Journal of Computer Networks, Architecture and High Performance Computing
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Web Based Social Assistance Distribution Monitoring System Using Waterfall Method
Get PDFCurrently, the Indonesian nation is in a state of economic crisis, many people are affected by the economic crisis. Social assistance is the provision of assistance in the form of money/goods from the government to underprivileged communities, which aims to improve people's welfare and meet the needs of the community in maintaining their lives during the current economic crisis. The village head is one of the government officials as well as officers from the social assistance distribution with the aim of minimizing the problem. A lot of assistance comes but is not evenly distributed to people in need, it is necessary to have a monitoring system for the distribution of social aid programs so that the assistance distributed remains on target and the quality of budget absorption is optimal. The monitoring process will be carried out by the village head directly to monitor the progress of the distribution of aid and submissions. Therefore, this research will build a web-based monitoring system for the distribution of social assistance. This social assistance distribution system in the form of a website, will contain data on recipients of the family hope program and community submission data. The design of this system uses Unified Modeling Language (UML) and the development of the system uses the Waterfall method which will test the system. With this system, it will help the Village Head in monitoring the distribution of aid and assist the community in submitting it
Analysis Of Decision Support Systems Edas Method In New Student Admission Selection
Get PDFUniversity of Harapan Medan is one of the private tertiary institutions in North Sumatra which has an informatics engineering study program. The informatics engineering study program is a study program that has many enthusiasts. Every year this study program graduates more than 200 students. To produce graduates who have potential, reliability and competence in the field of technology and information, it is necessary to make a selection at the beginning, namely at the time of admission of new students. There are 5 criteria used in the selection process, including the average report card score, basic ability test, computer ability test, psychological test, and interview. Each criterion has 5 weights of values, namely very high, high, medium, low and very low. The selection process for admission of new informatics engineering students with a decision support system for the EDAS (Evaluation Based On Distance From Average Solution) method. Where the stages in this method are by normalizing the decision matrix and looking for the average from alternatives, then from these results calculate the average positive distance (PDA) and negative distance (NDA) as well as the assessment of the weighted attribute weights of SPi and SNi, after that the normalization of positive and negative distance weights is carried out for determining the ranking score. From the results of the analysis carried out using the EDAS method, with a sample of 10 prospective students it was concluded that the 6th order student candidate had the highest score with a score of 0.519 and the lowest score in the 7th order student with a score of 0.14. Therefore, the level of accuracy of the EDAS method in selecting new student admissions is around 20%. Of course, this accuracy value will change with large data samples
Application of the Single Exponential Smoothing Method For Flood Disaster Prediction
Get PDFThe country of Indonesia is seen as one that is particularly vulnerable to natural catastrophes as well as calamities brought on by human activity. A disaster that may be brought on by both natural and human sources is a flood. Disasters brought on by flooding are unpredictable occurrences that frequently cause losses in the form of property damage, the theft of assets, and lost productivity at work and in school. Through this prediction information system, the people can find out the level of risk of flooding through excessive rainfall. in order to better anticipate and prepare for all possibilities that occur before the flood, the method used is Single Exponential Smoothing. This method was chosen because of the simple way the system works to find predictive values ??through past data. With this system, researchers can input rainfall data taken from the Meteorology, Climatology and Geophysics Agency, then the data is processed through the system and if rainfall gets high results. The risk of flooding will also be very high and a warning will be given to the public so that better prepared for the risk of flooding. The results obtained from this study are the results of an analysis of the exponential method single to obtain accurate rainfall prediction information with data MAD, MSE and MAPE
Implementation of Fuzzy Logic for Chili Irrigation Integrated with Internet of Things
