Reviewerly/exHarmony huggingface dataset:
THE SYNTAX OF TAMIANG LANGUAGE ACEH PROVINCE

Syntax is the study of rules for combining words into a sentence. The purpose of this research is to find out how the syntax of Tamiang language especially the sentences that are construction in the Language such as the patterns of phrases, clauses, and sentences. This research used descriptive design. The data in this research were collected through interviewing, noting and translating, recording and transcribing all utterances of Tamiang language. The number of subjects were about 24 persons. This research resulted that Tamiang language has four kinds of phrases. Meanwhile, Tamiang clauses have two forms: complete and incomplete form. The complete form has two patterns: subject-predicate and predicate -subject. Based on the parts of speech, Tamiang clauses have five forms: nominal clause, verbal clause, adjectival clause, numeral clause and prepositional clause. There are four kinds of sentences in Tamiang language: declarative sentence, imperative sentence, interrogative sentence and exclamatory sentence.Key Words: Syntax, Sentences, and Tamiang Language
ALGORITMA C4.5 DALAM MENGUKUR TINGKAT PENGETAHUAN SISWA TERHADAP PELAJARAN BAHASA INGGRIS

This study aims to categorize the level of students' knowledge of English lessons. To understand the lesson, the teaching and learning process is certainly very important for a student. Achievement of student knowledge is the main function of the existence of an educator. The large number of vocabulary that often sounds foreign to the ear makes it difficult for students to solve English questions because it is difficult to translate. The data source was obtained from students of class VII (seven) at SMP N 03 West Karawang who filled out an English knowledge questionnaire. The C4.5 algorithm is the classification method that is used, and is assisted by the RapidMiner application. The attributes used are student learning methods, learning tools, teacher teaching methods and student interest and student ambition. The results obtained from this study, the value of gain and entropy attributes obtained 23 English knowledge decision rules where the understanding status totaled 12 rules, the status did not understand totaled 11 rules. The accuracy resulting from classification modeling using the C4.5 Algorithm from RapidMiner is 78.12%. The application of the Algorithm C4.5 classification method can be implemented in order to provide new information related to the concept of students' knowledge of English lessons.
ANALISIS DAN PENGEMBANGAN SISTEM INFORMASI PENERIMAAN MAHAMAHAMAHASISWA BARU BERBASIS CODEIGNITER PHP FRAMEWORK

This study aims to develop a New Student Admissions Information System Based on Codeigniter PHP Framework. This software serves to simplify the process of registering new students who so far still use paper documents and Microsoft Excel. This study also aims to test the software based on McCall's quality factors which include correctness, reliability, efficiency, integrity, and usability. This research method is Research and Development. The development model used is Waterfall which consists of analysis, design, implementation, and testing. The data in this study were obtained from: (1) the correctness test using the KLOC calculation; (2) reliability testing using Blitz, Loader, LoadImpact, and Blazemeter; (3) efficiency testing using Pagespeed Insights, YSlow, Pingdom Tools, and Websitetest; (4) integrity testing using Acunetix and Netsparker; and (5) usability testing using the PSSUQ (Post-Study System Usability Questionnaire) questionnaire on fifty one respondents including lecturers, academic administration and students at Jabal Ghafur University.Keywords: Information Systems, Admission of New Students, CodeIgniter, McCall
Light Strands in Slit Diffraction: Confirmatory Visualization in Media Free Environment

Understanding of the makeup of light has swayed between concepts of particles, waves, and hybrid models. The classic double slit experiment provided seemingly conclusive support for wave theory of light with its resultant fringe patterns which were thought to only be due to wave interference. However, previous experiments have shown that light stratifies into strands not waves after diffraction that can be directly visualized utilizing a water vapor cloud chamber. A potential limitation of this approach is interaction of vapor media particles with light resulting in conversion of waves into particles, confounding the results. This experiment was designed to avoid any media interference by utilizing a moving screen in air along with extended photo exposure time to capture light behavior in free space after diffraction. In line with prior cloud chamber experiments, discrete light strands were visualized after diffraction through double slits. Distinct, isolated light strands, not waves, were again noted as light propagated through free space. Light strands were again visualized directly creating the pseudo-interference fringe pattern, counter to the concept of wave interference. Variations of the experiment using focal obstructions and hollow tubes did not demonstrate any strand loss or downstream reverberations which would have been characteristic of waves. Confirmatory visualization of distinct light strands after diffraction in a media free environment further supports the particle theory of light and questions wave theory. Diffractive fringe patterns are again shown to be created by the phenomena of discrete radiating strands, not wave interference, with its resulting implications.
High-frequency Noise Removal of Vintage Songs in Audio Cassettes using Signal Processing Techniques

