Journal of Informatics And Telecommunication Engineering
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Broadband Channel Based on Polar Codes At 2.3 GHz Frequency for 5G Networks in Digitalization Era
Get PDFThis research using a polar code and without polar codes -based broadband channel that is affected by human blockage using one of the 5G cellular network frequencies at 2.3 GHz, 99 MHz bandwidth, 128 blocks of Fast Fourier Transform (FFT) with Cyclic prefix-Orthogonal Frequency Division Multiplexing ( CP-OFDM) and Binary Shift Keying (BPSK) modulation. The use of high frequencies causes the technology to be sensitive to the surrounding environment and attenuation such as human blockage. The purpose of this research is to determine the performance results and analyze the BER parameters that use polar codes and without polar codes on 5G network broadband channels that are affected by human blockage. Broadband channel modeling on a 5G network is presented in a representative Power Delay Profile (PDP) with the influence of human blockage, which is obtained as many as 41 paths which have multiple delays of 10 ns on each path. This research also uses the scaling method on representative PDP because the use of FFT will produce 128 blocks, and the results of this scaling show that there are 9 lanes with multiple delays of 50 ns. The results of this study are close to the average Bit Error Rate (BER) of 10-4. BER performance without polar code is affected by human blockage requires Signal to Noise (SNR) of 30 dB, for theory BER on BPSK modulation requires SNR of 34.5 dB and BER performance using polar code only requires SNR of 23 dB. These results indicate that using a polar code can reduce or save power usage by 7 dB without a polar codes. Polar codes can minimize errors in the 5G network system, because polar codes are one of the strong codes and are one of the channel coding recommended by ITU to be applied to 5G network system
Comparative Test of the Effect of X-Ray Tube Current Analysis and Exposure Time on CR (Computed Radiography) Image Quality
Get PDFThe medical image system in the form of digital examination results using Computed Radiography (CR) needs to be analyzed, this can be done by knowing the quality of the image contrast resolution and the quality of its spatial resolution. This study conducted a comparative test between two methods of analyzing contrast resolution of medical images. Image quality on Computed Radiography can be determined using contrast resolution analysis, namely calculating the CNR value and PSNR value. The study was carried out using a phantom to represent the density of the bone. The voltages used are 50 kV, 60 kV, 70 kV and 81 kV, respectively. With each voltage, the tube current and exposure time (mAs) were varied 1.6 mAs, 2 mAs, 4 mAs, 8 mAs, 16 mAs, and 32 mAs. The higher the CNR value obtained, the better the image quality. While the PSNR value to get the optimal quality of medical image contrast, the current-time variation of 4 mAs and 16 mAs must be used. Due to the time-current variation, a high PSNR value is obtained, which indicates that the noise of the medical image is getting smaller so that a good contrast quality of the medical image is obtained. Both of these methods can be used to test the suitability of X-ray device, especially for quality control of medical image
Application of Artificial Intelligence Chi-Square Model and Classification Of KNN in Heart Disease Detection
Get PDFCardiovascular disease is a problem in the blood vessels that do not run smoothly into the heart. This is fatal in patients with a history of heart disease. This problem often occurs in the flow of blood pumps into the heart. The problem examined in this study is how to complete the level of accuracy of each data set and the reduction of each attribute in heart disease. The purpose of this study is to analyze heart disease and classify heart disease using the chi-square and K-Nearest Neighbor algorithms. The results of the study with patient age 57, gender LK, cp 3, trestbps 200, chol 564, fbs 1, restecg 2, thalach 202, oldpeak 6.2, slope 2, ca 4, and the value of thal 3 for the target is there is disease heart 0 or 1 is detected without heart disease when the max-min data is normalized. while to measure the performance of the algorithm with the value of the confusion matrix with the actual class value of 1, prediction class 1 value 44, actual class 0 and prediction class value 6. while the actual class value 0-1, prediction class 1 value 5 and 0-0 value 36. the final stage value of the accuracy measure is 0.87912, the recall value is 0.89797 and the precision value is 0.85714. The implication of the application of the test has an optimal test, the accuracy value with data K = 303 then it can be concluded that based on the test the calculation of the KNN model obtained an accuracy of 91
