Reviewerly/exHarmony huggingface dataset:
Comparison of MDKA Stock Price Prediction using Multi-Layer Perceptron, Long Short-Term Memory, and Gated Recurrent Unit

Shares are rights owned by a person against a company due to the delivery of capital, either in part or in whole. Investors invest in stocks and try to get maximum results, but many investors are still unsure about the risks involved in investing. To minimize risk, investors need to predict stock prices with an accurate method. Several methods that can be implemented to predict stock data include Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). The research objective to be achieved in this study is to compare the performance of each algorithm in producing a more accurate stock price forecasting model by testing neurons (10, 20, 30) and epochs (50, 75, 100). The research was conducted on the stock price data of PT. Merdeka Copper Gold Tbk (MDKA) which is a mining sector share with the largest capitalization value. Tests on some of the algorithms above got the best results using 82% training data and 18% test data, namely the MLP model with 10 neurons and 100 epochs with a MAPE training data result of 2.325 and a MAPE test data of 2.014. Based on the test results, MLP can predict MDKA stock prices for the 2018-2022 period with good performance and a relatively small error rate, while tests using the LSTM and GRU methods still produce large errors. Thus, it can be concluded that MLP can predict stock prices with more accurate results.
Analyzing Classical and LDI Depth-Aware Image Stitching for Enhanced Virtual View Representation

This article examines two image stitching methods for creating seamless images in stereo vision applications: a classical OpenCV-based approach and a depth-aware technique. Conventional methods, while effective for 2D image stitching, face limitations when applied to 3D scene reconstruction, where accurate depth information is crucial. We introduce a depth-aware image stitching method that utilizes depth maps to enhance alignment and blending in 3D scenes, demonstrating its superiority through comparative experiments. Depth-aware stitching offers notable advantages over classical methods in 3D scene reconstruction, reducing artifacts, minimizing distortions, and providing an accurate 3D representation, emphasizing the importance of depth estimation in image stitching and encouraging further research in this area.
Penggunaan Media Pop-Up Book Berbasis Komik Untuk Meningkatkan Hasil Belajar Siswa pada Mata Pelajaran Pendidikan Kewarganegaraan Kelas III Mi Ma’arif Kliwonan Wonosobo

The aims of this study were to: 1) find out the differences in learning outcomes between students who used comic-based pop-up book media and students who did not; 2) To find out whether comic-based pop-up book media can improve learning outcomes in class III citizenship education subjects that apply comic-based pop-up book media. This research uses a type of quantitative experimental research (quasi-experimental research). The design used in this research is one group pretest-posttest. This research was conducted at MI Ma'arif Kliwonan Wonosobo. There were two samples in this study: the experimental class consisted of 28 students and the control class consisted of 26 students. In this study using observation, tests and documentation to collect data. Meanwhile, the data analysis technique used prerequisite test and hypothesis test. The results of this study show: 1) The calculation of the hypothesis test states that there are differences in student learning outcomes in civics education subjects, namely 11,150 &gt; 2,006 with a significance level of 5% and 11,150 &gt; 2,673 with a significance level of 1%; 2) The increase in pretest and posttest results was carried out by calculating the N-Gain test in the experimental class of 0.774 in the high category.
Sentiment Analysis of Rising Fuel Prices on Social Media Twitter using the Naïve Algorithm Bayes Classifiers And AdaBoost

