This site uses cookies.
Some of these cookies are essential to the operation of the site,
while others help to improve your experience by providing insights into how the site is being used.
For more information, please see the ProZ.com privacy policy.
This person has a SecurePRO™ card. Because this person is not a ProZ.com Plus subscriber, to view his or her SecurePRO™ card you must be a ProZ.com Business member or Plus subscriber.
Affiliations
This person is not affiliated with any business or Blue Board record at ProZ.com.
English to Indonesian - Rates: 0.05 - 0.10 USD per word / 20 - 33 USD per hour Indonesian to English - Rates: 0.05 - 0.10 USD per word / 20 - 33 USD per hour Indonesian - Rates: 0.05 - 0.10 USD per word / 20 - 33 USD per hour English - Rates: 0.05 - 0.10 USD per word / 20 - 33 USD per hour
Indonesian to English: estimation of vector autoregressive model's parameter using genetic algorithm General field: Tech/Engineering Detailed field: Mathematics & Statistics
Source text - Indonesian Dalam pemodelan dengan tujuan peramalan yang melibatkan lebih dari satu variabel dapat dilakukan dengan melihat hubungan kausalitas diantara variabel terkait. Misalkan sebuah variabel X1 memiliki hubungan kausal dengan variabel X2, maka informasi masa lalu X1 dapat digunakan untuk memprediksi X2 dimasa mendatang begitu juga sebaliknya. Salah satu pemodelan multivariate time series yang dapat digunakan yaitu Vector Autoregressive. Namun terdapat masalah dalam melakukan proses estimasi dalam pemodelan VAR yang optimal sehingga akan menghasilkan hasil ramalan yang kurang tepat. Salah satu cara untuk mengatasi hal tersebut yaitu dengan melakukan optimasi pada estimasi parameternya. Algoritma genetika adalah salah satu metode optimasi yang dapat digunakan untuk mengatasi masalah tersebut karena menghasilkan solusi yang global optimum. Sehingga dalam penelitian ini akan dilakukan pemodelan dan peramalan menggunakan metode Vector Autoregressive dengan perbandingan estimasi parameter yaitu metode estimasi klasik Conditional Least Square dibandingan dengan optimasi parameter menggunakan algoritma genetika. Perbandingan dilakukan dengan melihat nilai RMSE terkecil diantara kedua hasil estimasi parameter model. Dalam penelitian ini digunakan data simulasi dan penerapan pada data riil, untuk melihat kesesuaian performansi yang diperoleh. Penerapan terhadap data riil menggunakan data harga saham penutupan untuk 4 perusahaan sektor konstruksi pembangunan yang masuk dalam indeks LQ45 yaitu PT. Adhi Karya Tbk, PT. Wijaya Karya Tbk, PT. Waskita Karya Tbk, dan PT. Pembangunan Perumahan Tbk.
Translation - English Model with the aim of estimating that uses more than one variables can be done by seeing the causal relationship between the variables. For example, variable X1 has a causal relationship with variable X2. Due to the relationship between the two variables, X1‘s historical records can be used to predict X2‘s impending events, and vice versa. One of the multivariate time series model that can be used is Vector Autoregressive. However, a problem during the optimal estimating process using VAR model can result in an inaccurate data. One of the ways to solve the problem is by using optimization during the estimation of the parameter. Genetic algorithm is one of the optimization methods that can be used to solve the inaccurate data because it creates a global optimum solution. Due to this reason, this research will use Vector Autoregressive for its modeling and estimating. It will be done by comparing the parameter’s estimation, which is classic estimating method Conditional Least Square compared with parameter optimization using genetic algorithm. The comparing is done by looking at the smallest RMSE value between the results of both estimation of parameter model. This research uses simulation data and the application to the raw data to see the harmony between the information that was received. The application to the raw data uses data of closing stock price from four companies. The companies are construction companies that are included in LQ45 index; they are PT. Adhi Karya Tbk, PT. Wijaya Karya Tbk, PT. Waskita Karya Tbk, and PT. Pembangunan Perumahan Tbk.
More
Less
Experience
Years of experience: 6. Registered at ProZ.com: Mar 2019.
"Two mother tongues" is the best term that describes my relationship with English and Indonesian language, as my background allowed me to speak and to be taught in English and Indonesian simultaneously until now.
I have been translating casually since 2016, but I have decided to venture translation professionally in 2018. Growing up in a diplomatic environment, I, a native Indonesian, have been taught to use both English and Indonesian in an exquisite and accurate manner in both written and oral ways. Because of that, I am able to adapt myself to the necessary language "level" the situation needs, from the most formal one to the most informal one.
Besides translation, I am also an English teacher with B.Ed. as my degree. Due to my education, I am best at translating works related with education. However, I also delve in other specializations, namely academic writing, game, and subtitles. I am available when you need me, as I always spend my week translating. If you need a quote, you are more than welcome to contact through ProZ or directly to [email protected]
Expertise