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<![CDATA[Pattern Recognition on Automated Guided Vehicles Two Wheel Drive (AGV 2WD) Robot for Location Detection Based on Raspberry Pi 4 Model B ]]>
<![CDATA[Setiawan, Florentinus Budi]]>;
<![CDATA[Muntaha, Ilyas]]>;
<![CDATA[Pratomo, Leonardus Heru]]>;
<![CDATA[Riyadi, Slamet]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v8i1.11990
<![CDATA[AGV (Automated Guided Vehicle) equipped with artificial intelligence (AI) is anticipated to boost Indonesia's industrial development. The little computer used to generate this robot's artificial intelligence used mechanical gears similar to those found in an eight-wheeled, two-wheel-drive car (2WD). This article outlines and demonstrates the usage of an AGV-controlled approach to determine a place inside a building by detecting text in different locations throughout the building. The current technique employs the programming languages Python and OpenCV. Optical Character Recognition (OCR) has been tweaked or enhanced for usage with OpenCV. Multiple texts are read using OCR as the principal technique. In this instance, OCR functions at many stages of the process, in addition to being employed for exploring letters and words, word translation, character classification, linguistic analysis, and adaptive character classification. The output text from the system's document processing procedure will likely contain the location or even the position of an AGV robot once the process has concluded. This text is produced from the text that was previously submitted using the camera function. After a thorough search, the AGV robot will go to the next area before returning to its starting point. The method above can be implemented on the AGV lab's hardware, which has a solid basis]]>
<![CDATA[Sentiment Analysis of Twitter User Opinions Related to Metaverse Technology Using Lexicon Based Method ]]>
<![CDATA[Akbari, Wahyu Azriel]]>;
<![CDATA[Tukino, Tukino]]>;
<![CDATA[Huda, Baenil]]>;
<![CDATA[Muslih, Muhamad]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v8i1.11992
<![CDATA[The technology of the metaverse has been a topic of discussion in the tech sector recently, and the implementation of the metaverse in the future is one of the most anticipated things for internet users around the world, allowing users to become the avatar they want in the virtual universe. To see how someone approaches metaverse technology, we can analyze it by looking at various opinions that emerge from the sentiment of internet users, one of which is from the social media Twitter. This study aims to analyze the sentiment of Twitter users' opinions, which is one of the most popular internet social media platforms. The researcher collects tweet data using the snscrape library in the Python programming language, a tool for mass data collection from Twitter. Then, the analysis of the sentiment of Twitter user opinions is carried out using the Lexicon Based method, which is a method that uses a dictionary of words to categorize the sentiment of a text. The results of this study show that the Lexicon Based method can classify the sentiment of Twitter user opinions related to metaverse technology with an accuracy value of 84%. This shows that the results of sentiment analysis using the Lexicon Based method have a good level of accuracy in performance in analyzing the sentiment of Twitter user opinions related to metaverse technology.]]>
<![CDATA[Artificial Neural Network Backpropagation Method to Predict Tuberculosis Cases ]]>
<![CDATA[Lestari, Valencya]]>;
<![CDATA[Mawengkang, Herman]]>;
<![CDATA[Situmorang, Zakarias]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v8i1.11998
<![CDATA[Artificial neural networks are information processing systems that have certain performance characteristics in common with biological neural networks. Backpropagation is a method in artificial neural networks that uses supervised learning. Backpropagation has a weakness in reaching the convergence level. The convergence rate is the difference from the mean square error value. The mean square error is the difference between the target value and the actual value. One way to increase the convergence rate is to provide input values. in this study using the nguyen widrow backpropagation method. The network will predict Tuberculosis cases. Data sourced from the North Sumatra Provincial Health Office from 2019 to 2021. architectural testing with a learning rate ranging from -0.5 to 0.5 and momentum ranging from 0 to 1 obtained a learning rate of 0.5, the epoch process stops at the 172nd iteration with an achievement gradient of 0.0001598 and the R value for training data is 0.99841 which means it is very good because it is close to 1 with an accuracy rate of 81.82%. ]]>
<![CDATA[Android Implementation of Traditional Indonesia Fashion Application ]]>
<![CDATA[Tukiyo, Tukiyo]]>;
<![CDATA[Arifin, Ardian]]>;
<![CDATA[Dewantara , Rizki]]>;
<![CDATA[Ratnadewi, Ratnadewi]]>;
<![CDATA[Anggraini, Julaiha Probo]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v8i1.11999
