Reviewerly/exHarmony huggingface dataset:
Fraud Detection for Online Interbank Transaction Using Deep Learning

The World Banking with its various financial services is an easy target for fraudsters to carry out their actions. Various kinds of fraud that occurred such as credit card fraud, online payment fraud, debit card fraud, online transaction fraud, e-commerce fraud and other services including interbank online transactions. Fast and reliable fraud detection is important because many financial losses have occurred due to fraud. The objective of this study is obtaining a more effective deep learning model for fraud detection in the interbank online transaction system compared to similar models. This study using CNN, LSTM and hybrid model CNN-LSTM models are used to build an interbank online transaction system. The proposed model CNN consist of three convolution layer, one maxpooling layer, one dropout layer and one fully connected layer. The proposed model LSTM built by double layer LSTM with each layer consist 32 cell LSTM, dropout layer and one fully connected layer. The proposed model CNN-LSTM built by combination three convolution layer, 1 maxpooling layer, dropout layer, 1 LSTM layer with 64 LSTM cell and one fully connected layer. The Dataset taken from an interbank online transaction in March 2021 from one of the switching company in Indonesia. SMOTE is use to overcome the imbalance Dataset in training and validation Dataset. The Dataset contains 279513 transactions with 2374 transactions categorized as fraud. The results showed that the CNN model scored an F1-score value at 93,09%, followed by the LSTM model at 86,25% and the CNN-LSTM hybrid model at 69,22%. Based on these results, the proposed CNN model can be accurate for fraud detection in interbank online transaction systems compared to similar models.
Kinerja Program Pendidikan di Kabupaten Kepulauan Yapen Provinsi Papua

Papua's Special Autonomy Policy, which is an opportunity to catch up with human resource development, has not been able to provide changes, especially education issues in the Land of Papua, especially in the Yapen Islands District, Papua Province. This research method is descriptive quantitative research. The results of this study showed that the percentage of school enrollment rate for residents of 7-12 years targeted at 99.22% of local governments succeeded in realizing 97.02% and a difference of 2.2%. Although it has not yet reached the target, this number is relatively small, meaning that the local government is quite successful in opening access to education for the community to receive elementary school education. Success in achieving the School Participation Rate target for residents aged 7-12 years and 13-15 years was not followed by the Participation Rate of residents aged 16-18 years. The local government targets 94.65% that has been achieved is 84.27%, a difference of 10.38%. The low participation rate is caused by the lack of educational infrastructure, especially high schools, which are only available in 3 districts out of 14 districts in Yapen Islands Regency. The conclusion in this study is that the high school enrollment rate is largely determined by the availability of existing infrastructure. The local government has prepared adequate educational infrastructure specifically for high schools in all districts or at least adjacent districts.
Analysing Learning Material For Young Learners Through The Framework

Nowadays, Indonesian kids are increasingly interested in bilingual education. They are exposed to the second language in their households in addition to acquiring it in school. Although there are still some myths about bilingualism in society, some parents still practice it because they think it helps their children develop, both linguistically and cognitively. Those, this essay focuses on the materials used by parents and teachers to teach bilinguals to the children including in the formal language learning. The literature review specifically served as the foundation for this paper. Here, seven frameworks about the learning materials are analysed to see whether the current materials are suitable for the students need. The results show that the learning materials still need some improvement and teachers need to do some innovation to make it happen the school level.
Validity Testing of Developed General English Modul for University Students at Universitas PGRI Silampari

This research aimed to find out the expert validity of developed modul “General English Modul” at PGRI Silampari University (UNPARI). The method used in this research was descriptive qualitative. There were three experts in validating the modul. They were expert of content, expert of instructional design and expert of media. The instrument used in collecting data was questionnaire. In analyzing data, the researchers read all comments given by experts for each espertise (data condensation). After that, the coment was interpreted by the researchers and rechecked to the experts (data display). Finally, the developed modul was revised based on the suggestion. For the results showed that for content validity, the expert coclude that the modul was in highly validity, but she suggested some revision. In validating instructional design, the expert also received the modul but with some revisions. And the last, there were some aspect of media such as the brightness of the cover, pictures and color must be revised. Finally, in conclusion, the modul of General English subject at UNPARI was accepted with some revision.&#x0D; Keywords: General English Modul, Validity
Politeness Strategies Employed by Lecturers in Undergraduate EFL Classroom

