SAINTEKS : Jurnal Sain dan Teknik

Investment cost analysis and payback period of waste heat recovery system technology in a nickel pyrometallurgical smelter with 300,000 tons NPI/ year capacity: a case study of PT “X” in the IMIP Morowali industrial area

2026-08-09T06:38:17+00:00

The pyrometallurgical nickel processing industry in the Morowali Industrial Area (IMIP) exhibits extremely high energy consumption, in which the Rotary Kiln-Electric Furnace (RKEF) process generates substantial quantities of waste heat that are routinely discharged into the atmosphere without utilization. This study aims to analyze the investment feasibility of implementing Waste Heat Recovery System (WHRS) technology based on the Organic Rankine Cycle (ORC) at PT “X” smelter with a production capacity of 300,000 tons of Nickel Pig Iron (NPI) per year for on-site power generation. The research employs a capital budgeting approach incorporating Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PP) as key financial parameters, supported by thermodynamic calculations to determine the potential electrical power output. Results indicate that the available waste heat potential from flue gas across four RKEF lines amounts to 156.8 MW thermal, yielding a net electrical output of 28.5 MW. The total WHRS investment cost is estimated at USD 42.75 million, generating annual energy cost savings of USD 14.93 million. Financial feasibility analysis produces an NPV of USD 56.82 million at a 10% discount rate, an IRR of 28.47%, and a Payback Period of 3 years and 2 months. The resulting energy cost reduction reaches 18.7% of the total smelter electrical energy expenditure. The findings confirm that WHRS implementation in nickel pyrometallurgical smelters is financially viable and contributes significantly to industrial energy efficiency and decarbonization efforts in Indonesia’s nickel processing sector.

Optimization of Seam Sealing Process Parameters Using Statistical Process Control for Waterproof Outerwear Production

2026-08-22T11:35:51+00:00

The seam sealing process is a critical stage in the production of waterproof outerwear because it seals needle holes created during sewing, thereby preventing water penetration and ensuring the waterproof performance of the garment. At PT X, leakage defects were identified in the neck, shoulder, and armhole areas, causing the products to fail to meet the buyer's zero-defect quality standard. This study aimed to identify defect patterns and root causes, control process variation using Statistical Process Control (SPC), and determine the optimum seam sealing parameters as a basis for process standardization. Previous studies have primarily focused on evaluating materials, seam construction, or seam sealing process parameters independently. This study extends previous research by integrating SPC with process parameter optimization to identify sources of process variation, determine the root causes of defects, and establish optimal process parameters for quality improvement. This study employed a quantitative, descriptive, and experimental approach using check sheets, histograms, Pareto diagrams, p-control charts, and fishbone diagrams, followed by experiments with sealing temperatures ranging from 450⁰C to 490⁰C and machine speeds of 3.5–4.0 ft/min at a constant pressure of 0.6 MPa. Water resistance was evaluated using an HTM-2225A waterproofness tester. The results showed that 75 of 90 inspection points (83.33%) experienced leakage defects. Pareto analysis revealed that the armhole and shoulder areas accounted for 72% of the total defects, making them the primary priorities for process improvement. Parameter optimization demonstrated that a sealing temperature of 480⁰C reduced the defect proportion to 33.33%, while the combination of 480⁰C, 3.8 ft/min, and 0.6 MPa achieved the best sealing performance with no leakage observed at any inspection point. These findings indicate that integrating SPC with process parameter optimization provides an effective basis for standardizing the seam sealing process, reducing process variation, and improving the quality consistency of waterproof outerwear.