<![CDATA[Indonesia has been gifted with a wide range of diverse cultures from Sabang to Merauke, making Indonesia one of the biggest country with multi ethnic groups, races and cultures. Meanwhile, a lack of information that can be accessed by the students causing a big issue that needs to be addressed. The information of Indonesian traditional clothing is very limited, which has been represented as a characteristic of tribe and culture in each region and also used in the traditional ceremony. Therefore, this study aims to develop an Android-based educational game of traditional Indonesian clothing. The method used in this study was Research and Development approach. The results of this study showed that developing an educational game "Introduction to Traditional Clothing in Indonesia" on the Android platform,that provided information to users about any traditional musical instruments in Indonesia, helped students to recognize the particular culture through its traditional clothing as it could give an insight to them. From the results of testing carried out with the black box method, it could be concluded that this application enabled to function well and provide the beneficial information to user about the traditional clothing.]]>
<![CDATA[Development of Web-based Single Channel Multi Steps Online Queuing System with Model View Controller ]]>
<![CDATA[Darmayunata, Yuvi]]>;
<![CDATA[Devega, Mariza]]>;
<![CDATA[Yuhelmi , Yuhelmi]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v8i1.12003
<![CDATA[Abstract: Improvement in service quality will be directly proportional to customer satisfaction. One form of improving the quality of services provided by a Government Institution engaged in the Health sector, namely the Health Center is an effective and efficient queue. This research is a follow-up research where previously an analysis and design of an online queuing system has been carried out. This study aims to make it easier for patients to take queue numbers in advance through the queue website, and patients can come based on a predetermined estimated time. This of course can minimize patient waiting time and also prevent the accumulation of patients in the waiting room of the puskesmas. Single Channel Multi Steps is one of four types of queues and is the type of queue currently running at the Siak Hulu I Kampar-Riau Health Center, while the Model View Controller (MVC) was chosen because it is a feature that makes it easy to create a Web-based application.]]>
<![CDATA[Application of the FP-Growth Method to Determine Drug Sales Patterns ]]>
<![CDATA[Anwar, Badrul]]>;
<![CDATA[Ambiyar, Ambiyar]]>;
<![CDATA[Fadhilah, Fadhilah]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v8i1.12004
<![CDATA[Pharmacies are shops that sell and mix medicines based on doctors’ prescriptions and trade medical goods. Apart from being a business actor, the pharmacy also plays a role in providing health services that are easily accessible to the public. The problem that often occurs in pharmacies selling drugs is that they are less than optimal in service to consumers. The habit of consumers buying more than one type of drug makes pharmacy staff slow in providing the drug due to the inaccurate layout of the drug. The FP-Growth method in Data Mining is a method that can provide a solution in determining drug sales patterns at pharmacies. The FP-Growth method is a method used in determining the data set that occurs most frequently together (Frequent Itemset). The research objective was to determine drug sales patterns based on drug sales transaction data so that drug layouts could be determined. This research was conducted at the Pharmacy at the Pratama Sehati Husada Clinic in Medan with drug sales transaction data from November 2021 to December 2021. The results of applying the FP-Growth method with a value of ≥ 15% as a minimum support and a value of ≥ 15% as a minimum confidence, a pattern of drug sales in pairs. The application of Data Mining with the FP-Growth method has been implemented at the Pharmacy at the Pratama Sehati Husada Clinic with the desired goals with the final result in the form of a report on the results of determining drug sales patterns.]]>
<![CDATA[Identification of Tempe Fermentation Maturity Using Principal Component Analysis and K-Nearest Neighbor ]]>
<![CDATA[Istiadi, Istiadi]]>;
<![CDATA[Rahman, Aviv Yuniar]]>;
<![CDATA[Wisnu, Alif Dio Raka]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v8i1.12006
<![CDATA[Tempe is one of the traditional foods in Indonesia which has nutritional content and benefits that are very much favored by all Indonesian people. To determine the maturity of tempe, it is generally done by fermenting it into tempeh using a certain temperature and usually tempe entrepreneurs are done traditionally. But in this way, tempe producers do not know what temperature and humidity are right for tempeh maturity. In this study, researchers used the MATLAB R2018a application with a total data set of 137 raw data, 137 ripe data and 136 rotten data, totaling 410 tempe image data. The purpose of this research is to produce a system that can detect the ripeness of tempe using the KNN (K-Nearest Neighbor) method which is equipped with GLCM texture feature extraction, with extraction of 8 color features, using the PCA (Principal Component Analysis) selection feature. And compare the results with the same method, namely KNN (K-Nearest Neighbor) without using the PCA (Principal Component Analysis) selection feature with the required running time between the two. KNN with PCA selection feature gets an average accuracy value of 80.63% and takes 1.06 seconds. Compared with the same method, namely KNN without using the selection feature, it gets an average accuracy value of 81.67% with a time of 1.18 seconds.]]>
