Reviewerly/exHarmony huggingface dataset:
CRRESS - Session 9 - Reproducibility, Confidentiality, and Open Data Mandates

Many granting agencies have adopted open data mandates. What is the interplay between reproducibility and those mandates? How can researchers be supported to meet those mandates, both in general, and specifically when data are confidential. At first glance, confidentiality and open data seem irreconciable, but could we find practices that both respect confidentiality and provide enough information and transparency to foster reproducibility?
A Comparative Study of Gender Bias Mitigation Techniques and the Role of Implicit Stereotypes

Abstract Natural language models and systems have been shown to reflect gender bias existing in training data. This bias can impact on the downstream task that machine learning models, built on this training data, are to accomplish. A variety of techniques have been proposed to mitigate gender bias in training data. In this paper we compare different gender bias mitigation approaches on a classification task. We consider mitigation techniques that manipulate the training data itself, including data scrubbing, gender-swapping, and counterfactual data augmentation approaches. We consider how gender neutralization , which replaces gender-specific terms with their gender-neutral equivalents, performs as a bias mitigation technique. We evaluate the effectiveness of the different approaches at reducing gender bias in the training data and consider the impact on task performance. We also look at the impact that de-biased word embeddings in the representation of the training data have on gender bias mitigation. Our results show that the performance of the classification task is not affected adversely by many of them but we show a significant variation in the effectiveness of the different gender bias mitigation techniques. These gender bias mitigation approaches typically focus on lexical or explicit gender in text and while these approaches reduce gender bias in training data, they do not remove it completely. We investigate the source of gender bias in the training data through the use of stereotypical masculine and feminine words that can signal gender implicitly due to gender roles or behaviour. We show how certain words which have an associated implicit gender may contribute to gender bias, even after attempts to neutralize gender in language.
ANALISIS UNSUR SOSIAL BUDAYA DALAM TEKS DRAMA “PANEMBAHAN RESO” KARYA W.S. RENDRA SEBAGAI ALTERNATIF PEMILIHAN BAHAN AJAR DI KELAS XI

Learning literature in education is presented in an integrated manner with language learning. This has an impact on the imbalance in the presentation of the weight of the material being taught between language learning and literature learning. So that many students do not understand the teaching of Indonesian literature. The formulation of the problem to be discussed in this study is formulated as follows. (1) how are the extrinsic elements related to socio-culture contained in the drama text Panembahan Reso by W.S. Rendra? (2) can the drama text Panembahan Reso by W.S. Rendra be used as an alternative for selecting Indonesian language teaching materials in class XI according to the demands of the 2013 curriculum? Based on these problems, this study aims to describe (1) the extrinsic socio-cultural elements in drama texts; (2) the drama text Panembahan Reso by W.S.Rendra as an alternative to selecting Indonesian language teaching materials in class XI according to the demands of the 2013 curriculum. This research method uses a qualitative descriptive method. The research data is in the form of extrinsic socio-cultural elements in the drama text Panembahan Reso by W.S. Rendra. The primary data source in this study is the drama text Panembahan Reso by W.S. Rendra. Secondary data sources in the form of books, scientific journals, websites that support research.
Enhanced Intelligent Water Drop Algorithm Optimized Routing (EIWDR) for Quality of Service Enhancement in Internet of Things-Based Wireless Sensor Networks (IWSN)

The Internet of Things (IoT) has transformed how humans engage with technology, allowing pervasive connection and data sharing.In the Wireless Sensor Networks (WSNs) framework, IoT-based applications have been created for several areas, including agriculture, where greenhouse automation has been deployed for enhanced agricultural yields.However, WSNs face significant challenges, such as limited resources, unpredictable communication, and energy consumption.These issues become more pronounced when applied to greenhouse agriculture due to interference, congestion, and quality of service (QoS) requirements.Therefore, efficient routing protocols are crucial to address these challenges.The proposed study addresses the routing issues in IoT-based WSNs (IWSN) for greenhouse agriculture.Specifically, the Enhanced Intelligent Water Drop Algorithm Optimized Routing (EIWDR) is proposed as a novel routing protocol to enhance the QoS in IoTbased WSNs.The EIWDR protocol utilizes the intelligent water drop algorithm to optimize the routing path selection.The algorithm prioritizes energy-efficient routing, selects the most reliable path with minimum delay and data loss, and balances network load to prevent congestion.The proposed protocol also uses a modified weight function to improve the routing performance when applied in IWSN.To test the efficacy of the EIWDR, simulation tests were conducted in the NS-3 simulator.The EIWDR protocol fares better regarding network lifetime, packet delivery ratio, energy consumption, and packet delay than other routing protocols.Improved greenhouse agricultural quality of service using IWSN is possible with the help of the proposed EIWDR protocol.With the help of intelligent routing algorithms, network resources are used effectively, data is sent reliably, and overall performance is enhanced.
Blockchain Assisted Chaotic Chameleon Swarm Optimization Based Clustering Technique in Vehicular Ad Hoc Networks

