Jurnal Teknik Indonesia

Driving Sustainability in Power Generation: Amine Scrubbing Integration as a Cost-Effective Measure for Carbon Dioxide Mitigation

2026-01-02T07:54:23+00:00

The imperative of energy security, sustainability, and independence necessitates the continued use of coal for electricity generation. However, to mitigate rising CO₂ levels, developing carbon capture and storage (CCS) technologies is crucial. This study explores various approaches to optimize CO₂ capture using chemical solvents, focusing on reducing the energy demands of solvent regeneration. Our analysis reveals that the current cost of CO₂capture stands at approximately #55,000.000 (Naira) per ton of CO₂ , with a target to reduce it to below #25,000.000,00 (Naira) per ton of CO₂ . We evaluate the technical and economic performance of different approaches, calculating the specific cost per ton of CO₂ captured. Our results show that:- Current Cost: #55,000.000,00 (Naira) per ton of CO₂ - Target Cost: Below #25,000.000,00 (Naira) per ton of CO₂ - Efficiency Reduction: Minor efficiency reductions observed in some proposed schemes

Exploring the Utilization of Plastic Sand in Construction to Drive Sustainable Practices and Foster a Circular Economy

2026-01-07T09:25:39+00:00

This research explores utilizing waste plastics in construction to promote a circular economy and mitigate plastic waste's environmental footprint in Nigeria's urban centers. Innovative bricks made from low-density polyethylene bags and sand offer thermal and sound insulation properties, pollution control, and cost reduction. The eco-friendly bricks demonstrate beneficial properties: lightweight, porous structure, low thermal conductivity, and high mechanical strength comparable to conventional bricks.The experimental process involved combining cement, sand, and waste plastic/nylon (0-15% by weight) with fly ash, followed by underwater curing and baking. Results show compressive strengths of 19.5 MPa (0% waste), 19.46 MPa (5% waste), 20.3 MPa (10% waste), and 21.1 MPa (15% waste). The bricks exhibit reduced water absorption capacity (0.085-0.34%) and lower efflorescence values.The innovative bricks offer numerous benefits: enhanced strength and durability, reduced environmental impact, and economic value for manufacturers. They contribute to sustainable construction practices, reducing sand extraction and plastic waste accumulation. This research showcases the potential for eco-friendly bricks to enhance energy efficiency in buildings and promote a sustainable ecosystem for plastic waste management.

Optimizing Oil Well Cementing: Effects of Dispersant and Fluid Loss Additive Concentrations on Thickening Time and Free Fluid Formation

2026-01-12T15:58:05+00:00

Optimising cement slurry properties through appropriate additive selection is critical for ensuring successful zonal isolation and preventing costly wellbore failures in oil and gas operations. This research investigated the effects of dispersant and fluid loss additive concentrations on the thickening time and free fluid formation of Class G cement slurry. A systematic two-factor three-level (3²) factorial design was employed, generating nine experimental runs. Statistical analysis included correlation analysis, ANOVA, and multiple regression modelling. The results revealed that dispersant concentration exhibited the strongest influence on thickening time behaviour, establishing it as the primary control mechanism for cement slurry pumpability. Fluid loss additive concentration demonstrated dual functionality, serving both as an effective filtration control agent and providing secondary influence on thickening time. Significant interaction effects were observed between dispersant and fluid loss additive concentrations (p = 0.040), indicating synergistic behaviours. Multiple regression analysis yielded highly predictive models for both response variables, with R² = 0.981 for thickening time and R² = 0.845 for free fluid. The developed models provide a systematic framework for cement slurry optimisation in oil well cementing operations, enabling precise targeting of cement slurry properties for improved well integrity and performance. The research demonstrates the effectiveness of factorial experimental design methodology for understanding complex additive interactions in cement slurry systems.

Evaluating the Impact of Dispersants and Fluid Loss Additives on Cement Slurry Thickening Time: Experimental Design and Statistical Modeling

2026-01-18T15:20:11+00:00

Optimising cement slurry properties is critical for successful zonal isolation and preventing wellbore failures in oil and gas operations. This research investigated the effects of dispersant (0.1-1.0% BWOC) and fluid loss additive (0.1-0.35 gal/sk) concentrations on thickening time and free fluid formation of Class G cement slurry using a 3² factorial design. Thickening time was measured with an atmospheric consistometer; free fluid via HTHP filter press. Analysis included ANOVA and multiple regression modeling. Key findings Dispersant strongly influences thickening time (R² = 0.981, RMSE = 8.731 min). Fluid loss additive controls filtration and moderately affects thickening time. Significant dispersant-fluid loss additive interaction (p = 0.040) indicates synergistic effects. Models enable predictive optimization of cement slurry properties

