Reviewerly/exHarmony huggingface dataset:
Sentiment Analysis of Pedulilindungi Application Reviews Using Machine Learning and Deep Learning

The COVID-19 pandemic that hit the world at the end of early 2020 caused many losses. The Indonesian government has established various ways to reduce the path of the COVID-19 pandemic by launching the PeduliLindungi application to reduce the spread of COVID-19. Various layers of society responded to the launch of the application with various opinions. This research mainly analyzes public opinion sentiment toward the PeduliLindungi application, as determined by 10,000 reviews on the Google Play Store. This study aims to compare the performance of deep learning and machine learning models in sentiment analysis. The stages of the research method begin with data collection methods, data pre-processing, and sentiment analysis using a machine learning model with the embedding of the word TF-IDF, which includes the Nave Bayes algorithm, Decision Tree, Random Forest, K-Nearest Neighbour, and SVM. As for the deep learning model with the fastText word embedding word representation technique using the LSTM algorithm, an evaluation is carried out using the confusion matrix. The results of this study state that deep learning models perform better than machine learning models.
Implementation of Pddikti Neo Feeder Web Service in Recording of Independent Campus Activities

Independent Learning-Independent Campus Program (MBKM) is a policy of granting the right for students to be able to take study activities outside the study program as many as three semesters with the division of two semesters of study outside the college and one semester in different study programs in one college. As well as teaching and learning activities, universities must report Independent Learning-Independent Campus activities to DIKTI every semester through the Neo Feeder PDDIKTI application. The Neo Feeder PDDIKTI application has a feature to enter the activities the operator will carry out. The operator enters this data individually on the Neo Feeder PDDIKTI application. This is a significant problem because the data entry process will take quite a lot of time, even though PDDIKTI has provided web service access to universities to optimize the data reporting process using the Neo Feeder PDDIKTI application. Building an application that can be used for recording MBKM activities by utilizing web services provided by PDDIKTI is the primary purpose of this study. The development of an application certainly requires a method as a framework or guide in facilitating the manufacturing process. The extreme Programming (XP) method becomes essential for applications with variable or non-fixed needs. This method has four working elements: planning, designing, coding, testing and software increment. The output generated by this study is an application for recording MBKM activities that use web service restful API technology so that data entry can be done en masse and not one by one.
Social Media as Mobile Learning Oral Chat-Based Constructive Communication to Improve Speaking Skills

WhatsApp is one of the most practical, cost-effective, and communicative mobile applications for college students to enhance their speaking skills. This study reconciled to consuetude college students to flexible habitual use of the English language learning and intended to improve their speaking abilities with specially tailored learning resources and activities aid known as WhatsApp-based speaking instructional material (WABSIM). This exploratory mixed-methods research evaluated oral chat-based utilization of WhatsApp by twenty-eight students for one semester using audio voice messages and video recordings of communicative activities in pairs or groups, dialogues, and interviews activities recorded in the WhatsApp group managed to produce every day classroom and noncollegiate activities. Speaking test consisted of an oral evaluation of student's fluency, vocabulary used, grammar, pronunciation, and comprehensibility aspects. It reveals that students demonstrated a stupendous developing speaking interest in building English sentences by raising questions and delivering responses, improved learning collaboration, created better learning engagement, increased learning self-awareness, and accelerated flexible communication. Besides, students achieved substantial academic progress astoundingly in a semester. Therefore, to emerge the significance acknowledged from this current study, in the current era of mobile technology advancement supporting teaching and learning English, WhatsApp oral chat-based assistance offering teaching and learning English flexibility is the most effective.
Comparative Analysis of Using Word Embedding in Deep Learning for Text Classification

A group of theory-driven computing techniques known as natural language processing (NLP) are used to interpret and represent human discourse automatically. From part-of-speech (POS) parsing and tagging to machine translation and dialogue systems, NLP enables computers to carry out various natural language-related activities at all levels. In this research, we compared word embedding techniques FastText and GloVe, which are used for text representation. This study aims to evaluate and compare the effectiveness of word embedding in text classification using LSTM (Long Short-Term Memory). The research stages start with dataset collection, pre-processing, word embedding, split data, and the last is deep learning techniques. According to the results of the experiments, when compared to the glove technique it seems that FastText is superior, the accuracy obtained reaches 90%. The number of epochs did not significantly improve the accuracy of the LSTM model with GloVe and FastText. It can be concluded that the FastText word embedding technique is superior to the GloVe technique.
Evaluation of Machine Learning Using The K-NN Algorithm to determine The Quality of Meat before consumption

