Reviewerly/exHarmony huggingface dataset:
Aspect-Based Sentiment Analysis On FLIP Application Reviews (Play Store) Using Support Vector Machine (SVM) Algorithm

The development of fintech has driven the rapid growth of e-wallets like Flip, offering a convenient solution for interbank transfers without administrative fees. User reviews on the Play Store serve as crucial feedback for understanding the user experience. This research utilizes aspect-based sentiment analysis (ABSA) in combination with the SVM method to detect opinions, perceptions, and reviews pertaining to Flip's speed, security, and cost aspects. The objective is to provide valuable insights to both users and companies regarding their experiences with Flip in conducting financial transactions. The study employs a dataset comprising 13,500 preprocessed and cleansed data points, followed by TF-IDF vectorization. The data is divided into training and testing sets, utilizing techniques such as the train-test split and K-Fold Cross Validation to assess model performance. GridSearch analysis reveals that specific parameter combinations, notably C=1.0 and test_size=0.1, yield high accuracy across all aspects, with the linear kernel displaying the highest overall accuracy. Model evaluation is conducted using the confusion matrix and classification report, presenting accuracy, precision, recall, and F1-scores for each aspect. Notably, the Support Vector Machine model performs well, particularly in the speed, security, and cost aspects, where the cost aspect demonstrates exceptionally strong results. In summary, this study employs ABSA to analyze Flip application reviews, with the Support Vector Machine model showcasing impressive performance across various aspects, providing valuable insights for users and companies engaging with Flip's financial transaction services.Keywords: aspect-based sentiment analysis, support vector machine, reviews, Flip
Developing and Implementing a Quantum Algorithm for the Sliding Mode Controller Using Multiple Qubit Operators: Application to DC Motor Speed Drive

With the advent of quantum computing, almost all classical computing concepts must be translated into quantum equivalents. Control theory, in particular, requires a large numbers of calculations. This paper designs and presents a quantum sliding mode controller. The controller uses two qubit states, one for detecting tracking errors and the other for determining the signs of the errors. The control signal to be applied to the system is stored in the third qubit state. This new controller is implemented on a DC motor to control the angular velocity using electrical current as an input signal. In terms of tracking error energy performance, the results show that the quantum sliding mode controller is just as efficient as the classical sliding mode controller. However, the quantum controller outperforms its predecessor by using 76% to 79% less control energy, allowing for smaller actuators. This represents a significant advancement in control theory in the era of quantum computers. Indeed, actuator control energy is the main drawback of the classical sliding mode control and reducing this energy is one of the main challenges for the control community.
DIJKSTRA ALGORITHM IN DETERMINING THE SHORTEST ROUTE FOR DELIVERY SERVICE BY J&amp;T EXPRESS IN BANDUNG

The determination of the shortest route can be done using various methods, one of which is the Dijkstra algorithm. This algorithm is often used in routing problems with minimum weight in computer networks, communication networks and transportation networks. There are several applications of the Djikstra algorithm, namely solving the problem of the shortest path of neutrosophy, mapping tourism potential, and developing geographic information systems in the health sector. In this research, Dijkstra algorithm will be applied to optimize the mileage of the delivery of goods packages. Data and information namely the address, weight and number of customer packages carried by a courier in one delivery trip are obtained from the drop point of PT. J&amp;T Express in Sarijadi area of Bandung City. Meanwhile, data about mileage is obtained from the Google Maps application. All this data is used to construct an initial model graph that is a connected weighted graph, where the location of a drop point or a customer is a vertex and a road connecting two locations is an edge on the graph. The weight in this graph is the mileage from the drop point to the customers or from one customer to another. Then, the Djikstra algorithm is run on this graph where the drop point is the starting point of the route, so that the courier visits all customers and returns again to the drop point. The resulting route is a cycle in the graph which is the shortest closed route at 1890 meters.
PENGARUH PENGGUNAAN LEMBAR KERJA PESERTA DIDIK ELEKTRONIK (E-LKPD) TERHADAP HASIL BELAJAR MATEMATIKA DI SMA HANG TUAH 1 JAKARTA

Based on the results of observations by researchers at Hang Tuah 1 High School Jakarta, several problems were found in the mathematics learning process, namely the E-LKPD had not been used by teachers at Hang Tuah 1 High School Jakarta. Thus, researchers are encouraged to fulfill research with the following topics: Effects of Using Electronic Student Worksheets (E-LKPD) on Mathematics Learning Outcomes. This study used quantitative research with experimental techniques with the aim of knowing the effect of using Electronic Student Worksheets on mathematics learning outcomes at Hang Tuah 1 High School Jakarta. There were 78 students, including 39 students from class X-3 and 39 students from class X-5 who were used as samples of this study. Class X-3 as an experimental class is taught using the Electronic Student Worksheet. In contrast, class X-5 as the control class was taught using Student Worksheets and was used as a research sample. The results of this study's data analysis show t.count = 4.501615253 &gt; t.table = 1.66515, which means that there is an influence on the Electronic Student Worksheets regarding relevant mathematics learning outcomes. Therefore, it can be concluded that the use of Electronic Student Worksheets has a positive and significant effect on mathematics learning outcomes
PENERAPAN METODE SINGLE EXPONENTIAL SMOOTHING DALAM MEMPREDIKSI JUMLAH PENERIMAAN MAHASISWA BARU

