Reviewerly/exHarmony huggingface dataset:
Rancang Bangun Aplikasi Pemesanan Tiket Kereta Cepat Jakarta – Bandung Khusus Lansia Dan Ibu Hamil Berbasis Mobile Web Secara Online

PT. Indonesia Indonesia Fast Train (KCIC) has begun to build its Project, namely the Jakarta-Bandung Fast Train, look at the application features of PT. KAI access that does not yet have a need for the elderly and pregnant wome to get special service, then in this study the train ticket booking application was designed Fast Jakarta-Bandung Special for the Elderly and Pregnant Women Online-Based Android Web. Ticket booking application This mobile web-based fast train aims to help the elderly and pregnant women make it easier in booking fast train tickets effectively and efficiently because the feature can be used in a reltime, inside in order to improve services aimed at making it easier for the Elderly and Pregnant Women to do Fast train ticket reservations, this application makes the elderly and pregnant women do not need to queue at the time will check in to get into the fast train. This research methodology uses Disciplined methodology Agile Delivery System design phase aims as a preparation for system design, sketching how the system is formed and provide a clear picture of the development to build the system The design of this system using the DAD (Disciplined Agile Delivery) DAD (Ambler and Lines) methodology, 2012). The results of this study are based on innovations of features that make it easy for the elderly and pregnant women to be designed then developed so as to produce a Jakarta-Bandung Cepata train ticket booking application specifically for the elderly and online android-based pregnant women who will help and facilitate the elderly and pregnant women in ordering fast train tickets, fast train ticket transactions and the use of fast trains jakarta-bandung.
Penerapan Metode K-Means Clustering Untuk Mengelompokkan Ketahanan Pangan

Food is a basic need that must be fulfilled and easily accessible by all people. After the end of the pandemic, it still caused several sectors to experience a decline, including the agricultural sector, which experienced a decline which resulted in crop yields also declining. The problem faced by several regions in Indonesia, one of which is the area of Indonesia, is the availability of food yields which has decreased and increased unstable due to lack of information about the grouping of harvest resilience each year. As a result, the food needs of the people in each region are not fulfilled. The purpose of this study was to classify regions with increasing and decreasing yields of food crops in Indonesia using the K-Medoids algorithm. The K-Means algorithm includes a clustering algorithm that is quite efficient in grouping small data and finding the most representative point and being able to overcome outliers. So that it can be used in grouping the effect of productivity and the level of food security.
Penerapan Data Mining Untuk Menentukan Jenis Asuransi Yang Paling Diminati Di Pt Aia Financial Dengan Metode Clustering

Finding information that is concealed in databases is referred to as data mining. Data mining is a process used to extract and find relevant information and related knowledge from numerous very big datasets using statistical, mathematical, artificial intelligence, and machine learning approaches. The steps involved in the data mining process start with the selection of data from the source data to the target data, followed by preprocessing to enhance the quality of the data, transformation, data mining, and stages of interpretation and assessment that result in new information. Organizing data sets into many groups through the process of clustering ensures that objects in one group share a lot in common and differ greatly from those in other groups. Data mining technique K-Means Clustering divides data into one or more clusters. RapidMiner is the program used in this data mining application, which uses the Knowledge Discovery in Databases (KDD) stage. According to this report, AIA Family First Protection, AIA Prolink, and AIA Life Secure are the three most popular insurance products. With the use of this research, PT. AIA Financial will be able to identify the most popular insurance product categories and market these products to the general public.
Game RPG RALANTAS sebagai Media Pembelajaran Pengenalan Rambu Lalu Lintas untuk Siswa Sekolah Dasar

Traffic signs are an important element to be known, especially by elementary school students. Lack of knowledge about traffic signs can lead to accidents while driving. The purpose of this research is to develop an RPG game for introducing traffic signs to elementary school students. The method used in this research is Research and Development with the ADDIE development model, consisting of Analysis, Design, Development, Implementation, and Evaluation stages. Testing conducted includes media testing and material testing using questionnaires for data collection. Data collection techniques involve questionnaires filled out by media and subject matter experts. Data analysis is performed using descriptive statistical analysis techniques. This study shows that the combination of an RPG game containing traffic sign introduction material can serve as a means to introduce traffic signs to students for better recognition. Based on student satisfaction questionnaire data, the System Usability Scale (SUS) score is 80, categorized as EXCELLENT, corresponding to a grade scale of B. It can be concluded that the Ralantas RPG game is highly suitable for use.
Penerapan Data Mining Untuk Memprediksi Pembelian Mobil Bekas Menggunakan Algoritma Naïve Bayes