Internet Data Quota Assistance for Students Using Reference Point MOORA Decision Analysis
Get PDFDecisions are made by those who are authorized and responsible decision makings for an institution or organization. Many decisions involve stakeholders who are individuals and organizations who can be affected by the future consequences of these decisions, including decision-making on Internet data quota assistance distributed by the Ministry of Education and Culture to support students' online learning from home (LFH). This Assistance Policy is very appropriate and well provided during the Covid-19 Pandemic. However, in an effort to optimize and objectify distribution so that it is right on target, this research is proposed solutions for applying the analysis decision-making mode using Multi-criteria Decision-making (MCDM). The criteria used include the amount of internet data consumption, Academic credits, courses, and student's economic capacity. The criteria weighting method uses Rank-order Centroid (ROC) and reference point MOORA for determining the best alternative. Â The results showed that the implementation of the MCDM ROC-Reference MOORA method affected the preference value and alternative ranking of internet data quota assistance. This shows that the criteria weight value and the analysis method are critical aspects in decision-making. Differences in weight, even the slightest change in weight, can drastically change the final decisio
Clustering Of Students Into A Specialization Of Expertise Using Genetic Algorithms
Get PDFClustering mahasiswa kedalam keminatan keahlian merupakan salah satu upaya yang perlu dilakukan oleh pihak jurusan untuk menjamin mahasiswa memperoleh pendidikan yang sesuai dengan keahliannya. Saat ini, terdapat banyak metode clustering yang sudah dikembangkan oleh pakar. Umumnya metode clustering mampu mengelompokkan objek-objek yang memiliki tingkat kesamaan ciri yang tinggi, tetapi tidak mampu membatasi jumlah objek yang boleh masuk kedalam suatu kelompok. Kasus klasterisasi mahasiswa kedalam keminatan keahlian merupakan kasus clustering yang membatasi jumlah objek yang boleh masuk kedalam suatu kelompok. Dengan kondisi tersebut, metode clustering yang ada tidak dapat digunakan untuk kasus ini. Peneliti mencoba melihat kasus ini dari sudut pandang optimasi, yaitu bagaimana mengoptimalkan pembentukan kelompok keminatan mahasiswa dengan tingkat ketidaksesuaian bakat yang rendah. Untuk penyelesaian kasus ini, peneliti menggunakan algoritma genetika sebagai metode untuk penyelesaian masalah. Algoritma genetika dibagi kedalam beberapa jenis, yaitu: algoritma genetika dengan prinsip elitisme dan non elitisme, algoritma genetika dengan persentase mutasi 0.01, 0.03 dan 0.05. Berdasarkan penelitian yang dilakukan, diperoleh bahwa algoritma genetika mampu melakukan clustering mahasiswa kedalam keminatan keahlian yang disediakan oleh jurusan. Algoritma genetika dengan prinsip elitisme mampu menemukan solusi optimum yang lebih baik sebesar 39% dibandingkan dengan algoritma genetika non elitisme. Algoritma genetika dengan persentase mutasi 0.05 menghasilkan solusi optimum terbaik, namum memiliki konsumsi waktu yang paling besar dibandingkan dengan persentase 0.01 dan 0.03
Implementation Of Data Mining On Sales At Resto D'sdl Lembang Using Aprioric Algorithm Method
Get PDFThis research was conducted to help determine the menu or package that is often purchased simultaneously. The priori algorithm is used to produce data mining regarding the determination of association rules which is carried out by calculating support and confidence in the sales of food menu mechanisms in a restaurant with a case study of the restaurant d'DSL Lembang. The resulting a priori algorithm will be implemented and tested with the Tanagra application. From the results of the discussion and data analysis carried out, it was found that with the application of the a priori algorithm in determining the combination between itemset with a minimum support of 60% and a minimum confidence of 90%, it was found in the initial calculation of the combination of one itemset, a combination of 2 itemset, a combination of 3 itemset and a final association rule with The highest value of support and confidence is if the consumer orders the Hot Sweet Tea menu, Chicken Driver Package and Liwet Rice at the same time with a support value of 58% and a confidence value of 100%
Performance Analysis of STBC 4x4 MIMO using Ray Tracing Channel Modelling in WLAN Technology