Forecasting is a technique for estimating future data by looking at past data and current data. Admissions of new students at Tribuana Kalabahi University are carried out every year since the founding of the Tribuana Kalabahi University campus, in 2007, the number of new student admissions from year to year has experienced an upward trend, therefore forecasting is carried out using Single Exponential Smoothing. The amount of data from 2007 to 2022 is 16 data. The calculation results with Single Exponential Smnothing have the lowest MAPE value, namely 1.41005% with a value of α = 0.1, the number of new student admissions is 664 people
PENGELOMPOKKAN KABUPATEN/KOTA DI INDONESIA BERDASARKAN MASALAH GIZI BALITA DENGAN MENGGUNAKAN METODE TWO STEP CLUSTER DAN ENSEMBLE CLUSTERING

The purpose of this study was to group districts/cities in Indonesia based on toddler nutrition problems.. The research method used in this research is Two Step Cluster, Fuzzy C-Means and K-Modes method. In the Two Step Cluster method, there are two stages carried out, namely Pre-Clustering and Case of Clustering. In the Ensemble K-modes method, there are two methods, namely Fuzzy C-Means and K-Modes. The data used in this study are secondary data in the form of data on under-five nutrition problems in Indonesia in 2022. After analysis, the grouping results obtained using the Two Step Cluster method consist of 2 clusters, while the Ensemble K-modes method produces 5 clusters
Smart Material Test: Optimalisasi Pengujian Bahan Bangunan Berbasis Web

In designing material requirements, it is very important to do so that the use of materials becomes effective and efficient. Building materials are an important component in producing a reliable quality building structure. One of the efforts made to ensure the quality of building materials is to carry out material tests in the laboratory. The Palembang Aviation Polytechnic materials laboratory performs the testing procedure manually using a calculator or Microsoft Excel. Manual test calculations pose potential problems (error calculation) and must be well-documented. A materials testing calculation application is made for data processing to get better results and more efficient and effective calculations. The research aims to optimize the data processing of building materials testing using an application so that it is more efficient and effective and the data can be well documented. The material was used to calculate fine aggregate and coarse aggregate tests. The research has implemented a web-based Smart Material Test application using the programming language PHP Version 7, Laravel 8 Framework, and MySQL Database to optimize material testing that is more accurate and well-documented. The results show of testing the application, as many as 50 trials for each test found no application errors, and the average calculation difference was 0.0005 or 0.01744%. Thus, the application is very useful in assisting the calculation of building material testing.
Designing a Bandung Perfume Shop Sales Information System Using Python

&lt;p&gt;Bandung Perfume Shop is a company that sells perfume. Based on observations, it was discovered that the Bandung Perfume Shop Information System activities maintain use the traditional way. Sales data collecting or recording operations continue to rely on paper media, specifically notebooks, which are prone to loss and damage, implying that the document preparation system is inadequate. Similarly, everything is done conventionally when it comes to data recapitulation and providing information or reports. Given this occurrence and all of its flaws, particularly low work efficiency, an information system that can replace the prior way is required in order to create efficient work. Information System Design as a solution to the above phenomenon at the Bandung Perfume Shop using the Python application (Object Oriented Programming Language), starting from March 2023. The research aims to provide an information system that can simplify and accelerate employee work processes in processing sales data at the Bandung Perfume Shop. The results of this study were collected in the form of an output Information System from the Python program that was created in outline by automating the old (traditional) system to the new system. The results of this study are projected to have a substantial impact on the sales and recapitulation processes in the future, improving work efficiency at the Bandung Perfume Shop.&lt;/p&gt;
Reservoir computing with error correction: Long-term behaviors of stochastic dynamical systems

The prediction of stochastic dynamical systems and the capture of dynamical behaviors are profound problems. In this article, we propose a data-driven framework combining Reservoir Computing and Normalizing Flow to study this issue, which mimics error modeling to improve traditional Reservoir Computing performance and integrates the virtues of both approaches. With few assumptions about the underlying stochastic dynamical systems, this model-free method successfully predicts the long-term evolution of stochastic dynamical systems and replicates dynamical behaviors. We verify the effectiveness of the proposed framework in several experiments, including the stochastic Van der Pal oscillator, El Niño-Southern Oscillation simplified model, and stochastic Lorenz system. These experiments consist of Markov/non-Markov and stationary/non-stationary stochastic processes, which are defined by linear/nonlinear stochastic differential equations or stochastic delay differential equations. Additionally, we explore the noise-induced tipping phenomenon, relaxation oscillation, stochastic mixed-mode oscillation, and replication of the strange attractor.
DRL-Assisted Network Selection for Federated IoV