This study investigates the politeness strategies employed by lecturers in EFL undergraduate online classroom. This study focuses on answering a research question; (1) how do the strategies employed by the lecturers in their teaching-learning activity. The qualitative method was used to fulfil the objective of the study. The data was collected from sit-in observation during their teaching-learning process. It was transcribed and analysed descriptively. The result shows that there are three strategies that employed by the lecturers namely positive politeness, negative politeness and bald-on-record. It can be concluded that this study will enrich the discussion which relates to the used of politeness strategies in teaching-learning program and how this study helps other lecturers/teacher to enrich their view in conducting kinds of strategies in their teaching-learning activity.&#x0D; Keywords: EFL Undergraduate Classroom, Online Classroom, Politeness Strategies
DEVELOP EARLY LITERACY SKILLS THROUGH COOPERATIVE LEARNING MODELS, MONTESSORI GAME METHODS AND SANDPAPER LETTERS MEDIA

This research was motivated by the low results of children's language development in the aspect of early literacy in recognizing and imitating (writing by mentioning) letters that are still not developed. The purpose ofthis study is teacher activity, child activity, and child development results in showing children's activities in recognizing and imitating (writing by mentioning) letters. This research approach uses a qualitative approach, the type of research is Classroom Action Research (PTK) which is carried out in 2 cycles. This researchwasconducted at Suka Maju Kindergarten, Lunjuk HST Village for the 2021/2022 school year in group A, which amounted to 12 children consisting of 4 boys and 8 girls. Datacollection techniques are carried out by observation, interviews, performances, and evaluation through LKPD. The results showed that teacher activity obtained very good categories, children's activities obtained very active categories, the results of the development of aspec early literacy aspects obtained categories developed as expected (BSH) and developed very well (BSB). The conclusion of this study is the use of cooperative learning models, Montessori game methods and sandpaper letters media in developing aspects of early literacy (recognizing and imitating) in group A children of Suka Maju Kindergarten Lunjuk HST Village.
DEVELOPING LANGUAGE ASPECTS IN MENTIONING LETTER SYMBOLS IN GROUP B OF NURUTTAQWA KINDERGARTEN BANJARMASIN

This research was motivated by the lack of development of children's ability to mention letter symbols caused by the media used by teachers in the learning process to recognize letters that did not attract children's hearts, thus making children less enthusiastic and not eager to participate in learning activities. The purpose of this study is to improve and improve the quality of the learning process of group B in Nuruttaqwa Kindergarten Banjarmasin. This research approach uses qualitative and quantitative approaches with the type of classroom action research (PTK) held 4 meetings. Techniques for collecting observations of teacher activities, observation of children's activities, children's learning outcomes, language skills. The results showed that teacher activity increased with a score of 25 criteria "Very Good" at meeting 4. Children's activity at each meeting increased with a percentage of 84.62% of the criteria being very active at meeting 4. Children's language development with a percentage of 92.31% or 30 children successfully developed at meeting 4.
A Mixed-Method Research on Digital Literacy of Middle School Students

The purpose of this study was to reveal middle school students’ digital literacy levels and their opinions about digital literacy. Convergent parallel design, one of the mixed-method designs, was used in the study. Quantitative part involved survey while qualitative part included case-study model. Digital literacy scale and semi-structured interview form were used to collect the data. The participants in the quantitative part involved 367 students studying at a state middle school in Kırşehir while 12 students took part in the qualitative part. The data analysis was conducted separately, and general conclusions were drawn and combined during interpretation. Although students had high scores from the digital literacy scale, the in-depth qualitative analyses showed that they did not have adequate information about the concept of digital literacy. Moreover, the quantitative results showed that students, who used digital technologies for research purposes, had higher scores from the security dimension of digital literacy scale than the students who used digital technologies for studying. However, the qualitative results revealed that students used digital technologies most commonly for entertainment. It was found that students’ digital literacy was significantly differed by their gender, grade level, book-reading duration, and internet-use duration while it did not significantly differ by their purpose of using digital technologies. Additionally, based on the qualitative results, students agreed that social studies course contributed to their digital literacy.
Consumer’s Personality Traits and Knowledge-sharing Behavior on Shoppertainment Platforms: The Mediating Role of Subjective Well-being and Trust

