This study examined the effects of calcium oxide (CaO) and natural zeolite (NZ) catalysts on the pyrolysis of palm kernel shell (PKS) to improve conversion efficiency and bio-oil quality. A 300 g sample of PKS was pyrolyzed in a stainless-steel reactor at 500 oC under four conditions: non-catalytic, CaO-catalyzed, NZ-catalyzed, and dual-catalyst (CaO‒NZ). The results showed that both CaO and NZ significantly affected the yields of bio-oil, non-condensable gas (NCG), and char. CaO enhanced cracking to produce lighter bio-oils (C2-C6), whereas NZ acted mainly on heavy intermediates; this upgrading produced both heavier condensed oxygenates and light fragments that remain non-condensable, leading to the highest NCG yield. The catalysts had little effect on bio-oil density but influenced viscosity, pH, and heating value. The dual catalyst produced bio-oil with improved properties: density 980 kg/m3, viscosity 1.63 cSt, pH 4.1, and heating value 30.76 MJ/kg. Mechanistically, CaO promoted cracking into lighter hydrocarbons (C2–C6), whereas NZ favored oligomerization, forming heavier molecules. In combination, CaO suppressed the oligomerization effect of NZ, giving a molecular distribution similar to CaO alone. Although the overall phenolic content changed only slightly, the catalysts significantly altered the ratio of simple to complex phenols. In addition, the dual catalyst facilitated the conversion of esters into ketones, further enhancing bio-oil composition.
Indonesia is known as a disaster-prone region. Located on the Pacific Ring of Fire, it is one of the countries most susceptible to various types of natural disasters. The province of Aceh is one of the regions in Indonesia that frequently experiences earthquakes due to its geographical location in a highly seismically active area. Therefore, an analysis of earthquake data clustering in the province of Aceh is necessary. The aim of this research is to determine earthquake clusters, which can be used for disaster mitigation and prevention measures. This research begins with examining the distribution pattern of data through a scatterplot. If the data distribution pattern shows varying density levels, then a clustering analysis using Ordering Points to Identify the Clustering Structure (OPTICS) is conducted. In the OPTICS algorithm, two parameters are required before clustering: minimum points (MinPts) and xi. The clustering results are evaluated using the silhouette coefficient (SC). Further data exploration is carried out by: (1) reducing the MinPts value, (2) clustering based on the supremum of the SC, and (3) identifying earthquake events with potential tsunami risks. The purpose of this data exploration is to increase the number of clusters formed while still considering the SC value limit, thus expanding the regions identified as earthquake-prone. The best clustering results are determined by comparing the obtained clusters. The best clustering result was found at MinPts = 20 and xi = 0.05, forming 4 clusters with a silhouette coefficient value of 0.72, indicating a strong cluster structure. This information is expected to benefit the public by raising awareness of earthquake-prone areas.
Hauling rocks or minerals in open-pit mines often experience inefficiencies due to a lack of real-time monitoring and assignment of dump trucks, resulting in reduced productivity and error prone manual data recording. This study evaluates the impact of the Fleet Management System (FMS) on dump truck productivity and discrepancies in gold grade data using four data sources: manual production data, block model data, raw FMS data, and geological sampling data from the processing plant. Key productivity metrics including payload, job efficiency, fixed time, and truck speed were analyzed along with comparisons of gold grade data between Ore Movement and Ore Crusher datasets. Results showed a 15% productivity increase for the CAT773 dump truck (from 147 BCM/km to 169 BCM/km) and a 15.6% rise for the CAT745 (from 96 BCM/km to 111 BCM/km). Additionally, the discrepancy in gold grade decreased by 5.3%, achieving a tonnage difference of 0%. Statistical analysis via a paired t-test confirmed significant improvements (p-value < 0.05). The FMS implementation significantly enhances productivity and gold grade data accuracy in mining material transport, driven by improvements in payload, job efficiency, fixed time, and truck speed.
