Reviewerly/exHarmony huggingface dataset:
EFFECTIVENESS OF SECURITY THROUGH OBSCURITY METHODS TO AVOID WEB APPLICATION VULNERABILITY SCANNERS

The concept of security through obscurity is not recommended by the National Institute of Standards and Technology (NIST) as a form of system security. Basically this concept hides assets as difficult as possible so that it is not easy for attackers to find them, so that it can be used to avoid vulnerability scanner applications that are widely used by attackers to find out web system weaknesses. This research was conducted by modifying the web application firewall (WAF) and testing using the SQLMap and OWASP Zed Attack Proxy (ZAP) vulnerability scanner applications. The results of the study show that SQLMap takes up to 1238 times longer to complete a scan on a modified web application firewall than without modification, while OWASP ZAP cannot complete a scan on the same treatment. Thus the concept of security through obscurity can be applied to web security to extend vulnerability scanning time.
IMPROVEMENT OF NAIVE BAYES ALGORITHM IN SENTIMENT ANALYSIS OF SHOPEE APPLICATION REVIEWS ON GOOGLE PLAY STORE

Reviews of the shopee application on the google play store are included in useful information if processed properly. Old or new users can analyze app reviews to get information that can be used to evaluate services. The activity of analyzing application reviews is not enough just to see the number of stars, it is necessary to see the entire contents of the review comments to be able to know the intent of the review. A sentiment analysis system is a system used to automatically analyze a review to obtain information including sentiment information that is part of an online review. The data is classified using Naive Bayes. A total of 1,000 shopee app user reviews were collected to form the sample dataset. The purpose of this study is to determine the sentiment analysis of shopee application reviews in the Google Play Store using the Naive Bayes algorithm. The stages of this research include, data collection, labeling, pre-processing, sentiment classification, and evaluation. In the pre-processing stage there are 6 stages, namely Cleaning, Case folding, Word Normalizer, Tokenizing, Stopword Removal and Stemming. TF-IDF (Term Frequency - Inverse Document Frequency) method is used for word weighting. The data will be grouped into two categories, namely negative and positive. The data will then be evaluated using accuracy parameter testing. The test results show an accuracy value of 81%, this result shows that shopee application reviews tend to be negative.
《中華字經》在對外漢語詞彙教學中應用研究

Zhong Hua Zi Jing is Chinese teaching material promoted nationwide and overseas for the purpose of “fast literacy and early reading”, which covers Level 4 Chinese characters specified in the HSK exam outline. Its content includes knowledge of fifty major categories, including astronomy, geography, human relations, history, and the like. Therefore, this study is based on Xu Tongqiang’s sinogram-based theory. This paper proposes a teaching plan using the Zhong Hua Zi Jing in teaching Chinese as a foreign language in order to achieves positive results in vocabulary and Chinese character learning. A survey was first conducted on Korean students in years three and four of the Chinese language major to demonstrate their level of understanding of Chinese characters included in Zhong Hua Zi Jing, and to elucidate the level of understanding of Chinese characters Zhong Hua Zi Jing. Then, the necessity and specific solutions of using Zhong Hua Zi Jing to teach vocabulary mainly based on Chinese characters was explored.
COMPARISON OF LEAST SQUARE AND QUADRATIC METHODS ON PREDICTION THE NUMBER OF NEW STUDENT APPLICANTS

New student registration is held every year with several mechanisms. However, in recent years the number of applicants has decreased even though it had experienced a surge in the previous year. So that, it is necessary to have a prediction to predict the number of applicants in the coming year. In addition, the results of these predictions can be used as material for consideration in determining the quota/ceiling for the number of new student admissions in the following academic year. This research used the Least Square and Quadratic methods to predict the number of new student applicants based on data on the number of applicants from the 2014/2015 to 2022/2023 academic years. Performance testing of the two methods was tested with three (3) testing methods : MAE, MAPE, and MSE. The performance test found that the Quadratic method is more suitable with the MAPE value in the "Good" forecasting accuracy category, which is 11%. For the MAE value, it gets 452,17 and an MSE of 302069,04. While Least Square produces a MAPE value in the "Enough" forecasting accuracy category of 30%, for the MAE value, it gets 996,97 and an MSE of 1494205,36.
IMPLEMENTATION OF LSTM (LONG SHORT TERM MEMORY) ALGORITHM TO PREDICT WEATHER IN CENTRAL JAVA