Meat is one of the sources of animal protein for humans, and one of the requirements that must be met so that the human body does not lack protein, especially animal; this protein can be obtained from beef, chicken, and other meats, but the most important thing here is the content contained in meat, whether it has been contaminated with chemicals, e.g., chicken that has been injected with chemicals that cause the chicken to look fat, or beef whose flexibility has decreased and the pH is getting more acidic. This research tries to predict meat quality by looking at two parameters: flexibility and acidity. The programming language used is R Language, using the k-NN method or Algorithm to determine the meat's condition suitable for consumption. In detail, it will be processed in Machine Learning using the k-NN Algorithm; there are two criteria for consumption of meat, namely good or not good for consumption; in detail, the output will be explained using a specific graph using a plot function, and array data will be specifically classified to represent values. The value of 2 variables, namely feasible or not suitable for consumption.&#x0D;
Development of material training of infographic video using adobe premiere cs6 in nonformal education

The perkumpulan alam hijau (A-HI) is a form of non-formal education that organizes various training activities and is located in Jambi City. One form of training held is infographic video-making training. So far, the training activities given to students are the delivery of material through power points. The final results of the training activities provided by delivering material through power points are not optimal. Therefore, it is necessary to carry out media development solutions in the delivery of training materials using adobe flash premiere cs6. This study aims to develop a medium for delivering material for making infographic videos based on adobe premiere cs6 using the analysis, design, development, implementation, and evaluation (ADDIE) model. The results showed that the training material for making infographic videos using adobe premiere cs6 was effective as shown by the results of an assessment conducted by multimedia experts based on three aspects, namely display, operation, and interaction. The percentage of the results of the assessment of the three aspects is 91%, with the highest percentage being in the operational aspect at 93% and followed successively by the interaction aspect (92.20%), and the display aspect at 87.40%. Meanwhile, the assessment carried out by the training participants was seen from four aspects, namely benefits, appearance, interaction, and independent learning. The percentage of the four aspects of an assessment is 88.10% with the largest percentage being in the interaction aspect, which is 92% and the lowest percentage is in the independent learning aspect, which is 80%.
Retorica e logica nella critica di Lorenzo Valla del quadrato delle opposizioni

In this paper I discuss Lorenzo Valla’s criticism of the traditional Square of Opposition displayed in the second book of the Dialectica. I show that, according to Valla, the opposition rules of the propositions must take into account both common speeches and the correct use of Latin language, not the formal link occurring between the parts of propositions. In Valla’s perspective, this theoretical change is carried out through rhetoric and philology, and it involves a reassessment of the arts of the trivium. As regards this topic, I argue that Valla aims niether to reduce dialectic to rhetoric nor to replace the former with the latter, but rather to establish some rhetorical principles as a better-suited way to set the opposition rules, because they take into account the linguistic context in which these rules apply.
Plug-and-Play Visual Subgraph Query Interfaces

The preceding chapter introduced a representative set of state-of-the-art visual subgraph query interfaces (VQIs) in the industrial and academic world. Although these VQIs enable subgraph query formulation without the need for end users to be familiar with the syntax and semantics of a graph query language, they suffer from several drawbacks that adversely impact not only their ease of deployment on increasingly diverse graph-structured data sources but also in promoting top-down and bottom-up search. In this chapter, we formally introduce the notion of plug-and-play (PnP) visual subgraph query interface (PnP interface for brevity) to mitigate these drawbacks. We begin by first summarizing the assumptions made by existing VQIs that lead to their limitations in Sects. 4.1 and 4.2. Next, in Sect. 4.3, we articulate the key design principles for realizing a PnP interface that can address these limitations. We formally introduce the architecture of a PnP interface in Sect. 4.4 based on these principles. We conclude the chapter by highlighting the benefits brought by a PnP interface.
Behavior Analysis on PLN Mobile Users Using UTAUT Method

