Reviewerly/exHarmony huggingface dataset:
Dominant Requirements for Student Graduation in the Faculty of Informatics using the C4.5 Algorithm

Graduating on time is one of the indicators in the achievement and ranking of educational institutions. The achievement of graduating on time in educational institutions is essential to balance incoming and graduating students. The problem that occurs, the attributes for graduating on time have varying weightings, so the determinants of the attributes for passing on time need to be known so that the anticipation of achieving graduation on time can be met. The purpose of this study is to find out the dominant attributes in the prediction of graduating on time for students. The attributes used are credit scores (Semester Credit Units), GPA scores (Grade Point Average), and English scores (TOEFL). The method used is the C4.5 Algorithm which is one of the classification methods in data mining. The data used was 262 data, split randomly with a composition of training and testing data of 80:20. Data is processed using the data mining process by creating decision trees. The decision tree results using the C4.5 Algorithm show that the GPA value is the most influential attribute in predicting a student's graduation time. In addition, predictions based on the decision tree of the C4.5 Algorithm with criterion = 'gini' and max_depth = 5 showed an accuracy result of 77%.
How do topological quantum error-correcting codes fare under non-Markovian noise

&lt;p&gt;We simulate the performance of toplogical error-correcting codes when all the encoding qubits share same non-Markovian bath. We find that scalable and reliable quantum computing may still be possible if error-rates decline as $\sqrt{n}$ where $n$ is the codeword size.&lt;/p&gt;
Design and Development of a Secure and Efficient Authentication System for Mobile Devices

&lt;p&gt;The proliferation of mobile technology has transformed the way I communicate, access information, and perform various activities. However, the increasing usage of mobile devices also introduces new challenges in terms of security and user authentication. Traditional password-based authentication mechanisms are often vulnerable to attacks such as brute-force, phishing, and dictionary attacks. Moreover, the limited input capabilities and small form factor of mobile devices impose additional constraints on authentication system design. &lt;/p&gt; &lt;p&gt;To address these challenges, I propose a novel authentication system specifically designed for mobile devices. Our system leverages the advantages of multi-factor authentication and biometric techniques to provide a robust and secure authentication mechanism. In this paper, I discuss the background and motivations for our research, review the existing literature on authentication systems, present the methodology and implementation details of our system, evaluate its performance, and conclude with insights and future research directions.&lt;/p&gt;
PIPELINE-GENERATED CONTINUOUS INTEGRATION AND DEPLOYMENT METHOD FOR AGILE SOFTWARE DEVELOPMENT

&lt;p&gt;This article presents a pipeline strategy for solving delivery issues, which speeds up the delivery process, simplifies testing, and enhances benchmarking. It increases stability and deliverability, reduces system disruption, and integrates numerous test phases.&lt;/p&gt;
R3−Rescale, Rotate and Randomize: A Novel Image Cryptosystem Utilizing Chaotic and Hyperchaotic Systems

&lt;p&gt;This work proposes a novel image encryption algorithm that combines unique image transformation techniques with the principles of chaotic and hyperchaotic systems. The proposed algorithm performs rescaling, rotation, and randomization on the target image by exploiting the unpredictable behavior of the Chua system and the hyperchaotic nature of the Chen system. These chaotic systems' unpredictability and sensitivity to initial conditions are utilized to create an encryption algorithm that provides an extensive key space of 2^(5208), contributing to its robustness against brute-force attacks and amplifying its overall security. The efficiency of the algorithm is demonstrated in its computational speed and minimal resource consumption, making it practical for real-time applications. A series of rigorous tests and analyses were conducted to evaluate the algorithm's performance, substantiating its capability to withstand a wide array of attacks, including differential attacks, statistical attacks, and brute-force attacks. With its vast key space, high efficiency, and robust resistance to attacks, the proposed algorithm shows potential as a vital tool for securing digital images in various applications, such as secure communication, data storage, and multimedia transmission. This research contributes to the ongoing development and evolution of high-security image encryption methodologies, meeting the escalating demand for advanced security in the digital information era.&lt;/p&gt;
LEARNING IMPLEMENTATION USING CHATGPT MEDIA AT SMA NEGERI 1 SUKABUMI