Soft System Methodology of Modeling Green Lean Production Halal SMEs in Tangerang Regency

2026-08-23T05:23:09+00:00

Halal food micro, small, and medium-sized enterprises (MSMEs) make a significant contribution to the local economy, but they still face challenges related to waste management, energy efficiency, and the sustainable use of resources. This study aims to develop a model for implementing clean production in halal food MSMEs in Tangerang Regency to support the achievement of Sustainable Development Goal (SDG) 12 on responsible consumption and production. The method used is the Soft System Methodology (SSM), which involves the following stages: problem identification, Rich Picture development, CATWOE analysis, conceptual model development, comparison of the model with actual conditions, and formulation of recommendations for improvement and implementation. The results of the study indicate that the main issues include production waste, plastic packaging waste, and water and energy waste. The CATWOE analysis identified the key actors in the system, the transition toward environmentally friendly, energy-efficient, and water-efficient waste management, and halal regulatory support as critical factors for implementation. A comparison of the model with actual conditions showed that 37.03% of respondents were optimistic that productivity gains could be achieved through the application of the 3R principles. In comparison, 51.8% of respondents were optimistic that work flexibility would increase. Proposed improvements include using technology in food packaging and waste management, as well as refining food processing procedures to reduce potential waste generation. Thus, SSM is an effective tool for developing an initial model for clean production implementation in halal food MSMEs and can serve as the foundation for developing sustainability strategies for the sector.

Proposed Improvement of Finished Goods Warehouse Layout Using FSN Analysis and CBS Method at PT XYZ

2026-07-15T11:51:42+00:00

PT XYZ is a company operating in the Fast Moving Consumer Goods (FMCG) industry that produces snack products. Based on observations, it was identified that the finished goods warehouse layout at PT XYZ is not yet optimally organized. This condition has resulted in several operational issues, such as increased travel distance of material handling and longer time required for order picking and preparation activities. These problems potentially reduce warehouse operational efficiency, and negatively impact the company’s distribution performance. This study aims to propose an improved finished goods warehouse layout at PT XYZ by implementing FSN (Fast Moving, Slow Moving, and Non Moving) analysis and the CBS (Class Based Storage) method. FSN analysis is applied to classify products according to their movement frequency, while the CBS method is used to arrange products based on their respective movement classes to create a more structured storage system. The data used in this study include product movement data, warehouse dimensions and layout, storage capacity requirements, material handling distances, and material handling times. The evaluation of the proposed warehouse layout shows an improvement in efficiency. In the existing layout, the total material handling distance is 14,333.40 meters, while after the implementation of the proposed layout becomes 13,520.10 meters, resulting in a reduction of 813,30 meters. In addition, the material handling time in the existing layout is 71,836.76 seconds, and after the implementation of the proposed layout it becomes 30,297.89 seconds, resulting in a reduction of 41,538.87 seconds. These results indicate that the application of FSN analysis combined with CBS method can improve operational efficiency of the finished goods warehouse at PT XYZ. The proposed layout is expected to serve as an alternative solution for improving warehouse management, particularly in reducing material handling distance and time, as well as supporting smoother warehouse operations.

Techno-economic analysis of solar photovoltaic integration as partial substitution of captive coal-fired power in nickel smelters

2026-08-11T03:36:14+00:00

The Indonesian nickel processing industry, concentrated in the Morowali (Central Sulawesi) and Obi Island (North Maluku) industrial parks, currently relies on captive coal-fired power plants (PLTU captive) to supply approximately 76% of its electricity demand. This dependency creates a structural barrier to decarbonization and exposes nickel exporters to forthcoming carbon border adjustment mechanisms (CBAM) in major destination markets. This study evaluates the techno-economic feasibility of integrating a 200 MWp ground-mounted photovoltaic (PV) plant coupled with an 80 MWh Battery Energy Storage System (BESS) as a partial substitute for captive coal generation in a representative nickel pyrometallurgical smelter (350,000 ton NPI/year, 132 MW captive load, 1,056 GWh/year electricity demand). The analysis combines solar resource assessment using long-term Global Horizontal Irradiation (GHI) data from the Global Solar Atlas (4.85–4.95 kWh/m²/day for the study locations), Levelized Cost of Energy (LCOE) calculation, and capital budgeting using NPV, IRR and Payback Period. Results show that the proposed configuration generates 279.0 GWh/year (substituting 26.4% of smelter consumption), with a total CAPEX of USD 197.76 million and LCOE of USD 0.0944/kWh (IDR 1,510/kWh). The avoided CO? emission reaches 237,155 tons/year. Although the project is not feasible under the current Indonesian carbon price (USD 2/ton, NPV negative), feasibility is achieved at carbon prices of USD 50/ton or above (NPV USD 19.84 million, IRR 11.33%) and becomes highly attractive at CBAM-equivalent USD 70/ton (NPV USD 61.34 million, IRR 14.01%, Payback Period 6 years 8 months). Sensitivity analysis identifies carbon price and PV CAPEX as the most influential variables. The study confirms that PV-BESS substitution is a strategically viable decarbonization pathway when supported by carbon pricing reform and ESG-aligned financing