The government issued a policy of increasing the price of Indonesian fuel oil (BBM) in September 2022. This policy resulted from the war in Europe between Russia and Ukraine, which caused a surge in world oil prices because many respondents complained about the increase in fuel. This condition has caused much controversy or opinion among the public on social media, especially Twitter. With this phenomenon, sentiment analysis uses the Naïve Bayes classifiers algorithms to see how the public responds to government policies. The classification used in this sentiment analysis is Complaint or Not Complaint. Sentiment analysis of fuel rise on Twitter using Naïve Bayes classifier algorithm and AdaBoost Naïve Bayes classifier algorithm is applied to get the best classification By using hashtag tweets The increase in the price of fuel oil (BBM) which was taken 1000 tweets to be Used US a dataset. Data preprocessing consists of Text, Status, removal annotations, Remove hashtags, Remove urls, regexp, Indonesian stemming, and Indonesian stopword removal. The analysis results obtained an accuracy value of 70.69%, precision of 70.49%, recall of 71.45%, and AUC of 0.729 (good classification). Pemerintah mengeluarkan kebijakan menaikkan harga bahan bakar minyak (BBM) Indonesia pada September 2022. Kebijakan ini adalah hasil dari perang di Eropa antara Rusia dan Ukraina hal ini menyebabkan lonjakan harga minyak dunia karena banyak responden masyarakat yang mengeluhkan atas kenaikan BBM. Hal ini banyak menimbulkan kontroversi ataupun opini pada kalangan masyarakat di social media khususnya twitter. Dengan adanya fenomena tersebut, untuk melihat bagaimana tanggapan masyarakat terhadap kebijakan pemerintah maka dilakukan analisis sentimen menggunakan algoritma naïve bayes classifier. Klasifikasi yang digunakan pada analisis sentimen ini adalah Complaint atau Not complaint. Analisis sentimen kenaikan bahan bakar pada twitter menggunakan algoritma naive bayes classifier dan adaboost, algoritma naïve bayes classifier ini diterapkan untuk mendapatkan klasifikasi terbaik. Dengan menggunakan hashtag tweets Kenaikan harga bahan bakar minyak (BBM) yang diambil 1000 tweet untuk di jadikan dataset. Preprocessing data terdiri dari Text, Status, Remove annotations, Remove hastag, Remove url, Regexp, Indonesian stemming, Indonesian stopword removal. Hasil analisis tersebut didapatkan nilai accuracy 70,69%, precision 70,49%, recall 71,45%, dan AUC yang didapat sebesar 0,729 (good classification).
Kaitan Luas Permukaan Pot Bonang Dengan Frekuensi Nada Dasar Yang Dibangkitkan

One of the musical instruments in the gamelan is the bonang instrument. A bonang is a musical instrument with a small, hollow structure. This study was conducted to determine the relationship between the surface area of the bonang pot and the frequency of the basic tone generated, and to find out the results of the variety of sounds on the bonang musical instrument. A bong that was stopped only after the sound was muted was applied to record the audio directly. Using AudioCyti software, a surface area and frequency are then measured, and the output signal is measured using the Fourier transform method. The parameters measured are surface area and frequency. In accordance with the results of this study, there is a connection between surface area, or the basic frequency, which is achieved with a frequency of 0.88363, and frequency, which is obtained with a frequency of 0.986053. So, it is concluded from the study that has been carried out that the surface area has an influence on the frequency. Users can determine the frequency of a bonang musical instrument's fundamental tone by varying its frequency values from lowest to highest and analyzing the output signal with audiocyti software. As a result, each sound produced by a bonang pot is distinct and nonsequential. This is because, like modern musical instruments, a bonang laras slendro does not yet have a set tone frequency.
ANALISIS FAKTOR-FAKTOR YANG MEMENGARUHI HASIL BELAJAR SISTEM INFORMASI AKUNTANSI PEACHTREE MAHASISWA UNAMA JAMBI

This study aims to determine the significant influence of introductory accounting mastery, English vocabulary and computer laboratory facilities on learning outcomes of Peachtree accounting information systems for Unama students. The method used is data collection, namely documentation and tests, the data analysis method used is descriptive and hypothesis testing uses multiple linear regression analysis. This study also uses references from previous studies, namely location, object and dependent variable (y), which are different from previous research. The results of this study indicate that Mastery of introductory accounting, English vocabulary and computer laboratory facilities each have a partial effect on learning outcomes of the Peachtree accounting information system for Unama students, namely indicated by a significant value of 0.038 for the variable of introductory accounting mastery, 0.002 for the vocabulary variable English, and 0.022 for the variable laboratory facilities, each of which shows a value smaller than the significance value of 0.05.
How Digitalized are School Students? Determining Digital Competencies and Motivation Factors in Using Technology for Learning

Technology in education has placed a great necessity in our education system.The teaching and learning process demonstrates more technology optimization due to the uncertain ecosystem that is happening around the globe.New modalities are being introduced as pedagogical supports to enrich students' learning experiences.However, a few issues arose related to motivation and adaptation to digitalization in the learning milieu among young learners.For instance, educators lack competency in utilizing specific technology and less motivation to engage students optimizing specific digital applications supporting their learning in the most effective ways.This research determines the relationship between digital competency and the motivation of secondary school students in the Klang Valley area.A quantitative correlation study design was employed involving 260 students who enrolled in Design and Technology (D&T) subjects from four public secondary schools.A self-developed questionnaire was validated by experts and piloted as instrumentation.The data of this research study was further analyzed using Statistical Package for Social Sciences (SPSS) version 27 software involving descriptive and inferential analysis.The findings were discussed and it is hoped the findings of the study would enlighten the educational stakeholders to spearhead the digitalization effort in the nation.
Multimodal Discourse Analysis of KFC Fried Chicken’s Video Advertisement

