Reviewerly/exHarmony huggingface dataset:
Hybrid Cryptosystem Analysis RSA Algorithm And Triple DES Algorithm

Data security is needed in terms of communication. To guarantee data security, a technique is needed to make data and information called Critography. This study aims to analyze the process of Super Encryption in symmetric and asymmetric criterias using the Triple DES Algorithm and the RSA Algorithm. This can improve data security so that data is more confidential. The method used in Triple DES which is also called the symmetric algorithm is the OFB (Output feeback) method, and the RSA Algorithm (Riverst - Shamir-Adleman) which is an asymmetric algorithm using a random number system so that when these two algorithms are combined in the Super Encryption process the more accurate the data security. Super DES Triple Encryption and RSA algorithm analysis shows that the data created by text will be encrypted into ciphertext using both methods and re-described, so that the security of the data is relatively safe. Super Encryption on the two methods Algorithm is done because the level of complexity is difficult to make Cryptanalysts to steal data and the Encryption process becomes slow but data security becomes safer and not easy to attack Cryptanalysts. The problem in this research is how to increase encryption security and speed up the encryption process by combining the RSA and Triple DES methods.
FREQUENCY ANALYSIS OF DELI RIVER FLOOD DISTRIBUTION PLAN USING THE GUMBEL PROBABILITY DISTRIBUTION METHOD

The Deli river basin is one of the rivers in North Sumatra Province which is in Medan City with an area of ​​394.88 km2 and a length of 166.01 km. Medan Maimun District which has an area of ​​2.98 km2 and a population density of 16,520 people/km2. Medan Mimun sub-district is one of the flood-prone areas which is drained by the Deli River. The cause of the flooding that occurred in Medan Maimun District was high rainfall so that the river flow rate increased and drainage was poor. So that the problem of flooding in the Deli river watershed, Medan Maimun sub-district, can hamper community activities, these floods can also harm and endanger the community. The flood discharge plan for each repeat period where the variable used is the maximum daily rainfall for 10 years From 2013-2022 which is sourced from the BMKG Deli Serdang. In this study using frequency analysis and then proceed with the Gumbel Probability Distribution method, Normal Distribution Log Person Type III. The result of this study with hydrological data and distribution test, the suitable method for analyzing the planned flood discharge in the Deli River is Log Person Type III that it can be flood discharge for a 2 year retention period is 12.7684672 m3/sec, 5 year return period is 12.56275855 m3/sec, 10 year return period is 15.91400029 m3/sec, 25 year return period is 16.87871678 m3/sec, 50 year return period is 17.43836748 m3/sec and a 100 year return period is 17.89619614 m3/sec.&#x0D; &#x0D; Keywords: Rainfall, Deli River, Planned Flood Discharge&#x0D;
Pareto Frontier Approach to Determining the Optimal Path on Multi-Objectives

Every issue we face in daily life can be resolved through mathematical modeling. The use of mathematical modeling to generate solutions frequently produces value that serves a single purpose. Sometimes a single-purpose function's solution does not offer the best solution value. In this study, the author models the multiobjective time-dependent vehicle routing problem using the Ant Colony Optimization (ACO) metaheuristic algorithm. The author then applies the pareto optimization principle to the determination of the optimal starting point for the route. An optimal Pareto frontier principle solution on a multi-objective model under control of the Ant Colony Optimization algorithm is the outcome of this study.&#x0D;
Crime of theft prediction using Machine Learning K-Nearest Neighbour Algorithm at Polresta Bandar Lampung

The era of the industrial revolution 4.0 is a time where cyber and physical technology collaborate. This study aims to predict the types of theft crimes that occur in the Bandar Lampung Police area with the K-Nearest Neighbor algorithm, evaluate the prediction results and profiling the prediction results carried out by Bandar Lampung Police investigators in efforts to prevent and handle criminal acts of theft in the jurisdiction of the Bandar Lampung Police Lampung. The approach was carried out using the quantitative method of the K-Nearest Neighbor algorithm using the Rapidminer application by utilizing 1671 police report data from the Bandar Lampung Police and a questionnaire survey method conducted on 49 police investigators from the Bandar Lampung Police. Data collection techniques are carried out in a valid and reliable manner as a support for predictive validity. Based on the results of the classification and questionnaire, it was found that the majority of victims of the crime of theft were adult men who did not have a job and lived in urban areas. It was found that the majority of thefts occurred in parking lots in urban areas on Monday morning where the perpetrators used tools and targeted moving objects by tampering with locks which caused losses of around 10-50 million rupiah. This type of theft is theft by weighting (CURAT) which applies to Article 363 of the Criminal Code. The prediction results show that the neighboring value (K) and the distribution ratio of training and testing data are K=3 and 7:3, respectively. Predictions using K values and data sharing ratios show a high level of accuracy, namely 99. 20%. The results of the questionnaire show results that are in line with the results of the classification with an accuracy rate of the actual data of 75. 7122%. So by increasing the understanding skills of Bandar Lampung Police investigators using technology to predict the crime of theft, the number of theft crimes can be reduced.
Sentiment Analysis Of Tourist Reviews Using K-Nearest Neighbors Algorithm And Support Vector Machine