Taguchi's Experiment to Reduce Body Puckering Defects in Jacket Products

2026-07-29T04:07:33+00:00

This research began with the company's losses due to numerous product defects. The dominant defects in body puckering originated from the body press finishing process, which is a finishing process using an automatic press machine. In the pressing process, there are several influential parameters, namely temperature settings, time, and pressure. In addition, the type of fabric to be pressed also has an effect. Currently, the company does not have a reference for the press machine settings, so workers in carrying out the pressing process only rely on intuition. Therefore, the purpose of this research is to determine the settings for the body press finishing process using an automatic press machine that are appropriate based on temperature settings, vacuum time, and pressure in the body press finishing process using the Taguchi experiment method to help reduce the number of body puckering defects. From observations and interviews, it was concluded that the control factors that can be controlled that affect the occurrence of defects in jacket products are the temperature factor of 125°C and 130°C, the vacuum time factor of 15 seconds and 20 seconds, and the pressure of 25Psi and 15Psi. The experiment was conducted three times, namely the actual condition experiment, the proposed experiment, and the confirmation experiment. Each experiment was conducted with 24 replicas and 600 products. The results of data processing obtained the best settings, namely a temperature factor setting of 125°C, a vacuum time setting of 15 seconds and a pressure setting of 25 Psi with a defect percentage of 5.89% to 1.67% per day.

Analysis of Student Purchasing Patterns in a Campus Convenience Store Using Market Basket Analysis

2026-08-19T02:27:21+00:00

Understanding customer purchasing patterns is essential for retailers to develop effective merchandising and promotional strategies. However, conventional transaction analysis is often limited to identifying the frequency of individual product purchases without revealing relationships among products purchased within the same transaction. This study aims to identify purchasing patterns among university students by applying Market Basket Analysis (MBA) using the Apriori algorithm. Primary data were collected from 100 purchase receipts obtained from students who shopped at a convenience store located in a university area. The transaction data were cleaned, grouped into 18 product categories, and transformed into a binary transaction matrix prior to analysis. The Apriori algorithm was implemented using a minimum support of 3% and a minimum confidence of 60%, while the resulting association rules were evaluated using lift values greater than one. The results indicate that Dairy (45%) and Bakery (43%) were the most frequently purchased product categories. The most frequent two-item combination was Bakery–Dairy, with a support value of 21%. Furthermore, nine association rules satisfied the predefined thresholds, with the strongest rule indicating that purchases containing Mineral Water and Body Care were consistently associated with Bakery purchases (confidence = 100%; lift = 2.33). These findings demonstrate that Market Basket Analysis can provide valuable insights into customer purchasing behavior and support data-driven decisions related to product placement, merchandising, and promotional strategies in convenience stores located within university environments.