Agro-indutrial agricultural production such as red onions in Indonesia has a very important share in driving Indonesia's economic growth, especially in Central Java province which contributed 28.15% of the total national red onion production in 2021. Weather conditions have a major influence on the red onion planting process until the red onions are ready to be harvested. In this study, the objective is to predict various types of weather such as rainfall, air temperature, and air humidity in seven districts in Central Java, namely Brebes, Temanggung, Demak, Boyolali, Kendal, Pati, and Tegal. To do this, the use of the LSTM (Long Short Term Memory) algorithm with its ability to store memory longer than RNN will be reliable for predicting various types of weather in the future. This research was developed with the CRISP-DM (Cross Industry Process Model for Data Mining) method which has a goal-oriented approach, this method is a mature and widely accepted method in Data Mining with various applications in Machine Learning. With the final results from 39 models by using the evaluation of the average value of train MSE 0.013, test RMSE 0.11, test MSE of 0.02, test RMSE 0.12 and succeed to predict 5 days or months ahead from the last data that is provided.
PERFORMANCE OF TEXT SIMILARITY ALGORITHMS FOR ESSAY ANSWER SCORING IN ONLINE EXAMINATIONS

The purpose of assessment is to determine learning success. Exams with question descriptions have several advantages, including ease of preparation and the ability to reveal student comprehension and originality. The problem with space is that it takes time to fix. Therefore, it is important to develop algorithms and software that automatically evaluate space. With the help of this algorithm and this software, you can solve some exam and assessment problems. This study aims to investigate similarity algorithms that approximate human patterns in evaluating ambiguous answers. This study examines his five similarity algorithms, including TF-IDF and LSA. The data was a collection of correct answers with a total of 371 texts. The similarity algorithm's performance was compared with human correction results. Evaluation was performed using Root Mean Square Error (RMSE). This study shows that his TF-IDF algorithm like Jaccard has the lowest his RMSE compared to human judgement. However, the LSA algorithm tended better to follow human rating patterns for descriptive tests..
COMPARATIVE STUDY OF CLOUD COMPUTING NETWORK SERVICES BASED ON QoS ANALYSIS USING TIPHON STANDARD

Currently, data plays a very important role for companies or agencies. The amount of data owned, processed, and exchanged is getting bigger, so companies need more and more resources to manage it. Cloud computing technology is an efficient and economical alternative that allows users to utilize Information Technology (IT) resources flexibly, in terms of infrastructure and applications. Its key advantages include cost efficiency, scalability, data security, disaster recovery, and fast global access. The rapid development of cloud technology has led to many Cloud Service Providers (CSPs). The performances of the CSPs vary widely, thus it is necessary to understand the network performance characteristic from the CSPs so that users can select a more suitable service. Network capabilities in cloud computing technology are crucial, considering that all company activities are carried out through the network. In this study, the main focus was to test the network capabilities of the two biggest cloud services The results of the Quality of Service (QoS) comparison will provide recommendations or input for companies or agencies in choosing the cloud service provider that best fits their needs. Thus, it was obtained that this research can provide useful guidance in optimizing the use of cloud computing technology to support business activities and innovation in various fields, including the field of education. Based on the results of the research, the network performance of the two CPS is very good in terms of the TIPHON standard. Based on QoS analysis, especially in terms of throughput, CPS “A” shows better upload activity results, while CPS B has better results for downloading activities.
DECISION SUPPORT SYSTEM FOR SELECTION OF PESTICIDES FOR CHILI PLANTS USING THE MABAC METHOD

The use of pesticides in agriculture plays a role in preventing and reducing diseases in chili plants. Pesticides for chili plants are quite widely spread on the market and have the advantages of each product offered to farmers, so farmers must be more careful and understanding in choosing pesticides to be used in preventing chili plant diseases. For that we need a decision support system (SPK). The data used in this research are 10 types of pesticides as an alternative. While the criteria are determined based on the agriculture and food service, namely price, classification, number of diseases eradicated, method of action, shelf life, and formulation concentration. Data analysis uses the MABAC method to support decision making for farmers in providing an assessment of the best pesticides on chili plants by steps to forming decision matrices, normalizing decision matrices, determining weighted matrices, determining border area matrices, determining alternative distance matrices, and ranking. The research results obtained the three best pesticides are Tridex 80 WP, Ziflo 76 WG, and Cabriotop 60 WG.
REAL-TIME DROWSY FACE DETECTION FOR ONLINE LEARNING BASED ON RANDOM FOREST AND DECISION TREE ALGORITHMS

In the current era, technology regarding artificial intelligence has developed rapidly and has been used in various areas of life. Face detection is one of the applications of Artificial Intelligence. This research aims to detect students' faces during the online learning process and succeeded in getting positive feedback when tested on students. Student detection includes drowsy and alertness. The method is via webcam in real-time so that the screen will show whether the student is drowsy or alert. In the trial, the teacher can find out who is in a drowsy and alert condition. On the other hand, students can find out that they fall into the drowsy or alert category. So that both parties immediately respond to what should be done based on the classification results. The algorithms used are Decision Tree and Random Forest. The accuracy results of the Random Forest algorithm are better than the Decision Tree algorithm, namely 65 percent, while the Decision Tree algorithm is 58 percent. The division of training data and test data uses a Kfold of 5. When Kfold is equal to 2, both algorithms have the highest accuracy, where Random Forest has an accuracy of 85 percent, and Decision Tre has an accuracy of 65 percent.
DESIGN OF A PLANE FIGURE MATHEMATICS EDUCATION GAME FOR CLASS IV STUDENTS BASED ON ANDROID