Evaluation of Orange Fruit Quality Clustering Using a Real-Time X-Means Algorithm

2026-01-30T02:42:46+00:00

The citrus farming industry faces major challenges in maintaining product quality consistency due to subjective manual sorting processes that are prone to fatigue and have varying standards. This problem results in economic losses due to errors in detecting ripeness levels and physical damage that hinders market competitiveness. This study aims to design and implement an automated citrus fruit quality evaluation system using a real-time X-Means algorithm. The research method begins with visual data acquisition through a camera sensor using the automatic snapshot feature to convert physical objects into digital data. The data then undergoes preprocessing, which includes filtering to remove noise, color (RGB) and texture feature extraction, and normalization using Min-Max Scaling to balance parameter weights. The X-Means algorithm is used because of its ability to independently determine the optimal number of clusters through the evaluation of the Bayesian Information Criterion (BIC) score. The processing results show that the system is able to accurately group oranges into three categories: ripe, which are dominated by bright orange colors; unripe, which are dominated by green colors; and rotten, which are identified through rough textures and dull colors. The integration of this technology ensures that all decision-making occurs quickly and objectively, providing a practical solution for the industry to consistently improve product quality control efficiency in the field.

Ecotourism Based Revitalization of Urban Riverfront: Design Guideline Framework for the Cikapundung Riverbank, Bandung

2026-06-07T00:09:32+00:00

Urban rivers in rapidly growing Indonesian cities are frequently marginalized by uncontrolled development, resulting in degraded riparian zones that are ecologically dysfunctional and spatially disconnected from urban life. The study investigates the application of ecotourism principles as a framework for the revitalization of the Cikapundung Riverfront in downtown Bandung, focusing on the abandoned former Palaguna Mall site (±2.5 ha). Through a descriptive qualitative methodology, the research conducts a comparative precedent analysis of the Malacca River (Malaysia) and Cheonggyecheon Stream (South Korea) to derive design criteria across seven urban design dimensions: land use, attraction and character, access and connection, building form and massing, open space, support activities, and preservation. The results suggest that successful riverfront revitalization requires the simultaneous pursuit of sustainable tourism, creative tourism resource development, and dualtrack preservation, both ecological and historical. This evolved guideline framework encourages mixed use zoning with at least 40% blue green open space corridor, pedestrian priority networks with universal accessibility, building heights not exceeding 12 meters within the riverbank zone and adaptive reuse of colonial era heritage structures. The framework provides a replicable model for tropical urban waterfronts across Southeast Asian cities and offers concrete policy recommendations for the Bandung City Government's ongoing revitalization program.

Resilient Data Analytics Pipelines for Fault-Tolerant Smart Manufacturing Systems

2026-06-15T07:07:49+00:00

This review examines resilient data analytics pipelines as critical infrastructure for fault-tolerant smart manufacturing systems. It addresses the need for reliable, low-latency, and integrity-preserving data flows in industrial environments where sensor failures, network disruptions, data corruption, platform faults, and cyber-physical disturbances can compromise real-time analytics and autonomous decision-making. The study synthesizes recent literature on Industrial Internet of Things-enabled manufacturing, distributed stream processing, edge-fog-cloud computing, fault-tolerant architectures, and data governance. It analyses pipeline layers covering data sources, edge preprocessing, fault-tolerant ingestion, stream analytics, distributed storage, security, governance, and decision-support applications. Core resilience mechanisms examined include redundancy, replication, monitoring, checkpointing, rollback recovery, graceful degradation, secure aggregation, audit logging, and adaptive recovery. The review also evaluates technologies such as Apache Kafka, Apache Flink, Apache Spark, Storm, HDFS, Cassandra, MongoDB, cloud-agnostic platforms, microservices, and digital twins. Findings show that resilient analytics pipelines support predictive maintenance, real-time process monitoring, quality assurance, supply-chain optimization, and autonomous manufacturing by preserving data continuity and analytical reliability during faults. However, major challenges remain in balancing scalability with performance, maintaining data integrity across heterogeneous edge-fog-cloud layers, achieving low-latency recovery, integrating legacy systems, securing distributed data flows, and establishing standardized design frameworks. The review identifies future directions in AI-driven fault detection, digital-twin-based resilience testing, scalable distributed architectures, autonomous data management, and benchmarking protocols. Resilient pipelines are therefore essential operational assets for sustaining reliable, secure, and fault-tolerant smart manufacturing intelligence.

