Browsing by Author "Yousuf, Ridwanullah"

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Identifying the Writing Style of Bangla Language Using Natural Language Processing
(11th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2020, IEEE, 2020-10-15) Shetu, Syeda Farjana; . Saifuzzaman, Mohd; Parvin, Masuma; Moon, Nazmun Nessa; Yousuf, Ridwanullah; Sultana, Sharmin
Bangla is one of the 8th major spoken languages around the world and like other widely spoken languages, it is a very morphologically rich language. It has two styles, one is standard literary style, known as Sadhu Bhasha and the other one is a standard colloquial style which is known as Cholito Bhasha. Mixing both the styles in a written document is considered as a grammatical error in Bangla language known as Guruchondali Dosh. This research aims to develop an algorithm to identify the style of a Bangla paragraph i.e. whether it is in Sadhu Bhasha or Cholito Bhasha from a given Bangla paragraph input. It's a contribution towards finding the Goruchondali Dosh which is a common grammatical mistake in written Bangla language as it was observed that a number of research work for identifying Bangla grammar mistakes is not so notable whereas it is a common trend in other language researchers.
Student’s Performance Prediction Using Data Mining Technique Depending On Overall Academic Status and Environmental Attributes
(Springer, 2021) Shetu, Syeda Farjana; Saifuzzaman, Mohd; Moon, Nazmun Nessa; Sultana, Sharmin; Yousuf, Ridwanullah
In the education sector, it has been a challenging task to identify the students individually to take appropriate actions to get a very deserving outcome from them. On the other hand, a student getting higher education should have the knowledge about the market demands and where are their weaknesses. If it is possible to get some data from students’ academic record and their percepts on some factors related to academic performances those may help to understand the reasons for success and failure which would be very useful in the educational environment and student success rate. We collect data from students from different institutes. First, we create an online survey form to get data, and then we process them to get some valuable information. After getting those data, we visualize then analyze them from different prospects. We try to get some exact knowledge which can be crucial for students’ success or failure in an academic environment. We apply the data mining technique decision tree algorithm (j48) to develop a model that shows us the hierarchy of different attributes related to students’ academic performance and their personal behaviors that affect a student’s academic status. Then we try to get information about which attributes have a positive and which attribute has a negative impact on students’ academic growth.