Federated learning, a distributed machine learning framework, can be used in many Internet of Vehicles (IoV) scenarios to enable privacy-preserving distributed intelligence. While federated learning avoids transmitting raw data in the learning process, it also requires to transmit learning models between clients and server, where the limited wireless resources is always the bottleneck for performance. In this paper, we propose a deep reinforcement learning (DRL) based approach for selecting the best wireless network in a multi-access environment to improve the performance of federated learning. The proposed approach can enhance the overall robustness of the network with efficient network switching based on network environment. We conduct realistic computer simulations to show that the proposed approach exhibits significant performance advantages over existing baselines.
KEMAMPUAN MENULIS TEKS PROSEDUR DENGAN MODEL DISCOVERY LEARNING PADA PESERTA DIDIK

This research is motivated by the reality in the field to find out the application of discovery learning models to the ability to write procedural texts. This type of research uses a qualitative approach with experimental methods. The subjects of this study were all class XI MAS Al Washliyah 12 Perbaungan, with a total of 241 students. The object of this study was class XI IPA, which consisted of 31 students. In data collection techniques using tests, observations, questionnaires, and documentation. Meanwhile, data analysis was used to obtain scores in the form of results for student work on the ability to write procedural texts using the discovery learning model with an average value of 9.3. Therefore, the influence of the discovery learning model on the ability to write procedural texts has an average value of 9.3. Therefore, it can be concluded that the ability to write procedural texts using the discovery learning model for XI MAS Al Washliyah 12 students in the 2022-2023 academic year is said to have an effect with an average score of 9.3 with an excellent qualification of 86% -95%. Thus, based on the assessment that has been carried out, it can be explained that using the discovery learning model in the writing ability of students XI has the effect of the desired value.
BUKU CERITA GAMBAR SEBAGAI MEDIA PENINGKATAN MINAT BACA SISWA SEKOLAH DASAR

The reading ability of Elementary students is a series of actions that must be developed so that students are not only good at reading but also able to explore and understand the text of reading books. This study shows that several picture books are an effort to increase elementary school students' reading interest. The methodology used in this study is a literature review and reports from various journals. To increase students' interest in reading, teachers must use appropriate media to attract students' attention. Picture storybooks have a function to enrich and support storytelling in the process of understanding the contents of the book. Picture books are one of the tools used in the curriculum. Storybooks feature many pictures to tell a story, character, setting, or whatever. This study describes the development of Elementary school picture storybooks and the benefits of using storybooks as a media in teaching elementary students. The study concludes that students' attraction to develop reading skills and develop previous skills can be done through the use of media, namely the use of stories presented in the media.
USING YOUTOBE VIDEOS TO IMPROVE STUDENT'S READING COMPREHENSION IN ONLINE LEARNING MODEL IN FIRST MIDDLE SCHOOL

ABSTRACT-In improving students' reading comprehension in online learning, it can be done by using the social media YouTube. The use of YouTube to encourage students' enthusiasm for learning during a pandemic can be a solution for the world of education so that it can continue and develop. This study aims to determine the benefits of using Youtube and the obstacles that occur in the use of Youtube in online learning in improving students' reading comprehension in the online learning model in junior high schools. The results of this study indicate that in improving reading comprehension in learning using this youtube video, it has a positive impact on the student learning process during the pandemic. The benefits provided by learning from YouTube are:improve students' understanding in understanding the material provided, the learning provided becomes more flexible, familiar with technological developments through online learning, and increasing student creativity in learning.the slow internet connection in the students and teachers' areas of residence, the small specifications or performance of the cellphones used by students, the large amount of quota required to access YouTube, and the high price of internet quotas, limited access to computers and smartphones. The solution in overcoming obstacles in online learning is that students will be directed to open the video provided via the video link in the WhatsApp Group directly without switching to the YouTube application even though with a lack of time it takes a little longer but this can overcome the use of internet quota because WhatsApp is included. into the e-learning quota.
Assessment of heavy metal content in groundwaters of Ikpe Community, Akwa Ibom State, Niger Delta, Nigeria