Objectives: This research analyzed the direct and indirect influences of consumer personality on knowledge-sharing behavior through shoppertainment platforms using subjective well-being and trust as mediators. Methods/Analysis: A questionnaire survey was developed and distributed to 320 consumers with familiarity and experience in purchasing products from the TikTok shop and sharing knowledge, information, news, and purchasing experiences with the Thai TikTok community. This study adopted non-probability and purposive sampling techniques, with measurements and structural model assessments performed before hypothesis testing using the partial least squares structural equation model (PLS-SEM) with SmartPLS statistical software. Findings: Extraversion and openness to experience had a direct positive influence on trust, while neuroticism showed a direct negative influence on trust. Extraversion had a direct positive influence on subjective well-being, while neuroticism showed a direct negative influence on subjective well-being. Both trust and subjective well-being directly influenced knowledge-sharing behavior on the shoppertainment platform. Extraversion and openness to experience positively influenced knowledge-sharing behavior on the shoppertainment platform via trust, while neuroticism negatively influenced knowledge-sharing behavior on the shoppertainment platform through trust. Importantly, extraversion, openness to experience, and agreeableness positively influenced knowledge-sharing behavior on the shoppertainment platform via subjective well-being, with neuroticism negatively influencing knowledge-sharing behavior on the platform through subjective well-being in the same manner. Novelty/Improvement:Results contribute to an improved understanding of the mechanisms of a robust and competitive online retail business model in the digital era that can best deliver business sustainability by elevating consumers’ knowledge-sharing behaviors to facilitate purchasing decisions on goods or services via shoppertainment platforms. Doi: 10.28991/HIJ-2023-04-01-014 Full Text: PDF
PEMODELAN DAN PREDIKSI HARGA SAHAM PERUSAHAAN FAST MOVING CUSTOMER GOODS MENGGUNAKAN VECTOR AUTOREGRESSIVE WITH EXOGENOUS VARIABLES (VARX)

The increase in the population of Indonesia causes consumption to increase. This has made the FMCG (Fast Moving Consumer Goods) industry in Indonesia grow rapidly and occupy the second largest proportion of market capitalization thereby attracting investors to invest. One way to choose the best stocks to invest is by modeling. Modeling is carried out on the share price of companies with large capitalization, namely Mayora Indah, Indofood CBP, and Siantar Top. One of the factors that influence a company's stock price is the stock price of a competitor, namely Unilever and Buyung Poetra. Therefore, to predict and determine the relationship between stocks, the VARX (Vector Autoregressive with Exogenous Variables) method is used. The data period in this study starts from January 4, 2021 to January 14, 2022 with the results of the analysis, namely VARX (1) is the model obtained for prediction. The errors from the model meet the white noise and multinormal assumptions. The SMAPE value of the Mayora, Indofood CBP, and Siantar Top variables is below 10% which means the model has very good predictive ability. In addition, the prediction results show that Indofood's share price is more stable than other stocks.
A New Method of Clusters Definition Based on a Saccadic Model of Human Vision

Annals of Reviews & Research open access journal that publishes high-quality solicited and unsolicited articles, from various types of subject areas ranging from management to engineering sciences, accounting, criminal sciences, etc. which deal with innovative research work.
Problem of Uniformity of Measurable KPI factors: A Lesson from three Companies using Blockchain Technology

Annals of Reviews & Research open access journal that publishes high-quality solicited and unsolicited articles, from various types of subject areas ranging from management to engineering sciences, accounting, criminal sciences, etc. which deal with innovative research work.
Fuzzy Inference System Modelling of the Mascarenes Anticyclone center Trajectory

This work objective is to determine the parameters of the fuzzy inference system model that best models the Mascarenes anticyclone trajectory. Our study area extends from 20°E to 110°E longitude and from 15°S to 50°S latitude. We start from the atmospheric pressure reanalysis data in grid point to determine the Mascarene anticyclone center. This center is none other than the center of the last closed Anticyclone's isobar. The monthly climatological mean value of the center coordinates are the data to be modeled by fuzzy inference system. The considered model parameters are the partitions number of the discourse universe and the model order. After evaluating the deviation between the input data and the simulated data, the minimum deviation is obtained with order model 2 by using 50 numbers of partitions.
Pre-processing Big Data for Business

Different types of data can be collected through various methods, and these data want to be used for data mining, its necessary path is data processing, because the collected data is often imperfect, there may be a variety of problems, must be processed through technical means these collected raw data, that is, through the process of data cleaning, data transformation, data integration, data attribution to process the raw data. The data obtained at the data processing stage is the result of preliminary analysis, and the data obtained through subsequent steps such as data mining and visual analysis can be used to assist in decision-making.
Business Big Data Knowledge Fusion

Knowledge graph is essentially a semantic network. Semantics is already an abused word, and each has a different understanding of what semantics is. The semantic web is an application of artificial intelligence in the era of big data, specifically, the application of knowledge representation and reasoning, with its back-end theoretical support of description logic and modal logic. The emergence of the Semantic Web is causing the Web to evolve from a document network to a data network.
A Path Recommender System for Enjoyment Improvement of the Cultural Heritage

The need for cultural heritage enhancement in the Italian context requires an effort from new technologies. Indeed, various tools can be functional to guarantee the improvement of the artistic artifacts’ maintenance or users’ enjoyment. This paper aims to present an architecture to improve the cultural experience through recommender systems and digital storytelling techniques. Moreover, the construction of a mathematical model allows for the building of personalized paths. An experimental phase, based on the development of a prototype, permits the evaluation of the proposed architecture, and obtained results are promising.
Processing Facial Emojis as Social Information: Evidence from Visual Working Memory for Facial Emojis, Simple Shapes, Human Faces, and Their Relations to Theory of Mind