Developing an Analytical Hierarchy Process Conceptual Framework for Fuel Cell Electric Vehicle Adoption in Indonesia Evidence from Literature Synthesis

2026-09-12T03:50:02+00:00

Fuel Cell Electric Vehicles (FCEV) are a zero-emission vehicle technology that has the potential to support the decarbonization of the road transportation sector in Indonesia. However, their adoption rate remains very low due to limited hydrogen infrastructure, the lack of specific policies, and the low readiness of the supporting ecosystem compared to battery-based electric vehicles. This study aims to develop a conceptual framework for the Analytical Hierarchy Process (AHP) based on literature synthesis to identify and prioritize factors influencing FCEV adoption in Indonesia from a multi-stakeholder perspective, particularly policymakers. The study uses a qualitative approach through literature synthesis of twelve relevant scientific articles. The synthesis results are used to construct a decision hierarchy structure consisting of four main criteria: policy, economic, socio-environmental, and technical aspects, with a total of 15 sub-criteria. The results show that policy aspects are the main priority in supporting FCEV adoption, primarily through the provision of fiscal incentives, reducing hydrogen production costs, harmonizing cross-sector regulations, developing a National Hydrogen Roadmap specifically for the transportation sector, and hydrogen pricing and subsidy policies. Economic aspects are the second priority, followed by socio-environmental and technical aspects. The resulting conceptual framework provides a systematic basis for the application of the AHP method in further research and can be used as a reference in formulating strategies and policies to accelerate the gradual and sustainable adoption of FCEVs in Indonesia

Effects of Reaction Temperature and Phosphoric Acid Catalyst Volume on Free Fatty Acid Reduction in Used Cooking Oil via Esterification

2026-09-13T13:24:56+00:00

Used cooking oil contains free fatty acids (FFAs), which can increase due to hydrolysis and repeated heating, thereby limiting its further use. This study descriptively evaluated the effects of reaction temperature (40 and 60 °C) and the volume of phosphoric acid catalyst (4 and 8 mL) on the reduction of FFAs through esterification with methanol. Each reaction used 100 mL of pretreated used cooking oil, 20 mL of methanol, and 85% H?PO? for 60 minutes at 500 rpm. FFA content was determined by alkalimetric titration, while FTIR was used for supporting qualitative characterization. The density and viscosity of the new oil and used oil were also compared. The initial FFA content was 2.11%. After esterification, the FFA contents were 1.33%, 0.88%, 0.70%; and 0.33% under the conditions of 4 mL–40 °C, 4 mL–60 °C, 8 mL–40 °C, and 8 mL–60 °C, with reported conversion rates ranging from 37.02% to 84.55%. The lowest FFA content was obtained at 60 °C with 8 mL of H?PO?. The FTIR spectra before and after treatment showed similar C=O and C–O ester bands because the triglycerides already contained ester groups; therefore, FFA titration was used as the primary indicator of esterification progress. Within the range of conditions tested, higher temperatures and catalyst volumes were associated with greater reductions in FFA.

Financial Analysis of 10MW Reserve Margin Bergerak (RMB) Provision in Island Power Systems Using LCT Platform

2026-07-15T10:55:23+00:00

This study offers a thorough financial and risk analysis of a Reserve Margin Bergerak power plant system installed on Landing Craft Tank (LCT) platforms, aimed at improving energy security in Indonesia's remote and archipelagic areas. The total capital expenditure (CAPEX), which is IDR 77.74 billion including taxes, mainly covers engine generators and associated electrical infrastructure. The project's economic viability is assessed using Net Present Value (NPV) and Internal Rate of Return (IRR) under a fixed tariff structure, with a minimum IRR threshold of 8.24%. Sensitivity tests show that the project's success is highly affected by changes in CAPEX but less influenced by operational expenditure (OPEX) variations. A 10% increase in CAPEX drops the IRR to the viability limit, while a 30% cost reduction greatly improves returns. Changes in operational costs have little effect on IRR but slightly boost NPV. Following ISO 31000:2018 standards, risk analysis highlights critical operational risks including design mismatches, tariff inefficiencies, and low LCT utilisation all of which can be addressed through targeted technical reviews, tariff reforms, and deployment strategies. These results emphasise the importance of controlling investment costs and implementing structured risk management to ensure the long-term viability and financial appeal of mobile energy projects.

