Science and Technology Nakhon Sawan Rajabhat University Journal

Stock Price Forecasting using SARIMA Time Series

Salman Saleng — 2026-04-16

This article presents stock price forecasting using SARIMA time series analysis, which is suitable for seasonal data. The study utilizes daily closing prices of CP All Public Company Limited (CPALL) stock from 2014 to 2024. The analysis process includes data collection, data formatting and cleaning, exploratory data analysis, and the creation and testing of the SARIMA model using Python on Google Colab. The research findings indicate that the SARIMA(0,1,1)(0,0,2,12) model can effectively forecast stock price trends with an RMSE of 6.226 baht, which represents a low average deviation between forecasted and actual prices. This reflects the accuracy of the model in capturing stock price trends. These research findings can effectively support long-term investment decision-making.

Diurnal Variations and Morphology of PM2.5 During Haze Period in Mueang Nakhon Sawan District, Nakhon Sawan Province

Anuwat Sangon — 2026-04-23

This research investigates the diurnal variations and morphology of PM2.5 during the haze period in Mueang Nakhon Sawan District, Nakhon Sawan Province. PM2.5 concentration and meteorological data were retrieved from the Pollution Control Department (PCD) database and the Meteostat website for the period of March–April 2025. Concurrently, PM2.5 samples were collected for morphological and elemental composition analysis via scanning electron microscopy. The results indicated that PM2.5 levels exhibited diurnal variations corresponding to agricultural residue burning and heavy traffic during rush hours. Correlation analysis with meteorological data suggested that atmospheric stability significantly influenced the accumulation and dispersion of PM2.5. Morphological and elemental analysis identified biomass burning, fossil fuel combustion, and long-range transport as the primary sources of PM2.5. Furthermore, two carcinogenic heavy metals—mercury (Hg) and chromium (Cr)—were detected within the PM2.5 samples.

A Study of Factors Affecting the Severity Level of Motorcycle Accidents in Bangkok

Patsornnat Yaempuang — 2026-06-23

According to road accident statistics in Thailand, Bangkok consistently reports the highest number of accidents each year. Most of these accidents involve motorcycles, reflecting the high risk associated with motorcycle use, which tends to result in more severe accidents compared to other types of vehicles. The objective of this research is to examine the factors affecting the severity level of motorcycle accidents in Bangkok, using multinomial logistic regression. The data for this study were obtained from the Ministry of Transport's accident reporting system, covering the period from 2019 to 2023. Eight factors were analyzed: the date of the accident, the time of the accident, the location of the accident, traffic rule violations, environmental conditions, characteristics of the accidents, weather conditions, and the parties involved. The severity of the accidents is classified into four levels: no injury, minor to moderate injury, severe injury, and death. The results indicate that six factors affect the severity level of motorcycle accidents in Bangkok: the date of the accident, the time of the accident, the location of the accident, environmental conditions, characteristics of the accidents, and weather conditions. Furthermore, the researcher proposes various measures and recommendations to enhance road safety and reduce the risk of motorcycle accidents in Bangkok.

Assessment of Urban Heat Island Severity from Land Use Changes Using Multi-temporal Landsat Data in Nakhon Ratchasima Municipality

Sunsanee Maneechot — 2026-06-23

Nakhon Ratchasima Municipality has experienced continuous urban expansion, resulting in significant changes in urban thermal dynamics. This study aimed to (1) examine land surface temperature (LST) dynamics between 2014 and 2024 and (2) assess the intensity of the Urban Heat Island (UHI) phenomenon using the Urban Thermal Field Variance Index (UTFVI). Landsat 8 OLI/TIR and Landsat 9 OLI-2/TIRS-2 imagery were employed for multitemporal analysis. The results revealed that built-up areas expanded from 85.63% in 2014 to 89.15% in 2024, while agricultural and forest areas declined. Higher LST values were strongly associated with dense urban zones and post-harvest agricultural lands, where bare soil contributed to heat accumulation. UTFVI indicated a bimodal distribution, with None accounting for about 44–48% and Strongest accounting for 26–33% of the study area across all years. However, a slight decrease in Strongest areas was observed over time, while the share of intermediate levels (Weak–Middle–Strong) increased, suggesting the spatial diffusion of heat from urban cores to surrounding areas. This study demonstrates that LULC change directly influences the intensity and spatial distribution of UHI. The findings provide useful implications for urban climate adaptation strategies, particularly in promoting urban greening, managing post-harvest agricultural lands, and integrating sustainable urban planning measures to mitigate heat stress in tropical cities under climate change.