Mathematics is a branch of knowledge related to developing abstract concepts, structures, and relationships in the form of numbers, symbols, and patterns. The issue some students still have trouble recalling formulas, doing division in one of the flat shape materials, and doing multiplication using the formula for the perimeter and area of flat shapes. This research discusses the design of educational games to help fourth-grade students learn flat-shape mathematics. Interviews were conducted with class IV teachers at SDN Sirnajaya Five in conveying material to students; they did not use learning media or visual aids. The problem that often arises is that some students still need help learning flat-shape mathematics. This research aims to build a flat-shape math educational game application for fourth-grade students so that these students can quickly understand the basics of flat-shape material, the definition of flat shapes, formulas, and the properties of flat shapes. The method used is the Multimedia Development Life Cycle (MDLC), a pattern for developing software systems consisting of Concept, Design, Material Collecting, Assembly, Testing, and Distribution stages, which form a workflow for planning and controlling the design of Educational Game applications. This research results in an Android-based flat-shape mathematics educational game application.
TEXT CLUSTERING IN KARO LANGUAGE USING TF-IDF WEIGHTING AND K-MEANS CLUSTERING

The aim of this research is to see how many presentations there are between dialects and look for clusters. There is also a method used for weighting, namely tf-idf, there are several steps used in this method, namely starting from the tokenizing process, transform cases, stopwords filter and token filter. to search for clusters using the k-means clustering method on rapidminer. The results of this research obtained a tf-idf weighting value, namely ginger dialect 37.5% for the number of word occurrences and 62.5% for the total of all words documented. Furthermore, for the Julu dialect, it was 37.5% for the number of word occurrences and 62.5% for the total of all words documented. The Singaporean Lau dialect accounts for 38% of the number of word occurrences and 62% of the total number of words documented. The singteruh deleng lau dialect accounts for 38% of the number of word occurrences and 62% of the total number of words documented. The Liang Melas dialect accounts for 38% of the number of word occurrences and 62% of the total number of words documented. Based on k-means clustering, it produces cluster 0: 68 items, cluster 1: 3 items, cluster 2: 15 items, cluster 3: 10 items, cluster 4: 4 items with a total sample of 100 items. The conclusion obtained is that the Ginger dialect and the Julu dialect are identical, while the Singaporean Lau dialect, the Teruh Deleng and Liang Melas dialects are also identical.
Application of the Learning Vector Quantization Algorithm for Classification of Students with the Potential to Drop Out

Universities, as providers of academic education services, are required to provide an optimal educational process for students to produce a generation of quality human beings. Student learning success is seen as the success of universities in implementing the higher education process. One of the problems universities face in maintaining the quality of education is student dropout. The high dropout rate in universities can impact accreditation assessments. As a result, it will affect the level of public trust. The number of dropouts in higher education can be minimized from an early age by analyzing the factors that cause student dropouts using data on students who graduated and those who dropped out. This data can be used to determine student dropout patterns by classifying them using the artificial neural network learning vector quantization (LVQ) approach. The data used in this research was 4053, consisting of 3840 graduate student data and 213 dropout student data. This data is considered unbalanced, an unbalanced dataset can cause errors because the model tends to classify the majority class with a high classification and pays less attention to the minority class. So, it is necessary to apply oversampling techniques to overcome this problem. The research results show that the application of the LVQ method to unbalanced data produces an accuracy value of 95.53%, a precision value of 100%, a recall value of 15.02% and an f1-score of 0.26, while the application of the LVQ method to data that has undergone resampling resulting in an accuracy value of 94.66%, a precision value of 92.22%, a recall value of 97.55%, and an f1-score value of 0.95. The LVQ method can be used to classify dropout students with excellent results.
The Implementation of Business Intelligence to Analyze Sales Trends in the Indofishing Online Store Using Power BI

The growth of online sales businesses by utilizing E-Commerce is increasing rapidly. One way that can be used as a tool to face competition is to apply Business Intelligence as a basis for making the right business strategy decisions. Indofishing Shop is an online shop selling various fishing gear and equipment. So far, online sales transaction data processing uses Microsoft Excel, which has created problems with the need for more information to analyze product trends. This research applies Business Intelligence to detect data extracted and collected in a data warehouse. The data will be analyzed statistically and visualized using Microsoft Power BI. Data warehouse design uses Kimball's Nine-Step method. The results of this research are in the form of a visualization dashboard that is used to analyze sales trends for the most sold fishing equipment products from the Indofishing Shop. Diagram visualization helps Indofishing understand the trend conditions of the most in-demand products and the cities of origin of the buyers who buy the most products.
D-RDMALib: InfiniBand-based RDMA Library for Distributed Cluster Applications