This study investigates the influence of CNC router machine parameters on wood surface roughness during engraving operations. Surface roughness directly affects paint adhesion, appearance, and quality of finished wood products. The main problem is that current machining practices use the same parameters for all wood types, leading to inconsistent surface quality. The objective is to find optimal cutting parameters for different wood species using the Taguchi method. Three wood types were tested: Merbau (hardwood), Pine (softwood), and Plywood (manufactured wood). The experiment used a CNC Router Z2-1325 with three parameters at three levels each: spindle speed (5,000-10,000 rpm), feed rate (100-300 mm/min), and depth of cut (3-9 mm). The Taguchi L9 orthogonal array design was used, requiring only nine experimental runs. Surface roughness was measured using a Mitutoyo Surftest SJ-210 portable tester. Results showed that different wood types require different optimal parameters. Merbau achieved the best surface finish (Ra = 2.093 μm) with 8,000 RPM spindle speed, 200 mm/min feed rate, and 9 mm depth of cut. Pine performed best (Ra = 4.318 μm) at 8,000 rpm, 100 mm/min, and 3 mm depth. Plywood achieved Ra = 2.093 μm at 8,000 rpm, 200 mm/min, and 6 mm depth. Statistical analysis showed that depth of cut was most important for Pine (p = 0.014), while 8,000 rpm was consistently optimal across all wood types. The optimization approach improved surface quality by 20-35% compared to standard practices. This study provides the systematic comparison of CNC machining parameters across hardwood, softwood, and manufactured wood categories. The findings give manufacturers practical guidelines for achieving better surface quality while reducing costs in wood processing industries. The Taguchi method proved effective for optimizing multiple parameters simultaneously with minimal experimental effort.
The growing need for renewable energy and effective waste management has encouraged the development of microbial fuel cells (MFCs), which convert organic waste into electricity. This study investigates electricity generation from food waste leachate, specifically rice slurry, using a dual-chamber MFC. The anode chamber was filled with rice slurry as the substrate, while the cathode chamber contained water with potassium permanganate as the oxidizing agent. Experimental trials were conducted under three conditions: (i) electrode comparison between copper and carbon graphite plates, (ii) temperature variations at room temperature and direct sunlight, and (iii) addition of potassium ferricyanide in the anode and potassium permanganate in the cathode chambers. Performance was evaluated by monitoring voltage, current, and power output across 10 days. Results showed a peak voltage of 137 mV, current of 1.37 mA, and maximum power of 0.1877 mW using graphite electrodes on Day 5. Elevated temperatures enhanced microbial activity and energy generation, while chemical additives improved electron transfer and redox efficiency. These findings demonstrate the potential of MFCs to provide dual benefits of renewable energy generation and sustainable waste reduction, supporting scalable eco-friendly energy solutions.
This study analyses the factors influencing the implementation of sustainable safety and health practices within the Nigerian oil and gas industry. Basically, the study focused on examining organizational commitment, communication strategies, training programs, cultural factors, and human behaviour regarding safety and health practices. This research used a quantitative methodology and questionnaires was administered to 330 experienced employees within the oil and gas industry in the Niger Delta region of Nigeria who were purposefully selected as respondents. SPSS, a social sciences statistical tool was used for data analysis using descriptive statistics and structural equation modelling to establish relationships among the identified variables. The research findings point to the fact that cultural factors and human behaviour have a direct impact on safety practices, considering that the coefficient was found to be β = 0.54 and p < 0.05 indicates a strong significant relationship. On the other hand, communication strategies indicated a positive but insignificant effect on safety practices with β = 0.20 and p > 0.05 respectively while training programs also depicted a positive but insignificant effect with β = 0.05 and p > 0.05 respectively. This shows that while they are essential, communication and training alone cannot develop a healthy safety culture in the organization. Thus, the study concludes that cultural factors and human behaviour become the most significant factors influencing sustainable safety and health practices. Hence, it is suggested that organizations should pay more attention to the development of safety culture in compliance with cultural norms and values besides improving communication and training activities to be more appealing to the workers. Future training programs should include cultural sensitivity to remind the workers of safety measures adequately.
This study evaluates the influence of surface meteorological data on the dispersion of Total Suspended Particulates (TSP) emitted from a Medium Density Fiberboard (MDF) factory in Southern Thailand using AERMOD model. Meteorological inputs from two nearby stations, Khohong and Sadao, were applied to simulate emissions from six stacks and predict concentrations at 15 receptors within a 10 km radius during 2020–2023. The results demonstrated that Sadao data generated higher localized concentrations due to weaker winds and more stable atmospheric conditions, whereas Khohong data produced wider dispersion plumes with lower ground-level concentrations under stronger mixing. Despite these differences, all predicted values complied with Thailand’s National Ambient Air Quality Standards (NAAQS) (24-hour: 200 µg/m3; annual: 80 µg/m3). Model validation indicated moderate agreement with observations, highlighting both the capability of AERMOD for regulatory applications and the sensitivity of outcomes to meteorological inputs. The findings underscore the importance of selecting appropriate meteorological stations in tropical monsoon climates to ensure accurate and representative air quality assessments.