This paper describes the use of ChatGPT in learning. The research is a qualitative descriptive study with a case study at SMA Negeri 1 Sukabumi in West Java Province Indonesia. The research begins with a survey, which involves the distribution of questionnaires to 13 learning subject teachers in grade 10 and 69 tenth-grade students who were selected randomly. The questionnaire results were analyzed as a basis for further research, including in-depth interviews, observations, and document studies. Classroom observations were carried out on two teachers who have implemented learning using ChatGPT. To deepen the results of the observations, interviews were distributed to the two teachers and three students who were randomly selected from the observed classes. The research findings indicate that learning using ChatGPT can assist teachers in preparing and directing students in the teaching and learning process. With teacher guidance, students are expected to gain knowledge more comprehensively and deeply by asking specific questions that align with learning objectives. The teacher’s competence to guide students in the use of ChatGPT in terms of n achieving learning objectives determines the achievement of learning outcomes from each student. ChatGPT, as one of the Artificial Intelligence (AI) technologies, offers new challenges in the field of education. The research in this paper provides insights into how this AI technology can be utilized in classroom learning
PENGARUH MODEL PEMBELAJARAN CONTEXTUAL TEACHING AND LEARNING (CTL) BERBANTUAN GAMES EDUCATION TERHADAP HASIL BELAJAR SISWA KELAS IV PADA MATERI GAYA DAN GERAK

This research is motivated by the lack of variation in the learning process in the observed schools so that impact on student participation and low learning outcomes. The purpuso of this study was to investigate the effect of the Contextual Teaching Learning (CTL) model by wordwall games on the learning outcomes of fourth grade student in the material of Gerak dan Gaya. The research method is experimental one group pretes-posttes. The sample is 38 student. The instrument used is s cognitive test based on Bloom’s Taxonomy. The results of the study based on statistical test stated that CTL model had an effect on student learning outcomes as evidenced by the significant defference between pretes and posttest scores after applying the model.
Implementasi Model Pembelajaran Problem Based Learning Sebagai Keterampilan Menulis Deskripsi Siswa Pada Abad 21

The problem-based learning model as a student description writing skill in the 21st Century requires students to keep up with the times in the 4.0 revolution era. This study aims to determine 1). Problem Based Learning learning model as a student description writing skills in the 21st Century 2). How to apply the Problem Based Learning learning model as a student description writing skill in the 21st Century. This research is a systematic literature study, the research steps are to find articles that match two keywords, meet the inclusion inclusion criteria, pass the quality assessment consisting of an assessment of research questions, methodology, and research results. The results showed that by implementing the writing process in learning, the learning steps also used the writing process, including prewriting, drafting, revising, editing, and publishing. Learning Indonesian about writing descriptive texts for fictional characters, students learn new things, open students' knowledge that writing is not just a product, but writing also has processes including prewriting (prewriting), writing (drafting), revision (revising), editing ( editing), and publication (publishing).
Sistem Informasi Manajemen Pelayanan Desa Berbasis Web di Desa Lebani Kecamatan Belopa Utara

The rapid development of technology is very influential on community service in the village area. Therefor Lebani Village, Belopa Utara sub district, Luwu Regency has made various improvements, including one of them is an increase in the information system. The current condition of the population administration service system in the village is still conventional or manual, such as: (a) Village population recording data in register book; (b) Archival data collection, especially correspondence, has not implemented an application-based information system. This has an impact on both village officials and villagers, where human error often occurs, queues for sevice, and a waste of time and money. Therefore we need a system to solve the existing problems. Based on this problem, community service inplementers develop a Village Service Management Information System (SIMPEDA)to facilitate population data service and administration. It is hoped that by using empowement, and support village operational costs. The service implementation program is divided into thee stages, namely the socialization stage, the village management infomation system training stage, and the monitoring and evaluation stage.
Analysis of Flood Hazards and Risk in the Sirimau District Ambon City

