Journal of Computer Networks, Architecture and High Performance Computing
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Recognition of Regional Traditional House in Indonesia Using Convolutional Neural Network (CNN) Method
Get PDFIndonesia is a country that has a lot of cultural diversity. This cultural diversity needs to be preserved. If this is not done, the culture that is owned by Indonesia can slowly disappear. The reduction in cultural values can also reduce the sense of belonging to the culture. This lack of sense of ownership makes it easy for other nations to make claims on the culture that is owned by Indonesia. Indonesia will lose its characteristics as a country that has a lot of cultural diversity. One of the efforts to preserve culture is to recognize the characteristics of each culture and be able to recognize the differences between one culture and another. For example, recognizing traditional houses from various ethnic groups based on their image. In this research, the image classification of the characteristics of traditional houses from several ethnic groups in Indonesia was carried out. The classification used to identify an image. In this study, deep learning techniques are used with the Convolutional Neural Network (CNN) algorithm and Keras framework. This CNN use several layers namely convolutional, pooling, flatten, and dense layer. The development of deep learning models uses the Knowledge Discovery in Database (KDD) method. This method consists of nine stages. The built model is evaluated using k-fold cross validation with a k value of 5 and produces an average accuracy of 80%. This shows that the model built is capable of classifying well. The built model is evaluated with 3 different epoch values, namely 50, 75, and 100. The larger the epoch value used, the greater the accuracy value. The model built is also able to make predictions with an accuracy of 80%
Implementation of The K-Nearest Neighbor Method to Determine The Quality of Export Import Swallow's Nest
No full textIn this study discusses the quality of the feasibility of swallow's nests that are suitable for export, Based on the problem from the research, it discusses how to select export-worthy swallow's nests in order to maintain the confidence of buying from abroad. The method used in this research is the K-NN method which can determine the feasibility of applying for the rank of lecturer. The data that is processed is 100, the input criteria for bowl 4, broken 2, destroyed a 2, destroyed b 2. This system succeeded in displaying appropriate and inappropriate results for lecturer data that had been input into the data set
Android Based Spark and Gas Leak Detection and Monitoring
Get PDFLPG cylinder leakage is one of the causes of fires in the community. To prevent fires, a fire and gas leak detection and monitoring device were made using a fire detector sensor and an Android-based MQ-6 to trigger it. Data collection techniques in the manufacture of gas and fire leak detection using a flame detector and the MQ-6 sensor can be obtained from datasheets, journals, books and articles, and several internet sites that support the manufacture of this device. In the manufacture of gas leak detection devices or tools, there are also two parts, namely the first to make hardware (hardware), then software (software). The result of this tool detection is that users can find out the level of LPG due to leaking of LPG cylinders and detect fire using Android notifications in real-time and the data is displayed in detail on the browser page. The conclusion of this study is that users are safer because there is a gas leak, the tool will detect LPG gas, then a message will be displayed on the LCD screen and a notification on Android and the buzzer will automatically turn on. If there is a fire from detecting the gas leak, the fire detector will detect the fire, which will result in a notification sent to Android that there is a fire and the buzzer will turn o
Classification of Covid-19 vaccine data screening with Naive Bayes algorithm using Knowledge Discovery in database method
Get PDFAcute Respiratory Syndrome Coronavirus-2 (SARS-Cov-2) known as covid-19 was detected and caused a very large number of deaths due to a mysterious respiratory disease. With the death toll continuing to rise, the government was forced to take swift action to break the chain of spread and reduce the number of deaths by taking vaccinations. An adequate vaccine against Covid-19 is expected to vaccinate at least 70% of the population. Therefore, this study was carried out as a step to help break the chain of the spread of the Covid-19 virus, by classifying the Covid-19 vaccine screening data. The research method applied in this study is the Knowledge Discovery in Database (KDD) method, in which there are several processes, namely selection, pre-processing, transformation, data mining, and evaluation. The application of the Naive Bayes method is expected to be able to classify Covid-19 vaccine screening data with vaccine class values, no, and delay. The results of the research on the classification of the Naive Bayes method show that there are 959 data with Vaccine data 695, No 200, and Delay 64. Processed using the Rapidminer application, the accuracy is 96.56%, Precision is 92.46%, and Recall is 92.13%
Tsukamoto Fuzzy Method Analysis in Laptop Damage Diagnosis (Retracted)
No full textThe author's request letter for manuscript withdrawal is in the PDF download section. Dec 5, 202
Comparison of Evaluation Image Segmentation Metrics on Sasirangan Fabric Pattern
Get PDFSasirangan fabric is a typical fabric from the South Kalimantan area. Sasirangan fabric patterns or motifs have a unique archetype that is different from other typical fabrics in Indonesia. The design of Sasirangan fabric is formed from the process of juju or seam. The pattern of Sasirangan fabric that has this uniqueness can be segmented into a more meaningful shape so that it is easy to analyze. The image segmentation that will be tested is the basic pattern of Sasirangan fabric with a random sample to compare the results of the evaluation of the metric evaluation of the image segmentation process from the Sasirangan fabric pattern. Image segmentation is a different segmentation with certain characteristics, namely using the compact watershed approach, canny filter, and morphological geodesic active contours method in the evaluation of image segmentation metrics using precision-recall, which serves to evaluate the quality of the classifier's output. After the image segmentation process is evaluated, the Sasirangan fabric pattern is grouped using the K-means algorithm as a different labelling strategy. This labelling process uses the K-means algorithm to better match details but can be unstable because it relies on random initialization. Alternatives to balance the unstable labelling process using the means algorithm can use discretization. The addition of the K-means method with discretization can create fields with geometric shapes that are pretty flat. The segmentation with Sasirangan fabric with a full motif or data number four 741.78s, results in processing the fastest and the longest computational time on data number two 120.79s