Coal mining operation at Sesayap field, Tana Tidung Regency, North Kalimantan Province, Indonesia lies on material soil, sandy clay, claystone and claystone intercalated sandstone and siltstone. The sliding was occurred on soil and loose sandy clay in October 2022, which caused mining infrastructure and financial losses. The objective of this research is to characterize soft rock lithology and its implication to slope stability. The analysis for soft rock material use RQD, SPT, UCS, water content, mineralogy and cohesion. Material characteristic result: RQD average for sandy clay 1.41%, claystone 56.14%, claystone intercalated sandstone 70.80%; water content average for sandy clay 46%, claystone 9%; mineralogy composition for sandy clay quartz 65%, kaolinite 6%, ilit 28%; UCS average data: sandy clay 0.005 Mpa, claystone 0.47 MPa, claystone intercalated sandstone and carbonaceous 1.32 MPa; refer to ISRM 1981 all lithology classified to soft rock. Unit weight for soil 1.53 Kg/m3, sandy clay 1.47 Kg/m3, claystone intercalated sandstone-siltstone 1.94 Kg/m3; cohesion average for soil 6.30 kPa, sandy clay 12.32 kPa, claystone intercalated sandstone 77.14 kPa. Single slope geometry for soil: bench height 5m, slope 200; sandy clay bench height 7m, slope 200; claystone intercalated sandstone-siltstone bench height 10 m, slope 550. Over all slope stability analysis: slope model 1, total height 58m, over all slope 250, berm between sandy clay and claystone is 10m, FS static 1.019; slope model 2, total height 58m, over all slope 240, berm between sandy clay and claystone is 20m, FS static 1.102; slope model 3, total height 58m, over all slope 220, berm between sandy clay and claystone is 30m, FS static 1.194; slope model 4, total height 58m, overall slope 210, berm between sandy clay and claystone is 40m, FS static 1.314.
Monitoring chemical properties in liquid samples, such as pH, glucose, and protein concentration, is essential in applications ranging from environmental water analysis to early-stage healthcare diagnostics. Multi-parameter test strips offer a commonly used and straightforward method for assessing these parameters in liquid samples, particularly in urine analysis. However, observer-dependent variability was noted in the interpretation of color changes, indicating potential bias among different evaluators. This study proposes a low-cost and accessible sensing method by integrating paper-based colorimetric sensing with image processing and supervised machine learning models to enhance the assessment using reagent test strips. Paper test strips were used as the medium for capturing chemical reactions., with color changes recorded using a PhotoBox equipped with a microcomputer and a Raspberry Pi camera. Extracted color features, such as Red (R), Green (G), Blue (B), Grayscale, Hue (H), Saturation (S), and Value (V) were used as inputs for predictive models, including Random Forest Regressor (RFR), Support Vector Regression (SVR), Gradient Boosting Regressor (GBR), Linear Regression (LR), K-Nearest Neighbors (KNN), and Multi-Layer Perceptron Neural Network (MLP-NN). Experimental results demonstrate that the proposed approach can accurately predict target values with strong predictive performance, achieving R² scores exceeding 0.90 in several models. Outlier handling and hyperparameter optimization were also conducted to improve prediction performance. These results suggest that this accessible and portable approach has significant potential for precise, scalable chemical assessment of multiple parameters (pH, glucose, and protein content) in liquid samples, supporting reliable monitoring in both environmental and healthcare-related applications.
Due to the irregular availability of solar energy, the increment in the effective working period of the distillation process is a big challenge. Since nanofluids are highly efficient heat transfer carriers for harvesting solar energy to be used in the solar distillation process. Therefore, the present research work has been carried out to analyze the productivity of single slope solar still using two different nanofluids of Al2O3 and CuO along with base fluid (water). In this experiment, the comparison of the performance of solar stills at 2cm water depth without and with Al2O3 nanofluid, as well as CuO nanofluid of 0.2% concentration in a floating cylinder of silver (Ag), has been done. The results show that the nanofluids enhance the evaporation rate and the distillate output as 505ml and 650ml using Al2O3 and CuO nanofluid, respectively while without nanofluid, the output was 265 ml. It has also been found that solar still with CuO nanofluid in Ag cylinder has greater solar still efficiency than solar still with Al2O3 nanofluid and without any nanofluid.
