ORDINAL REGRESSION FOR MODELLING THE FAMILY WELL-BEING AMONG THE MALAYSIANS

Background and Purpose: Understanding factors which affect the level of family well-being is important as it contributes to effective decision making among the policymakers to improve the family lives as well as to strengthen the family institution. Accordingly, this line of research is gaining attention. This study develops an ordinal regression model which identifies demographic, economic and social factors that are significant in explaining the status of family well-being.    Methodology: Data involving 2,808 respondents from a nationwide survey conducted by the National Population and Family Development Board of Malaysia in 2011 were used in this study. Ordinal regression model was implemented to describe the three levels of family well-being.   Findings: The national survey reported that high level of family well-being was experienced by 76.3 per cent of the respondents, followed by moderate (18.4%) and low (5.3%). The fitted ordinal regression model found that ethnic background, family relationship, community relationship, health and safety levels, economic situation of the family, religious practice, housing, and environment are significantly related to family well-being. Meanwhile, it was found that the level of income is not a significant factor in determining the level of family well-being.     Contributions: There are a limited number of studies on the application of ordinal regression for modelling the level of family well-being, particularly with covariates involving the demographic and social characteristics of the respondents. This study fills in the gap in the literature where the ordinal regression model provides useful information for policymakers to enhance the status of family well-being in Malaysia via various policy initiatives.   Keywords: Family well-being, Ordinal Regression Model, ordinal data, Proportional Odds Model.   Cite as: Muhammad Sapri, N. A., Ibrahim, K., Abu Bakar, M. A., & Mohd Ariff, N. (2021). Ordinal regression for modelling the family well-being among the Malaysians.  Journal of Nusantara Studies, 6(2), 424-447. http://dx.doi.org/10.24200/jonus.vol6iss2pp424-44

Time series clustering of Malaysia Air quality time series data

Air quality is often associated with the area location and activities where air quality in cities is usually more polluted than in rural areas. This study aims to study the pattern of time series data from air quality stations by performing cluster analysis of air quality station based on the particulate matter 10 micrometres or less in diameter (PM10) and particulate matter 2.5 micrometres or less in diameter (PM2.5) time series data. The clusters obtained from the cluster analysis were compared with the station area category and station location. This study which uses air quality data obtained from the Department of Environment, Malaysia from 5 July 2017 until 30 June 2019, shows five types of air quality patterns in Malaysia. The results also show that none of the clusters is dominated by any station's category. Therefore, it is less appropriate to relate the air quality patterns and the station area category. However, the results show that air quality patterns were related to the station's location, where nearby stations have similar air quality patterns

Wavelet characterizations for investigating nonlinear oscillators

This study investigates the wavelet-based system identification capabilities on determining the system nonlinearity based on the system impulse response function. Wavelet estimates of the instantaneous envelopes and instantaneous frequency are used to plot the system backbone curve. This wavelet estimate is then used to estimate the values of the parameter for the system. Two weakly nonlinear oscillators, which are the Duffing and the Van der Pol oscillators, have been analyzed using this wavelet approach. A case study based on a model of an oscillating flap wave energy converter (OFWEC) was also discussed in this study. Based on the results, it was shown that this technique is recommended for nonlinear system identification provided the impulse response of the system can be captured. This technique is also suitable when the system’s form is unknown and for estimating the instantaneous frequency even when the impulse responses were polluted with noise

Peramalan kualiti udara menggunakan kaedah pembelajaran mendalam rangkaian perlingkaran temporal (TCN)

Kajian ini bertujuan untuk membina model kualiti udara untuk meramalkan kepekatan bahan pencemar udara di Malaysia. Kaedah peramalan yang dipilih dalam kajian ini adalah suatu teknik pembelajaran mendalam iaitu Rangkaian Perlingkaran Temporal (TCN). Set data yang digunakan adalah siri masa zarahan terampai bersaiz diameter lebih kecil atau sama dengan 10 mikrometer (PM10) yang diperoleh daripada Jabatan Alam Sekitar Malaysia dari 5 Julai 2017 hingga 31 Januari 2019. Data daripada lima stesen pemantauan kualiti udara di Semenanjung Malaysia dipilih untuk kajian ini. Bagi tujuan perbandingan, kaedah rangkaian memori jangka pendek panjang (LSTM) juga digunakan dalam kajian ini yang mana ketepatan antara kedua-dua model dibandingkan. Secara amnya, nilai model ramalan daripada kedua-dua model adalah menghampiri data asal. Walau bagaimanapun, model yang dibina dengan kaedah TCN adalah lebih baik berbanding model LSTM dari segi ketepatan nilai ramalan. Kajian ini menunjukkan bahawa TCN merupakan teknik yang sesuai digunakan dalam peramalan data siri masa bagi kualiti udara di Semenanjung Malaysia