This study aims to target the threat and risk of flooding in Sirimau District, Ambon City from a multi-criteria perspective using a Geographic Information System (GIS). Important flood hazard characteristics include land use, elevation, slope, distance from rivers, soil, and rainfall. Two risk factors, namely population density and land use as well as flood hazard characteristics are used in flood risk analysis. Map aggregation procedure for flood risk and hazard analysis uses the Weighted Linear Combination (WLC) approach. The results of the flood hazard at the study site revealed that the flood hazard category was very high and high, namely 12.26%, and the flood hazard category was very low and low, namely 87.84% and only. The results of the flood risk in the research location revealed that the flood risk with very high and high-risk categories was around 17.28%, and very low and flood low-risk categories (82.77%). This is because the Sirimau District is mostly dominated by hilly and mountainous areas.
UNVEILING COHERENCE: ANALYZING GRAMMATICAL DEVICES IN RECOUNT TEXT

The purpose of this study is to examine the grammatical cohesive devices used in the recount text writing of bilingual students. The cohesive device is crucial because it consists of grammatical and lexical devices that contribute to the writing’s strength and accuracy, as well as its contextual understanding. Twenty bilingual ninth-grade students of a junior high school participated in this study. The students’ recount text writings were used as the main data in this research. The qualitative descriptive method employed in this study to thoroughly assess and describe students’ writing and its’ cohesive device used. The result shows that the bilingual ninth-grade students were able to use grammatical cohesion in their recount text writing. The result revealed the reference is most dominated in 68.42% and the second device is in conjunction with 29.97%. Meanwhile, substitution showed the low rank with 1.61% and the last was ellipsis with 0%. Furthermore, in the reference device category, personal reference becomes the most highly used at 85%, meanwhile in the conjunction category, additive category becomes the most frequent one at 46% as well as nominal substitution at 50% in the substitution device. It was also found that the ninth-grade students of bilingual class can write well using numbers of grammatical cohesive devices even though there was still some monotonous repetition in their writing. he findings of this study have pedagogical implicature as the need to enhance students’ knowledge of grammatical cohesion device because understanding of cohesiveness is necessary for pertaining to the text’s cohesion and coherence particularly in writing ability.
INFORMATION SECURITY RISK MANAGEMENT DESIGN OF SUPERVISION MANAGEMENT INFORMATION SYSTEM AT XYZ MINISTRY USING NIST SP 800-30

SIMWAS is an information system at the XYZ Ministry that is used to manage supervisory activities and follow up on supervisory results. SIMWAS is an important asset that contains all internal control business processes, but in practice, SIMWAS information security risks have not been managed properly. To overcome these problems, information security risk management is needed at SIMWAS. This study aims to design and analyze SIMWAS information security risk management using the NIST SP 800-30 framework. NIST SP 800-30 focuses on a particular infrastructure and its boundaries. Since the purpose is to perform a technical risk analysis of the core IT infrastructure, it is highly prescriptive. It has nine primary steps to conduct risk assessment. The NIST SP 800-30 framework is used to design and analyze SIMWAS information security risks by identifying threats, vulnerabilities, impacts, likelihoods, and recommendations for controls. SIMWAS information security risk assessment is carried out by analyzing data obtained from the results of interviews, observations, and document reviews. The results of this study show that SIMWAS information security has four low-level risks, eight moderate-level risks, and five high-level risks. Very low and low risk levels are acceptable according to the risk appetite of the business owner, but moderate, high, and very high-risk levels require risk avoidance, risk transfer and risk reduction. The XYZ Ministry need to carry out residual risk analysis and cost-benefit analysis from implementing controls in each risk scenarios.
ACCREDITATION PREDICTION OF EARLY CHILDHOOD EDUCATION INSTITUTIONS USING MACHINE LEARNING TECHNIQUES

