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AHP approach for employee recruitment with COVID-19 situation in Thailand
(2026-01-01)
Narabin, Akan
;
Boonjing, Veera
;
Wuttanachamsri, Kanognudge
With the COVID-19 situation being unlike the usual, selecting an appropriate person for a job position requires the criteria and weight of each criterion be determined and adjusted to suit the crisis. The criteria chosen in this work are emphasised on selecting applicants who, while studying, have been in the midst of the COVID-19 situation. In this research, we employ analytic hierarchy process to assist the committee to have an agreement. In this study, each person in the committee can have his/her own pairwise comparison matrix of the criteria with a three-level hierarchical model. Some ambiguity may occur when initiating a hierarchical model; therefore, in this work, the criteria used in the three-level model are properly adjusted to create a four-level hierarchical model. The comparison inspected, provide some guidance in both theoretical manner and applications.
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Navigating online learning challenges and educational infrastructure in times of crisis: Insights and solutions among Thai engineering students utilizing a mixed-methods analysis
(2024-01-01)
Sirikasemsuk, Kittiwat
;
Leerojanaprapa, Kanogkan
;
Khwanpruk, Kankanit
The rapid shift to online learning during COVID-19 posed challenges for students. This investigation explored these hurdles and suggested effective solutions using mixed methods. By combining a literature review, interviews, surveys, and the analytic hierarchy process (AHP), the study identified five key challenges: lack of practical experience, disruptions in learning environments, condensed assessments, technology and financial constraints, and health and mental well-being concerns. Notably, it found differences in priorities among students across academic years. Freshmen struggled with the absence of hands-on courses, sophomores with workload demands, and upperclassmen with mental health challenges. The research also discussed preferred strategies for resolution, emphasizing independent learning methods, managing distractions, and adjusting assessments. By providing tailored insights, this study aimed to enhance online learning. Governments and universities should support practical work, prioritize student well-being, improve digital infrastructure, adapt assessments, foster innovation, and ensure resilience.
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A Result Verification of Decision Tree Model for Industrial Wireless Sensors Selection using Analytic Hierarchy Process
(2019-07-01)
Meesawad, Saksiri
;
Thanasopon, Bundit
;
Wongwirat, Olarn
Nowadays, an industrial wireless sensor (IWS) is interested and widely used in a Gas industry in Thailand. There are many vendors trying to improve quality of IWS products for gaining advantage in competitive market. Therefore, choosing the IWS becomes a challenge for users not only the brand name and price but also several factors needed to be considered, e.g., data rate, output power, operating voltage, transmitting current, receiving current, and operating temperature. Selecting the proper IWS is considered as a multi-objective decision problem that is complicated for an engineer and a project manager. The classification method using a Decision Tree)DT(model can be applied to solve such the problem, but the accuracy is depended on the number of historical data. For IWS in the Gas industry in Thailand, not only the number of training and testing data is limited but also there are only a few brands that are chosen regularly. In this paper, the method of applying the DT model for IWS classification and selection is presented. Then, the classification result of the DT model is verified by using an Analytic Hierarchy Process)AHP(for confirming whether it is accurate based on the limit number of historical data. The verification result can be preliminarily ensured that the DT model can be applied as a decision tool for choosing the appropriate IWS accurately.
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Choosing industrial wireless sensor by using analytic hierarchy process
(2017-02-23)
Meesawad, Saksiri
;
Prapawat, Sumet
;
Wongwirat, Olarn
Nowadays, an industrial wireless sensor (IWS) is interested and widely used by various industries. There are many industries trying to adopt qualified IWS products in competitive market for gaining advantage. The challenge in choosing IWS includes not only the price, but also several factors, e.g., operating frequency, data rate, output power, interface, brand, and so on. These factors cause difficulty for decision making by engineers or project managers, since there are a number of factors to choose simultaneously in order to find the optimal IWS to use. In this paper, we propose the method for choosing IWS by using analytic hierarchy process (AHP). The proposed method is suitable for the problems that involve multiple criteria selection simultaneously, as in the IWS choosing problem. The IWS factors used for decision criteria are defined in this work, as well as the model of alternate preferences. The pairwise comparison and scoring metrics are also derived in the process to acquire the result, including the consistency check for the result obtained. The result expressed that the AHP provides the correct decision result. It is rationality and feasibility for choosing the qualified IWS products.

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