Improvement of SMK Senopati’s Quality using SMART-Based Strategic Management and SWOT Analysis

2026-07-15T11:07:56+00:00

The success of SMK Senopati Sidoarjo is very important, because it can increase the competitiveness of its graduates in the world of work. Therefore, it is necessary to make efforts to improve the performance of SMK Senopati Sidoarjo, especially from the perspective of productivity and quality. The study was conducted to determine the criteria for success of SMK Senopati Sidoarjo, assess the achievement of KPIs and design a robust strategic management. The research methodology uses a mix method, involving respondents to fill out AHP questionnaires, secondary data related to KPI achievement targets to design SMART, which underlies the strategy design process using SWOT. The results showed that there were 17 KPIs that were not achieved. Based on the internal factor analysis summary, the IFAS score was 2.59 and the EFAS score was 2.96 this shows that there is still potential to improve the performance of SMK Senopati Sidoarjo, especially in the perspective of productivity and quality. This vocational school needs to implement an W-O strategy, which is a strategy that utilizes strengths to seize existing opportunities. SMK Senopati Sidoarjo needs to improve the productivity and quality of its graduates by strengthening collaboration with industry, improving the quality of the learning process, and conducting more intensive socialization and promotion.

Feasibility Evaluation of Energy Source Selection for Aluminum Ingot Smelter Industry with 1 Million TPY Capacity in Sukamara Regency, Central Kalimantan Using Simple Additive Weighting (SAW) Method and Monte Carlo Simulation Sensitivity Analysis

2026-07-28T16:14:50+00:00

This study evaluates the feasibility of energy source selection for an aluminum ingot smelter with a capacity of 1 million tons per year (TPY) in Sukamara Regency, Central Kalimantan, using the Simple Additive Weighting (SAW) multi-criteria decision-making method integrated with Monte Carlo Simulation sensitivity analysis. Five energy source alternatives are evaluated: Coal Steam Power Plant (PLTU), Natural Gas Combined Cycle (PLTG-CC), Run-of-River Hydropower (PLTA RoR), Solar PV Utility Scale with Battery Energy Storage System (PLTS+BESS), and a Hybrid Coal-Solar combination. Six evaluation criteria are applied: Levelized Cost of Energy (LCOE), supply reliability, carbon emission intensity, CAPEX investment, local energy potential suitability, and regulatory compliance with the National Energy Mix (Rencana Umum Energi Nasional/RUEN). Expert weighting was conducted through Analytical Hierarchy Process (AHP) involving 12 experts from the energy, industry, and government sectors. SAW calculation results show that PLTU Coal ranks first with a normalized score of 0.847 for short-term cost economy, followed by Hybrid Coal-Solar (0.763), PLTG-CC (0.689), and PLTS+BESS (0.534) among the alternatives able to independently meet the smelter's power demand. PLTA RoR (Run-of-River Hydropower) attains the highest technical SAW score (0.942), but because its 800 MW installed capacity cannot cover the 1,800 MW demand on its own, it is excluded from this standalone ranking and instead evaluated as a component of an integrated energy mix. However, Monte Carlo Simulation with 10,000 iterations on LCOE uncertainty variables (±15%), carbon price (USD 2–70/ton CO?), and supply reliability (±10%) shifts the ranking significantly: PLTS+BESS rises to the highest composite robustness score at the 95th percentile. At a carbon price of USD 50/ton, the probability of PLTU maintaining top ranking drops to 34%, while PLTS+BESS achieves 61% probability as the optimal alternative. These findings serve as a quantitative basis for the Feasibility Study (FS) of the Aluminum Ingot Smelter in Sukamara, Central Kalimantan, particularly for the energy chapter and ESG-aligned investment framework.