Isoprene hotspots at the Western Coast of Antarctic Peninsula during MASEC′16

Isoprene (C5H8) plays an important role in the formation of surface ozone (O3) and the secondary organic aerosol (SOA) which contributed to the climate change. This study aims to determine hourly distribution of tropospheric isoprene over the Western Coast of Antarctic Peninsula (WCAP) during the Malaysian Antarctic Scientific Expedition Cruise 2016 (MASEC′16). In-situ measurements of isoprene were taken using a custom-built gas chromatography with photoionization detector, known as iDirac. Biological parameters such as chlorophyll a (chl-a) and particulate organic carbon (POC) were compared to the in-situ isoprene measurements. Significant positive correlation was observed between isoprene and POC concentrations (r2 = 0.67, p < 0.001), but not between isoprene and chl-a. The hotspots of isoprene over maritime Antarctic were then were investigated using NAME dispersion model reanalysis. Measurements showed that isoprene mixing ratio were the highest over region of King George Island, Deception Island and Booth Island with values of ∼5.0, ∼0.9 and ∼5.2 ppb, respectively. Backward trajectory analysis showed that air masses may have lifted the isoprene emitted by marine algae. We believe our findings provide valuable data set of isoprene estimation over the under sampled WCAP

Regional frequency analysis of maximum daily rainfalls using TL-Moment approach

Analyzing rainfalls data are important in order to obtain the probability distribution of flood. The main aim of the study is to perform regional frequency analysis of maximum daily rainfalls measured over stations in Selangor and Kuala Lumpur by using the TL-moment method with t = 0, t = 1 and t = 2. Initially, the maximum of each daily rainfall for each year were obtained. Then, parameters of every distributions considered including the normal (N), logistic (LOG), generalized logistic (GLO), extreme value type I (EV), generalized extreme value (GEV) and generalized Pareto (GPA) distribution were estimated using TL-moment approach. TL-moments with t = 0 are known as L-moments while TL-moments with and imply TLmoments that are symmetrically trimmed by one and two conceptual sample values respectively. The most suitable distribution were determined according to the mean absolute deviation index (MADI), mean square deviation index (MSDI) and correlation, r. L-moment and TL-moment ratio diagrams provided visual proofs of the results. The L-moment method showed that the generalized logistic (GLO) distribution is the best distribution whilst TL-moment method with t = 1 and t = 2 concluded that the extreme value type I (EV) and generalized extreme value (GEV) distributions are the most suitable distributions to fit the data of maximum daily rainfalls for stations in Selangor and Kuala Lumpur

Regional analysis of annual maximum rainfall using TL-moments method

Information related to distributions of rainfall amounts are of great importance for designs of water-related structures. One of the concerns of hydrologists and engineers is the probability distribution for modeling of regional data. In this study, a novel approach to regional frequency analysis using L-moments is revisited. Subsequently, an alternative regional frequency analysis using the TL-moments method is employed. The results from both methods were then compared. The analysis was based on daily annual maximum rainfall data from 40 stations in Selangor Malaysia. TL-moments for the generalized extreme value (GEV) and generalized logistic (GLO) distributions were derived and used to develop the regional frequency analysis procedure. TL-moment ratio diagram and Z-test were employed in determining the best-fit distribution. Comparison between the two approaches showed that the L-moments and TL-moments produced equivalent results. GLO and GEV distributions were identified as the most suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation was used for performance evaluation, and it showed that the method of TL-moments was more efficient for lower quantile estimation compared with the L-moments

On selection of probability distributions of annual maximum daily rainfalls using TL-moments