The advancement of information technology is currently accelerating in all aspects of life. The presence of information technology, which is constantly evolving, makes it easier for users to use information systems. Technological advancements show that information technology is not currently required for businesses or organizations. PT. PLN (Persero) is a State-Owned Enterprise (BUMN) in the electricity sector that controls, supplies, and serves the community's electricity needs. PT. PLN (Persero) is committed to improving electricity services for all customers. PT. PLN (Persero) provides innovation in the form of the PLN Mobile Application to improve electrical services. The PLN Mobile Application provides users with up-to-date information on electricity services, allows them to register independently based on their needs, and calculates costs. This research aimed to identify the behavioral factors influencing users' acceptance of the PLN Mobile Application. The UTAUT model was used for the research, and it was modified with seven variables: performance expectation, effort expectation, social influence, facilitating conditions, trust, information quality, and behavioral Intention. Sampling using the Probability Sampling Technique, with Random Sampling as the sampling type. The sample size was 400 respondents from Surabaya City who have used the PLN Mobile Application. SEM-PLS and SmartPls 3 software were used to analyze research data. According to the research finding, the factors influencing Behavioral Intention or user behavior on the PLN Mobile Application were Performance Expectancy, Effort Expectancy, Facilitating Conditions, and Social Influence (p-value 0, 05). In contrast, Trust and Information Quality had no positive and insignificant effect on Behavioral Intention.
Investigating implicature in the machine translation of selected conversations from the novel ‘The hunger games’

This study aims at investigating implicatures in the machine translation of selected conversations from the novel “The Hunger Games” by Collins (2008). The selected conversations are nine conversations taken from the beginning, middle and end of the novel from crucial points in the novel’s plot and are conversations that push the action of the novel forward. This study analyzes conversational implicatures according to Grice’s maxims (1991). It specifically examines the MT system’s translation of instances where these maxims were flouted in the source text. This is done through putting the novel’s conversations in to Google translate and the output translation is then analyzed and compared with the source text’s implicature . The study reaches the following findings: the MT system can translate conversational implied meanings correctly when the maxims of relation or quantity were flouted. This is due to the fact that it translates the utterance literally and thus the same effect is mimicked in the target text. However, the implied meanings created through the flouting of quality or manner maxims are harder for the machine to translate. Therefore, researchers in the field of machine translation should work to improve the machine translation regarding implicature created through the flouting of these two maxims.
Video Recommendation System using Collaborative Filtering - A Systematic Review

Recommendation System is basically an algorithm that recommends useful content like videos, images or information to people. Like, choosing which movie to watch, which item to purchase, which book to read, etc. based on user’s actions on previous views. There are various algorithms used to perform this recommendation technique. This paper reviews different algorithms of recommendation system used in different applications where video/visual broadcasting is involved and it concludes how collaborative filtering is the most commonly used method out of all.
Quartering of the Disabled Team in Krasnoyarsk in the 1820s: Microhistorical Analysis

In the Russian Empire from 1764 to 1864 existed disabled teams, which included military personnel who had lost the ability to serve in the military, but were able to perform the functions of maintaining public order in provincial cities.The support of disabled teams was entrusted to the local population.In the article the issues of accommodation and housing for employees of the disabled team in Krasnoyarsk in the first third of the 19th century are considered, using the methods of microhistorical analysis of documents from the State Archives of the Krasnoyarsk Territory, first introduced into the scientific use.The basic rules for the quartering of single and family military invalids from the lower ranks and non-commissioned officers are presented.Also, the features of the fulfillment, as well as the procedure of refusing of housing obligation by the city commoners of Krasnoyarsk are analyzed.The characteristic of the social status of the citizens involved in obligation and released from its performance is provided.The problems of the relationship between the local population and the representatives of the disabled team, located in the apartments of citizens, were studied.Specific examples of both Krasnoyarsk residents repeatedly providing apartments for members of the disabled team and conflict situations that were resolved with different results for their participants are considered.With that in mind, a conclusion was reached about the effectiveness of organizing public charity for war invalids with the involvement of ordinary citizens in providing them with housing in a provincial city.
Dancing feet and gecko toes

Groove is a feeling On the dance floor, the warmth of a “disco inferno” can certainly be felt, even when its flames are invisible. At least that’s what a recent study on inaudible bass and dancing found. Dance floor science is one subject of study at LIVELab, a unique fusion of performance hall and research facility, which is part of the McMaster Institute for Music and the Mind. Centered on exploring the interplay of science and the arts, LIVELab has the capability to manipulate acoustics in real time while recording the motion and physiological responses of both performers and audience members. Recently, LIVELab hosted an electronic music concert to study whether deep bass contributes to groove, even if inaudible. Every 2.5 min of the continuous 55 min concert, the researchers dropped a beat so low— 8–37 Hz—that it was below the range of human hearing. The lucky dance floor participants,
A Survey of Numerous Text Similarity Approach

