Algorithm Symmetric 2-DLDA for Recognizing Handwritten Capital Letters

Statistical pattern recognition is the process of using statistical techniques to obtain information and make informed decisions based on data measurements. It is possible to solve the doubt inherent in the objective function of the 2-Dimension Linear Discriminant Analysis by employing the symmetrical 2-Dimension Linear Discriminant Analysis approach. Symmetrical 2-dimensional linear discriminant analysis has found widespread use as a method of introducing handwritten capital letters. Symmetric 2-DLDA, according to Symmetric 2-DLDA, produces better and more accurate results than Symmetric 2-DLDA. So far, pattern recognition has been based solely on computer knowledge, with no connection to statistical measurements, such as data variation and Euclidean distance, particularly in symmetrical images. As a result, the aim of this research is to create algorithms for recognizing capital letter patterns in a wide range of handwriting. The ADL2-D symmetric method is used in this study as the development of the ADL2-D method. The research results in an algorithm that considers the left and right sides of the image matrix, as opposed to ADL2-D, which does not consider the left and right sides of the image matrix. In pattern recognition, the results with symmetric ADL2-D are more accurat

RELATIVE RISK ANALYSIS OF THE SPREAD OF COVID-19 VIRUS IN MEDAN CITY BY SPATIAL AND NON-SPATIAL APPROACHES

The city of Medan is the city with the highest cases of COVID-19 virus among cities in North Sumatra. This study was conducted to analyze the relative risk level for the spread of the COVID-19 virus. Estimation of relative risk is a statistic in disease mapping that is used to determine the distribution of disease. Relative risk estimation can be estimated using a direct estimator model or Standardized Morbility ratio and a small area estimation model using Bayesian Conditional Autoregressive (CAR) with the Poisson-Gamma model. The Poisson-Gamma model is one of the models in estimating small areas in the form of count data which is suitable for use in disease mapping cases. This study aims to find the relative risk value as the basis for mapping the spread of the COVID-19 virus in the city of Medan using the Standardized Morbility Ratio and Bayesian Condition Autoregressive models. And look for the value of the Central Error Squared (KTG) / Mean Squared Error (MSE) as a comparison which model is more efficient in estimating this research. Condition Autoregressive models. And look for the value of the Central Error Squared (KTG) / Mean Squared Error (MSE) as a comparison which model is more efficient in estimating this research

APPLICATION OF HYBRID LSTAR-GARCH MODEL WITH EXPECTED TAILL LOSS IN PREDICTING THE PRICE MOVEMENT OF BITCOIN CRYPTOCURRENCY AGAINST RUPIAH CURRENCY

Time series data from bitcoin has nonlinear data fluctuations so that a model is needed that can accommodate data with these conditions. The method that can be used for nonlinear time series data cases such as bitcoin is the LSTAR-GARCH model. LSTAR-GARCH is a combination of the LSTAR model and the GARCH model. Bitcoin investment also contains an element of risk. To find out the value of risk, the Expected Tail Loss risk measurement tool can be used. Expected Tail Loss (ETL). The data used in this study are historical daily bitcoin price data for the period April 1, 2022 to April 1, 2023. The modeling results obtained based on the MAPE value show that the LSTAR-GARCH model is the best model with the smallest MAPE value of 30% compared to the AR, LSTAR, or AR-GARCH models. The expected Taill loss value of bitcoin is -0.06784

Prediksi Jumlah Penduduk Miskin Di Sumatera Utara Dengan Metode Jaringan Syaraf Tiruan Backpropagation

Abstract:  A artificial neural network is an information processing system that is inspired by the biological nervous system, such as the performance of the brain that processes information. In the 2017-2020 period the data on the number of poor people in North Sumatra used were secondary data obtained from the Central Statistics Agency. There are prediction results for the number of poor people in North Sumatra, namely 77,927 people in 2022 consisting of 25 districts, where the data is divided into two parts, namely 5 test data and 20 training data. Artificial neural networks with the Backpropagation method are able to determine or predict the number of poor people in North Sumatra.Abstrak: Jaringan syaraf tiruan adalah sebuah pengolahan informasi yang terinspirasi dari system kerja syaraf biologis, seperti kinerja otak yang memproses suatu informasi. Pada periode 2017-2020 data jumlah penduduk miskin di Sumatera Utara yang digunakan adalah data skunder yang diperoleh dari Badan Pusat Statistik Sumatera Utara Medan. Terdapat hasil prediksi jumlah penduduk miskin di Sumatera Utara adalah 77. 927 jiwa pada tahun 2022 yang terdiri dari 25 kabupaten, dimana data tersebut terbagi menjadi dua bagian yaitu 5 data uji dan 20 data latih. Jaringan syaraf tiruan dengan metode Backpropagation mampu menentukan atau memprediksi jumlah penduduk miskin di Sumatera Utara

Analysis Of Multi Item Raw Material Inventory Supply Using The Economic Order Quantity Method

