Journal of Informatics And Telecommunication Engineering
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Design of 2x1 MIMO Microstrip Antenna Using Slit and Inset Technique For 5G Communication
Get PDFThe fifth generation (5G) technology offers high speed communication systems and requires a multi input and multi output (Multiple Input Multiple Output / MIMO) antenna system to increase customer capacity. This research proposes a microstrip antenna design for a fifth-generation (5G) communication system that works at a frequency of 3.5 GHz. The antenna was designed using the RT-Duroid R5880 substrate type with dielectric constant (εr) = 2.2, thickness (h) = 1.57 mm and loss tan (tan α) = 0.0009. To produce optimal parameter, the antenna is optimized using slit on the edge with a total of 2 pairs. The addition of an inset aims to reduce the reflection coefficient of the proposed antenna. From the simulation results, the reflection coefficient value is -25 dB at a frequency of 3.5 GHz with a bandwidth of 220 MHz. The gain of the proposed antenna is 10 dB at a frequency of 3.5 GHz. The isolation coefficient obtained is -70 dB with a distance between (d) = 43 mm. The application of the MIMO antenna increases the gain by 49.52% compared to the single element microstrip antenna
Qr Code Reader System Assisted With Face Detection Using Multi Webcam
No full textInformasi yang terdapat pada QR Code dapat dibaca dengan alat pemindainya. Alat pemindai yang digunakan berupa kamera yang terkoneksi ke sistemnya, contohnya webcam. Saat sekarang ini, alat pemindai akan bekerja secara otomatis jika mendeteksi objek QR Code tersebut. Pada penelitian ini, alat pemindai QR Code yang sudah ada akan dikembangkan dengan menambahkan deteksi wajah manusia di dalam sistemnya, yang mana proses memindai dan mendeteksi akan berjalan secara bersamaan di satu sistem. Tanpa deteksi wajah maka sistem tidak bisa bekerja. Metode penelitian yang dipakai adalah jenis research and development (R&D). Sistem yang dihasilkan terdiri dari server penghasil gambar QR Code dan sistem pemindai dengan dua webcam. Fungsi server adalah untuk mendaftarkan informasi yang akan disimpan ke gambar QR Code. Untuk akses ke server menggunakan browser, sedangkan pada sistem pemindai menggunakan aplikasi yang dibuat dengan bahasa pemrograman Processing. Antara server dan sistem pemindai terkoneksi secara otomatis ketika mengekstrak informasi yang ada pada gambar QR Code. Jarak baca agar sistem pemindai bekerja adalah antara 10 cm sampai dengan 55 cm
Wayang Image Classification Using SVM Method and GLCM Feature Extraction
Get PDFWayang is a masterpiece of art that has been able to survive centuries of change and development as a reflection of life for the majority of society. Wayang has a high value because it does not only function as a "entertainment" spectacle, but also has many lessons and life values that can be learned from a wayang show. Puppet itself has various types and forms, and these forms have their own uniqueness, because of the many types of Puppet, many people do not know all the names and types of wayang. Therefore, in this research, we will discuss how to recognize wayang objects based on wayang images using the SVM and GLCM methods as feature extraction. The results showed that the classification of wayang using the SVM (Support Vector Machine) method and the GLCM (Gray Level Co-Occurrence Matrix) feature extraction can recognize wayang objects based on wayang images and classify them quite accurately and a maximum total accuracy of 83.2% is obtained
Comparison of Neural Network Algorithms, Naive Bayes and Logistic Regression to predict diabetes
Get PDFDiabetes is a disease that affects many people with the characteristics of high blood sugar levels. The International Diabetic Federation (IDF) estimates the number of Indonesians aged 20 years and over, suffering from diabetes at 5.6 million people in 2001, and increasing to 8.2 million people in 2020. The problem that occurs is that many people do not know that they suffer from diabetes because they do not have basic knowledge about diabetes and the existing methods to detect diabetes are time consuming. In this study, three data mining methods were compared, namely the neural network algorithm, naïve Bayes, and logistic regression using the rapid miner application by applying the Confusion Matrix Evaluation (Accuracy) and the ROC Curve. The result of this research is that logistic regression method is a fairly good method in predicting early diagnosis of diabetes compared to the naïve Bayes method and the neural network. From the evaluation and validation, it is known that logistic regression has the highest accuracy and AUC values among the comparable methods, namely 75.78% and AUC 0.801, followed by the naïve Bayes algorithm which is 74.87% and AUC 0.799, and the neural network is 69.27% and AUC 0.736. has the lowest accuracy
Pierce Similarity Algorithm In Detection Of Jar Letter In Al-Quran As Basic Media For Learning Arabic Language Structure
Get PDFAl-Quran is the basic reason someone should understand the rules of Arabic. One of the basic rules is knowing the jar type which we generally often encounter in Arabic, but we do not understand that this letter has its own duties and functions. In this study, samples of Jar letters were used as many as 7 jar letter patterns which are generally often encountered in the Al-Quran. The purpose of this research is to build a system that can recognize Jar letters using the Pierce Similarity method and performs the performance on the algorithm. The research method used is the theory of pattern recognition in image processing with 2 processes, namely the Training Process and the Testing Process. The value of each letter pattern obtained in the Training Process will be the weight benchmark for the Testing Process, so that we can measure the performance level of Algortima Pierce Similarity in detecting the Jar letter pattern. The results can vary for each letter pattern ranging from 60% to 80%