Database can also be interpreted as a data warehouse. The amount of data collected in the database can be processed to generate valuable knowledge for science. One popular and widely used technique for processing databases is data mining. Data mining is the process of extracting knowledge from large and complex data warehouse. Data mining encompasses various algorithm to generate knowledge, one of which is naïve bayes. The dataset used in this research, employing the naïve bayes algorithm, consists of attributes relevant to the purchase of used cars, such year, transmission, mileage, car condition, and brand. This research aims to produce patterns and additional knowledge for participants in the used car business to identify the supporting factors in purchasing used cars.
Block chain-Based Federated Learning: Incentivizing Data Sharing and Penalizing Dishonest Behavior

With the increasing importance of data sharing for collaboration and innovation, it is becoming more important to ensure that data is managed and shared in a secure and trustworthy manner. Data governance is a common approach to managing data, but it faces many challenges such as data silos, data consistency, privacy, security, and access control. To address these challenges, this paper proposes a comprehensive framework that integrates data trust in federated learning with Inter Planetary File System, block chain, and smart contracts to facilitate secure and mutually beneficial data sharing while providing incentives, access control mechanisms, and penalizing any dishonest behavior. The experimental results demonstrate that the proposed model is effective in improving the accuracy of federated learning models while ensuring the security and fairness of the data-sharing process. The research paper also presents a decentralized federated learning platform that successfully trained a CNN model on the MNIST dataset using block chain technology. The platform enables multiple workers to train the model simultaneously while maintaining data privacy and security. The decentralized architecture and use of block chain technology allow for efficient communication and coordination between workers. This platform has the potential to facilitate decentralized machine learning and support privacy preserving collaboration in various domains.
Modern General Game Playing with Reinforcement Learning

In computational science and robotics, game playing and artificial intelligence (AI) are research areas that have long been studied. RL systems represent a major step towards autonomous systems that comprehend the visual world at an incredibly deep level and are poised to revolutionize the field of artificial intelligence (AI). Game Play is the testbench where environmental variables can be evaluated to generate adaptive, intelligent, or responsive behavior or simulate real-world scenarios. In this survey, we will explore general gameplay (GGP) with reinforcement learning and its various applications. This survey will cover central algorithms in deep RL, including the deep Qnetwork (DQN) and general mathematical and pragmatic approaches taken in the field. The objective of the current review is to examine the history, associations, and recent advances in the field of general game playing with reinforcement learning and its subfields. We conclude by describing several current areas of research within this field.
ANALISIS KESULITAN BELAJAR SISWA KELAS XII IPA SMA NEGERI 9 MANDAU DURI PADA MATERI REPRODUKSI SEL TAHUN AJARAN 2021/2022

This study aims to describe and determine students' learning difficulties in cell reproduction material and factors that affect student learning difficulties. The type of research used is quantitative descriptive research. The sample determination technique is to use a saturated sampling technique. The research sample was 3 classes, namely class XII IPA1, XII IPA2, and XII IPA3 which totaled 100 students. Data on student learning difficulties were obtained through the results of questionnaires, teacher and student interviews, and documentation. The results showed that the average learning difficulty of students in cell reproduction material through questionnaires was 69.10% included in the high category. The learning difficulties of students, namely on the indicators explain the definition of cell reproduction with a percentage of 63.46% falling into the low category. The indicator describes the miscellaneous reproduction of cells with a percentage of 66.14% belonging to the low category. The indicator explains the important stages and features of mitosis with a percentage of 72.11% belongs to the high category. The indicators explain the important stages and features of meiosis with a percentage of 69.8% belong to the high category, and the Indicators understand the stages of mitosis through activities with a percentage of 74% belonging to the high category.
Peran Data Science dan Data Scientist Untuk Mentransformasi Data Dalam Industri 4.0

Technological developments in the era of the industrial revolution 4.0, which places the role of Data Science and Data Scientist as tools to transform data into very important data, plus the need for Data Science and Data Scientist, which is very much needed in the midst of Industry 4.0 and is able to accompany increasingly large digital data in its management. This research aims to find out how big the role of Data Science and Data Scientist in transforming data in industry 4.0. This study uses the Research Area Coverage method because this research has shifted from various fields of science, with a method design with the SISP (Strategic Information System Planning) approach using steps such as data collection, condition analysis and interpretation. The data collection technique in this research is a survey and case study approach which is conditioned by the facts or facts that occur in the field. The results of the study show that the role of Data Science and Data Scientist is very much needed in industry 4.0 to perform very large data processing, with the capabilities and skills possessed by Data Science and Data Scientist being able to accompany digital technology that develops in industry 4.0.
Modul Customer Service pada Aplikasi Komputerisasi Standar Akuntansi Perbankan berbasis Website

