- Volume 11, Number 3 (2023)
SOWING SUCCESS: A HOLISTIC ANALYSIS OF CAREER CHOICES AND CHALLENGES AMONG AGRICULTURAL STUDENTS IN ANAMBRA STATE, NIGERIA
Obinna Chinedu Okoye
The study accessed agricultural undergraduate students’ reasons for choosing agriculture as a career, sources of their motivation, and problems encountered in their study. Data were collected through a structured questionnaire administered on 100 respondents selected through simple random sampling process from two Faculties of Agriculture of two universities: Chukwuemeka Odumegwu Ojukwu University (COOU) and Nnamdi Azikiwe University (NAU) both in the Anambra State of Nigeria. Some of the information provided by the respondents was verified through 4 in-depth interviews. Descriptive statistics such as percentage, frequency distributions, and Tables were used in analyzing the data. The result show that the majority...
ON THE ROAD TO UNDERSTANDING: EXPLORING TEUKU UMAR UNIVERSITY STUDENT MOBILITY AND ITS CONSEQUENCES FOR CAMPUS TRANSPORT SYSTEMS
Siti Aisyah Rahmadhani
Teuku Umar University (UTU) is a prominent public university located in Meulaboh City, West Aceh Regency, situated in the Southwestern part of Aceh, Indonesia. With the passage of time, the student population at UTU has been steadily increasing, with 6,636 active students enrolled in the academic year 2021-2022. This growth has raised concerns about traffic congestion and the demand for additional parking spaces around the campus, primarily due to an increase in the number of students using private vehicles. Such transportation trends have resulted in significant external costs. To address these challenges and promote sustainable mobility solutions, the implementation of...
TOMORROW'S HEALTH TODAY: A COMPARATIVE STUDY OF MACHINE LEARNING ALGORITHMS FOR PREDICTING ANEMIA IN YOUNG CHILDREN
Alok Prasad Subedi
Anemia is a common health issue in young children, which can lead to serious consequences if not detected and treated early. In this study, we explore the potential of using machine learning algorithms to predict anemia in children under the age of five. We collected data from Kanti Children Hospital in Nepal, consisting of 700 data records, and selected six different machine learning algorithms for verification and validation, including Random Forest, Decision Tree, Naïve Bayes, Artificial Neural Network, Support Vector Machine, and Logistic Regression. The data was preprocessed, normalized, and balanced, and the algorithms were applied to improve accuracy in...
ADSORBING CONTAMINANTS: A COMPREHENSIVE STUDY OF CHEMICALLY ACTIVATED NYPA FROND POWDER FOR LEAD REMOVAL
Rizky Akbar Setiawan
Nypa fruticans, commonly known as the Nipa palm, is a palm species that thrives along brackish coastlines in swampy areas, covering a significant portion of Indonesia's tidal regions. With its abundant cellulose (35.1%), lignin (17.8%), and ash (11.7%) content, the Nipa palm presents promising potential as a biosorbent for heavy metal removal from liquid waste. This study explores the viability of utilizing Nipa palm as an eco-friendly and cost-effective adsorbent material for heavy metal remediation. The growing environmental concern over heavy metal pollution, which poses serious health risks to living organisms, calls for effective and efficient remediation methods. Adsorption, among...