Diagnosing Feed Concentrate Supply Chain Performance in an Agribusiness Cooperative via "SCOR-AHP"

2026-08-11T13:52:18+00:00

This study aims to measure the supply chain performance of the Animal Feed Concentrate (MAKO) business unit at KUD Sarwa Mukti Cisarua, particularly for the F1 product, which faces recurring problems of production-sales mismatch, inventory fluctuation, delivery delay, and demand forecasting inaccuracy. A descriptive quantitative approach with a case study design was employed, integrating the Supply Chain Operation Reference (SCOR) model, Snorm De Boer normalization, and the Analytical Hierarchy Process (AHP). Data were collected through observation, interviews, AHP pairwise comparison questionnaires, and company documentation for the 2024 period. Fifteen performance metrics were mapped across the five core SCOR processes (plan, source, make, deliver, return), categorized as Larger is Better or Lower is Better, normalized to a 0–100 scale, and weighted through pairwise comparisons with a consistency ratio (CR) of no more than 0.10. The results show an overall supply chain performance score of 64.36, classified as Average. The Make process recorded the lowest attribute score (56.94), while three indicators fell into the red category of the traffic light system, namely Production Plan Adjustment Time, Production Volume Accuracy, and Production Cost per Ton. These findings indicate that the company's supply chain performance has not yet been optimal, particularly in production planning and control, so improvement priorities are recommended through a rolling forecast mechanism, periodic evaluation of the production plan based on actual demand data, and more efficient production scheduling. This study contributes to the limited body of SCOR-AHP research on agribusiness cooperatives by simultaneously integrating SCOR, AHP, and Snorm De Boer normalization for a feed-concentrate production unit, an operational context that has received far less attention than plantation- or manufacturing-based supply chains. Practically, the findings provide cooperative managers with a concrete, low-cost diagnostic tool for prioritizing production-planning interventions without requiring sophisticated information-technology infrastructure.

Cotton Ply Yarn Twist and Filling Stop in Air-Jet Woven Mori Fabric

2026-08-25T15:48:49+00:00

The aerodynamic interaction between weft yarn and compressed air plays a critical role in determining weaving performance in air-jet looms. Although increasing ply twist is known to reduce yarn hairiness by improving yarn compactness, its influence on actual filling stop behavior under industrial weaving conditions has not been comprehensively investigated. This study investigated how cotton ply yarn twist affects yarn hairiness and filling stop rate during the production of 100% cotton greige (mori) fabric on a Toyoda air-jet loom under commercial manufacturing conditions. Cotton Ne 20 ply yarns were prepared from two Ne 40 single yarns using a two-for-one twisting process with ply twist levels of 400, 600, and 800 TPM while maintaining identical yarn count, fiber composition, and weaving parameters. Yarn hairiness was measured using a COVATEST hairiness tester, whereas weaving performance was evaluated based on the filling stop rate recorded over five weaving repetitions of 100,000 picks for each twist level. One-way ANOVA was performed to assess the effect of ply twist on filling stop rate, followed by Tukey’s HSD test for post-hoc comparisons. In addition, linear regression analysis was performed to quantify the observed association between yarn hairiness and filling stop rate. Yarn hairiness decreased progressively from 5.63 ± 0.06 at 400 TPM to 4.54 ± 0.05 at 800 TPM, corresponding to an overall reduction of 19.36%. Conversely, the filling stop rate increased from 0.80 ± 0.84 to 6.20 ± 1.48 stops per 100,000 picks as the ply twist increased. Statistical analysis confirmed that ply twist significantly affected the filling stop rate (F = 19.895, p < 0.001). Linear regression showed a strong negative association between yarn hairiness and filling stop rate (r = ?0.855, R² = 0.731, p < 0.001). However, because both variables varied systematically with ply twist, this association does not establish an independent causal effect of hairiness on filling stop occurrence. The observed increase in filling stop rate with higher ply twist, together with the reduction in yarn hairiness, suggests that changes in yarn surface characteristics may influence weft insertion under compressed airflow. A possible explanation, consistent with previous studies, is that the smoother and more compact yarn surface associated with higher ply twist may reduce aerodynamic interaction during weft insertion. However, this aerodynamic mechanism was not directly measured in the present study. These findings demonstrate an association between ply twist, yarn hairiness, and filling stop behavior under commercial air-jet weaving conditions, providing practical insight into ply yarn design for weaving performance.