Accumulation of heavy metals in groundwater system could portend adverse health consequences to users. Heavy metal content of five randomly selected hand dug wells in Ikpe community, Akwa Ibom State, Nigeria was assessed between April and November 2022. The water was evaluated using standard methods and water quality indices to determine its suitability for human consumption. Eight heavy metals were evaluated using Heavy metal Pollution Index (HPI) and Comprehensive Pollution Index (CPI). The results were compared with the National drinking water standard. Results showed that chromium ranged from 0.001 to 0.20 mg/L, cadmium (0.001 - 0.008 mg/L), nickel (0.01- 0.08 mg/L), manganese (0.001- 0.6 mg/L), zinc (0.36 -1.90 mg/L), iron (0.1 - 0.8 mg/L), lead (0.001 - 0.02 mg/L) and arsenic (0.00 - 0.004 mg/L). HPI and CPI ranged between 44.62-126.30 and 0.18-1.33, respectively. Concentrations of these heavy metals exceeded acceptable limits, except lead and arsenic. The concentration of the metals from wells 2, 4 and 5 were generally higher and/or had values that exceeded acceptable limits. This could be attributed with geogenic and anthropogenic influences as well as the general conditions of the wells and their environment. The water quality indices (HPI and CPI) showed varying levels of heavy metal pollution in line with the heavy metal concentrations. Consequently, it can be concluded that water from wells 2, 4 and 5 is not suitable for human consumption, and it can be used for other purposes.
Performance Evaluation of the Transfer Learning Model in Car Vehicle Detection

Congestion is a common problem that occurs in big cities. It is necessary to make an ITS (Intelligent Transportation System) using computer vision to monitor street density by counting the number of passing vehicles. The basis of vehicle counting is vehicle detection. This study will compare the performance of vehicle detection models in order to make it easier to determine which model is suitable for implementation. The dataset used is the Vehicle Detection Image Set. The models used are InceptionV3, Xception, MobileNet, MobileNet V2, VGG 16, VGG 19, Efficientnet (B7), and Efficientnet V2 (L). The results show that Inception, Xception, Mobilenet, and VGG19 are the models with the highest test accuracy. The VGG 16 model has the shortest training duration while the Efficientnet V2 (L) has the longest training duration.
KESALAHAN EJAAN BAHASA INDONESIA PADA SURAT DINAS DI KANTOR CAMAT SIULAK MUKAI KABUPATEN KERINCI

The purpose of research on Indonesian spelling errors in official letters at the Siulak Mukai sub-district office is to describe errors in punctuation marks and letters. The background of this research is that there are still many errors in using Indonesian spelling in writing official letters at the Siulak Mukai district office. The type of research used is qualitative research with descriptive methods. The data source is official letters issued by the Siulak Mukai sub-district office in 2020 for the January–December period of 25 letters. The data collection technique was carried out through observation and document analysis techniques. Data analysis techniques consist of two activities simultaneously, namely data reduction and data presentation. From the analysis carried out on 25-letter data, it was found that there were errors in using dots in 23-letter data, or 92% of errors. Errors in using commas amount to as many as 14 data letters, or 56% of errors. Slash mark errors can be as high as 10 letters, or 40% of the time. Hyphen error amounts to as much as one letter of data or a 4% error. Capital letter errors accounted for 21 letters or 84% of all errors. Italics errors are as common as four-letter data, accounting for 16% of all errors. The error in using bold letters is four, or 16% of the time.
Meta-Analysis of Inter-Rater Agreement and Discrepancy Between Human and Automated English Essay Scoring

Studies on automatic scoring systems in writing assessments have also evaluated the relationship between human and machine scores for the reliability of automated essay scoring systems. This study investigated the magnitudes of indices for inter-rater agreement and discrepancy, especially regarding human and machine scoring, in writing assessment. The mean of the overall population correlation between automated and human scoring in essay writing was .78. The overall common d effect size was 0.001. Results from this meta-analysis indicated a strong relationship with no discrepancies between automated and human scoring. Both the I2 and Q values suggested that the population correlation values studied seemed to be heterogeneous, in contrast to homogenous d effect sizes. Therefore, it is necessary to investigate the sources of the between-studies variations for r correlations. Practical implications for ways of reporting results of automatic-scoring systems research and limitations of the study are also discussed.
Installing V8 is now even easier

Google’s amazing V8 JavaScript/WASM engine is probably one of the most sophisticated open-source software libraries available today. It is used to power the computation in Google Chrome, NodeJS, and also CloudFlare Workers, which make it possible to run code for your website inside the CDN edges. The R package V8 exposes this same engine in R, and has been on CRAN since 2014.
The Dawn of the Porttinari Multigenre Treebank: Introducing its Journalistic Portion

This paper introduces the journalistic portion of the Porttinari treebank, which aims to be a multigenre NLP resource for Brazilian Portuguese. We report the construction of the treebank, in particular, the human-revised portion with 8,418 sentences, whose annotation process lasted almost three years and involved more than a dozen trained annotators. The full treebank offers to the Portuguese-speaking NLP community nearly 4 million sentences annotated according to the Universal Dependencies framework.