motivated the exploration of other innovative solutions. As there is limited research on the design and development of interactive dome experiences, this paper will present the challenges encountered in developing productions for the world's largest dome display system and in building the underlying real-time display and support systems.
Televerse

This course introduces "Televerse", a new framework to provide augmented telepresence in the real environment. The framework is able to provide telepresence at the captured real environment, enhance people's situational awareness for better telecommunication, and allow rich interactions with people at a distance through blended 3D assets and live visual effects.
Polimarin Alumni's English Proficiency in Maritime Industry Competitiveness in Indonesia

The background of this research is the competition in looking for jobs, which is getting harder day by day, with the large number of alumni who have graduated from each educational institution in Indonesia; plus the narrowing of job opportunities makes everyone compete to fight for employment. Currently, English is a prerequisite for getting a job or doing further schooling. The research is entitled "Polimarin Alumni's English Proficiency in the Maritime Industry Competitiveness in Indonesia". The focus of this research is aimed at the alumni of POLIMARIN (Politeknik Maritim Negeri Indonesia) / (Indonesian State Maritim Polytechnic) who have worked or carried out an internship. The purpose of this research is that alumni can compete in the work age by mastering good English. The steps in conducting this research were by distributing questionnaires to alumni and also students who were still doing the internship. The result of this research is that the alumni of Polimarin has unsatisfactory proficiency in English. The conclusion from these findings can be used as a reference to improve ways or better learning methods for English language skills, especially speaking skills, because it is the most difficult material to master and a most important issue to alumni. Thus, the learning objectives based on the curriculum can increase English competency for cadets or students.
Comparison of Seven Machine Learning Algorithms in the Classification of Public Opinion

Sentiment analysis is one way that is widely used to identify the beginning of public opinion in various fields of life which are associated with very massive and a lot of information through social media. This study aims to compare several algorithms in machine learning to see the best ability in sentiment classification. The research dataset uses a dataset of public opinion related to tourism in Indonesia. The number of datasets used is 10,228 twitter data that have been cleaned and labelled. The machine learning algorithm used is Logistic Regression, KNN, AdaBoost, Decision Tree, SVM, Random Forest and Gaussian. The seven algorithms for sentiment classification from the Twitter public opinion each produce a Gaussian accuracy of 0.52; SVM 0.78; KNN 0.98; Logistic Regression, Random Forest, Decision Tree, AdaBoost of 0.99. This study shows that the selection of the right machine learning algorithm will have a very good impact on the classification of public opinion through social media
Implementation of The Framework for The Application of System Thinking for School Financial Information Systems

The library at SMK Negeri Sukoharjo is a library that has library management staff and several book collections according to library standards and has adequate library facilities and infrastructure. Students are required to become members of the school library to support the learning process. However, the process of borrowing and returning books is still conventional, that is, all library administration data collection in borrowing and returning books is still written in the book, and when looking for the required data, you must open the book page. Implementation of a library administration information system using FAST (Framework for the Application of Systems Technique), users can better understand and easily use applications made to maximize the performance of library staff, principals, and students in managing library administration. The design of the library administration information system using FAST (Framework for the Application of Systems Technique) has a Scope Definition, Problem Analysis, Requirement Analysis, Logical Design, Decision Analysis, Physical Design, Construction and Testing, Installation and Delivery, and Prototype. In accordance with the needs of users on the library administration information system based on the user experience design carried out. The results of web quality testing are 88.31% with very good criteria.
Smart Wifi Design for Integrated Tourist Destinations in Smart Tourism

The use of public wireless networks and not integrated between tourist destinations is an obstacle for visitors when moving to other tourist destinations. This is an obstacle to internet access in the tourism era 4.0. To overcome this, smart wifi is needed. Smart wifi is an integrated internet network access among other tourist destinations so as to expand the connectivity and interaction of tourist visitors. This study used the NDLC method. The result of this research was the design of smart wifi which was built on a wireless network with captive portal technology and barcode scanning. Smart wifi contributes to the development of digitalization in smart tourism, making it easier for visitors to get internet access in various tourist destinations.
Reorganization of the Elementary School System

본 연구는 학생수 급감으로 인한 소규모학교와 학교급간 이음학교의 증가, 아동의 조숙, 고교생의 정치참여 연령 하향화, 늦어지는 입직연령 등으로 1950년대 정해진 학제가 오늘날에 얼마나 적합한가에 대해 논의하고자 하였다. 학생수 급감을 가장 먼저 맞게 되는 초등학교부터 유-초, 초-중 이음학교가 늘어나고 있어 학제 개선에 대한 종합적 탐구가 필요하다. 문헌 연구와 해외 사례 비교 연구를 통해 학제의 개편 방안으로, 초등 입학 전 1년 혹은 한 학기동안 기초 학습의 준비를 명시하는 기초학습준비반 개설안, 기존에 여러 차례 제안된 초등학교 수업 연한 1년 단축안, 실질적 속진 활성화안, 최근 논란을 빚은 초등학교 입학 연령을 하향화안 등을 종합적으로 비교 검토하였다. 학제 개선 방안에 관한 관계자 의견 조사 결과, 학제 개편의 필요성과 기초학습준비반의 도입에 대해서는 동의하였으나, 기초학습준비반의 학제 운영과 교사 활용 및 교육과정 운영 방안 등의 사안에 관해서는 교사 및 학부모 집단별 통계적으로 유의미한 의견 차이가 있었다. 속진의 경우 동의와 부동의 의견 비율이 비슷하였으며, 속진을 할 경우 고학년에서, 전체 학생의 5% 이하의 비율로 실시하는 것이 좋다고 응답하였다. 연구를 통해 기초학습준비반의 개설을 포함한 학제 전반의 종합적 개편논의가 요구되며, 구체적인 실행 방안은 이해관계자들의 협의 절차가 필요함을 제언하였다.This study discusses reform of the school system to respond to learners’ maturation and changes in society. The curriculum, the content of education, has been regularly revised, but the container for the curriculum, the school system, has not been revised from that of the 1950s. It is necessary to reduce the length of the school year, since the recent revision of the Political Party Act and the Public Official Election Act call for a role as a citizen at an earlier age. For this study, we conducted a literature study and an opinion survey on the overall school system and specific implementation plans. Through the literature study and overseas case studies, we propose a learning preparation class for one year before elementary school, reducing the years of elementary school to five years, the activation of grade skipping, and the lowering of the elementary school entrance age. As a result of the opinion survey, respondents generally agreed on the necessity to reorganize the school system and including a learning preparation class, but there were significant differences in relation to specific plans. The opinions for and against grade skipping were similar. Through this research, it is suggested that reform of the school system, including a learning preparation class, is required, and that consultation between the relevant parties is necessary for agreement on a specific plan.