Get PDFChili, mustard greens, and tomatoes have always been farmers' favored crops, despite their high water and labor demands. Adapt to these conditions by utilizing smart agriculture systems (SAS) agricultural techniques that involve technology such as automatic irrigation that regulates watering based solely on routine, regardless of land conditions. This type of control during the transitional season can lead to root rot and fungisarium disease on chile plants. In the form of an embedded system with internet of things (IoT) monitoring, a system incorporating artificial intelligence such as fuzzy logic is proposed as a solution. Fuzzy logic will regulate irrigation based on the land's humidity and temperature using computational mathematics. Beginning with the fuzzyification stage to map the sensor's temperature and humidity input values, fuzzy logic is applied. The creation of an inference engine in the NodeMcu 8266 microcontroller to interpret fuzzy rule statements in the form of aggregation of minimum conditions with the AND operator, followed by the combination of a single set value of 0 and 1 in the fuzzy system to produce an appropriate actuator response After the entire system has been prototyped, testing is conducted to determine the responsiveness of the fuzzy program code to changes in the simulated agricultural cultivation land ecosystem. This study found that the fuzzy logic program code embedded in the nodeMCU8266 microcontroller effectively controls the spraying duration of the pump in response to various simulated environmental conditions within 3.6 seconds
Application of Dijkstra's Algorithm to Determine the Shortest Route from City Center to Medan City Tourist Attractions
Get PDFTourist attractions are very interesting things to visit in an area that we are living. It is no exception when visiting the city of Medan, the tourists will visit interesting tourist spots in the city of Medan. To optimize time so that you can visit all tourist attractions in Medan City, you need to map locations so that you can create the shortest route that can be used to take all the tourist sites you want to visit in Medan City. The shortest route of a trip will shorten the travel time. Likewise in terms of seeking experts. When requesting a route from one point (start point) to another location (destination point), usually the result that comes out is the "shortest path" from the starting point to the destination point. The shortest path is the problem of finding a path between two or more vertices in a minimum weighted graph. To simplify solving the shortest path problem, a search algorithm is needed. Dijkstra's algorithm solves the problem of finding the shortest path between two vertices in a weighted graph with the smallest total number, by finding the shortest distance between the initial vertex and other vertices, so that the path formed from the initial vertex to the destination vertex has the smallest total weight. In this study, Dijkstra's algorithm looks for the shortest path based on the smallest weight from one point to another, so that it can help provide a choice of paths. Based on the trials of Dijkstra's algorithm, it has the ability to find the shortest path, because in this algorithm each graph is selected an edge with a minimum weight that connects the selected vertices with other unselected vertices
Analysis of the Implementation of E-Learning in Melajah.id Using Human Organization Technology (HOT) Fit Model
Get PDFThis research is motivated by the absence of prior analysis on the success level of implementing Melajah.id e-learning and the performance analysis of the e-learning platform from the perspective of human, organizational, and technological support aspects. Therefore, the existence of this scholarly research is considered necessary as a consideration for stakeholders involved in the policy-making for the development of educational service quality in vocational schools. The purpose of this research is to assess the performance and success level of the implementation of the Melajah.id e-learning platform in use at SMK Negeri 3 Tabanan. For the indicators of the human variable, they include: (a) System Use and (b) User Satisfaction. For the indicators of the organizational variable, they include: (a) Organization Structure and (b) Organization Environment. As for the indicators of the technology variable, they encompass: (a) System Quality, (b) Information Quality, and (c) Service Quality. Data collection for the research was conducted through the distribution of online questionnaires using Google Forms, while supplementary data was obtained through observation and interviews to gather information that could not be revealed through questionnaires. Subsequently, the data analysis approach used to measure the success and performance of the e-learning system implementation was linear regression analysis as the quantitative method. Furthermore, qualitative data analysis was performed through content analysis of interview scripts and interpretation of observational data (photos and videos). The combination of the results from quantitative and qualitative analyses served as the basis for drawing conclusions and making recommendations regarding the analysis of the success of the Melajah.id e-learning implementation in the vocational school where the research was conducted
Performance Comparison of the Combination of Smarter-Fuzzy and Smarter-Fuzzy-Topsis Methods on the accuracy of the PPA Scholarship Acceptance Decision Support System
