|
Active engagement and health status of older Malaysians evidence from a household survey
Item Type: Article
Editor:
Year: 17/03/2023
Abstract: Malaysia is undergoing rapid age structural shift to becoming an ageing nation by 2030 when 14% of its population will be aged 60 and over. Population ageing strains the healthcare system due to the rapid rise in non-communicable diseases and poses enormous challenges in providing social protection.
|
|
|
|
Prosiding Persidangan Kependudukan Kebangsaan 2022 (PERKKS 22): “Pemerkasaan Penduduk dan Keluarga, Teras Negara Maju”
Item Type: Book
Editor:
Year: 00/12/2022
Abstract: Collection of papers presented during the 2022 National Population Conference (PERKKS 22), 10-11 November 2022, Bangi Resort Hotel, Selangor.
|
|
|
|
Intergenerational support and labour participation among older people in Malaysia
Item Type: Book Section
Editor:
Year: 00/12/2022
Abstract: Most older people receive significant assistance from their adult children. Some rely solely on their retirement savings, while others continue to work to support themselves in old age. This study examines the role that adult children play in shaping their parents’ decisions to participate in the labour market. When compared to older people who never received any help from their adult children, the results showed that older people who received assistance more often were less likely to work. This suggests that older individuals’ reduced incentive to work in the labour market is a result of their greater reliance on family support.
|
|
|
|
A world of 8 billion: Towards a resilient future, harnessing opportunities and ensuring rights and choices for all
Item Type: Newsletter
Editor:
Year: 00/11/2022
Abstract: The world's population is projected to reach 8 billion on 15 November 2022. The best way to ensure demographic resilience is to support human rights, including individuals' reproductive rights and choices.
|
|
|
|
Prediction of Malaysian women divorce using machine learning techniques
Item Type: Article
Editor:
Year: 01/10/2022
Abstract: This paper discusses the performance of three machine learning techniques namely Decision Tree, Logistic Regression and Artificial Neural Network for predicting divorce among Malaysian women. Secondary data were obtained from the Fifth Malaysia Population and Family Survey (MPFS-5) conducted by the National Population and Family Development Board (LPPKN). The total number of instances in the dataset was 7,644 ever married Malaysian women aged 15 to 59 years old. Divorce is currently a serious problem among the Malaysian community due to various reasons. In 2019, the divorce rate in Malaysia rose by 12% from the previous year. During the first three months of the movement Control Order (MCO), i.e. from March 18 to June 18, 2020, the Syariah Court of Malaysia recorded 6,569 divorce cases. Worse, a total of 90,766 divorce cases were recorded from January to October 2020. Among the six predictive methods, The Decision Tree Model (C5.0) was found to be the best model in classifying divorce among Malaysian women. The accuracy of the C5.0 model was 77.96% followed by the Artificial Neural Network (Multi-Layer Perceptron) and Logistic Regression (Forward Stepwise) model (74.68% and 67.89%, respectively). The order of important predictors in predicting divorce among Malaysian women is the wives’ employment status (0.1531) followed by the husbands’ employment status (0.1396), type of marriage (0.1327), race/ethnicity (0.1327), distant relationship (0.1212). the wives’ qualification level (0.1115), age group (0.1053) and religion (0.0998)
|
|
|
|
Bandar pintar inklusif warga emas: Bagaimana ketersediaan kita?
Item Type: Book Section
Editor:
Year: 01/07/2022
Abstract: The Third National Physical Plan projects that about 77% of Malaysia’s population will live in cities in 2020 and is expected to increase to 82% by 2030 and 87% by 2050. The elderly in Malaysia (those aged 60 and above) will increase from a total of 2,875 in 2015, to 5,196 million in 2030 and 9,593 in 2050. Malaysia as a developing country will experience an ageing population in the near future.
|
|
|