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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Research Journal on Education
Hasan, Nahid
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Tomato pest recognition using convolutional neural network in Bangladesh Polin, Johora Akter; Hasan, Nahid; Habib, Md. Tarek; Rahman, Atiqur; Vasha, Zannatun Nayem; Sharma, Bidyut
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.6073

Abstract

The tomato is one of the most popular and well-liked veggies among Asians. It is interesting to note that in Bangladesh, it is the second most significant vegetable consumed. Moreover, tomato is served not only as a vegetable, but it is also served as sauce, jam, etc., and used in making different types of cuisines. But the fact is due to the pests, thousands of tons of tomatoes are harmed every year in Bangladesh. The production of tomatoes in Bangladesh is harmed by a number of dangerous pests. We develop a solution to recognize pests at an early stage. Five different pest types, including aphids, red spider mites, whiteflies, looper caterpillars, and thrips, have been studied in this research. To identify tomato pests, we curated image datasets from online and offline repositories and processed them using a convolutional neural network (CNN) model. We used features from CNN layers for three machine learning algorithms: Random Forest (RF), support vector machine (SVM), and K-Nearest Neighbors (K-NN). This comprehensive approach allowed a thorough comparison of these algorithms in tomato pest recognition. For recognizing tomato pests, our methods generate excellent results. The accuracy of our experiment is 95.49% which indicates the successful completion of the experiment.
Predicting the effects of microcredit on women’s empowerment in rural Bangladesh: using machine learning algorithms Polin, Johora Akter; Sarker, Md. Fouad Hossain; Dolon, Mst Dilruba Khanom; Hasan, Nahid; Rahman, Md. Mahafuzur; Vasha, Zannatun Nayem
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.7169

Abstract

This study aimed to predict the impact of microcredit on women’s empowerment in Bangladesh using machine learning (ML) algorithms. In rural Bangladesh, where microcredit programs are not significantly employed, data for the study was gathered through a survey. The study gathered data on a range of socioeconomic, demographic, and women’s empowerment indicators. The Naive Bayes (NB), sequential minimal optimization (SMO), k-nearest neighbor (k-NN), decision tree (DT), and random forest (RF) ML techniques were used in the investigation. In terms of the prediction of women’s empowerment, the findings indicated that all five algorithms performed well, with the DT having the highest level of accuracy (83.72%). The results of this study have significant consequences for Bangladesh’s microcredit programs and those in nations that are developing. Microcredit programs can focus their efforts on women who, based on their socioeconomic and demographic features, are most likely to benefit from the program by employing ML algorithms. This may result in more successful microcredit projects that support the empowerment of women and general socioeconomic growth.
A novel approach to analyzing the impact of AI, ChatGPT, and chatbot on education using machine learning algorithms Hasan, Nahid; Polin, Johora Akter; Ahmmed, Md. Rayhan; Sakib, Md. Mamun; Jahin, Md. Farhan; Rahman, Md. Mahfuzur
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.7158

Abstract

Artificial intelligence (AI) is one of the most common and essential technologies in this modern era, especially in the education and research sectors. It mimics machine-processed human intellect. In modern times, ChatGPT is one of the most effective and beneficial tools developed by OpenAI. Provides prompt answers and feedback to help academics and researchers. Using ChatGPT has various advantages, including improving methods of instruction, preparing interactive lessons, assessment, and advanced problem-solving. Threats against ChatGPT, however, include diminishing creativity, and analytical thinking. Additionally, students would adopt unfair procedures when submitting any tests or assignments online, which would increase their dependency on AI systems rather than thinking analytically. In this study, we have demonstrated arguments on both sides of AI technology. We believe that our study would provide a depth of knowledge and more informed discussion. Data is collected via an offline platform and then machine learning algorithms such as K-nearest neighbour (K-NN), support vector machine (SVM), naive bayes (NB), decision tree (DT), and random forest (RF) are used to analyze the data which helps to improve teaching and learning techniques where SVM shows best performance. The results of the study would offer several significant learning and research directions as well as ensure safe and responsible adoption.
Evaluating the Impact of Primary Education in Bangladesh: An In-Depth Investigation of Bagha Upazila in the Rajshahi District. Al Zaman, Md. Pervaz; Hasan, Nahid; Islam, Md. Hafizul; Amin, Md. Ruhul
Indonesian Research Journal on Education Vol. 4 No. 1 (2024): irje 2024
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/irje.v4i1.420

Abstract

Primary education is the most crucial and fundamental stage of education. This paper explores the quality and effectiveness of primary education in government primary schools in Bagha Upazila of Rajshahi district. It also found out the reasons for the increase in the trend of enrollment of children in kindergarten schools. In addition, the reasons for the establishment of kindergarten schools have been explored. Further, barriers to the development of primary education are examined. Besides, steps taken by government officials and primary school teachers to improve primary education have been assessed. It also found that a child is being deprived of the services it deserves from primary school. Moreover, suggestions were sought from the respondents on how to make primary education more effective. In this study, a qualitative approach was applied. This includes open ended questionnaire as data collection tool. Primary data was collected from government officials, civil society, teachers of primary school, guardians of primary school students and guardians of kindergarten school students. The findings of this research show that primary school students are being deprived of quality education due to shortage of primary school teachers, inefficiency of teachers, lack of sincerity of teachers, lack of proper status of teachers, inadequate teaching materials, pressure of extra clerical work on teachers, underdeveloped infrastructure, poverty of families, lack of awareness of guardians. And for these reasons students are enrolling in kindergarten schools.
Co-Authors Ahmmed, Md. Rayhan Al Zaman, Md. Pervaz Atiqur Rahman Dolon, Mst Dilruba Khanom Habib, Md. Tarek Islam, Md. Hafizul Jahin, Md. Farhan Md. Ruhul Amin Polin, Johora Akter Rahman, Md. Mahafuzur Rahman, Md. Mahfuzur Sakib, Md. Mamun Sarker, Md. Fouad Hossain Sharma, Bidyut Vasha, Zannatun Nayem