Accreditation is an acknowledgement of an educational institution regarding the feasibility of carrying out the educational process. Making predictions can save time for early childhood education institutions in compiling accreditation forms that will be submitted. Prediction in determining accreditation becomes an important lesson for an institution in self-assessing the quality of its services. Choosing which method to use in the accreditation prediction process becomes a serious problem, so the prediction results can be the closest or most accurate. Machine Learning is an application that is part of Artificial Intelligence which is widely used in prediction research. In this experiment, three algorithms in machine learning are tested, namely SVM, KNN and ANN. This study uses data from the accreditation results of early childhood education institutions in South Kalimantan; the sample data is 75%, and the remaining data is 25%. The results of the KNN algorithm with Euclidean distance and the number of neighbours 5 have the best performance in predicting the value of the accreditation predicate compared to other methods. The results of calculations using the KNN method produce Area Under Curve values of 1,000, CA 1,000, F1 1,000, precision 1,000 and Recall 1,000.
IMPROVING ONLINE MEETING EFFICIENCY USING LATENT DIRICHLET ALLOCATION (LDA) AND SOCIAL NETWORK ANALYSIS (SNA) METHODS

The pandemic period can change the habits of a person and organization, where all meetings are not held face-to-face/offline but virtually, so it is not uncommon for meetings to be attended by employees who are not Persons in Charge (PIC) on certain meeting topics. This study aims to identify trends in time, day, and duration of meetings within the Secretariat General of the Ministry of Finance and to cluster meeting matters into several themes so that further identification can be carried out to provide recommendations for units having duties related to the meeting using networking analysis. This study uses the Natural Language Processing (NLP) method with Latent Dirichlet Allocation (LDA) which can conclude the factors that represent topics to produce topic clustering and Social Network Analysis (SNA) modeling using the Degree Centrality method to find out the closest relationship between topics and names. unit based on the highest centrality value and the possibility of a unit attending a meeting that discusses a particular topic. Data used in this reseacrh are meetings held during April 2020 up to April 2022 with 59,891 data records. The modeling results shows clustering result dashboard based on meeting topics and to produce an analysis of which meeting topics are often discussed and become a concern. The results of the research are expected to be used to provide recommendations to unit leaders to assign meeting dispositions for each PIC to attend the meeting.
FUEL INCREASE SENTIMENT ANALYSIS USING SUPPORT VECTOR MACHINE WITH PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM AS FEATURE SELECTION

BBM, or fuel oil, is one of the essential needs of the Indonesian people. The government's policy regarding the increase in fuel prices raises many opinions from the public. Twitter is one of the social media that Indonesian people often use to express opinions on a topic. In this study, sentiment analysis was carried out on public opinion regarding the fuel price increase policy from Twitter social media. This research is expected to help determine public opinion regarding the fuel price increase policy with positive, neutral and negative sentiments. The sentiment analysis method used is the Support Vector Machine (SVM) classification algorithm. The results of the accuracy of SVM were compared with accuracy by adding a feature selection process. The Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) algorithms are used for the feature selection method. After several experiments using the three methods, the SVM method with the Radial Basis Function (RBF) kernel produced the best accuracy of 71.2%. The combination of the SVM method with the RBF and PSO kernels obtained an accuracy of 68.84%, and the combination of the RBF and GA kernel SVM methods obtained an accuracy of 69.52%.
IMPLEMENTATION OF THE RANDOM FOREST ALGORITHM IN CLASSIFYING THE ACCURACY OF GRADUATION TIME FOR COMPUTER ENGINEERING STUDENTS AT DIAN NUSWANTORO UNIVERSITY