Analyzing Lead Time Reduction In The Rice Supply Chain Using Promodel Simulation: A Case Study Of Subur Jaya Rice Milling, Bekasi

2026-08-25T15:43:09+00:00

The efficiency of the rice supply chain is strongly influenced by lead time, particularly in activities related to raw material supply and paddy drying. Long waiting times in these processes can disrupt material flow and limit production capacity. This study aims to analyze the lead time of the rice supply chain at Subur Jaya, based on direct observations and interviews with rice milling personnel. A simulation model was developed based on actual operating conditions, covering the processes from paddy delivery by suppliers to rice distribution to customers. The results show that the activities contributing most significantly to lead time are paddy delivery from suppliers, which requires 14 days, and the manual paddy drying process, which takes 5 days. The simulation of the existing condition resulted in a total processing time of 587.99 hours, with a production capacity of 2.418 tons of rice per month. An improvement scenario was developed by increasing the frequency of paddy supply and replacing the manual drying process with a mechanical dryer. The simulation results indicate that the total processing time can be reduced to 208.47 hours, representing a reduction of approximately 64.54%, while production capacity can be increased to 4.836 tons per month. The reduction in processing time is primarily attributed to decreased waiting time in the drying area. The use of a mechanical dryer reduces dependence on weather conditions and enables a more stable and predictable material flow, while shorter queues allow paddy to enter the milling process more quickly. These findings demonstrate that improvements in drying technology and supply management can significantly enhance rice supply chain efficiency and provide substantial operational benefits compared with increasing production capacity solely at the milling stage.

Flexible Pavement Design Using MDP 2024 and Asphalt Institute

2026-09-14T06:25:19+00:00

Accurate flexible pavement thickness design is essential for structural reliability, particularly under high heavy-vehicle traffic and Over Dimension Over Load (ODOL) conditions that may accelerate fatigue cracking and rutting. This study compares pavement thickness, structural responses, and estimated service life obtained using the 2024 Pavement Design Manual (MDP 2024) and the Asphalt Institute method, supported by Pavement-PastDean, under three planned traffic-load scenarios of 5, 15, and 60 million CESA. The analysis uses actual field subgrade CBR data from Jalan Simpang Maruyung, Kutamandiri, Tanjungsari, Sumedang Regency, with a design CBR of 9%, selected from the lowest of three field measurements. Both methods produced pavement structures that met the design criteria in all scenarios. At 5 million CESA, the total thicknesses were 300 mm for MDP 2024 and 450 mm for the Asphalt Institute; at 15 million CESA, they were 385 mm and 505 mm, respectively; and at 60 million CESA, both converged to 540 mm. At 5 million CESA, estimated service life was 6.41 million CESA for MDP 2024 and 7.17 million CESA for the Asphalt Institute, while at 15 million CESA the values were 20.43 and 18.48 million CESA, respectively. At 60 million CESA, MDP 2024 produced an extreme value of 980,184.82 million CESA versus 79.35 million CESA for the Asphalt Institute. This extreme value is attributed to the transfer-function formulation after the AC-Base tensile strain decreased to 7.499 microstrain due to the stiff cement-treated base (CTB, E = 3,000 MPa), and should not be interpreted as evidence of superior rutting performance because both methods produced the same subgrade compressive strain. Overall, the relative performance of the two methods varied with traffic level, indicating a nonlinear relationship between load level and predicted pavement performance.