Development Of E-Research Information System To Support Research Management (Case Study of Wastukancana University)
No full textE-research management is an implementation mechanism of information and communication technologies on the research management so that the research runs effectively and efficiently. E-research STT Wastukancana is an information system for submission of a thesis title and undergraduate internship but there are still many incomplete features, so it needs system development so the system can run well. Therefore author does the development system of e-research STT Wastukancana Web-Based so that admin, students, and lecturers can carry out business processes well on online system mode. The result of this research is an information system that can help out and ease users in doing business processes and information around e-research STT Wastukancan
Evaluation of ATM Location Placement Using the K-Means Clustering in BNI Denpasar Regional Office
Get PDFThe existence of an ATM location requires a placement evaluation that aims to support business and provide convenience and comfort to customers when using or transacting. This study aims to evaluate the placement of ATM locations using the K-Means method, and research using data obtained from data mining to obtain decisions that lead to not strategic, strategic, and very strategic ATM locations. This study uses data sourced from the BNI ATM database and performance data in one semester or six months, namely January to June 2021, as many as 121 ATM locations spread across the island of Bali. The application of the K-Means Algorithm in this study uses 6 clustering criteria, namely ATMs Usage, ATMs Fee-Based Income/ FBI, ATMs Service Level Agreement/ SLA, ATMs distance, competitor ATMs, and Business Distance. In addition to presenting calculations using spreadsheets, this research also produces implementations in web-based software. The results of alternative classifications based on K-Means on very strategic centroids of 27 locations or covering 22.31%, strategic several 77 locations or covering 63.64%, and non-strategic 17 locations or covering 14.05%. Although the location of ATMs that are classified as non-strategic criteria is quite small, this can be optimized by several strategic steps that can be taken by stakeholders within the company, such as evaluating the bank's business plan in 2022 and improving the supervision of machines at ATM locations
Implementation of K-Medoids Clustering Method for Indihome Service Package Market Segmentation
Get PDFIndiHome (Indonesia Digital Home) is a leading digital fibre optic service product consisting of fibre optic internet services, landline telephones, and interactive TV services. Although the coverage of Indihome products is extensive in the city of Medan, in marketing, Indihome products have not reached the planned target. Based on data from Indihome service package users that have been received, Indihome product users only numbered 6419 customers in all STOs in Medan City. At the same time, the target was planned by PT. Telkom Access Medan, namely Marketing Indihome products, must reach 5,000 customers per month in all STOs in Medan City. Indihome product marketing is an obstacle for PT. Telkom Access Medan, because the Indihome product is a new product, the people of Medan City do not fully know what Indihome is and what facilities they get from using the Indihome service package. Therefore PT. Telkom Access Medan needs to make a plan to make a marketing strategy. The first step that needs to be done is to segment the market for the Indihome service package. This study aimed to determine the application of Data Mining using the K-Medoids Clustering method in the Indihome service package market segmentation at PT. Telkom Access Medan. With this research, it is hoped that it can provide a reference for the results of the decision so that it can help related parties to make it easier to classify the market segmentation of the Indihome service package at PT. Telkom Access Medan. Because the value of S > 0, then the calculation is stopped and ends in the 3rd iteration. Indihome service package data processing uses the k-medoids clustering method in the form of potential, potential, and not potential STO (Sentral Telephone Automated) cluster members
Design And Build The AMANAH Vocational School Main Book Application Using The Waterfall Model
Get PDFThe benefits of information technology in the field of education include improving educational services, facilitating the collection and dissemination of educational information, educational data storage media, improving teaching skills, motivating students, thus helping communication activities in education. The concept of this information system has the effect of transforming the filling of the conventional ledger into digital form, by carrying out this transformation it can affect the easier filling of the master book and secure data storage and a longer time. After the process of accepting new students at SMK AMANAH is completed, the administrative officer or administrative administration enters student data, the value of student report cards per semester into the student master book, the difficulties encountered by administrative officers during the process of entering the data, officers have difficulty in terms of The main book used has a large size and the storage of the master book is still less effective and does not last long because it can be damaged, even though the master book should be able to be used for a long time as a document that is needed at any time. The research method used to design a student master book system is to use the waterfall or waterfall method to produce a design for the school's main book information system (SIBIS). Starting from the login page, the new student registration page, the grade submission page, and reports to help the school