After Indonesia was awarded as a country with extraordinary natural charm, many foreign tourists came to Indonesia. According to the records of the Central Bureau of Statistics for 2020, approximately 5.47 million foreign tourists entered Indonesia. With the large number of foreign tourist visits, the need for tourist attractions is increasing, but finding information is now not difficult. One source of information for finding reviews of tourist attractions is TripAdvisor. On this website, there is a lot of information or reviews about various tourist attractions. However, the number of reviews makes tourists confused about identifying the quality of tourist attractions to be visited, so sentiment analysis needs to be done. Sentiment analysis itself is a technique to extract, identify, and understand sentiments or opinions contained in a text. In this research, two classification methods will be used in sentiment analysis techniques, namely K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM). Besides that, the object of this research will be to focus on the most popular tourist attractions in Indonesia according to Trip Advisor, namely Waterbom Bali, Mandala Suci Wenara Wana, Teras Sawah Tegalalang, Pura Tanah Lot, and Pura Luhur Uluwatu. The purpose of the research is to find out the results of accurate sentiment analysis for the five tourist attractions and compare the two algorithms used. and after testing, it was found that the Support Vector Machine algorithm is superior to the K-Nearest Neighbors algorithm.
Integer Linear Programming Model for Multicast Routing to Minimize Link Cost at Wavelengths

Routing is a technique or process carried out in a packet or information delivery system from a source to a destination or a place that requests the information needed from a source. Routing is done in solving a problem and is well-known is unicast routing. Unicast routing can transmit information from a source to a single destination. However, this is ineffective for an infinite number of requests to be served because the unicast routing system only funnels one destination to one source. So that another route is needed that can handle this, this route is called a multicast route. Multicast routing that can serve multiple destinations with only one source so that a collection of destinations to get the same request in the same time and data. This research will discuss multicast routing to minimize link costs at wavelengths using a hierarchical structure. To help provide reduction or savings on the link by offering an integer linear programming model formulation to minimize link costs at wavelengths. An update from previous studies is to use a hierarchical structure with wavelength conversion taking into account the links that are traversed and the requests that will be served by the source to the destination. Using wavelength conversion so that there are no wavelength continuity problems, so that when sending information you get more path choices and you can save on sending information using a link that will be passed from the source to the intermediate node until it reaches the destination node, with this it will find a path more efficiently so that the goal of minimizing link cost at wavelengths on multicast routing is achieved&#x0D;
COMPARISON OF LASSO AND ADAPTIVE LASSO METHODS IN IDENTIFYING VARIABLES AFFECTING POPULATION EXPENDITURE

Abstract: Since 2019, the difference in the increase in per capita expenditure of the population has continued to decline, and the most significant was only IDR 18,464 in 2021, indicating that the level of consumption of the population has not improved significantly, and the turnover of the community's economy is also not good. Multiple linear regression is more appropriate than other types of linear regression because it considers the influence of more than one independent variable on the dependent variable. However, problems may arise in the use of multiple linear regression, such as multicollinearity. To overcome this problem, other methods such as LASSO and adaptive LASSO should be used. Both methods have the ability to overcome multicollinearity between independent variables, thereby reducing the risk of misestimation. Nevertheless, the LASSO and Adaptive LASSO methods have differences in selecting important variables, so it is necessary to compare which method is better in terms of identifying influential variables. Based on the MSE and R-square comparison values, it is concluded that the Adaptive LASSO method model is the best model with a lower MSE value and a higher R-square value of 93%. The variable selection results of the Adaptive LASSO model are population size, number of households, average number of household members, constant price GDP, confirmed cases of COVID-19, human development index, percentage of the poor population, university student participation rate, and open unemployment rate.
Perceived Usability Evaluation of TikTok Shop Platform Using the System Usability Scale