Raw material inventory control has a positive impact to support the smooth production process in increasing company profits, one of which is the production of chicken feed at PT. Mabar Feed Indonesia. This study aims to determine the economic order quantity of multi-item chicken feed raw material inventory, and to compare the control of multi-item chicken feed raw material inventory used by companies with the control of multi item chicken feed inventory using the EOQ method. In this study to analyze the data first used the normality test data with the Lilliefors test where the data is normally distributed. The total cost of raw material inventory according to PT Mabar Feed Indonesia is Rp.   the cost is greater than the cost obtained by the EOQ method, which is Rp.   and savings can be made of  Rp.   of the cost of raw material inventory according to PT. Mabar Feed Indonesia

Survival Analysis of Covid-19 Patients Based on Time of Recovery

Corona virus is a virus that can cause the respiratory tract to become infected, and this viral infection is called COVID-19. This virus spreads so fast that it has spread to several countries, including Indonesia. In Indonesia, COVID-19 was detected in early March, precisely on March 2, 2020. The uncertain increase in the number of COVID-19 patients will have an impact on society and the country. This condition is compounded by the high number of deaths due to the COVID-19 virus. Therefore, this study was conducted to analyze survival based on the healing rate of COVID-19 patients, in order to obtain information about the time period and the factors that cause a person with COVID-19 to survive. The method used in the survival analysis is the Kaplan-Meier test as a counter to the estimated recovery time of COVID-19 patients and the Log-Rank test to test for differences in the survival function of the recovery time of COVID-19 patients in the two groups. Kaplan-Meier and Log-Rank tests are part of the non-parametric method which is a statistical test that does not require any assumptions about the distribution of population data. The data used is data on COVID-19 patients at the Malahayati Hospital from January to May 31, 2021. The conclusion obtained is the survival function curve / length of time on the recovery rate of COVID-19 patients based on gender, age, and positive and suspected COVID-19 patients. with and without comorbidities. However, based on the Log-Rank test with = 0.05, it was concluded that there was no significant difference in the length of time for recovery of COVID-19 patients based on gender, age and positive patients and patients with suspected COVID-19 with comorbid and without comorbidities.Corona virus adalah virus yang dapat membuat saluran pernapasan mengalami infeksi, dan infeksi virus ini disebut dengan COVID-19. Virus ini menyebar dengan sangat cepat hingga telah menyebar ke beberapa negara, termasuk Indonesia. Di Indonesia, COVID-19 terdeteksi pada awal bulan Maret tepatnya pada 2 Maret 2020. Kota Medan memiliki jumlah terkonfirmasi positif COVID-19 terbanyak di Sumatera Utara yaitu 18.522 orang. Selain jumlah terkonfirmasi positif, di kota Medan juga tercatat angka kematian sebanyak 631 pasien dan menjadi kota dengan jumlah meninggal terbanyak di Provinsi Sumatera Utara. Kota Medan mencatat pasien yang sembuh dari COVID-19 adalah sebanyak 16.596 pasien. Peningkatan jumlah pasien COVID-19 yang tidak menentu akan berdampak bagi masyarakat dan Negara. Hingga peneliti melakukan penelitian dengan maksud untuk mencari fungsi survival/lama waktu pada laju kesembuhan pasien COVID-19 di salah satu rumah sakit kota Medan yaitu RSI Malahayati Medan. Tingginya angka kematian dikarenakan virus COVID-19 ini sangat berbahaya bagi masyarakat. Untuk itu dilakukan analisis survival pada waktu laju kesembuhan pasien COVID-19 di RSI Malahayati dengan uji Kaplan-Meier sebagai penghitung estimasi waktu sembuh pasien COVID-19 dan uji Log-Rank untuk menguji adanya perbedaan pada fungsi survival waktu sembuh pasien COVID-19 pada dua kelompok. Data yang digunakan adalah data pasien COVID-19 di RSI Malahayati sejak Januari sampai 31 Mei 2021. Kesimpulan yang diperoleh adalah kurva fungsi survival/lama waktu pada laju kesembuhan pasien COVID-19 berdasarkan jenis kelamin, usia, dan pasien positif serta suspect COVID-19 dengan komorbid dan tanpa komorbid. Namun berdasarkan uji Log-Rank dengan α=0.05, disimpulkan tidak terdapat perbedaan yang signifikan pada lama waktu sembuh pasien COVID-19 berdasarkan jenis kelamin, usia dan pasien positif serta pasien suspect COVID-19 dengan komorbid dan tanpa komorbid

ANALISIS PENJUALAN DAN PERSAINGAN AIR MINERAL KEMASAN BOTOL SELAMA PANDEMI COVID-19 DI KOTA MEDAN MENGGUNAKAN RANTAI MARKOV ORDE DUA

Markov chain is a method used to identify variables in the present, which is based on past variables in order to obtain an estimate of the probability of these variables in the future. The CoVid-19 virus outbreak has also had a negative impact on economic problems, because this pandemic resulted in a decrease in sales of mineral water. in bottles that experienced a decline in sales results during the COVID-19 pandemic. The formulation of the problem of how companies compete during Covid-19 which continues to experience a decline in sales? . Based on the results of this study, there is a large chance of a second order transition, namely AQUA products in September, which is 61%, an increase of 0.39% from October, in October it was 61.39, a decline of 0.02% so that in November it was 61.37% while Le Mineral products in September were 39%, decreased 0.39% from October, October was 38.61%, experienced a fix in November so November was 38.61%