&#x0D; From 1960 to the early 2000s, the audio cassette was one of the three most used storage devices for prerecorded music, alongside gramophone records (LPs) and compact discs (CDs). A compact cassette consists of two miniature spools, between which a magnetic tape is passed and wound. The tape head in tape recorders and cassette players is used to store and play audio tracks in these magnetic tapes by converting the electric signal to a magnetic fluctuation and vice versa. The sound quality of an audio track recorded on a compact cassette is decent. However, as these cassettes are stored in the Earth’s magnetic field for longer periods, the effect from it influences magnetic particles to change their orientation and distort the recorded audio signal. As a result, high-frequency noise is generated in the audio signal, resulting in a great disturbance when listening to songs and other audio recordings on vintage cassettes.&#x0D; 168Therefore, the removal of such noises while minimizing the impact on the original audio signal will make sure the listener gets to enjoy the original quality of the vintage audio recordings. Fourier transform of a given distorted audio file (in “wav” format) was obtained to identify the high-frequency noise using Wolfram Mathematica 12.3. Then a variable “m” was introduced to the program to identify magnitudes of high-frequency components and remove their effect on the original audio recording. A trial-and-error approach was taken to identify the adequate “m" value for each channel of a given audio signal. Vintage songs were used to evaluate the accuracy of the developed method in this study. It was identified that the suitable “m” value changes for each channel in each song. Therefore, it is impossible to state a constant value for the variable “m”. However, the accuracy of the output also depends on the hearing frequency of the person, and the audio equipment being used. As an application, this technique can be used to conserve vintage songs that were originally stored in compact cassettes and spools, because it allows the user to control the number of high-frequency components removed from the distorted audio signal.&#x0D; Keywords: Signal Processing Techniques, Fourier Transforms, Mathematica, Noise Removing,Audio Cassettes
Hybrid Method dalam Menentukan Rekomendasi Penerima KIP Kuliah

Indonesia Smart Card (KIP) College has been applied by the government in accordance with the instructions of the president where it is expected that with the Kip college students who are not able and graduated college will be able to continue to a higher level of Higher Education. In the selection of candidates for college KIP recipients, they are selected through several criteria ranging from parental work, a parental income, and others. In the selection system, inaccuracies are still founding for Kip college recipients, this is a discrepancy that is entitled and not entitled to receive Kip assistance. The importance of a decision support system that aims to facilitate decision-making. SPK method that can be used there are several methods one of which is a hybrid method. By using a hybrid method with the stages of calculation of the weight of the criteria to determine the consistency of the criteria and obtained an CR value of 0.08, this proves the weight of the criteria used are consistent. Furthermore, the data comparison of criteria and alternatives in the process that will produce data into two types, namely data recommendations Kip college recipients and non-recommendation data.
Management Information System Web Based Visitor Data Center on PT. Media Nusantara Citra. Tbk (MNC Media)

Information technology is currently developing very quickly. Hardware and software are tools created to facilitate human work. PT Media Nusantara Citra is a company engaged in the field of information media; of course, it is very dependent on information systems in its operations. This is to provide support and make it easy to make decisions. And one of them that is still managed manually is the management of visitor activity data in the PT Media Nusantara Citra data center. Departing from this, the author chose the theme of the web-based Visitor Management Information System at PT Media Nusantara Citra, what is currently happening in the management of visitor data in the data center is the inaccuracy of visitor data every day, and the lack of efficiency in document recording and storage, starting from recording data processing of incoming visitor activities, recording various types of visitor data activities that have been completed, to preparing reports on incoming visitor data activities and various types of visitor activities that have been completed, the authors propose a web-based Visitor Management Information System to be a solution to some of the above, and information system-based visitor data management is expected to increase effectiveness and efficiency in data management.
Student Identification Based on Patterns of Association For Student Misbehaviour Using Frequent Pattern Growth Algorithms

Student infractions are incidents often committed by students who break the rules at school. This naturally worries school authorities and overwhelms them with student misbehavior. Student rule-breaking is a common problem that can interfere with a safe and orderly learning environment. The more students break the rules, the greater the impact on several aspects, including student achievement, discipline, suboptimal teaching and learning activities, and students' social lives outside of school. Identifying students who are prone to rule violations can help school officials implement more effective prevention programs. Data mining is a process of extracting information from large data sets to discover patterns and relationships hidden within them. This study aims to identify frequent student infractions using the Frequent Pattern Growth algorithm. The Frequent Pattern Growth (FP -growth) algorithm is used to generate frequent itemsets that are then used in the association rules process. The association rules process aims to find rules or relationships between violations based on the discovered Frequent Itemsets. This process is influenced by predefined minimum support and minimum confidence values. A Minimum Support value of 30% and a Minimum Confidence value of 50% are used to obtain rules with a sufficiently high confidence level. It is expected that the identification results from this study will provide a better understanding of the types of violations commonly committed by students in school. This information can be used by school officials to develop more effective prevention strategies and focus on.
USING PYTHON FOR TEACHING CLASSIC MECHANICS IN UNIVERSITY STUDENTS