Design of an Experimental Procedure for Measuring Liquid Surface Tension Using the Pendant Drop Method and Tracker Software

Vitchuda Suknui — 2026-06-28

This research aimed to: (1) design an experimental procedure for measuring the surface tension of liquids, suitable for resources and budget limitations, (2) apply image analysis technology using Tracker software, and (3) evaluate the developed experimental setup’s feasibility and accuracy for future practical implementation in science education. The study focused on measuring the surface tension of water and vegetable oil using the Pendant Drop Method. The research process consisted of two main steps: (1) designing an experimental setup for capturing images of liquid droplets, and (2) analyzing the shape of the droplets from the captured images by applying Tracker software to measure relevant parameters and calculate surface tension using the Young–Laplace equation. The results demonstrated that: (1) the developed experimental setup was capable of capturing clear images of liquid droplets while employing low-cost equipment and aligning well with resource limitations; (2) the application of Tracker for image analysis effectively enabled the measurement of relevant parameters and the calculation of liquid surface tension using the Young–Laplace equation, with the obtained values showing trends consistent with the standard values of water and vegetable oil; and (3) the experimental procedure is suitable for instructional implementation, as it involves non-complex steps and yields measurement errors within acceptable limits.

Development of a web application for recommending Buddhist attraction tourism based on tourist behavior in Phra Nakhon District, Bangkok

Phattaramon Klaasa — 2026-06-28

The objective of this research is to develop and evaluate the effectiveness of a web-based application for recommending Buddhist tourism attractions based on tourist behavior in Phra Nakhon District, Bangkok, Thailand. The research methodology includes review of relevant documents and field surveys to collect data on Buddhist tourist attractions. The data obtained from the in-depth interview was used to analyze problems and user requirements for the web application. The web application was developed using HTML, CSS, and JavaScript with Microsoft Visual Studio Code. The recommendation system was designed based on the concept of content-based recommendation to support the presentation of tourism information that aligns with individual user behavior. The evaluation of the web application’s effectiveness was conducted using questionnaires to collect data from a sample group consisting of 400 technical experts and tourists. Data analysis uses descriptive statistics, including mean and standard deviation. The results show that the web application for recommending Buddhist attraction tourism consists of 5 subsystems: tourist attraction management system, public relations system, tourist information management system, tourist attraction search and filtering system, and review and rating system. The evaluation results across three aspects found that the majority of the sample group gave high scores in all aspects, ranked by average scores from highest to lowest as follows: usability efficiency (𝑥̅ = 4.47, S.D. = 0.61), content accuracy (𝑥̅ = 4.41, S.D. = 0.59), and design (𝑥̅ = 4.40, S.D. = 0.61).

Development of a Solar Dryer for Jew's Ear Mushroom with Internet of Things Technology to Promote the Processing of a Mushroom Farming Community Enterprise Group

Pipop Maneejamnong — 2026-06-29

This study aimed to design, develop, and evaluate the efficiency of a solar dryer for Wood Ear mushroom (Auricularia spp.) controlled by Internet of Things (IoT) technology, in order to address processing limitations and promote value-added production for a mushroom-farming community enterprise in Thung Si Thong Subdistrict, Nan Province. A research and development (R&D) approach was adopted. A greenhouse-type dryer using forced convection which is automatically regulated by an ESP32 microcontroller together with an AM2305 sensor to maintain suitable drying conditions. The efficiency was assessed through a comparative experiment between an experimental group (the developed dryer) and a control group (traditional open-sun drying), using fresh mushrooms with an initial weight of 1,000 g. The experiment was repeated by three trials. The results showed that the developed dryer performed markedly better than the traditional one. The average drying rate of the proposed dryer was 103.1 g/h compared with only 49.2 g/h for open-sun drying, and reduced the mushroom weight by an average of 72.2%, whereas open-sun drying reduced it by only 34.4% within a 7-hour duration. This superior performance resulted from the proposed dryer's ability to generate a higher average internal temperature of 53.8°C — above the average ambient temperature of 35.7°C — while maintaining a lower average relative humidity (59.7% RH versus 66.5% RH). In addition, the dried products from the dryer exhibited better physical quality in terms of color, shape, and cleanliness. In conclusion, the developed IoT-controlled solar dryer is a highly effective technology that can shorten production time, reduce weather-related risks, and enhance product quality, making it a highly suitable tool for adding value and strengthening the economic resilience of community enterprises in a sustainable manner.