One of the most common NLP use cases is text similarity. Every domain comes with a variety of use cases. The most common uses of text similarity include finding related articles/news/genres, efficient use of search engines, classification of related issues on any topic, etc. It serves as a framework for many text analytics use cases. Methods to solve text similarity use cases have been around for a while, but the main drawbacks of the old methods are loss of dependency information, difficulty remembering long conversations, exploding gradient problems, etc. Recent advanced deep learning-based models pay attention to both contiguous and distant words, making their learning ability more rigorous. This white paper focuses on various text similarity techniques that can be used in everyday life to solve these use cases.
Gender Differences Influence Student’s Numeracy Literacy in Secondary Schools in Kolaka Regency, Indonesia

This study aims to describe students' numeracy literacy skills by gender, and analyze inferentially the differences in numeracy literacy between male and female students. The sample of this study involved 48 students of MTs Negeri 1 Kolaka consisting of 21 male students and 27 female students. Research data were collected using numeracy literacy test instruments, data analysis includes: (1) descriptive analysis that aims to describe students' numeracy literacy ability which includes mean score, standard deviation and variance; and (2) inferential analysis aimed at determining differences in numeracy literacy skills between male students and female students using independent sample t tests on the condition that the normality and homogeneity of the data are met. The results of the study include: (1) descriptively, including: students' numeracy literacy ability is in the low category, and the numeracy literacy ability of female students is higher than that of male students; and (2) inferentially, including: data on students' numeracy literacy ability are normally distributed, and homogeneous, and there is no difference in numeracy literacy ability between male and female students.
Biophysical characteristics of Wosi Watershed area in Manokwari Regency, Indonesia

Flood is number one Indonesian natural disaster in the last 10 years and its occurrence at Manokwari is frequently reported. Biophysical condition is playing a key role in carrying capacity of this catchment area.This study is to determine biophysical characteristics of Wosi Watershed to manage and mitigate flooding in Manokwari. Spatial analysis and field observation methods were used to collect the data. Biophysical variables are rainfall, watershed morphometric, slope, and land used. Carrying capacity is measured using flow regime coefficient and annual flow coefficient. The results showed that the heavy rainfall (&gt; 100 mm) throughout the ten years with 10.5 wet months at average resulting very wet tropical climate. This watershed has an area of 2,346.32 ha, its circumference of 29.95 km2 with river length of 8.38 km resulting 0.33 (triangle) and 1.027 (triangle) for Rc and Re, respectively. This morphometry is rectangular and slightly oval(triangular) formed of four rivers with drainage pattern of dendritic, which resembles the shape of a tree branch/twig. Steep slopes are dominant (58.5%), with non-forest area (62%) of the flat and steep slope for settlement (698 ha), and flat slope for mixed dry farming (707 ha). From 2016-2020, river water flow changes rapidly from low to very high to generate flooding, but the carrying capacity is sometime changeable from good to bad. Water drainage, retaining walls, replantation, early warning system, and flooding leaflets mitigation campaign, are structural and non-structural mitigation could be parallelly conducted to manage and mitigate the flooding risks in future.
Multiple access steganographic method based on code control and frequency arrangements

The development, as well as the wider practical application of modern steganography, leads to the need to create steganographic methods with multiple access, which would be able to ensure the simultaneous transmission and division of information from several users in a steganographic channel.The currently known multiple-access steganographic methods are based on MC-CDMA technology and do not show how exactly the embedding and extraction of additional information should be performed.The purpose of this paper is to develop a multiple-access steganographic method based on code control and frequency arrangements.This purpose was achieved through the development of a steganographic method with code control and the use of frequency arrangements based on double-cyclic Reed-Solomon codes over Galois fields GF(q), which provides separate embedding of information by each user at any time which is convenient for him using a personal frequency arrangement.It was proposed to construct the frequency arrangements on the basis of Reed-Solomon codes over the Galois fields GF(5) and GF(13).The characteristics of the developed method are researched, within which it is shown that the PSNR of the resulting steganographic message depends on the number of users simultaneously transmitting information through the steganographic channel.With the number of simultaneously operating users N8, the PSNR values remain at an acceptable level.During the operation of the proposed steganographic method, the occurrence of intra-system interference in the steganographic channel was detected with the number of users simultaneously transmitting information N>q, however, when using frequency arrangements based on the Reed-Solomon code over the GF(13), their effect is insignificant with a practically justified number of divided channels.The developed steganographic method is a rational solution if it is necessary to organize a steganographic channel with multiple access and can provide flexible resource allocation: the operation of the required number of users with a given bandwidth and the required perception reliability.