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Padang, Id

Padang, Sumatera Barat, Indonesia

Padang, Sumatera Barat, Indonesia

*Have 2 years of experience in data analysis, preferably in a business setting *Processing, analyzing and interpreting data *Create programming scripts to manage data *Discuss research results with lecturer *Profciency in data visualization tools such as Pandas package in python, minitab, and R to create interactive dashboards, enhancing data comprehension and decision-making by 30% *Obtaining a model with an accuracy rate of 83-99% *Already published 2 articles and still in the works

Padang, Sumatera Barat, Indonesia

I am a teaching assistant for the courses Mathematical Statistics 1, Mathematical Statistics 2, Data Analysis, Elementary Statistics, Calculus 1, Ordinary Differential Equations, and Economic Statistics. I assist the instructors in conducting tutorials in class, checking assignments and quizzes, as well as inputting grades into Excel. Occasionally, I also assist in checking assignments from other departments where the instructors teach

Padang, Sumatera Barat, Indonesia

I interned in 3 units, namely Quality Control (QC), Production Support , and Clinker Production. 1. Quality ControlThe main issue faced during my internship was how to optimise the use of clinker, where the expected clinker is around 57-58%. Due to the impact on the compressive strength of the cement produced. To overcome this problem, a statistical method approach is carried out, namely Response Surface Methodology (RSM).After the analysis, it was found that the significant variables were Sieve, Blaine, SIM, FCaO and obtained the optimum point to be used for the desired clinker around 57-58%.2. Production SupportIn this unit, I identified a problem related to the absence of a simpler programme to calculate the TSR value of production waste generated in the factory. To overcome this, I implemented mathematics through Python, and I succeeded in developing a programme that can automatically calculate TSR in production waste management.3. Clinker Production Staff In this unit, I performed modelling to predict SO3 in clinker, freelime in clinker, how Sieving Raw Mix relates to the homogenising effect of CFSilo and to coal usage, and relationship between Clinker SO3 and Hot Meal SO3, FCao, LTW, Torque, Burner Temperature, and Peak O2.*Modelling SO3 in clinker is very complex, consisting of 4 stages, resulting in 4 prediction models. When the ordinary least square (OLS) method is used, there is an assumption that is violated, namely that the error is not normally distributed, which results in OLS not being used. So the quantile regression method is used with the help of R software to overcome this. After obtaining the model, then look for the best model with the goodness of model test, namely pseudo R2. For the model obtained, the pseudo R2 value is more than 90% which indicates that the model obtained is good. To predict freelime in clinker was performed with quantile regression. And to obtain the relationship between variables used spearman correlation

Padang, Sumatera Barat, Indonesia

Creating and selling flower bouquets, money bouquets, and gifts for events such as Proposal Seminars, Results Seminars, Comprehensive Examinations, and Graduations.Promoting and becoming a social media admin to assist buyers with their ordersProduced and curated over 41 Instagram posts, resulting in the acquisition of 200+ new followers

Padang, Sumatera Barat, Indonesia

Assisting students in understanding course material, Teaching students about subjects at campus

Master Of Science - Ms, Mathematics, 3.83

Focus of Interest : Focusing on the field of statistics, especially Bayesian research Final Research Thesis Title: Modeling the Growth.

Bachelor Of Science - Bs, Mathematics, 3.73

Activities and Societies: Himpunan Mahasiswa Matematika Universitas Andalas, Public Services.Focus of Interest : Focusing on the field.

Education record