Get PDFThe PPA Scholarship is a scholarship intended for students who excel, are active in campus activities, and are economically disadvantaged in accordance with predetermined conditions. Currently, STAHN MPU Kuturan Singaraja in calculations often takes a long time, causing delays from the predetermined schedule and less accurate results. Based on this, it is necessary to develop a Decision Support System that can provide recommendations for prospective PPA scholarship recipients. There are 6 criteria being used, including: GPA, semester, credits, charter/certificate, assignment letter, and parent's income. In this study, comparing the performance of the combination of the Smarter-Fuzzy and Smarter-Fuzzy-Topsis methods through testing using the confusion matrix method. Smarter method is used to be able to give weighting criteria with ROC technique. The Fuzzy method is used to convert the criteria values ??for each alternative from 0 to 1. The Topsis method is used to rank. The ranking results of the combination Smarter-Fuzzy method show an accuracy rate of 86.6%, and the combination of the Smarter-Fuzzy-Topsis method of 75.5%
Comparative Study of Iconnet Jabodetabek and Banten Using Linear Regression and Support Vector Regression
Get PDFPT PLN Indonesia Comnets Plus has little information regarding future customer growth, making it difficult to take steps to meet customer needs. This research aims to predict customer growth in the future based on quantitative data from the previous year, where the output provided produces data in the form of numbers that are analyzed using statistical methods. The hope is to provide information to maximize customer growth with the minimum area or bandwidth used by the company. This research uses linear regression and support vector regression (SVR) algorithms using a company secondary dataset of 252 data points with 5 attributes. Data was collected during the last one-year period, from January to December 2021. The results of the research show that predictions using both algorithms have increased, customer growth when viewed from the number of customers, bandwidth, and regional data has increased significantly. This can be seen from the value of the number of customers, which continues to increase, while the highest number of customers falls in December, the most requested bandwidth is 20 mbps, and the largest customer area is in the Depok area. The results of the research show that the SVR algorithm is superior in terms of mean absolute percentage error (MAPE): 0.02% MAPE, 0.10 MAE, and 0.99 RMSE, while for linear regression, the MAPE values were 36.28%, MAE 201, and RMSE 0.80
Base-Delta Dynamic Block Length and Optimization on File Compression
Get PDFDelta compression uses the previous block of bytes to be used as a reference in the compression process for the next blocks. This approach is increasingly ineffective due to the duplication of byte sequences in modern files. Another delta compression model uses the numerical difference approach of the sequence of bytes contained in a file. Storing the difference value will require fewer representation bits than the original value. Base + Delta is a compression model that uses delta which is obtained from the numerical differences in blocks of a fixed size. Developed with the aim of compressing memory blocks, this model uses fixed-sized blocks and does not have a special mechanism when applied to file compression in general. This study proposes a compression model by developing the concept of Base+Delta encoding which aims to be applicable to all file types. Modification and development carried out by adopting a dynamic block size using a sliding window and block header optimization on compressed and uncompressed blocks giving promising test results where almost all file formats tested can be compressed with a ratio that is not too large but consistent for all file formats where the ratio compression for all file formats obtained between 0.04 to 12.3. The developed compression model also produces compression failures in files with high uncompressed blocks where the overhead of additional uncompressed blocks of information causes files to become larger with a negative ratio obtained of -0.39 to -0.48 which is still relatively small and acceptable
Forecasting the Number of Patient Visits by Arima and Holwinters Method at the Public Health Center
Get PDFAs the number of human populations increases and the economy becomes more advanced, people's awareness of health increases. This can increase the number of patient visits if the community will visit for treatment, therefore it is necessary to pay special attention from the health center to carry out readiness in the fulfillment of facilities and service support equipment, such as services in the outpatient registration place where registration documents must be adjusted to the number of existing patients, if the documents are lacking or have not been made, there can be long queues or accumulation of patients which leads to inadequate service. For this reason, the public health center must carry out careful planning activities, one of which is by conducting forecasting activities in order to overcome these problems.This study compares the best method among the 2 time series methods, then the forecasting results will be compared with the actual data to find which forecasting is the best.The final results showed the MAPE value of the arima method for Direct Patient Visits data was worth 22.55% while the Referral Patient Visits were valued at 47.40% with the Moderate/Feasible category, the Holwinters method for Direct Patient Visits data was worth 7.90% while the Referral Patient Visits were worth 11.90% with the excellent category.can be said that the smallest error value is Holtwinters from Direct Patient Visit data with MAPE 7.90% and from Referral Patient Visit data with MAPE 11.90%. Which is where it is said to be an excellent forecasting categor