Market Basket Analysis for Books Sales Promotion using FP Growth Algorithm, Case Study : Gramedia Matraman Jakarta
Get PDFFor retail companies such as Gramedia stores, promotion and strategies to sell books are important, so tools are needed to analyze past sales data. Gramedia does not yet have tools to analyze shopping cart patterns that aim to carry out product promotions appropriately. To promote what books should be promoted using the market basket analysis method or shopping basket analysis. The algorithm used in the data mining process is Frequent Pattern Growth (FP Growth) because it is faster in processing large data. The data analyzed is historical data on book sales from January to March 2020 which is taken randomly (random sampling). The framework used in the data mining process is the Cross Industry Standard Process for Data Mining (CRISP-DM) and the tool used is the Rapid Miner using a market basket analysis framework. With a minimum support of 0.003 and a minimum confidence 0.3 using the FP-Growth algorithm to produce an item set of 7 rules to recommend product promotions. The algorithm results are also in accordance with the business understanding phase of CRISP-DM
Detection of Banana and Its Ripeness Using Residual Neural Network
Get PDFAutomatic fruit detection utilizing computer vision techniques has been carried out to help the agriculture and plantation industries. This study researches smart systems to detect bananas and ripeness classification utilizing residual neural networks. The method used to detect bananas is transfer learning from pretraned Model VGG-19. Whereas, in the bananas ripeness classification process, residual neural networks, which are trained from the start, are used. Sliding Windows is used to detect the position of bananas followed by Non-Max Suppression to summarize the results of several detected bananas. Previous studies were limited to the level of ripeness, but in this study, bananas are detected and followed by the level of bananas ripeness (raw, ripe, and overripe). This study’s data uses bananas which were mixed with other kinds of fruit. There two kinds of bananas detection architecture used in this study, VGG-19 and Restnet. After they were used to detect bananas, it was found that VGG-19 was more suitable. The results of this study are very satisfying as it is seen from the bananas detection testing percentage using VGG-19 architecture which shows 100% ripe bananas, 99 % raw bananas, and 100% overripe bananas.Keywords: Detection of banana, banana ripeness, Non-Max suppression, residual block
High Precision 3D Printed Syringe Pump for Contact Angle Goniometer
Get PDFContact angle goniometer is a tool used to measure the contact angle of a surface which is usually coated with nanomaterial. Contact angle goniometer has an important part, that is syringe pump as a tool for dripping a number of liquids with high precision and accurate flowrate. The function of the syringe pump is to control amount and feedrate of liquid on a milliliter to microliter scale per minute using a simple microcontroller. In this study, this syringe pump used an arduino as a controller and a stepper motor as a syringe driver. Casing and the syringe pump mechanism were designed with AutoCAD Fusion360 software and printed using a 3D printer. This syringe pump has an accuracy value of 99.5%, a precision value of 99.7% and a deviation value 0.4 µL which is based on the solution measured using Mettler Toledo 204 analytical balance. From the result, it is obtained that the syringe pump has been used for the contact angle goniometer with an experiment of water being dripped onto the ABS plastic surface with flowrate 100 µL/minute and the surface contact angle was analyzed using imageJ software and the result of the contact angle was 179°. Therefore, based on the result of this study, it can be concluded that the syringe pump can be used as a contact angle goniomete
Classification of Wheat Seeds Using Neural Network Backpropagation Algorithm
Get PDFThere are various types of wheat scattered in the world. Usually it takes a long time to recognize the type of wheat seed by manual method because wheat germ has a physical appearance that looks the same as others. One method that can be used is an Artificial Neural Network. In this study, the data used were secondary data which consisted of data from the variable physical characteristics of wheat germ. The types of wheat seeds that are classified are 3. The Artificial Neural Network architecture used in this study is 5. By comparing the 5 Artificial Neural Network architectures, it is concluded that the architecture consisting of 3 layers and 4 layers is more precise in the classification of wheat germ types. The accuracy obtained by the 2 Artificial Neural Network architectures is 90% and 90%, respectively
News Opinion Classification Application With Support Vector Machine Algorithm Using Framework Codeigniter
Get PDFNews is an information that contains a lot of data, one of which is data about opinion / sentiment. The opinion / sentiment data of a news can be used for many things. To get the opinion value of a news, it is necessary to do a sentiment analysis technique on the news data that wants to know the level of opinion produced. Sentiment analysis is a technique that uses the data mining method. To see the height of the opinion value of a news item, the Support Vector Machine algorithm is used, which is one of the algorithms in the data mining method that is able to classify data sets into two classes. Using the CodeIgniter framework based on the PHP programming language, an application was developed that can classify the news into two classes, namely the positive class and the negative class. By using 100 pieces of news data from the national news portal, namely detik.com, about 700 sentences and more than 1000 words are generated which are then classified using the SVM algorithm. Applications are able to achieve an accuracy rate of 76