Heavy metal pollution has posed a significant threat to environmental and human health. In this work, activated carbon synthesized from shrimp shells through KOH activation was employed as an adsorbent for Fe³⁺ ion removal from aqueous solutions. The material was characterized using X-ray diffraction, scanning electron microscopy, and N₂ adsorption/desorption analysis. Batch adsorption experiments were conducted to assess the adsorption capacity of the activated carbon, while the effects of initial ion concentration, contact time, pH, and adsorbent dosage were analyzed using Response Surface Methodology. The results showed that the adsorption process followed pseudo-second-order kinetics, indicating a chemisorption mechanism. While the Langmuir isotherm effectively described the adsorption behavior. The results also showed that a maximum removal efficiency of 72.31% was achieved at the optimal conditions (19.131 mg/L initial concentration, pH 6, and 130.394 minutes). The findings revealed that shrimp shell–derived activated carbon displayed strong adsorption efficiency for Fe³⁺ ions. This study contributes to the development of eco-friendly and cost-effective materials for heavy metal removal and underscores the significance of utilizing waste materials for value-added purposes in the field of environmental science and engineering.
The continuous growth of the global population, urbanization and industrialization has led to a steep increase in worldwide energy demand, exerting immense pressure on conventional fossil fuel reserves. Fossil fuels currently dominate the global energy mix but are associated with severe environmental challenges such as greenhouse gas emissions, global warming and air pollution, highlighting the urgent need to explore sustainable and alternative energy sources. In response, renewable and sustainable energy resources have emerged as viable alternatives. Among these, biomass stands out as an abundant, carbon-neutral and renewable resource capable of producing valuable biofuels and bio-products. This review focuses on biomass availability, classification, composition, conversion pathways and the role of torrefaction and pyrolysis in producing energy-dense solid fuel biochar. The physicochemical characterization of biochar, its testing standards and its comparative performance with coal are discussed in detail. The paper further explores the applications of torrefied biomass, including its use as a co-firing agent in thermal power plants, feedstock for gasification and briquetting and a sustainable substitute for fossil coal in industrial and domestic heating. Moreover, the challenges and opportunities in biomass valorization are analyzed, emphasizing emerging opportunities in circular economy integration and decentralized energy systems. The study also identifies research gaps, particularly in optimizing process parameters for consistent biochar quality, developing cost-efficient torrefaction technologies and establishing standardized testing and classification methods. Overall, this review highlights the importance of optimizing thermochemical conversion processes to improve biochar yield and quality, contributing to clean, sustainable and circular bioenergy systems.
The Pulau Pangkor plant is one of five small-scale incinerators in different locations in Malaysia. Due to the influence of waste components on the physical and chemical properties of resulting municipal solid waste incineration ash, fly ash (MSWI-FA) and bottom ash (MSWI-BA), the ash of each plant needs to be studied separately. Therefore, this study aims to investigate the effect of using Pulau Pangkor MSWI-FA as a supplementary cementitious material and MSWI-BA as a partial replacement for fine aggregate on mortar performance. Several experiments were conducted to evaluate the material properties, as well as the properties of fresh and hardened mortars, using 5-20% MSWI-FA and 5-25% MSWI-BA replacement ratios. The inclusion of MSWI-FA increased mortar flow by up to 16%, whereas the addition of 25% MSWI-BA reduced flow by up to 76% relative to the control mix. Replacing cement with MSWI-FA reduced compressive strength by 6%–26% across the range of replacement levels, due to MSWI-FA's lack of pozzolanic properties. The results also indicated that lower ash density significantly reduced the resulting mortar density by up to 23%. The higher water absorption of MSWIA also increased the mortar's absorbency; the effect of MSWI-BA was higher. In conclusion, this work provides important insights into the future applications of MSWIA in contexts requiring lightweight, highly absorbent additives with low compressive strength.
Pond ash, a residue generated from thermal power plant operations, presents significant environmental challenges and land management issues in its disposal. Lime sludge is also a by-product of water softening and paper mill industries, with few applications in the agriculture and construction industries. This study investigates the influence of the dosage of lime sludge on the mechanical, chemical and microstructural properties of pond ash for its applications as filler material. This research considered lime sludge dosage in 5%, 10%, 15%, and 20% as the variable. The optimum moisture content was evaluated for all dosages using compaction tests. The unconfined compressive strength of the samples after 7 days,14 days and 28 days was assessed to determine the optimum dosage. Unconfined compressive strength tests demonstrated significant strength improvements, with values rising from 67 kPa for untreated pond ash to 149 kPa at 7 days, 296 kPa at 14 days, and 386 kPa at 28 days, identifying 15% lime sludge as the most effective dosage. To study the microstructural characteristics of the lime sludge stabilised pond ash, FTIR, XRD and SEM analysis were conducted. Results show that lime sludge significantly improves pond ash's strength, making it a suitable filler material for geotechnical applications like embankments, pavement subgrades, and backfill materials. This research highlights the effectiveness of lime sludge as an economical and sustainable stabilizing agent for the practical use of pond ash.