This article contains codes in Python programming language as a tool to support the teaching of classical physics, presents a menu of options for calculating magnitudes within uniformly varied rectilinear motion, parabolic motion, free fall, and uniform circular motion. The written codes can be verified using Python online, and there is also a code that does require the installation of Python and additional libraries to be able to see the graph of position-time, speed-time and acceleration-time. It was verified that each code works in two different online Python links and for a better understanding of the user the calculation menu is explained in parts.
Paradigm Fitness Indonesia Digital Marketing Communication Through Instagram

Sport has now become a way of life for people. Another growing trend in daily activities and efforts to live a healthy lifestyle is exercise. Additionally, regular exercise can keep the body in shape and boost immunity to a variety of ailments. Sports activities can be done both indoors and outdoors. Outdoor sports can be done in parks and fields, which are generally free. In contrast to indoor sports, which tend to be paid for, such as in fitness centres that has grown, one of them is Paradigm Fitness Indonesia. This study's goal is to know how Paradigm Fitness Indonesia uses Instagram to communicate with customers. This study used Krippendorff's content analysis of Instagram postings @paradigmfitnessindonesia as its methodology during January and June 2022. This study's findings lead to the conclusion that Paradigm Fitness Indonesia conducts marketing communications by displaying posts on Instagram @paradigmfitnessindonesia, which are more dominated by posts containing relating to public relations and publicity. Through these public relations and publicity posts, Paradigm Fitness Indonesia brings up the figures of pageant actors who are required to maintain their body appearance. In addition, Paradigm Fitness Indonesia also creates a challenging program for members every month (monthly challenge) to further build bonds between members, coaches/trainers, and Paradigm Fitness Indonesia.&#x0D; Abstrak&#x0D; Olahraga kini telah menjadi gaya hidup masyarakat. Tren lain yang berkembang dalam aktivitas sehari-hari dan upaya untuk menjalani gaya hidup sehat adalah olahraga. Selain itu, olahraga teratur dapat menjaga tubuh tetap bugar dan meningkatkan kekebalan terhadap berbagai penyakit. Kegiatan olahraga dapat dilakukan baik di dalam maupun di luar ruangan. Olahraga luar ruangan dapat dilakukan di taman dan lapangan, yang umumnya gratis. Berbeda dengan olahraga indoor yang cenderung berbayar seperti di fitness center yang sudah berkembang salah satunya Paradigm Fitness Indonesia. Tujuan penelitian ini adalah untuk mengetahui bagaimana Paradigm Fitness Indonesia menggunakan Instagram untuk berkomunikasi dengan pelanggan. Penelitian ini menggunakan metode analisis konten Krippendorff pada unggahan Instagram @paradigmfitnessindonesia selama bulan Januari dan Juni 2022. Temuan penelitian ini menghasilkan kesimpulan bahwa Paradigm Fitness Indonesia melakukan komunikasi pemasaran dengan menampilkan postingan di Instagram @paradigmfitnessindonesia, yang lebih didominasi oleh postingan yang berisi terkait untuk hubungan masyarakat dan publisitas. Melalui unggahan kehumasan dan publisitas tersebut, Paradigm Fitness Indonesia mengangkat sosok-sosok aktor kontes yang dituntut untuk menjaga penampilan tubuhnya. Selain itu, Paradigm Fitness Indonesia juga membuat program yang menantang bagi member setiap bulannya (monthly challenge) untuk lebih membangun ikatan antara member, coach/trainer, dan Paradigm Fitness Indonesia.
Future Smart City with Less Traffic Congestion Model Enabled by (IoT)