Vehicular Ad Hoc network (VANET) has group of stationary or moving vehicles linked via wireless networks.Clustering in VANET is used to enhance network efficiency, scalability, and performance.By aggregating vehicles into clusters, communication overhead was decreased, and the network was managed with a greater count of vehicles.Moreover, clustering supports minimizing inter-cluster communication and decreasing congestion, therefore enhancing network reliability.The cluster head (CH) has the responsibility to manage communication in the cluster and forward communications to other clusters.In recent times, Blockchain (BC) technology has been executed to VANETs for enhancing privacy and security.A BC-based scheme is utilized for recording transactions like the change of data amongst vehicles from the secure and tamper-proof method.This makes sure that data cannot be falsified or altered and that the authenticity of data is verified.Therefore, this study develops a Blockchain Assisted Chaotic Chameleon Swarm Optimization based Energy Aware Clustering (BCCSO-EAC) technique in VANET.The presented BCCSO-EAC technique constructs clusters and selects CHs using a fitness function comprising residual energy (RE), node degree (ND), and intra-cluster distance parameters.The BCCSO-EAC technique selects CHs in such that the load among the nodes gets distributed properly.Moreover, BC technology was carried out to enable secure inter-cluster and intra-cluster VANET communication.The experimental result analysis of the BCCSO-EAC method is tested under various measures.The outcomes stated the improved results of the BCCSO-EAC technique over other recent approaches in terms of different evaluation metrics.
Upaya Meningkatkan Ketrampilan Membaca Siswa dengan Penggunaan Media Kartu Kata pada Pembelajaran Bahasa Indonesia Kelas III SD Negeri Jurang Mangu Barat 03

This research was motivated by the low reading skills of students in class III Indonesian language learning at SDN JURANG MANGU BARAT 03. The method for overcoming this problem is to apply a special Classroom Action Research model, namely by using word card media to find out and deal with learning to read problems start. When the research was carried out in February 2018. Data collection techniques were tests, observation, documentation. The results of this study can be concluded that from several types of teacher efforts it is felt that there is an increase for students, both in the academic and non-academic fields. However, in the academic field it turns out that they have not been able to meet the expectations as stated in the indicators, because according to the results of the teacher's observations of students, they do not fully have reading skills according to the standards given. Based on the analysis used to test the hypothesis that the use of word card media in Indonesian lessons can improve the reading skills of Grade III students at SD Negeri Jurang Mangu Barat 03, South Tangerang City. The use of word card media in Indonesian lessons can improve student achievement in Class III SD Negeri Jurang Mangu Barat 03 Kota Tangerang Selatan for the 2017/2018 academic year with an average score of 82.31 out of 22 students.
An Enhanced Authorization Protocol in Blockchain for Personal Health Information Management System

Blockchain and cloud-edge computing paradigms have gradually evolved as a profitable alternative for managing patient data in clinical Internet-of-Things (IoT) devices.Various studies are presented to secure medical records in IoT devices using blockchain schemes.Amongst, eHealthChain is developed to handle medical records obtained from clinical IoT systems.It utilizes Hyperledger Fabric as a blockchain policy to accumulate private medical records.The client's medical record is collected by utilizing the OAuth 2.0 protocol that guarantees the client's authority.Besides, a Message Queuing Telemetry Transport (MQTT) protocol is applied to communicate within an IoT platform.The reliability of the medical data is guaranteed by a consensus method called Kafka.However, the standard OAuth 2.0 protocol neglects the client security problem.Though MQTT offers many-to-many transmissions, the restricted sleep time of devices related to the fixed query waiting is ineffective for resource-constrained networks.Hence, the major contributions of this article are: (i) to develop an Enhanced OAuth (EOAuth) 2.0-based protocol which solves the client security problem and (ii) to utilize a protocol called Constrained Application Protocol (CoAP) for reliable transmission.It reduces the user verification time by obtaining more trusted clients according to their trust level.Also, a certified security service is employed to get the client's input securely and conduct the cryptographic processes.Finally, the implementation findings exhibit that the EOAuth and CoAP achieve higher efficiency than the standard protocols.
K-Means and AHC Methods for Classifying Crime Victims by Indonesian Provinces: A Comparative Analysis

