Wanitjirattikal, Puntipa

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puntipa.wa@kmitl.ac.th

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An Integrated Factor Analysis-Technique for Order Preference by Similarity to Ideal Solution for Location Decision in ASEAN Region: A Case Study of Thai Fabric Manufacturing Plant
(2023-01-01)
Atthirawong, Walailak
;
Panprung, Wariya
;
Wanitjirattikal, Puntipa
In this paper, we propose an integrated model for selecting a suitable location for fabric manufacturing plants in the ASEAN region. In the first phase, Cambodia, Vietnam and Indonesia were determined as candidate locations for evaluation from the screening process. In this regard, key criteria influencing location decisions were derived using factor analysis of responses extracted from questionnaires. In the second phase, criterion weights were calculated using the rank of centroid (ROC) method. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was then used to prioritize three location alternatives, and sensitivity analysis was also employed to verify the stability of the method. Based on TOPSIS method, Vietnam was the preferred location, followed by Indonesia while Cambodia was not recommended. Sensitivity analysis also showed that the proposed model was valid. The findings from this study provided references for enterprises engaged in international location decision making. The results can help them better understand the decision-making process and identify key criteria that can influence location decisions internationally.
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Simplified Approach to Constructing Coherent Topics and Subtopics from Text Data: A Case Study Using University Reviews
(2024-01-01)
Tunyut, Wuttipong
;
Wanitjirattikal, Puntipa
This study introduces a streamlined framework for analyzing hierarchical topic structures in text data, integrating Latent Dirichlet Allocation (LDA), Word2Vec, Bigram phasing, Doc2Vec, and hierarchical clustering. The method ensures both statistical coherence and practical interpretability while avoiding the complexities of traditional hierarchical topic models. Applied to university reviews from various educational platforms, this data offers valuable insights into user experiences but presents challenges due to its unstructured nature. Our framework reveals key topics and sentiment variations: positive feedback highlights facilities and cultural experiences, while negative reviews emphasize workload, academic challenges, and financial pressures, identifying areas for improvement. This approach is particularly effective for moderately sized datasets with well-defined scopes, such as university reviews, where the subject matter is clearly understood.
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Comparison of Machine Learning Methods for Binary Classification of Multicollinearity Data
(2024-12-02)
Araveeporn, Autcha
;
Wanitjirattikal, Puntipa
This study examines the effectiveness of binary classification performance in multicollinearity. Four machine learning methods, namely backpropagation neural network, Naïve Bayes, support vector machine, and random forest, are compared in terms of their efficiency in handling multicollinear data. The evaluation of binary classification performance efficiency considers multicollinearity in independent variables, considering both a constant correlation model and the Toeplitz correlation. Correlation coefficients of 0.1 and 0.9 are explored in the analysis. The independent variables in this study are simulated from a multivariate normal distribution with 10, 20, 30, and 40 variables, respectively. The dependent variable is constructed using the logit function with sample sizes of 100 and 200. The simulation and data analysis are performed using the R Studio program and repeated 1,000 times for each scenario. The findings of this research reveal that the backpropagation neural network and Naïve Bayes methods exhibit superior performance in determining the mean accuracy percentage under constant correlation. On the other hand, the backpropagation neural network and support vector machine are the most effective methods in determining the mean accuracy percentage when dealing with multicollinearity in the form of Toeplitz correlation.
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Superiority, Non-inferiority, Equivalence Test, and Innovative Equivalence Test
(2021-06-24)
Wanitjirattikal, Puntipa
In pharmaceutical and medical studies, randomized controlled trials (RCTs) aim to prove that a new treatment has better or superior efficacy than standard treatment or placebo. In fact, RCTs can also be used to evaluate the efficacy of a new treatment having similar or equivalence efficacy, or not worse or non-inferior efficacy depending on the objectives of the research. Meanwhile, the non-inferiority trials are more frequently found in research. However, the equivalence trials are another efficacy that RCTs would like to know sometimes. The purposes of this article are to provide a basic understanding for readers about the distinctions among the types of research, statistical hypothesis testing, the interpretation of hypothesis testing as well as the differences between statistical significance and clinical significance and also introduce an innovative equivalence test calls 2-df for shift-scale equivalence test.
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Genetic Differentiation and Population Structure of the Freshwater Snail Rivomarginella morrisoni (Gastropoda: Marginellidae) in Central and Southern Thailand
(2026-03-01)
Subpayakom, Navapong
;
Wanitjirattikal, Puntipa
;
Dumrongrojwattana, Pongrat
;
Poeaim, Supattra
Rivomarginella morrisoni (Gastropoda: Marginellidae) is a narrowly distributed freshwater snail inhabiting drainage basins of central and southern Thailand. To clarify patterns of genetic differentiation across its range, 45 individuals from 11 sites across eight river basins were analyzed using two dominant molecular markers: sequence-related amplified polymorphism (SRAP) and inter-simple sequence repeats (ISSR). SRAP primers produced higher polymorphic information content (PIC) values than ISSR primers (0.35 vs. 0.27). Analysis of molecular variance (AMOVA) revealed strong population structure, with 80.29% of the genetic variation occurring among populations and 19.71% within populations Population differentiation statistic (PhiPT) = 0.803, p < 0.001). Unweighted Pair Group Method with Arithmetic mean (UPGMA) and principal coordinate analysis (PCoA) consistently separated central and southern populations, and STRUCTURE supported K = 2 as the most likely number of clusters. Similarly, principal component analysis (PCA) of morphological traits also distinguished specimens into two groups corresponding to these geographic regions, confirming region-specific divergence. Overall, the genetic and morphological patterns indicate restricted gene flow among basins and a clear separation between central and southern lineages of R. morrisoni. This study provides the first molecular evidence of population structure in this species and offers important baseline information for future taxonomic, ecological, and conservation research on freshwater marginellid snails.

Wanitjirattikal, Puntipa

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