RDMA (Remote Direct Memory Access) is a recent communication protocol that allows for the maximum utilization of the performance of InfiniBand, a high-speed network device based on Data Processing Units (DPUs). However, the existing RDMA development method incurs a high implementation complexity, which makes it difficult to apply to a multi-node environment. To solve these problems, we propose D-RDMALib, an efficient and easy-to-use RDMA library suitable for distributed cluster environments. As an effective development tool, D-RDMALib can reduce the implementation difficulty of applying RDMA to distributed multinode environments. It also improves the accessibility of InfiniBand and RDMA technologies with high entry barriers. In this paper, we demonstrate the efficiency of D-RDMALib by 1) verifying the successful operation of many-to-many communication in distributed nodes, and 2) evaluating the performance by implementing PageRank-based on DRDMALib. We believe that our work is a novel technique that can be easily applied to existing distributed processing environments as well as to emerging ultra-high-speed in-network technologies such as Quantum InfiniBand.
SIMULASI SISTEM MONITORING OKSIGEN TERLARUT (DO) PADA BUDIDAYA UDANG VANAME BERBASIS INTERNET OF THINGS (IoT)

Indonesia has a prospective fishery sector, with an elongated coastline making it potential in the vannamei shrimp farming sector using an Internet of Things (IoT)-based system. Vannamei shrimp (Litopenaeus vannamei) is cultivated with an intensive application of high-density systems with a stocking density of 150 m2, so vannamei shrimp cultivation, namely water quality management to balance the bioenergy metabolism of shrimp, requires water quality such as dissolved oxygen (DO) to increase yields and production. To increase production yields, a system is needed that can monitor dissolved oxygen (DO) levels, an important factor for shrimp growth. The minimum DO level for shrimp growth is 3.0 mg/L, and DO that has the potential to cause mortality is &lt;2.0 mg/L, while the optimal DO value for vannamei shrimp cultivation is &gt;3 mg/L with a tolerance of 2 mg/L. The simulation results of an IoT-based system state that if the green light is on as a sign that the oxygen in the pond has been fulfilled, the results of dissolved oxygen readings are good or normal as seen from the display on the LCD, and the simulation value of the temperature system analysis is seen using ThingsBoard, so that the simulation system can be implemented in real terms.
The Influence of Problem-Based Learning on Problem-solving Ability and Self-directed Learning Ability in College Students Majoring in Cosmetology

This study attempted to investigate the influence of problem-based learning (PBL) on problem-solving abilities and self-directed learning capabilities in college students majoring in cosmetology. For this, a survey was performed against 45 students who attended PBL courses. The collected data were analyzed, using SPSS 21.0. To examine subjects’ general characteristics, frequency analysis was performed. To investigate changes in major satisfaction, teaching methods and PBL preferences, the t-test and the χ2 (chi-square) test were conducted. In addition, the paired t-test and the Pearson correlation coefficient were performed, and the results found the followings: First, a statistically significant difference was found in problem-solving abilities. Second, a statistically significant difference was also observed in self-directed learning capabilities. Third, a statistically significant positive correlation was found among self-directed learning capabilities, problem-solving abilities and major satisfaction. Third, average major satisfaction increased after PBL, which confirms the improvement of students’ preferences for PBL.
KONSEP DASAR DALAM SISTEM INFORMASI MANAJEMEN DALAM PENDIDIKAN

Abstract : Management in education requires a system that stores various information needed in educational institutions. The system can be said to be a management information system. Management information systems in education have a very broad scope and are based on initial concepts such as systems, data, databases, and information presentation in an educational institution. This article aims to explain the basic concepts related to management information systems in education. This article uses descriptive qualitative and literature study methods by collecting various information from various references related to systems, system development, education systems, information, data, databases and the provision of educational data and information. The education system is a regular arrangement of activities and sub-systems that are interrelated with each other and correlated to achieve the desired educational goals. In the system there are two parts that should not conflict with each other, the difference only lies in the procedures for use and elements such as teachers, students, student guardians, principals, and the community. Furthermore, the system requires development that is useful as an improvement in achieving educational goals through stored data and information.
Domain Ontology Evaluation in Software Development: Questionnaire Proposal

Knowledge has become increasingly important as a resource for organizations. In line with this, there arises the need for the classification and organization of knowledge bases in knowledge-oriented organizations. In this regard, ontologies support the process of structuring and classifying information, facilitating and simplifying the continuous data processing. The present work aims to propose a questionnaire for the validation of a domain ontology.