Emojis, recognized as crucial nonverbal cues within computer-mediated communication (CMC), have gained widespread usage. Through the lens of visual working memory (WM), four experiments (N = 315) systematically investigate whether the cognitive processing of emojis elicit unique mechanisms akin to those involved in processing nonverbal cues within real-life social contexts. Experiment 1&4 reveal that despite the markedly higher visual complexity of facial emojis compared to simple objects (i.e., simple shapes), their WM capacities are comparable and notably surpass those for complex stimuli (e.g., human faces). This efficient processing can likely be attributed to their holistic processing manner, as demonstrated by Experiment 2, which reveals that inversion and scrambling significantly impair the WM of facial emojis. Furthermore, Experiment 3 indicates that facial emojis receive higher prioritization than simple shapes in WM, while Experiment 4 establishes a substantial association between WM for facial emojis and high-level social cognitive functions (theory of mind), similar to that for human faces. This study unveils a probable explanation for the widespread use of facial emojis: they are processed as social information similar to human faces, invoking social cognitive mechanisms, while also being efficiently processed like simple shapes, requiring minimal cognitive resources.
PERBANDINGAN GULUD REGRESSION DAN PRINCIPAL COMPONENT REGRESSION (PCR) TERHADAP PEMODELAN INDEKS PEMBANGUNAN MANUSIA PROVINSI JAWA TIMUR

Human resources is valuable asset in a country. Human Development Index (HDI) becomes important indicator of quality of human resources in an area. HDI value is affected by a variety of factors that are strongly related to each other so they cause multicollinearity. This observation aims to deal with multicollinearity optimally by comparing Gulud Regression to Component Regression in modeling factors that affect East Java HDI in 2020. Data that are used in this observation are East Java HDI in 2020 (Y), Life Expectancy (X1), Infant Mortality Rate (X2), Mean Years of Schooling (X3), Expected Years of Schooling (X4), Open-Unemployment Rate (X5), Average Household Expenditure per Capita (X6), and Labor Force Participation Rate (X7). Based on MSE value, the Gulud Regression method is better than Principal Component Regression (PCR) method in dealing with multicollinearity problem. Based on adjusted score that is 0,954, feasibility test of the best model of Gulud Regression method is a strong model.
PEMODELAN PRODUK DOMESTIK BRUTO DI INDONESIA DENGAN PENDEKATAN SEMIPARAMETRIK POLINOMIAL LOKAL DILENGKAPI GUI-R

Gross domestic product is a measuring tool for a country's economy that needs to be known so that the country is able to consider decisions taken regarding future economic policies. The local polynomial semiparametric method that combines parametric regression and local polynomial nonparametric can be one way of predicting a country's GDP. This method is used because in GDP modeling there is one independent variable that has a linear relationship while the other variables have a pattern that tends to cluster. The modeling aims to obtain a semiparametric local polynomial model on GDP in Indonesia with the influence of coal export volume as a parametric independent variable and world oil prices as a nonparametric independent variable from the first quarter of 2005 to the second quarter of 2021 which is equipped with a GUI to simplify calculations. Based on experiments on several types of kernels, bandwidth and model degrees, the best model is local polynomial semiparametric model with Gaussian kernel weighting at degree 2 which has the smallest GCV. This model also has an R-Square value of 89.2% where the value of GDP is strongly influenced by world oil prices and coal export volumes together. The forecasting ability of this best model is said to be good because it has a MAPE of 17.127%.
On GCYD-Method In e-Abacus Diagram

We will provide a new method in this study that integrates two types of applications, namely Graph Theory and Conjugate Young Diagram, the idea of combining the graph and the Young diagram is presented by Ali And Mahmood, which is primarily based on the idea of the e-abacus diagram, the new method is called GCYD, it directly applies to the English letter section, which will be a two-layer coding. It makes it difficult to detect the word or sentence.
Real-time Ball Detection and Tracking using Raspberry PI

This paper presents a real-time system for ball detection and tracking system which is reliable in any conditions. Images from the webcam are processed by openCV library running on a Raspberry Pi to move the camera pan and tilt servo and two DC motors to drive the robot body using the Arduino Nano microcontroller. The webcam is integrated in a robot prototype to represent the wheel football robot type. The results show that a ball tracking webcam system is obtained with the capability to detect a ball with a diameter of 17cm within a maximum distance of 200 cm, a stable ball reading when the light intensity is at 32 lux and above. Furthermore, the experimental results demonstrated the system’s robustness in detecting and tracking ball in different distance and ligthing conditions.