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This research focuses on the development of a web-based Computer Based Test (CBT) Application for Madrasah Tsanawiyah (MTs) Faqih Hasyim in Sidoarjo, East Java. This application aims to overcome conventional evaluation problems with paper and pen, such as cheating, scoring errors, and data management difficulties. Using web technologies such as HTML, CSS, PHP, and JavaScript, the application integrates the Fisher-Yates Shuffle algorithm to randomize the order of questions, reducing the possibility of cheating during the exam. Equipped with session tokens, exam timing, and result reports, the app improves the overall efficiency of the evaluation process. This study refers to previous research and highlights the importance of adopting technology to simplify assessment and facilitate online data management. The Fisher-Yates Shuffle algorithm, used to generate a unique sequence of questions for each student during the exam, minimizes the risk of cheating. The app implements a staged exam, ensuring students who meet the minimum criteria proceed to the next stage. In addition, the app achieves a degree of randomization of the exam content, eliminating patterns that may affect the exam results. The feasibility testing results show that the app is highly feasible, with a feasibility percentage of 92.4%. This conclusion signifies the app's success in achieving its development goals and making a positive contribution in easing the exam grading process. It is recommended to simplify the interface for senior users, improve the responsiveness of the website display for mobile access, and add a time limitation method in future research.   Keywords: Fisher-Yates Shuffle Algorithm, Computer Base Test, Question Randomization.  

The Erlang distribution is a special case of the Gamma distribution with the k shape parameter and the λ rate parameter. In this study, the parameter estimation of the Erlang distribution was carried out using the Maximum Likelihood method. In maximizing the function, an implicit and non-linear form is obtained, then it is solved using the Newton Raphson algorithm. Apart from Newton Raphon, the estimation of parameters was also carried out using the Fisher Scoring algorithm. The Fisher Scoring algorithm is similar to the Newton Raphson algorithm, the difference is that Fisher Scoring uses an matrix information. The result of parameter estimation in Erlang distribution using Newton Raphson algorithm which is applied to outgoing telephone call data that generated by Matlab R2010a software cannot be done simultaneously. Therefore, the parameter assessment is carried out on the k parameter first, then followed by the λ parameter estimation and the parameter and  = 0.6886812 are obtained. Meanwhile, the parameter estimation using the Fisher Scoring algorithm produces an equation that is not different from the Newton Raphson algorithm