Gas turbine blades operate under extreme thermal and mechanical loads, requiring efficient cooling strategies and materials with high-temperature resistance. This study presents a comparative thermal and structural analysis of blades made from Ti-T6, Haynes 188, and X-40 using finite element analysis (FEA). Blade models with 8, 12, and 16 radial cooling holes were developed in SolidWorks and analysed in ANSYS 2023 R1 under steady-state conditions from 800 °C to 1600 °C. Thermal performance was evaluated through temperature distribution, while structural behavior was assessed using deformation, strain, and stress. Results showed that additional cooling holes reduced blade temperature, with Ti-T6providing the best thermal performance but exhibiting higher deformation and strain due to its lower stiffness. Haynes 188 and X-40 demonstrated greater structural stability, with X-40 maintaining the most uniform stress distribution. Overall, X-40 offers the best balance between cooling efficiency and structural integrity, making it a promising choice for advanced turbine blade applications.
As large-scale construction projects continue to expand in Bangladesh, the use of batching plants for large-scale concrete production is on the rise. Ensuring the quality and workability of concrete has become increasingly vital, particularly as mass concrete is used for casting. Multiple destructive and non-destructive techniques are utilized to evaluate or estimate the in-situ strength of concrete. Common destructive testing methods include the following tests which are commonly employed to assess concrete strength: splitting tensile strength test, compressive strength, concrete core, bending strength, impact test, semi destructive testing method includes pullout test and Non-destructive techniques, on the other hand, include shock pulse measurement, ultrasonic wave propagation, and maturity testing. The maturity method, which estimates concrete strength during the early curing stages, is a widely accepted indirect approach. This method relies on the concrete's internal temperature, which corresponds to the heat produced by the chemical curing process. While most studies to date have focused on maturity models under controlled laboratory conditions, where temperature and curing are regulated, a significant gap remains in research regarding the application of these models in batching plant trial mixes. In such conditions, environmental variables such as air/wind speed, humidity and ambient atmospheric temperature and can fluctuate significantly, influencing the maturity of the concrete. In most existing calculations, external variables like humidity and ambient atmospheric temperature are often disregarded. This study aims to address these environmental parameters and offers a more precise prediction of concrete strength development in real-world conditions by using a complex maturity model, developed in accordance with ASTM C1074. This model considers ambient temperature, relative humidity, wind speed, and introduces coefficients that reflect the impact of each factor. The incorporation of wind velocity into the maturity equation is an innovative aspect of this study to the best of the author’s knowledge. After including wind velocity, the complex maturity approach achieved a coefficient of determination R² = 0.9326, nearer to R² values for standard (ASTM C1074‑2019) maturity method which is 0.9694, demonstrating its enhanced reliability aligned with traditional maturity methods. The findings show an inverse relationship between evaporation rate and slump, a key discovery for optimizing the workability of concrete under fluctuating environmental conditions. The evaporation rate was determined using a nomograph found in ACI publications. In conclusion, the study highlights the practical application of the advanced maturity method in large-scale construction projects in Bangladesh.As most previous research has focused on controlled laboratory environments, this method not only allows for an accurate assessment of concrete strength but also optimizes curing time, ultimately improving economic efficiency throughout the construction process.
Conventional concrete has limitations in tensile strength and crack control. Fiber-reinforced concrete improves these properties, but single fiber types can hinder performance. While steel fibers are common, synthetic and natural fibers are gaining traction due to their cost-effectiveness, performance, and eco-friendliness. This research explores hybrid fiber concrete using micro synthetic (polyamide, 12 mm, 0.06% fiber volume fractions) and natural ramie (19 mm, 0.25%, 0.50%, 0.75% by cement weight) fibers to enhance mechanical performance. Five mix designs (V1-V5) were evaluated for compressive strength, splitting tensile strength, and modulus of elasticity at 28 days. Results showed that plain concrete (V1) had the highest compressive strength of 32.44 MPa but suffered brittle failure. V2 (micro synthetic fibers only) showed the lowest strength, indicating limited effectiveness. The addition of hybrid fibers (V3-V5) significantly increased the splitting tensile strength of concrete by 0.99-15.84% and modulus of elasticity by 101.73-198.05% higher than plain concrete. Hybrid fibers also transformed the failure mode from brittle to ductile. The V4 mixture represents the most effective combination of strength, stiffness, and crack resistance. This research highlights the synergistic potential of hybrid fiber reinforcement for improving concrete's tensile capacity, stiffness, and post-cracking behavior, offering valuable insights for durable concrete applications.