Get PDFIEEE 802.11n technology comes with many advantages such as high data rate and reliability. In 2,4 GHz and 20 MHz bandwidth, it gives data rate up to 300 Mbps. In order to improve reliability without complexity, it uses STBC (Space Time Block Coding) using Alamouti algorithm. This algorithm can be implemented with many STBC scheme, i.e., 2x1, 2x2, 3x1, 3x2, 3x3, 4x1, 4x2, 4x3 and 4x4 using BPSK, QPSK, 16-QAM and 64-QAM modulation. Impulse respons of (Laboratorium Telekomunikasi Radio dan Gelombang Mikro) LTRGM indoor channel can be modeled by using ray tracing method. This simulation also investigates the effect of MIMO channel corelation caused by channel fading and physical antenna factor. The results, LTRGM indoor channel give delay spread and rms delay of 71.94 ns and 1.5 ns respectively. The ergodic channel capacity declines steadily as the channel correlation becomes worse. This problem also cause a decrease in SNR performance to achieve SER of 10-3 with various modulation. However, this does not have significant influence on WLAN system that uses STBC with four both transmit and receive antenn
Machine Learning Dengan Decision Tree untuk Prediksi Pembayaran Invoice, Case Study : Gramedia Jakarta
Get PDFArus keuangan yang lancar merupakan salah satu kunci agar perusahaan tetap bertahan dan memiliki keberlangsungan. Pembayaran atas faktur penjualan adalah salah satu masalah yang dapat mempengaruhi keuangan, jika pembayaran faktur terlambat maka perputaran kas menjadi lambat dan berdampak pada operasional perusahaan. Belum adanya alat yang dapat memprediksi pembayaran faktur di Gramedia menyulitkan bagian keuangan. Dari permasalahan itu, maka diterapkan machine learning untuk memprediksi pembayaran faktur oleh customer, apakah pembayarannya terlambat atau tidak terlambat. Proses dalam data mining menggunakan framework CRISP-DM (Cross Standard Industry for Data Mining). Fitur data yang digunakan sebagai parameter yaitu invoice amount, payment method, paid invoice, average days late dan ratio amount of overdue by amount of balance. Data faktur penjualan diprediksi menggunakan model decision tree algoritma C5.0 dengan hasil akurasi mencapai 71.84%. Algoritma C5.0 terbukti mampu memprediksi faktur yang pembayarannya terlambat (melewati jatuh tempo) dan pembayarannya tepat waktu (sebelum jatuh tempo)
Data Mining Optimization Based on Particle Swarm Optimization For Diagnosis of Inflammatory Liver Disease
Get PDFInflammation of the liver is a contagious disease that is a public health problem that affects morbidity, mortality, public health status, life expectancy, and other socio-economic impacts. Early diagnosis of this disease is very important so that it can be quickly treated and treated. In this study the researchers will apply and compare several data mining and optimization classification methods with particle swarm optimization (pso), including the C4.5 algorithm, k-Nearest Neighbor, C4.5 with PSO, and k-Nearest Neighbor with PSO to diagnose inflammatory diseases. carefully, then compare which of the several of these methods is the most accurate. Based on the results of measuring the performance of the three models using the Cross Validation, Confusion Matrix and ROC Curve methods. Based on the research results, it is known that the C4.5 method with PSO is the best method with an accuracy of 79.51% and an under the curva (AUC) value of 0.950, then the k-Nearest Neighbor method with PSO has an accuracy of 75.59% and an AUC value of 0.909, then the C4.5 method with an accuracy rate of 70.99% and an AUC value of 0.950, then the k-Nearest Neighbor method with an accuracy rate of 67.19%, and an AUC value of 0.873. This proves that particle swarm optimization can improve the performance of the classification method used
Analysis of Definite Integral Material Topics for Improve Student Learning Using Apriori Algorithm
Get PDFDefinite Integral is one of the most important subjects in calculus. The use of integrals that must be studied is calculating the area and drawing curves based on the equation of functions. However, there are still many students have difficult to understand integral material, especially definite integral. Most students have difficult to understand Integral learning because they do not understand the basic and material that needs to be mastered. The purpose of this study is to find a pattern of relationship to the understanding the topic of integral material about calculation and drawing of integral curves using apriori algorithm. Apriori algorithms can be used to determine learning patterns and linkages between definite integral material. Apriori algorithms can be used to determine learning patterns and linkages between definite integral material. The results of this study indicate that understanding of the material is the topic of calculation with 1 functional equation and 2 functional equations, and the depiction of integral curves at X and Y coordinates with a confidence value of 96% and basic integral material such as understanding basic integral techniques, definite integral formulas, calculations and curve depiction on cartesian diagram coordinates X and Y with a confidence value of 76%