Practicing students have difficulty in using standard banking accounting computerization applications because they still use disk operating systems and virtual machines. This happens because special knowledge is needed to run the application. This research aims to create a customer service module on a website-based standard banking accounting computerized application so that it can be used for learning operations in the ManLan Lab more easily. Programming using CodeIgniter and MySQL with a waterfall method approach in the system development life cycle, starting from the initial phase to the final phase of development. Data analysis using literature study and observation. This research involved 1 staff, 3 practicum students, and 2 assistants and programmers at the Advanced Management Laboratory as research subjects. The system design stage uses a navigation structure and four types of Unified Modeling Language (UML). Testing is done with black box testing to ensure there are no functional errors in the system. The results of our finding are in the form of a customer service module in the computerized application of banking accounting standards which is used as a depiction of customer service tasks in banks through an application system. And the results of black box testing show the system runs well as expected. Therefore, this application is suitable for operational learning practicum.
LC-Score: Reference-less Estimation of Text Comprehension Difficulty

Being able to read and understand written text is critical in a digital era. However, studies shows that a large fraction of the population experiences comprehension issues. In this context, further initiatives in accessibility are required to improve the audience text comprehension. However, writers are hardly assisted nor encouraged to produce easy-to-understand content. Moreover, Automatic Text Simplification (ATS) model development suffers from the lack of metric to accurately estimate comprehension difficulty We present LC-SCORE, a simple approach for training text comprehension metric for any French text without reference i.e. predicting how easy to understand a given text is on a [0,100] scale. Our objective with this scale is to quantitatively capture the extend to which a text suits to the Langage Clair (LC, Clear Language) guidelines, a French initiative closely related to English Plain Language. We explore two approaches: (i) using linguistically motivated indicators used to train statistical models, and (ii) neural learning directly from text leveraging pre-trained language models. We introduce a simple proxy task for comprehension difficulty training as a classification task. To evaluate our models, we run two distinct human annotation experiments, and find that both approaches (indicator based and neural) outperforms commonly used readability and comprehension metrics such as FKGL and SAMSA.
Implementing Minimum Message Length to the Modelling of Denpasar City Inflation Rate

Inflation is an economic indicator that is used to evaluate economic performance of an area. It is an important indicator in managing consumer’s purchasing power. Rising inflation rate can influence the interest rate. Studies have conducted in regard to inflation with the main focus of developing time series and forecasting models. However, for the modelling, pattern changes in time series and existence of outlier values have not been analyzed. For the purpose, a study was conducted in looking at the pattern existing in the inflation rate data using the monthly inflation rate in Denpasar City of Bali, Indonesia during January 2010, and April 2023. The study was performed by implementing the Minimum Message Length (MML) principle through the process of mixture modelling. Two distributions are considered in this study i.e., Gaussian and Student t distributions. Based on the conducted modelling, it was found that the best MML model for the dataset was a one Student t class mixture model. This shows that outliers exist in the inflation rates data in Denpasar City of Bali, Indonesia. The resulting MML model has also produced a slightly better probability bit costing compared to the Akaike Information Criterion (AIC) and Schwarz’s Bayesian Information Criterion (BIC) models. Further modelling for different time range of the data shows that inflation rates during the year 2010 to 2014 was fitted best using a one Student t class model, whereas the inflation rates during the year of 2015 to 2019 resulted in a one Gaussian class model. This shows that outliers exists during the former time range, whereas during the latter time range, the rates were managed better. For the data during the pandemic Covid-19, MML resulted in a one Gaussian class model, whereas AIC and BIC resulted in a two Gaussian classes model. This proves that MML accommodates a certain degree of uncertainty in data during the modelling.
Gus Bahauddin Nursalim’s Speech and Language Politeness Strategy on YouTube

This study aims to describe the form of language politeness strategies in Gus Bahauddin Nursalim's video lectures on Youtube. This research focuses on Gus Bahauddin Nursalim's lectures on Youtube, Santri Gayeng, with the most views in the last six months. This research uses a descriptive-qualitative approach that seeks to collect descriptive information and present it in text about the subject under study. The collected data is then analysed with Brown and Levinson's theory of language politeness. The results of this study show that there are 23 videos that fall into the category of language politeness strategies. The data shows a variety of positive politeness strategies, indirect strategies or vague speech, and straightforward strategies without preamble. The form of language politeness strategy is inseparable from Gus Baha's social influence in the community. He is known to have the characteristic of giving lectures with a speech that can have an influence on his listeners. Through the study of the language politeness of a preacher, this article contributes to the discussion of language studies and preacing activities in Indonesia.
Fast Underground Positioning Method of Mine Based on ELM Algorithm Optimized by Improved QPSO