The use of industrial waste as concrete additives is a strategic approach to support sustainable construction. One of the underutilised wastes is BWG (Birmingham Wire Gauge) wire, which has the potential to improve the performance of paving blocks. This study evaluated the effect of BWG wire fibre content and diameter on the compressive strength and water absorption of paving blocks. Paving blocks were made by a conventional method, using wire fibres with diameters of No.10 (3.1 mm), No. 16 (1.55 mm), and No. 24 (0.5 mm) at varying levels 0% to 5%. The test results showed that 1% fibre content was the optimal configuration, with the highest compressive strength increase of 55.8% for No. 24 wire (from 14.6 MPa to 22.60 MPa). The addition of fibre above 1% caused a decrease in strength due to agglomeration and compaction resistance. Water absorption decreased as fibre content increased, with a maximum decrease of 33.8% at 5% content and small diameter. Smaller fibre diameters gave the best performance, both in increasing strength and decreasing porosity.Overall, 1% BWG wire fibre configuration with No. 24 diameter is recommended to produce high-performance and environmentally efficient paving blocks.
Hydrostatic pressure testing is a significant procedure for evaluating fire protection equipment’s structural integrity and leak resistance, particularly devices with flexible structures and variable internal volumes such as fire hoses. Instability, safety concerns, and environmental risks hinder conventional pressure generation methods relying on compressed air or hydraulic oil. This study is devoted to introducing a novel dual hydraulic actuation system (D-HAST) that employs water as the working fluid. By substituting compressed air and hydraulic oil, the D-HAST effectively mitigates pressure fluctuations arising from air compressibility and eliminates leakage risks associated with hydraulic oil, thereby establishing a safer and more environmentally sustainable framework for hydrostatic pressure testing. The system leverages two double acting cylinders operating in an alternating compression mode under a finite state machine (FSM) control scheme. The system architecture, component sizing methodology and control logic are systematically developed to achieve rapid pressurization, stable pressure maintenance and real time leakage compensation. A laboratory-scale prototype, designed to ISO 4642:2015 standards, was experimentally validated under both low- and high-leakage conditions. Results show that under low-leakage scenarios, the D-HAST achieved the target pressure within "120 s" and maintained stability ("±0.02 MPa" ) for "180 s" , while high-leakage tests revealed extended pressurization times ("964÷2675 s" ) and clear differentiation between compliant and defective hoses. The findings confirm that the proposed D-HAST offers a safe, precise, and environmentally sustainable solution for hydrostatic pressure testing, with strong potential for industrial deployment and adaptation to various leakage rates and expansion capacities.
Climate change poses a critical threat to Malaysia, particularly in the context of increasing flood risks. The country is experiencing more frequent and intense rainfall events, leading to heightened incidences of flooding. These climatic shifts can be attributed to global warming and changing weather patterns. Malaysia's vulnerability to climate-induced floods necessitates urgent and comprehensive adaptation strategies. However, if there are any lacking or missing data to be analyze, hence the next step could be jive. Addressing missing data considers to be the most important part to do before proceeding to further hydrological procedure such as statistical comparison or Intensity-Duration-Frequency (IDF). Arithmetic Mean Average and Inverse Distance Weighing method would be use in this study to address missing data. The site location for this study were in Kelantan and Pahang. The stations involved in addressing the missing data are Station Pertanian Lundang, Stor JPS Kota Bharu and Mardi Kubang Keranji in Kelantan while Station Sungai Lembing, Bukit Goh and Sungai Panching Selatan in Pahang were selected. The range of data for all the stations were from 2013 to 2023 depends on which station have missing data throughout the years. The results shown that the percentage difference or compatibility between the two methods varies from 0 up to 50 percent difference. This study considers to be significance as this method would be the first step to do before proceeding to another hydrological method. Authorities such as Department of Irrigation and Drainage (DID) would be beneficiary to this study as they will use the missing rainfall data for further hydrological steps.
