Research review on time series forecasting of gold price movement

This paper propose different techniques used in forecasting on time series analysis. Various techniques had been used in the field of time series forecasting from the traditional Box-Jenkins approach to the most popular neural network technique nowadays. However, there is no specifically the best method to deal with time series forecasting as the application of different time series forecasting methods has their own requirements and restrictions. In determining the movement of gold price, there are a lot of different methods being implemented by various authors to propose their models. Various time series forecasting method have been discussed in this paper which consists of several journal articles that related to gold price and some of the data mining techniques in time series forecasting retrieved from Google Scholar in this review

Mathematical approach for serving nutritious menu for secondary school student using “delete-reshuffle-reoptimize algorithm”

Secondary school student need to eat a well nutritious and healthy food that gives enough supplements for improvement, safeguarding and rebuilding the human body. In addition, with legitimate supplement, it can keep any undesirable diseases and infections. At this moment, medicinal disclosure demonstrates that by expending very much adjusted nutritious sustenance, it can anticipate and decrease the dangers of certain illness. Menu organizers, nutritionist and dietitians faced with mind boggling undertakings and inconveniences obstacles to grow human wellbeing. Serving more beneficial meal is a noteworthy step towards accomplishing one of the objectives for this study. However reorganizing a nutritious and well balanced menu by hand is difficult, insufficient and time consuming. The target of this study is to build up a mathematical technique for menu scheduling that fulfill the whole supplement prerequisite for secondary school student, reduce processing time, minimize the budget and furthermore serve assortment type of food consistently. It additionally gives the adaptability for the cook to change any favored menu even after the ideal arrangement and optimal solution has been acquired. A recalculation procedure will be performed in light of the ideal arrangement. The data was obtained from the Ministry of Health Malaysian and school specialists. The model was solved by using Binary Programming and “Delete-Reshuffle-Reoptimize Algorithm”

The expectation requirement prospective in fulfill industries needs in technical skills among vocational students (TVET).

The investigation of the research is based on the expectation prospective requirement that’s needs to acquire among vocational students in University Tun Hussein On Malaysia (UTHM) The main objective is to observe the prospective students and establishment of foundation understanding that they need to fulfill the expectation of the industries. This is to ensure that they are well preparing in workplace in the future time. To achieve this by doing so is by implementation of phenomenological research method .From the experimental procedure is base from students prospective and by conducting questionnaire and interview. From these results, it can be conclude that students need more influence of self-establishment as they need to be ready entering in the industries of vocational

A study of nanoparticles as a drug carrier on the wall of Stenosed Arteries

The influences of nanoparticles as drug carriers on the walls of stenosed arteries are presented. In this study, three nanoparticles namely Fe3O4 , TiO2 and Cu were used. It is observed that the addition of Fe3O4 nanoparticles tends to reduce the resistance impedance of blood temperature in bell shaped stenosed arteries. The blood temperature increases slightly in the streamwise direction before the throat region. Thereafter, the blood temperature increases at a higher rate and reaches its maximum value at the stenosis throat. It is found that the temperature distribution is heavily dependent on parameters such as periodic body acceleration and Prandtl number

PENCAPAIAN KURSUS MATEMATIK DAN STATISTIK DI KALANGAN PELAJAR UTHM: FAKTOR MEMPENGARUHI DAN TEKNIK PENGAJARAN DAN PEMBELAJARAN YANG LEBIH DIMINATI

Kajian ini bertujuan mengenal pasti punca yang mempengaruhi pencapaian kursus matematik dan statistik di kalangan pelajar Universiti Tun Hussein Onn Malaysia (UTHM). Seramai 2605 orang pelajar telah terlibat dalam kajian ini dan pemilihan responden adalah dilakukan secara rawak berstrata berdasarkan jumlah populasi pelajar di setiap fakulti. Kajian ini menggunakan statistik deskriptif analisis seperti min, sisihan piawai, kekerapan dan peratus untuk menjelaskan faktor-faktor yang mempengaruhi pencapaian pelajar dalam kursus matematik dan statistik. Seterusnya, kajian ini juga mengenalpasti kaedah dan teknik pembelajaran yang lebih diminati pelajar dan dianalisis dengan menggunakan kaedah analisis Pareto. Hasil kajian mendapati faktor latar belakang diri, faktor tenaga pengajar, dan faktor kondisi tempat pengajian mempengaruhi pencapaian pelajar dalam kursus matematik dan statistik manakala kaedah pembelajaran berpusatkan pelajar adalah lebih diminati oleh pelajar berbanding pembelajaran berpusatkan guru

Analysis of time series for Malaysian currency exchange rate to the United States currency