Crime is a common phenomenon that often occurs in society and has a negative impact both individually and collectively. Gaining a deeper understanding of crime can help us tackle the problem more efficiently. In an era that is increasingly complex and globally connected as it is now, crime has undergone significant developments and changes. Crime remains a serious threat to our security, integrity, and well-being. Some common types of crime include theft, robbery, fraud, physical abuse, and murder. Crime can happen anytime and anywhere. To tackle crime, data mining techniques can be used to analyze the surrounding situation and gain new knowledge. One approach is to classify provinces based on crime data from previous years so that crime-prone areas can be identified and security measures can be increased. In this study, two grouping methods were used, namely K-Means and AHC using the complete linkage mode. There are 34 provinces in Indonesia which are grouped based on the number of victims of crime from 2019 to 2021. The grouping results using the K-Means method yield two groups with 17 provinces each. However, using the AHC complete linkage method, there is a difference in the number of provinces between cluster 0 and cluster 1 compared to the K-Means results. In addition, there are differences in the location of the province in the cluster between the two methods. In the K-Means method, provincial data is located in cluster 0, while in the AHC method, the province's data is in cluster 1. Thus, this study provides insight into crime in Indonesia and provides information about the grouping of provinces based on crime rates using the K-Means method. Means and AHC
Penerapan Metode Principal Component Analysis (PCA) dan Long Short-Term Memory (LSTM) dalam Memprediksi Prediksi Curah Hujan Harian

Since the last three years North Luwu has experienced frequent hydrological disasters in the form of floods and landslides. The disaster had a negative impact on the availability of clean water, failed to plant and even tended to reduce the quality of the harvest. Cocoa is one of the leading commodities of North Luwu Regency whose productivity has decreased due to the impact of climate change so that it will affect the sustainability of the local population's income. Therefore, the purpose of this research is to anticipate rainfall that will occur to prevent or reduce the risk of failure and loss. Principal Component Analysis (PCA) Method is used as feature extraction to find out the most influential variables and the Long Short-Term Memory (LSTM) method is used as a prediction method. Future rainfall is predicted using meteorological variables such as pressure, evaporation, maximum temperature, average humidity, and sunshine duration from 1 January 2017 to 30 September 2022. Based on the PCA results, 4 variables are obtained that have the most influence on rainfall, namely: variable evaporation, maximum temperature, average humidity, and length of sunlight. These variables are used as input to predict rainfall using LSTM. In this study using trial parameters, namely the number of hidden, batch size, and learn rate drop period. The best prediction results were obtained for MAPE of 0.0018 with the number of hidden, batch size and learn rate drop periods of 100, 32, and 50 respectively. The prediction results show very heavy rainfall occurring on August 28, 2021 of 101.9734 mm, 21 September 2021 of 108.6528 mm, and 5 April 2022 of 116.5510 mm. In this study PCA was able to increase accuracy in considering all parameters and choosing the most effective.
Sentiment Analysis of Practo App Reviews using KNN and Word2Vec

The development of technology and communication is used by the community to facilitate daily activities, one of which is in the field of health services. Health services are good enough, but there are still some obstacles that are commonly found, including not allowing to leave the house or a short schedule of doctor consultations. With the presence of health service applications, one of which is Practo, it makes it easier for people to consult online. This convenience makes a lot of reviews regarding the Practo healthcare application. The diversity of opinions on the internet, makes Practo app reviews varied. Therefore, sentiment analysis of Practo app reviews is necessary. In this study, the algorithm used was KNN. The KNN algorithm was chosen because it is very effective if the amount of data is large and easy to implement. The feature extraction used in this study is Word2Vec. Word2Vec was chosen as a feature extraction because it was considered good enough to use because it represented each word with a vector. This research produced the best model built when using stemming with Word2Vec dimensions of 300 and K = 3 values on the KNN parammeter, capable of producing an f1-score of 77.30%.
Klasifikasi Penerima Bantuan Beras Miskin Menggunakan Algoritma K-NN, NBC dan C4.5

One of the tasks of the Dumai City Social Service is to provide poor rice assistance to people in need. The problem that often occurs in the distribution of rice to the poor is that the target recipients of poor rice often occur. In overcoming the existing problems, this research has carried out classification models using the K-Nearest Neighbor (K-NN) algorithm, Naïve Bayes Classifier (NBC), and C4.5 Algorithm. Based on the experimental results, it was found that the best classification model was produced by the K-NN Algorithm with a value of K equal to 21. Besides that, the C4.5 algorithm succeeded in making a decision tree for the classification model with the lowest complexity because it succeeded in reducing the number of attributes from 33 to 5 attributes. The decision tree can be used as material for consideration to the Social Service in making decisions on Raskin beneficiaries.
CP Clustering Performance