Knowledge related to distributions of rainfall amounts are of great impor- tant for designs of water related structures. The greater problem facing hydrologists and engineering is the identification the best distribution form for regional data. The main goal of the study is to perform regional frequency analysis of maximum daily rainfalls selected each year among daily rainfalls measured over stations in Selangor and Kuala Lumpur by using the method of TL-moment. Several distributions were taken into account in this study which include two-parameter normal (NOM), log- normal (LN2), three-parameter lognormal (LN3), logistic (LOG), generalized logistic (GLO), extreme value type I (EV1), generalized extreme value (GEV) and general- ized Pareto (GPA) distribution. The most suitable distribution among the selected distributions was determined according to the mean absolute deviation index (MADI), mean square deviation index (MSDI) and the L-moment ratio diagram. The result of this study showed that the GLO distribution is the most suitable distribution to fit the data of maximum daily rainfalls for stations in Selangor and Kuala Lumpur

Comparisons between the window-based and storm-event analysis

Rainfalls data have been broadly used in researches including in hydrological and meteorological areas. Two common ways in extracting observations from hourly rainfalls data are the window-based analysis (WBA) and storm-event analysis (SEA) approach. However, the differences in the qualitative and quantitative properties of both methods are still vaguely discussed. The aim of studying these dissimilarities is to understand the effects of each approach in modelling and analysis. The qualitative difference is due to the way the two analyses define the accumulated rainfalls for observations which are referred to as rainfall and storm depths, respectively. The repetitiveness of rainfall depths provide nested structure while the storm depths are considered independent. The quantitative comparisons include their statistical and scaling properties that are linked by the self-similarity concept from simple scaling characteristics. If self-similarity concept holds, then the rainfall or storm depths follow simple scaling and the analysis would be simplified. The rainfall depths showed clearer simple scaling characteristics compared to the storm depths. Though the storm depths do not yield self-similarity for a large range of storm duration but the characteristics of simple scaling can be observed for a reduced range of the considered duration. In general, the context of the research and the region of the time interval and duration will be an important aspects to consider in choosing which method is best to use for analyzing the data

Pengitlakan lengkung IDF untuk peristiwa ribut ekstrim di Semenanjung Malaysia

Lengkung keamatan-tempoh-kekerapan (IDF, daripada intensity-duration-frequency) adalah suatu model peristiwa ribut ekstrim yang mampu merumuskan ciri statistik penting dan menggambarkan hubungan antara keamatan, tempoh dan tempoh ulangan sesuatu peristiwa ribut. Tujuan kajian ini adalah untuk mendapatkan suatu taburan serta persamaan IDF teritlak untuk membina lengkung IDF teritlak bagi sebarang stesen curahan hujan di Semenanjung Malaysia. Oleh itu, kajian ini mengenal pasti taburan kebarangkalian terbaik untuk dijadikan taburan teritlak bagi keamatan ribut maksimum tahunan untuk peristiwa ribut di Semenanjung Malaysia menggunakan kaedah momen-L. Seterusnya, dua set lengkung IDF dibina untuk keamatan ribut maksimum tahun di setiap stesen dengan masing-masing menggunakan taburan terbaik bagi stesen tersebut dan taburan teritlak yang dikenal pasti. Kedua-dua set lengkung IDF ini dibandingkan dengan data asal dan antara satu sama lain dengan menggunakan tiga indeks ketepatan padanan, iaitu peratusan pekali variasi punca min ralat kuasa dua, min peratusan perbezaan mutlak dan pekali penentuan. Berdasarkan hasil kajian ini, taburan nilai ekstrim teritlak merupakan taburan terbaik untuk dijadikan taburan teritlak bagi keamatan ribut maksimum tahunan di Semenanjung Malaysia. Selain itu, kedua-dua set lengkung IDF yang dibina didapati sesuai untuk menggambarkan peristiwa ribut ekstrim di Semenanjung Malaysia dan perbezaan antara kedua-dua set lengkung adalah sangat kecil. Oleh itu, pengitlakan lengkung IDF dengan menggunakan taburan dan persamaan yang sama bagi setiap stesen curahan hujan dapat memudahkan pembinaan lengkung IDF di seluruh Semenanjung Malaysia dan membantu dalam pembentukan lengkung IDF di kawasan yang tiada stesen curahan hujan