Currency exchange rate is one of the external factors that will affect the financial status of Malaysia. Therefore, forecasting the foreign currency exchange rate is important for the financial decision makers, bankers, academic researchers and business practitioners. Time series method is an important area of predicting future data based on the past data. In this study, Auto-Regressive Integrated Moving Average (ARIMA), Double Exponential Smoothing method and Holt-Winter additive method will be used to forecast the data of currency exchange rate of Malaysia Ringgit (RM) to United States of America Dollar (USD). The Mean Absolute Percentage Error (MAPE) for ARIMA, Double Exponential Smoothing method and Holt-Winter additive method are 0.9400, 0.9035 and 2.2686 respectively. In conclusion, the model generated by using Double exponential Smoothing method is the best model to forecast the currency data with the lowest value of MAPE, Mean Absolute Error (MAE) and Mean Square Error (MSE) compared to ARIMA method and Holt-Winter Additive method

A non-classical optimal control problem

We consider another non-classical of optimal control problem that is spurred by some current research on the nonlinear income issue in the field of financial matters. This class of issue can be set up as a maximizing issue in the area of Optimal Control. In any case, the state value at the final fixed time, y(T), is priori unknown and the integrand is an element of the unknown y(T). This is a non-classical optimal control problem. In this paper we apply the new costate value conditions p(T) in the definition of the optimal control problem. We solve some examples in this issue using the numerical shooting method to illuminate the subsequent Two Point Boundary Value Problem (TPBVP) and join the free y(T) as an additionally unknown. Basically similar outcomes are obtained through the nonlinear programming (NP) discrete-time results

Forecasting currency in circulation in Malaysia using arch and garch models

The monthly economic time series commonly contains the volatility periods and it is suitable to apply the Heteroscedastic model to it where the conditional variance is not constant throughout the time trend. The aim of this study is to model and forecast the currency in circulation (CIC) in Malaysia over the time period, from January 1998 to January 2016. Two methods are considered, which are Autoregressive Conditional Heteroscedastic (ARCH) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH). Using the Root Mean Square Error (RMSE) as the forecasting performance measure, this study concludes that GARCH is a more appropriate model compared to ARCH

Buli di kalangan pelajar sekolah rendah luar bandar: kajian kes di kawasan Felda Utara Kedah-Perlis, Malaysia

Objektif utama kajian ialah mengkaji tingkah laku buli dalam kalangan pelajar sekolah rendah yang bersekolah di dalam ladang. Instrumen BBQ Olweus telah implementasi kepada n=110 orang pelajar sekolah rendah dengan croncbach alph 0.899. Hasil kajian mendapati 37.3% daripada n=110 responden mempunyai pengalaman dibuli. Didapati buli secara verbal adalah pengalaman buli yang seringkali dialami iaitu sebanyak (¯x=0.9873); buli relational (¯x=0.8065) dan buli secara fizikal (¯x=4591). Justeru itu, hasil kajian juga merumuskan waktu rehat adalah waktu yang paling kritikal berlakunya buli iaitu (89% semasa beratur ; 80% semasa beratur dan sedang mengambil makanan, 69% dalam tandas and 46.4% perjalanan pergi dan pulang dari kelas). Manakala, terdapatnya hubungan yang signifikan di antara lokasi buli dengan jenis buli iaitu relational (r=0.833,>0.05), verbal (r=0.704,>0.05) and fizikal (r=0.619,>0.05). Hasil kajian juga mendapati adanya hubungan di antara siapa pembuli dengan jenis buli iaitu verbal (r=0.692,p>0.05), relational (r=0.614,p>0.05) and fizikal (r=0.468,p>0.05)

Comparative analysis of support vector machine, maximum likelihood and neural network classification on multispectral remote sensing data

Land cover classification is an essential process in many remote sensing applications. Classification based on supervised methods have been preferred by many due to its practicality, accuracy and objectivity compared to unsupervised methods. Nevertheless, the performance of different supervised methods particularly for classifying land covers in Tropical regions such as Malaysia has not been evaluated thoroughly. The study reported in this paper aims to detect land cover changes using multispectral remote sensing data. The data come from Landsat satellite covering part of Klang District, located in Selangor, Malaysia. Landsat bands 1, 2, 3, 4, 5 and 7 are used as the input for three supervised classification methods namely support vector machines (SVM), maximum likelihood (ML) and neural network (NN). The accuracy of the generated classifications is then assessed by means of classification accuracy. Land cover change analysis is also carried out to identify the most reliable method to detect land changes in which showing SVM gives a more stable and realistic outcomes compared to ML and NN