The popularity of TikTok is getting higher because from the start TikTok is a platform that provides a new experience that combines the experience of social media as well as transacting online.TikTok allows businesses to market their products in as creative a form as possible, such as making videos and building a community with their market share. TikTok is an application that plays an important role in paid promotional media, which is of course directly related to digital marketing carried out by business people in the e-commerce sector. In this research, the author wants to know the usability of the TikTok Shop feature as an e-commerce feature that has recently become increasingly popular in society. The System Usability Scale (SUS) will be used to test whether the TikTok application, especially the TikTok Shop feature. The standard SUS version has 10 instruments. The accuracy value is then measured using acceptable rage, grade scale and adjective ratings System Usability Scale (SUS). Based on questionnaire data collected from 49 respondents, it was found that 10.6 percent of the respondents were male and 93.6 percent of the respondents were female. The accuracy value of 79.49 is included in the acceptability ranges acceptable category, meaning that the TikTok Shop platform can be accepted by users, getting a C grade scale means it is quite good and is included in the adjective ratings excellent category.
Analysis of Public Purchase Interest in Yamaha Motorcycles Using the K-Nearest Neighbor Method

This data mining will carry out a classification of people who are interested and not interested in buying Yamaha motorcycles. In the data mining process, a method is needed that can provide goals to the data mining process. That's because there are many data mining methods that can be used. In this study the method that will be used by the author is the K-Nearest Neighbor (kNN) method. This method will be used to classify people's buying interest in Yamaha motorbikes. This research was conducted because there are some people who say that Yamaha motorbikes are not good, use of wasteful fuel. Therefore this research was conducted to prove this statement. So a research was made about people's buying interest in Yamaha motorbikes. Classification results obtained from 100 community data. From the classification process that has been carried out, the results show that 41 community data (41% representation) are interested in buying Yamaha motorcycles and 59 community data (59% representation) are not interested in buying Yamaha motorbikes. The results obtained state that there are still many people who are interested in Yamaha motorbikes. But it can be used as a reference that people are interested in motorbikes that have a good appearance, use economical fuel and are affordable. These results were obtained from the community's answers in the questionnaire, they were interested in motorbikes that use little fuel, have good designs and are affordable.
Development of Augmented Reality Multiple Markers Application Used for Interactive Learning Media

Augmented Reality (AR) is a technology that can turn virtual objects in the form of two dimensions (2D) or three dimensions (3D) into an object that looks real, then able to display objects in real-time. Using AR technology, you can visualize learning material into 3D objects to make it easier to understand when using it as a learning medium. This research aims to develop an AR application with multiple marker features that can be used as an interactive learning medium. The method used is Research and Development (R&amp;D), and the development model used is 4D. The evaluation used was the Software Usability Measurement Inventory (SUMI), involving 11th-grade which involved 30 students consisting of 20 male students and 10 female students, the parameters assessed in this evaluation were between others are Efficiency, Affect, Helpfulness, Control, and Learnability. Based on the analysis performed on these parameters, the results show that all five parameters obtain valid and reliable results for each parameter in the validity and reliability tests with a Cronbach's alpha score of 0.934 (Efficiency), 0.868 (Affect), 0.917 (Helpfulness), 0.878 (Control), and 0.919 (Learnability). Thus, this multiple marker-based interactive learning media, Augmented Reality (AR), can be used in learning activities.
A Mathematical Approach to Dampening Sea Waves Using Submerged Permeable Breakwater

A wave is an energy that can propagate with a medium; the propagation of a wave moves with respect to time by carrying energy that moves with velocity per unit of time. Sea waves are one of the propagating wave problems that are broken down to produce wave propagation with a relatively inhomogeneous minimum amplitude and speed of sea waves, which have their own difficulties in solving them numerically. This study aims to analyze the stability of wave propagation on submerged breakwaters. This research will approximate the finite discretization of the breakwater domain and then combine it with the Finite Element Method to determine the moving elements of the velocity of fluid flow through a porous submerged breakwater. The research has explained the equation of the inflated wave and the simulated representation displayed on the wave breakdown process, the point that becomes the center of the waves breakdown will give a focused red color indicator meaning there is a change in momentum and potential energy that occurs and then changes the colour of the post-flattering of the sea wave so that the sinking wave breaker is a method to obtain the minimum speed and amplitude values that can be used for coastal engineering.&#x0D; &#x0D;
Survey Paper: Optimization and Monitoring of Kubernetes Cluster using Various Approaches