<![CDATA[Data Mining Sales of Skin Care Products Using the K-Means Method ]]>
<![CDATA[Aldo, Dasril]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v8i1.12007
<![CDATA[Data mining is a form of method advancement in computerization that can dig past data into very valuable information. The problem in this study is that the sale of beauty and skincare carried out by Toko Hayati Store is still done manually so that it can cause it to not match the stock in the storage warehouse with changing market demand. Data mining with the K-Means method is one solution to this problem by grouping similar data, in this study grouping into two, namely best-selling and unsold products. The purpose of this study is that the store can provide stock of products in the warehouse according to market demand. Using a sample of 30 data resulted in 18 data as skin care products were not selling well and 12 data as skin care products were not selling well. With the results of a 100% similarity between manual calculations and using the rapid miner application, it can be concluded that the K-Means algorithm can be used as a solution to the problems that exist in the Toko Hayati Store.]]>
<![CDATA[Analysis of Book Distribution Routes Using the Capacity Vehicle Routing Problem (CVRP) Method Using the Sweep Algorithm ]]>
<![CDATA[Arifta, Ega]]>;
<![CDATA[Rakhmawati, Fibri]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v8i1.12013
<![CDATA[Distribution is the process of distributing products from producers to consumers. The ease of consumers in obtaining the desired product is the top priority of every company. In the distribution system, the chosen route is the most important element in determining the distance to be traveled and the costs to be incurred. If the chosen route is optimal, then the distribution system becomes more effective and efficient. Basedon the results of the author's observations, the delivery of goods in the company is still manual and irregular, where the goods are sent from the depot to the consumer and back to the depot so that it takes a lot of time and costs. One solution in solving the distribution problem is the Capacity Vehicle Routing Problem (CVRP). The Sweep algorithm is the simplest clustering method to solve CVRP. In this study, the author used a sweep algorithm because this algorithm is one of the methods that can solve the problem of the distribution route of Quranic books. Based onthe results of the study, researchers compared the distribution route usingthe sweep algorithm and the distributionroute of the previous company, obtained a percentage of total mileage savings of 35.35%, namely from the previous total company mileage of 135.2 Km to 87.4 Km by using the Sweep algorithm. This shows that the CVRP method using the sweep algorithm can provide optimal distance and save company expenses.]]>
<![CDATA[COMPARISON OF SIMPLE ADITIVE WEIGHTING MEHOD WITH MULTI-OBJECTIVE OPTIMIZATION BY RATIO ANALYSIS: SAW and MOORA DSS ]]>
<![CDATA[Panggabean, Erwin]]>;
<![CDATA[Sianturi, Fricles Ariwisanto]]>;
<![CDATA[Selvia, Sindu]]>;
<![CDATA[Dewi, Sumitra]]>
<![CDATA[ Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023 ]]>
Publisher : <![CDATA[Politeknik Ganesha Medan ]]>
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DOI: 10.33395/sinkron.v8i1.12015
<![CDATA[Abstract: One of the advantages of the MOORA method is its high flexibility and good selectivity. This is because MOORA is able to determine the goals of conflicting criteria, where the criteria can be profitable or unfavorable. While the advantage of the SAW method is that it can determine the weight value of each attribute, then proceed with a ranking process that will select the best alternative from a number of alternatives and the assessment will be more precise because it is based on the predetermined criteria and preference weights. Some of the weaknesses of the SAW method include, the data entered must be correct and precise, so as not to cause errors during the weighting and ranking of criteria, while the drawback of this MOORA method is that there must be a weight that is calculated to continue the calculation of the data which is then calculated on each criterion and range of criteria. This is what prompted the researchers to explore the research entitled "Comparison of the Simple Additive Weighting Method (SAW) with Multi-Objective Optimization on The Basis of Ratio Analysis (MOORA) in determining the best housing". This research activity plan is carried out in the Medan city area using data that has been published previously through national journals in Indonesia. The final result of the research is expected to be obtained by comparing the results of the two methods according to the decision support system data used, and the results of the research will be published on Sinta 4 accredited national journal articles or better.]]>