In recent years, underground positioning algorithms based on WiFi have received widespread attention. To further improve the speed and accuracy of positioning algorithms, this paper proposes an underground positioning method based on the improved quantum particle swarm optimization (QPSO) extreme learning machine (ELM) algorithm. This method effectively improves the search performance of the QPSO algorithm by introducing an S-type adaptive contraction expansion factor and dynamically adjusting the search step size. The improved QPSO algorithm is used to optimize the Extreme Learning Machine (ELM) localization model. The simulation experiment results based on the ray tracing algorithm show that the ELM positioning model optimized by the improved QPSO algorithm has both positioning accuracy and efficiency, with an average positioning time of only 1.07 seconds and a cumulative probability of positioning accuracy within 2 meters of 86.52%, which has high practical value.
Sistem Pakar Diagnosa Penyakit Tetelo Menggunakan Metode Certainty Factor

In today's technological era, computers are not only used as a tool to complete human work but can also run applications designed to access information quickly. Expert systems are one part of artificial intelligence. An Expert Systems application is an application that transfers expert knowledge to a computer. That way the computer can also solve problems as is usually done by experts. Expert systems have been widely developed in various fields, including the field of animal husbandry. Detection of tetelo disease can use an expert system application. One of them is to detect Tetelo disease. Therefore, breeders can access information about Tetelo disease that is diagnosed with the help of an expert system that uses the Certainty Factor method. The Certainty Factor method serves to determine the degree of certainty of the diagnosis result.
Perancangan Media Pembelajaran E-Learning Sebagai Sarana Penunjang Proses Pembelajaran Di Smkn 1 Ampek Angkek Canduang

far, all learning processes in schools are still conventional, in other words that the teaching and learning process between students and teachers can only be done on condition that a meeting occurs between students and teachers. teacher in the classroom. One of the teaching methods that are currently being developed is e-learning. E-learning can help teachers distribute their teaching materials without having to be in class using the internet. This can maximize learning time in a limited class. In making this elearning using PHP which is used to create web pages and MySQL as a database where data is stored. The results obtained by e-learning can be applied and implemented to help teachers and students in schools in facilitating the teaching and learning process.
Dental Patient Chief Complaint Classification

A patient who has dental health problems usually needs assistance in determining the most suitable dental specialist, due to their unfamiliarity with the dental field. Patients need to express the symptoms, usually in a natural language text, before being recommended to visit a dental specialist. This study proposes a system to classify dental patient complaints based on the most suitable dental specialist. The problem is tackled as a text classification involving the following methods: CNN, Bi-LSTM, and Multinomial Naïve Bayes. The dataset used contains 2199 items and the experimental results show that the model with the best performance is the model with CNN architecture, outperforms Bi-LSTM with Attention layer and Multinomial NB.
Exploring Pauli Configurations in Quantum Kernels for Enhanced Binary Classification

This study pretends to set one’s sights on advancing the understanding of quantum machine learning’s applicability in binary tasks. By systematically assessing quantum kernels and their performance, the primary objective is to determine and evaluate how different Pauli configurations—precisely, ZZ, ZY, and a custom configuration (Z, YY, ZXZ)—impact execution accuracy running in simulator and 7-qubits IBM quantum hardware. The paper encompasses a robust methodology, including data preprocessing, quantum kernel creation, and integration into classical SVMs. It provides essential guidance for discussing the strengths and limitations of quantum methods, highlighting their potential as a valuable tool for developing accurate diagnostic models
Sistem Informasi Penjualan Diamond Mobile Legends Di Moro Cell Berbasis Web

The transaction process in purchasing a game feature often makes it difficult for someone to make a purchase of game features so that a third party is needed to make it easier to purchase features in the game. However, there are problems where related parties need a means to attract customers as a means of promoting products sold by related parties, therefore it is necessary to have a system where in the system there is a useful feature to attract customers. From there, a diamond sales information system for Mobile Legends was built for the Moro Cell company as a means to attract customers. In the development of this system there are steps that are carried out, namely analysis, design, implementation, testing and maintenance of these steps a system is built that can be used to purchase a diamond which aims to attract customer interest with a feature contained in it, namely a member feature that can provide a 5% discount to customers for every diamond purchase transaction. The result of this research is that a diamond sales information system for Mobile Legends has been built in Moro Cell that can help users make diamond purchases and can attract customers from Moro Cell. With this sales system, users are more helped by the transaction process provided by the system and some users are interested in some of the offers in this system such as the member features offered in this system.