This research compares different methods for optimizing and monitoring Kubernetes clusters. Three referenced journals are analyzed: "Kubernetes cluster optimization using hybrid shared-state scheduling framework" by Oana-Mihaela Ungureanu, Călin Vlădeanu, Robert Kooij; "Monitoring Kubernetes Clusters Using Prometheus and Grafana" by Salma Rachman Dira, Muhammad Arif Fadhly Ridha; and "Cluster Frameworks for Efficient Scheduling and Resource Allocation in Data Center Networks: A Survey" by Kun Wang, Qihua Zhou, Song Guo, and Jiangtao Luo. These journals explore various approaches to optimizing and monitoring Kubernetes clusters. This review concludes that selecting appropriate technologies for optimizing and monitoring Kubernetes clusters can enhance performance and resource management efficiency in data centre networks. The research addresses the problem of improving Kubernetes cluster performance through optimization and efficient monitoring. The required methods include utilizing hybrid state-sharing scheduling frameworks, implementing Prometheus and Grafana for monitoring, and employing efficient cluster frameworks. The study's findings demonstrate that adopting a hybrid shared-state scheduling framework can improve Kubernetes cluster performance. Additionally, leveraging Prometheus and Grafana as monitoring tools offer valuable insights into cluster health and performance. The survey also reveals various cluster frameworks that enable efficient scheduling and resource allocation in data centre networks. In conclusion, this research emphasizes the significance of employing suitable technologies to optimize and monitor Kubernetes clusters, leading to enhanced performance and efficient resource management in data centre networks. By leveraging appropriate scheduling frameworks and monitoring tools, organizations can optimize their utilization of Kubernetes clusters and ensure efficient resource allocation
Sentiment Analysis of Shopee Food Application User Satisfaction Using the C4.5 Decision Tree Method

Sentiment analysis on public opinion regarding the shopee food application is an interesting topic in the context of evaluating service quality in the shopee food application. In this digital era, user opinion has a very important role in shaping public perception of the application. Therefore, sentiment analysis is needed to understand user opinion about the shopee food application. This study uses Decision Tree C4.5 to analyze public sentiment on the use of the Shopee Food application on Twitter users. However, beforehand it is necessary to overcome the problem of data imbalance which is common in datasets, where the number of positive, negative, and neutral sentiments is not balanced. To overcome this problem, three different techniques are used, namely SMOTE, undersampling, and a combination of oversampling and undersampling. The results of this study indicate that the SMOTE technique provides better results in overcoming data imbalances and increasing prediction accuracy. With an accuracy of 0.88. the SMOTE technique can provide more accurate sentiment predictions than the undersampling technique and the combination of oversampling and undersampling. This is because SMOTE can synthetically expand the number of minority samples, thereby preventing the loss of information and maintaining variation in the dataset. In conclusion, sentiment analysis on the Shopee Food application on Google Play using the Decision Tree C4.5 algorithm and the SMOTE technique can overcome data imbalances with a prediction accuracy of 0.88. This technique is more efficient than the undersampling technique and the combination of oversampling and undersampling. These results can provide developers with valuable insights to improve app quality and user satisfaction.
Leveraging Technology for MSME Development: A Case Study of the Sistem Informasi Hasil Desa (SIHASA) V2 in Banyumas Regency

Banyumas Regency in Central Java Province comprises 27 districts and 331 villages, showcasing its vast geographical coverage. Over three years, from 2006 to 2009, the region witnessed a notable increase in small businesses, rising from 643 to 717 establishments. Despite this growth, MSMEs in Banyumas face a prevalent challenge of inadequate information dissemination for effectively promoting their products. To tackle this issue, a proposed solution is the Village Results Information System (SIHASA) V2 website. This website supports village communities, MSMEs, and governments in managing their respective activities and operations. To expedite the creation of the system, the Rapid Application Development (RAD) method is employed, encompassing essential stages such as project requirement determination, prototype creation, development processes, and gathering feedback.&#x0D; Furthermore, to ensure an efficient system design, the implementation of Unified Modeling Language (UML) is integrated, incorporating crucial components like Use Case Diagrams and Class Diagrams. This meticulous design approach guarantees that the system effectively caters to the community's diverse needs, specifically benefiting the village community in Banyumas Regency in terms of managing village products and facilitating efficient MSME operations. The outcomes of this research endeavor hold significant promise for the community, providing practical tools and resources to enhance their livelihoods and contribute to the overall development of the Banyumas Regency.
Analysis And Design of Mobile Applications For Make-Up Artist Services (Halomua) With The Design Thinking Framework

Designing an application user interface design is an important part of creating an attractive application. However, there are several problems such as lack of attention to detail, failure to identify and solve customer problems, and poor planning or organization. The design thinking method performs stages ranging from empathize, define, ideate, and prototype, to usability testing to reduce these problems. At the empathize stage, data is obtained through interviews with MUAs and online questionnaires that have been filled out by respondents. At the define stage, a profile picture of each respondent along with their problems and goals was created. At the idea stage, feature mapping, information architecture, low fidelity wireframe, medium fidelity wireframe, and user flow are made so that it can facilitate users in operating the tasks designed in the application. The prototype stage is to create a flowchart design for each case so that users can find out how the application can run properly. The results of usability and user satisfaction are measured using the System Usability Scale (SUS). The SUS average value of 85.2 is obtained, which means that the value of the UI design results is included in category B with an "Excellent" status.