The interest of high school students is an important thing to do to see the talents of each student based on the academic scores obtained in the first and second semesters. There are two majors of interest in this case study, namely natural and social studies with criteria for natural studies scores including mathematics, chemistry, biology and physics. Meanwhile, the social studies criteria include history, economics, geography and sociology. This research propose comparing of clustering time and accuracy based on manual data from school as a reference of clustering in SMAN 1 Wonosari for 2011/2012 academic year using two clustering methods namely K-means and Bisecting K-Means. The results of this research compare to manual results interest from class teacher, so this work can demonstrate the run time comparison and accuracy of this study. The accuracy result shows 87.5% for both methods but different run times. For bisecting k-means got 0.0229849 seconds to complete the clustering process faster than k-means only got 0.0929448 seconds
Content of Future Teachers’ Organizational Skills and Ways to Improve Them

The organization of the process in the pedagogical system depends on its elements and participants. The elements of the pedagogical system are: the educational purpose, the content of training, techniques and methods of training and education, organizational forms, means and results of training, management and pedagogical technologies. The implementation of educational activities by a teacher participating in the pedagogical system largely depends on pedagogical skills, including organizational ones. In addition, the teacher can organize an effective educational process taking into account the components of the pedagogical system. In this article the author describes the components of teacher training in the implementation of the pedagogical process, including the types of pedagogical skills. The types of pedagogical activity in research work and their differentiation are considered there. It is indicated that organizational skills differ depending on the purpose of training, the level of pedagogical activity, object and subject. The teacher's pedagogical skills are characterized by the connection of organizational skills with other skills, considered as a managerial matter. In addition, on the part of researchers, it is proposed that organizational skills consist of: designing (research, constructive actions), technological (or activity: organizational, informational, communicative actions), analytical and evaluative (control) actions. The system of training future teachers provides information about their organizational skills: substantive and procedural aspects; intensive and extensive ways from the point of view of the pedagogical system.
Analysis of Financial Ratios and Data Visualization of Share Prices in Coal Mining Company

Many novice investors do not analyze financial ratios and thus suffer many losses. Analyzing the fundamentals of financial ratios that can maximize investment returns, and see information on the current and future profits and health of the company. In addition to profits, there are also risks from stock investment. To reduce risk, analysis is needed to predict stock prices. The data used is the company's annual report with the correlation coefficient method with Tableau tools so that it can find the correlation between financial ratios and the company's stock price and visualize the data. The results showed that there is a strong positive relationship between the price of the company's shares and financial ratios so that this analysis can be used to predict stock prices and investors in making stock investment decisions.
INVESTIGATING STUDENTS’ EFFORT IN SUCCEED IN SPEAKING ENGLISH: A CASE STUDY ON STUDENTS’ PERSPECTIVE

Abstract: This research was conducted to investigate the students’ efforts in speaking skills and the aspects of speaking skill that mostly developed by the students at the seond grade of SMAN 1 Mowewe. This research used a descriptive qualitative method by using case study English design. In conducting this research, the researcher took class XI MIA 1 of SMAN 1 Mowewe as a subject of the research with considerable that the class have the highest effort to improve speaking skill. The researcher used two kinds of instrument, namely questionnaire and interview. The researcher analyzed the data of the questionnaire by calculating and analyzing the students’ answer. For the interview the researcher used transcribing the tape recording, coding (labeling) the whole transcribed text, seeking for and naming the themes, reviewing the themes to make sure they fit the data, and the write-up (creating a coherent narrative).&#x0D; The result of this research showed that the students had six activities of students’ efforts in speaking skill. There were 1) students used the new vocabulary in speaking for easily remember the vocabulary, 2) students used mirror in speaking English fluently, 3) students checked the correct pronunciation on an online dictionary, 4) students asked a friend for helping them if they forgot the vocabulary, 5) students looked for the native speakers in improving their pronunciation, and 6) students made a small note to write the new vocabulary. In additional the interview data showed that there were some aspects of the speaking skill, namely vocabulary, comprehension, fluency, pronunciation, and grammar. Then the researcher got information from the interview about the aspect of speaking skill that mostly developed by the students is vocabulary. There were 4 students from 5 students chose vocabulary as an aspect that mostly developed by the students
Mediated-Moderation Model of Digital Education Competencies in Teaching and Learning System

Students in today’s Digital Education (DE) society are held to a higher standard of expectation and are expected to demonstrate greater levels of responsibility than their forefathers did while in school. Cognitive abilities (COA), process skills (PRS), systems skills (SYS), and social skills (SOS) are the four primary qualities of DE competencies. Therefore, we will look into the roles of COA, PRS, SYS, and SOS as the fundamental constructs required for compelling mastery of abilities in DE. This study employs a cross￾sectional survey for data collection and analysis. The structural equation model (SEM) is used to define the relationship between the DE competencies. The sample consisted of 871 and 1,309 students in University of Muhammadiyah Purwokerto, Indonesia (UMP) and the University of Riau, Indonesia (UNRI). The findings revealed a significant interaction between COA and PRS, PRS and SYS. However, has no connection to COA and SOS. In a result, students who complete the DE competencies will be able to find solutions to any problems in the global challenges.