To ensure the existence of a university remains intact, one way that can be done is by optimizing the performance of the students so that they can graduate on time. A high percentage of on-time graduation will result in a good assessment of the accreditation of the department in the university. However, there are many factors that affect the graduation rate, such as the student's academic performance, extracurricular activities, and other factors. The data of graduation of students in the Computer Science program at the Faculty of Computer Science, Dian Nuswantoro University, for the academic years 2008-2017 is the object of this study. The objective of this research is to create the best classification model using the Random Forest algorithm to predict the accuracy of the graduation time of students, which will be useful for policy making in the future. The results of the classification using this algorithm received an accuracy of 93% for the training data and 91% for the test data.
PERFORMANCE OF K-MEANS CLUSTERING AND KNN CLASSIFIER IN FISH FEED SELLER DETERMINATION MODELS

Feed is a crucial variable because it can determine the success of fish farming. Farmers can use two types of artificial feed, namely alternative feed and pellets. Many cultivators need pellets as the main food for the fish they are cultivating because the pellets contain a composition that has been adjusted to their needs based on the type and age of the fish. However, currently, cultivators are facing problem, namely the high price of fish pellets on the market. Therefore, an analysis of the classification of the selection of fish feed sellers is needed according to several criteria like the number of types of feed, price, order, delivery, payment, availability of discounts, and the number of assessments. This study conducted a predictive analysis to determine the criteria for selecting fish feed sellers in Kendal Regency by utilizing the K-Means Clustering and KNN Classifier methods in the classification method. This research aims to compare the fish feed seller classification method where the pattern of fish feed seller is identified by K-Means Clustering and KNN Classifier, and then the researcher conducts performance appraisal and evaluation. The results of this study are decision-making patterns to help formulate strategies for cultivators and other interested parties. For verifying the method used, measurements were made to obtain an accuracy value where K-Means was 98.6% and KNN was 86.7%.The results of this study indicate that the K-Means Clustering and KNN Classifier methods can classify the selection of freshwater fish feed sellers in Kendal Regency.
ANALYSIS OF E-OFFICE SYSTEM USER SATISFACTION AT LAND OFFICE PEKANBARU CITY USING END USER COMPUTING SATISFACTION METHOD

An E-Office system is available at the National Land Agency, which is part of the Ministry of Agrarian Affairs and Spatial Planning and the National Land Agency. It is designed to make office administration easier. However, the use of E-Office is still not optimally used, such as the minutes feature that is underused, errors in sending letters that are sent not as desired, the dashboard display is less attractive and the guide menu cannot be accessed because of a link error. The purpose of this study is to evaluate user satisfaction with the E-Office system and identify its results. The End User Computing Satisfaction (EUCS) method with six variables (content, accuracy, format, ease of use, timeliness, user satisfaction) was used by researchers to assess user satisfaction with the E-Office system. 37 individuals from the E-Office system user population comprised the sample. The results of the proposed hypothesis test show that the hypothesis is accepted and has a significant effect of 78.9% on user satisfaction.
Research Areas in Cyber Security and Forensic and Centre of Excellence for Forensic Laboratory

This research work identifies the national and international related work to identify the cutting-edge areas of research problems in the domain of cloud computing , mobile software and multimedia data for its security and cyber forensics. The explanatory research identifies the statement of problems with its aim, objectives, and the scope of the work to be conducted into the proposed cyber forensic laboratory. The hardware and software requirements for the cybercrime digital forensic laboratory are identified to conduct cybercrime research in the domain of cyber security for the recommendation of security. The Centre of excellence for computer cybercrime digital forensics will be useful for reading, writing, research, and development to give practical and feasible solutions for building digital forensic tools in the cutting domain of computing systems such as Cloud Computing, Web Applications, Mobile communication, and Multimedia Systems. The hardware and software requirements for setting up the forensic laboratory are identified and the budget expected to set the centre of excellence for a cybercrime investigation laboratory is approximately Rs.7,79,83,434.39/- which may vary depending on versions and updates to hardware and software’s.