The advancement in wireless telecommunication network has increase the accessibility of more users to wireless connectivity. With the advent of the fifth-generation (5G) wireless network, a seamless connectivity is available for internet users globally. A future smart city is a metropolis that utilizes information and communication technologies (ICT) to grow its functionality effectively to disseminate information among the public and to develop the quality of government facilities and the welfare of the citizen. The Internet of Things (IoT) refer to the interconnection of several systems, devices or physical objects/things which are driven by sensors, software, and other equipment in order to interconnect and interchange data with other devices and systems through the internet. The Internet of things (IoT), is a revolutionary method that allows a diverse number of applications to be interconnected in order to create a single communication architecture. Future smart city has resulted in the increase in population, hence there is need to develop a smart traffic light system to help in managing the problem of future smart city; traffic congestion. The Internet of Things (IoT) a key features necessary for employing a large-scale in IoTS are low-cost sensors, high-speed and error-tolerant data communications, smart computations, and numerous applications which helps in solving these challenges associated with traffic congestion. It enables a smart environment, smart energy, and smart transportation system. In this paper, we shall discuss IoT technology, review some literatures on application area of Internet of Things (IoT), and challenges of IoT. And also discuss the applications of IoT, in smart city development, and traffic congestion management in smart city design, and how it proffers solution to future smart city problem.
Admission BOT: Unleashing the Potential of Neural Networks in Streamlining the Admission Process

This paper discuss the problems identified in admission guidance process conducted by the Government Agency where students, parents and other stakeholders of admission do not understand complicated language used in the policy documents and misinformed by the lack of knowledge. This problem can be reduced by the creation and development of an admission Auto-Reply Bot designed to reduce human efforts and provide automated solutions to queries related to admission process. For this dataset of question and answers are created using information brochure data available in public domain which is conducted by one of the government agency [4]. Different NLP techniques such as tokenization, lemmatization &amp; stemming are applied to the data this data later stored in JSON. Artificial neural network is used to train this dataset. ANN model is trained, Chatbot performed well with selected question set, accuracy of the model increased to 0.9918 using hyper parameters adjustments such as dropout and Adam optimizer.
Context Mining with Machine Learning Approach: Understanding, Sensing, Categorizing, and Analyzing Context Parameters

Context is a vital concept in various fields, such as linguistics, psychology, and computer science. It refers to the background, environment, or situation in which an event, action, or idea occurs or exists. Categorization of context involves grouping contexts into different types or classes based on shared characteristics. Physical context, social context, cultural context, temporal context, and cognitive context are a few categories under which context can be divided. Each type of context plays a significant role in shaping our understanding and interpretation of events or actions. Understanding and categorizing context is essential for many applications, such as natural language processing, human-computer interaction, and communication studies, as it provides valuable information for interpretation, prediction, and decision-making.&#x0D; In this paper, we will provide an overview of the concept of context and its categorization, highlighting the importance of context in various fields and applications. We will discuss each type of context and provide examples of how they are used in different fields. Finally, we will conclude by emphasizing the significance of understanding and categorizing context for interpretation, prediction, and decision-making.
Randomized Ensemble Approach with ID3 Algorithm For the Prediction datasets with Imbalance Problem

Nowadays, it is significant to make accurate prediction model by handling imbalance problem. When the larger dataset has been used in the prediction model, that data should be classified into classes which gives ‘0’ and ‘1’ to indicate negative and positive results. While classifying this target value, the larger number of instances can reside in one class and the remaining lower number of instances can be stored in another class. Because of this unequal distribution of data, the machine can be biased and there is high possibility to give wrong predictions. An inaccurate Dataset leads to misprediction. Hence, the imbalanced prediction dataset has been taken. This paper gives a proper information on Randomized ensemble approach with ID3 classifier for the imbalanced prediction dataset.
Distributed Improved Deep Prediction for Recommender System using an Ensemble Learning

If online businesses possess valuable interest for suggesting their items by scoring them, then digital advertising gains their profits depending on their promotions or marketing task. Web users cannot be certain that the products handled via big-data recommendation are either advanced or interesting to their needs. In recent decades, recommender system models have been widely used to analyses large quantities of information. Amongst, a Distributed Improved Prediction with Matrix Factorization (MF) and Random Forest (RF) called DIPMF model exploits individual’s desires, choices and social context together for predicting the ratings of a particular item. But, the RF scheme needs high computation power and time for learning process. Also, its outcome was influenced by the training parameters. Hence this article proposes a Distributed Improved Deep Prediction with MF and ensemble learning (DIDPMF) model is proposed to decrease the computational difficulty of RF learning and increasing the efficiency of rating prediction. In this DIDPMF, a forest attribute extractor is ensemble with the Deep Neural Network (fDNN) for extracting the sparse attribute correlations from an extremely large attribute space. So, incorporating RF over DNN has the ability to provide prediction outcomes from all its base trainers instead of a single estimated possibility rate. This fDNN encompasses forest module and DNN module. The forest module is employed as an attribute extractor to extract the sparse representations from the given raw input data with the supervision of learning outcomes. First, independent decision trees are constructed and then ensemble those trees to obtain the forest. After, this forest is fed to the DNN module which acts as a learner to predict the individual’s ratings with the aid of novel attribute representations. Finally, the experimental results reveal that the DIDPMF outperforms than the other conventional recommender systems.