In recreating new advertisement during the pandemic, the culinary companies, including KFC Indonesia, take full advantage of using Instagram in promoting their brand and product. This study examined the process of how semiotic system create the overall meaning of the advertisement, used in KFC Indonesia’s Instagram video in order to attract customers. The data of this study were collected from a video advertisement published by KFC Indonesia on Instagram.The video was chosen because it was posted in period of the pandemic.This study employed descriptive qualitative study. This study focuses on the analysis of linguistics, visual, gestural and audio analysis of multimodal system occured in the video. The analysis found that the combination of linguistics, visual, and gestural elements in the video advertisement of KFC Indonesia could maintain the aim of advertisement to influence the customers to purchase the products, eventhough it was spesifictly created for pandemic situation.In linguistics analysis, the study found that the video used formal and standard Indonesian language as the script of the video. Further, the language used could deliver the process of informing new policy to the customers. Meanwhile, the analysis of audio used on the video determined that the use of music and narrator’s voice in the same volume could affect the ambiance of the video. The findings revealed that the video was created to influence the customers to keep buying the products despite the pandemic by delivering the video advertisement in the Instagram account.
The Use of Representations in Supporting Early Mathematics Learning and Problem Solving

Early mathematics or also known as early numeracy is one of the important areas of learning for children's cognitive development at an early age.The learning of Early Mathematics has the goal of fostering young children's capabilities for problem-solving and their interest in mathematics Therefore, a fun and effective learning experience of Early Mathematics very important for prepares children with various important Mathematical concepts in preparation before entering Standard One.One of the ways to enhance the process of learning and to provide a more enjoyable experience of solving Early Mathematics problems is by using representations.Therefore, this study was carried out to identify how representation can help the mastery and support the learning of Early Mathematics to prepare children with a good concept of Mathematics, especially in addition.A total of two 6 years olds children involved as a participant in this study.Descriptive analysis shows that representation can help children make problem solving to the addition operation better and more accurately, as well as easily.The high score in post-test compared to pre-test score also proves that the use of representation in the teaching of additional concepts for Early Mathematics can help children understand Mathematical concepts more effectively.It is hoped this study can serve as a guide for early childhood teachers to provide a more enjoyable experience of solving Early Mathematics problems.
Designing an Android-Based Educational Game for Fruit Recognition in Seruni Pertiwi Preschool

The objective of this research is to design and develop an Android-based educational game for fruit recognition in Seruni Pertiwi Preschool. The educational game application consists of a main menu, fruit menu, and tree menu. The fruit menu includes various fruit options such as bananas, papayas, apples, grapes, oranges, pineapples, watermelons, durians, rambutans, and strawberries. The research methodology employed in this thesis includes data and information collection, system design, software requirement analysis, interface design, coding, testing, and implementation. The Unity 3D engine is utilized for designing the educational game application. Based on the conducted testing, the following conclusions can be drawn: the developed educational game is free from errors based on the black-box testing results. The research findings indicate that the average validation score from user feedback, ranging from user 1 to user 10, is 4.6, which indicates a high level of agreement with the system assessment, falling under the category of "strongly agree".
ANALISIS EFEKTIVITAS PEMBELAJARAN VIRTUAL DALAM PEMBENTUKAN KARAKTER DI SEKOLAH DASAR DAN PERGURUAN TINGGI

The learning process is experiencing development and improvement. Various offers and choices of teachers appeared to carry out the learning process. One of them is by carrying out the learning process virtually. Every learning process certainly shapes the character of students. In this study, researchers wanted to reveal the character that was formed in students through a virtual learning process. The research method used is descriptive research. The results show that the virtual learning process can be carried out efficiently, but it is less effective in building character in students. The decrease in good character and the increase in bad character is the conclusion of this study.
ANALISIS HUBUNGAN LITERASI NUMERASI DAN HASIL BELAJAR SISWA

This article aims to determine the relationship between numeracy literacy and learning outcomes in schools, especially in elementary schools. The method used in this research is descriptive with a qualitative approach. The results of the study show that numeracy literacy has a relationship that influences each other on student learning outcomes, because with students understanding and being able to use skills in managing numbers and symbols properly, learning outcomes especially in mathematics can be further improved than before. In addition, numeracy literacy skills can also improve the ability to solve problems related to numbers, tables and symbols in everyday life. Thus, it can be concluded that numeracy literacy has a very influential relationship with student learning outcomes.
Visual secret sharing and related Works -A Review