Enhancing the Potential of Elderly through Online Social Networks in Lum Khao Subdistrict, Khok Samrong District, Lopburi Province

Doungporn Maiprasert — 2026-06-29

This research aimed to: (1) enhance the potential of older adults through online social networks in Lum Khao Subdistrict, Khok Samrong District, Lopburi Province; (2) evaluate the online social media usage skills of older adults in Lum Khao Subdistrict, Khok Samrong District, Lopburi Province; and (3) assess the satisfaction of older adults in Lum Khao Subdistrict, Khok Samrong District, Lopburi Province. The sample group consisted of 20 older adults from Ban Lum Khao Community, Lum Khao Subdistrict, Khok Samrong District, Lopburi Province, selected through purposive sampling. The research instruments included: (1) an online social networking platforms; (2) a satisfaction assessment from for services provided to older adults in Lum Khao Subdistrict, Khok Samrong District, Lopburi Province; and (3) a skills assessment form for older adults’ use of online social networks in Lum Khao Subdistrict. Data were analyzed using mean and standard deviation. The research findings revealed that 1) Older adults were able to effectively use online social media to communicate with their children and relatives, as well as to generate additional income for themselves and their families. 2) The skill assessment results indicated that the online social network usage skill scores of older adults in Lum Khao Subdistrict ranged from 20 to 32 points, equivalent to 57.14% - 91.42%. 3) The satisfaction assessment showed that older adults’ satisfaction with learning to use online social media was at the highest level, with a mean score of 4.54 and a standard deviation of 0.55.

Forecasting PM2.5 Concentrations in Nakhon Sawan Province Using Machine Learning, Deep Learning, and Prophet-Based Hybrid Models

Thiraphat Meesumrarn — 2026-06-30

Particulate matter with an aerodynamic diameter of less than 2.5 microns (PM2.5) in Nakhon Sawan Province is an important environmental and public health issue. PM2.5 concentrations vary seasonally and are influenced by several air pollution and meteorological factors. This study aimed to compare the performance of baseline models, machine learning models, deep learning models, and Prophet-based hybrid models for daily PM2.5 forecasting in Nakhon Sawan Province. The study used secondary data collected from January 2020 to December 2025, consisting of PM2.5 concentrations and ten air pollution and meteorological variables. The data were divided chronologically into a training set from 2020 to 2023, a validation set from 2024, and a test set from 2025. Forecasting performance was evaluated for 1-, 3-, and 7-day-ahead horizons by comparing Persistence, Moving Average, Prophet, LSTM, GRU, XGBoost, Prophet-LSTM, Prophet-GRU, and Prophet-XGBoost models. The models were assessed using RMSE, MAE, MAPE, and , together with the classification of days when PM2.5 concentrations exceeded 50 µg/m³. The results showed that GRU achieved the best performance for 1- and 3-day-ahead forecasting, with RMSE values of 12.2476 and 18.4001, respectively. In contrast, Prophet achieved the best performance for 7-day-ahead forecasting, with an RMSE of 20.5216. These findings indicate that the most suitable forecasting model may vary depending on the forecasting horizon. Comparing multiple groups of models provides a clearer understanding of the strengths and limitations of each approach. The findings can support the development of forecasting tools and local PM2.5 monitoring systems.

Analysis of the Angular Velocity of a Spinner using Smartphone-Based Measurement

Nichawee Sangsen — 2026-04-16

Rotation is a fundamental topic in physics education at both secondary and university levels, helping students understand the concepts of torque, moment of inertia, and angular velocity. However, students often encounter difficulties in linking theoretical models with the actual behavior of systems subject to rotational damping. This article presents a study on the decrease in angular velocity of a modified spinner using a smartphone as a measuring device through its gyroscope sensor to explain the mechanism of rotational damping torque and enhance the empirical understanding of the theoretical model. The experimental results show that the angular deceleration exhibits distinct behaviors between the high and low angular velocity ranges. In the high angular velocity range, the decrease follows an exponential relationship, reflecting the influence of linear damping torque caused by air resistance and internal bearing friction. In contrast, in the low angular velocity range, the decrease is nearly linear, consistent with constant frictional torque. The analysis reveals a transition between these two damping mechanisms and suggests that this phenomenon can be effectively used as a case study to help students connect theoretical models with real experimental observations in rotational dynamics.