The accelerated development of network technology and internet applications has increased the significance of protecting digital data and images from unauthorized access and manipulation. The secret image-sharing network (SIS) is a crucial technique used to protect private digital photos from illegal editing and copying. SIS can be classified into two types: single-secret sharing (SSS) and multi-secret sharing (MSS). In SSS, a single secret image is divided into multiple shares, while in MSS, multiple secret images are divided into multiple shares. Both SSS and MSS ensure that the original secret images cannot be reconstructed without the correct combination of shares. Therefore, several secret image-sharing methods have been developed depending on these two methods for example visual cryptography, steganography, discrete wavelet transform, watermarking, and threshold. All of these techniques are capable of randomly dividing the secret image into a large number of shares, each of which cannot provide any information to the intrusion team. This study examined various visual secret-sharing schemes as unique examples of participant secret-sharing methods. Several structures that generalize and enhance VSS were also discussed in this study on covert image-sharing protocols and also this research also gives a comparative analysis of several methods based on various attributes in order to better concentrate on the future directions of the secret image. Generally speaking, the image quality generated employing developed methodologies is preferable to the image quality achieved through using the traditional visual secret-sharing methodology.
WATER LEVEL PROFILE IN PARIT BERKAT DRAINAGE CHANNEL OF PUNGGUR BESAR

Floods are common natural catastrophes in Indonesia, particularly during the rainy season. The Parit Berkat water catchment region is one of the locations that frequently experience flooding. The channel's capacity must be increased to accommodate the current water discharge, resulting in this condition. Several reasons are responsible for the diminished capacity of the canal. For instance, inhabitants' activities along canal banks might contribute to the siltation of channels. This research aimed to evaluate the influence of tides and rainfall on the flow of the Parit Berkat Canal. This research provided the use of both primary and secondary data. The leading information consists of measurements of the cross-section and length of the channel and the elevation of the tidal water level over 15 days. Secondary data consists of the maximum daily rainfall data received from Balai Wilayah Sungai Kalimantan I (BWSK I) and the location map for the research. The flow profile is simulated using HEC-RAS. The findings demonstrate that when maximum rainfall and low tides coincide, 13 stations are safe in the 2-year return period of rain, eight stations are safe in the 5-year return period, and six stations are safe in the 10-year return period.
The role of an expert in searching premises. Comments in the context of computer forensics

The article is an attempt to prove the importance of the role of an IT expert as a consultant in the search of premises. The author proposes using the expert knowledge of the expert already at the initial stage of the pre-trial investigation in the course of revealing and securing digital traces. The study briefly characterizes the search institution as a non-repeatable evidence gathering step in the context of the specificity of digital traces as future electronic evidence. The main aspects of law enforcement cooperation with the expert in the field of IT as a consultant were also presented, as well as an attempt to indicate the reasons for the insufficient degree of engaging an expert in the indicated specialty at the initialstage of criminal proceedings.
Innovative reform strategy of Chinese language and literature education practice for college students based on information fusion technology

Abstract With the rapid development and updating of information technology and the gradual increase of economic and social influence, the Chinese language, as an important discipline in China’s higher education, has undergone a great transformation in its teaching conditions and teaching environment in the information age. To obtain more reliable information and better reform and innovation, this paper analyzes the machine model established based on information fusion and investigates the employment situation of Chinese language and literature graduates in university colleges and universities in the past five years to analyze the improvement of employment under the information fusion model establishment. The results show that the teaching process of Chinese language and literature can be well optimized through the machine learning model and is no longer homogeneous compared with the traditional teaching process of Chinese language and literature. The information fusion model can provide a certain degree of help in the employment of students in this major. Therefore, the introduction of information fusion technology is indispensable in the process of reform and innovation of the Chinese language and literature, and schools should also increase relevant courses and policies to encourage college students to actively cooperate with the reform and practice process.
EVALUASI PUSTAKA SISTEM INFORMASI AKUNTANSI PADA DATABASE WEB OF SCIENCE (WOS)

This article aims to review and analyze the Topic of Accounting Information Systems published in the Web of Science database. This research uses the Bibliometric method through Vos Viewer and Biblioshiny to show information about trend set, frequency of article production, frequency of authors, and some other information. The results showed that SIA's research, which was first published in the Web of Science database, was recorded in 1975 and reached its peak in 2011. However, the peak of SIA's article production in 2011 was due to a symposium held in China. However, after that, SIA's article production continued to decline and in the 2012-2021 period tends to increase. Other results show that there are no researchers who focus on producing SIA research articles consistently, this is evidenced by the authors who published the most SIA articles, only 4 articles. This low publication proves that collaboration between SIA researchers is lacking so that many articles are single author status.