Analysis of Resident Satisfaction Evaluation at St. Titus Brandsma Dormitory Using Importance Performance Analysis Method

2026-05-28T01:00:22+00:00

St. Titus Brandsma Dormitory was built to provide temporary housing for male students of Santo Thomas Catholic University Medan. To date, the evaluation is determined by the priest at the end of the semester through a collective discussion in the dormitory hall. This study aims to measure the level of satisfaction of dormitory residents and determine service attributes that are priority for improvement using the Importance Performance Analysis (IPA) method. Research data were obtained through distributing questionnaires to dormitory residents using a Likert scale that measures the level of importance and performance. The results of the analysis show that most residents are in the satisfied category with the facilities and services provided. The study results on dormitory resident satisfaction revealed that 33.93% of respondents felt highly satisfied, whereas 42.86% indicated that they were satisfied. In addition, 19.64% of the respondents felt fairly satisfied, whereas 1.79% expressed dissatisfaction and another 1.79% indicated that they were very dissatisfied. The results of the Importance Performance Analysis also showed that the availability of a stable Wi-Fi signal across the dormitory area was categorized in Quadrant I, meaning it became the main priority for improvement. Therefore, enhancing the Wi-Fi service should be addressed immediately to increase resident satisfaction.

Analysis of the Effect of Using a Natural Water Filter on the Efficiency of Household Expenditure and Customer Satisfaction at Perumda Tirtanadi in Hamparan Perak Sub-District

2026-06-25T07:04:59+00:00

Clean water is a basic human need that plays a vital role in supporting health, comfort, and quality of life. Although piped water services are available through Perumda Tirtanadi, some customers still undergo additional treatment using natural water filters to improve respondents' perceptions of the quality of their daily water use. In addition to improving respondents' perceptions of water quality, the use of natural water filters also has the potential to provide economic benefits through savings on household expenses and increased customer satisfaction with clean water services. This study aims to analyze the effect of the use of natural water filters on household water expenditure efficiency and customer satisfaction at Perumda Tirtanadi in Hamparan Perak District. The study used a quantitative approach with descriptive and explanatory methods. Data were obtained by distributing questionnaires to 100 respondents selected using a purposive sampling technique. Data analysis was performed using descriptive statistics and natural linear regression. The results showed that the utilization rate of natural water filters was in the high category with an average value of 4.14. Household expenditure efficiency was also in the high category with an average value of 4.02, while the level of customer satisfaction had an average value of 3.90. The results of the regression analysis indicate that the use of natural water filters has a positive and significant effect on household expenditure efficiency and customer satisfaction with a significance value of less than 0.05. These findings indicate that the use of natural water filters can be an effective alternative to improve respondents' perceptions of the quality of water used by the community, reduce household expenditure, and increase customer satisfaction with Perumda Tirtanadi services. Therefore, the use of natural water filters can support efforts to provide more efficient and sustainable clean water at the household level.

Design and Development of a Mobile Plastic Paving Block Unit for the Revitalization of the Parking Area at the Faculty of Engineering, Universitas Graha Nusantara Padangsidimpuan

2026-07-08T08:55:19+00:00

Pavement damage and standing water in the parking area of the Faculty of Engineering, Universitas Graha Nusantara (UGN) Padangsidimpuan indicate that sustainable infrastructure principles have not yet been optimally applied in the revitalization of campus facilities, while the national plastic-waste recycling rate remains low. This study aims to analyze the existing condition of the pavement, examine the potential of plastic waste as an environmentally friendly paving-block material, and design a mobile plastic paving-block unit that is technically feasible for revitalizing the parking area. The study employs an engineering-based research approach at Technology Readiness Level (TRL) 3, drawing on field observation, compressive-strength and water-absorption testing of four polypropylene (PP) plastic-waste mix compositions, and functional testing of the mobile-unit prototype across five production batches. The results show that the existing pavement damage ratio reaches 34.0% of the total parking area, dominated by standing water and alligator cracking. The PP:sand 60:40 composition yields a compressive strength of 15.6 MPa and a water absorption of 2.1%, satisfying SNI 03-0691-1996 Grade C for pedestrian walkways and two-wheeled-vehicle parking, but not yet meeting Grade B for four-wheeled-vehicle parking. The mobile unit achieved an average production efficiency of 87.2%, rising from 76% in the first batch to 92% in the fifth. This study contributes an integration of plastic-waste-based material innovation with a mobile, field-deployable production system, distinct from conventional approaches that remain static and laboratory-oriented, and provides a foundation for advancing to the next technology readiness stage.

Data-Driven Decision Support System for Scholarship Selection Based on Multi-Criteria Analytics

2026-07-14T01:18:10+00:00

Scholarship selection is a strategic process in higher education institutions that requires fairness, transparency, and objective decision-making. However, conventional selection methods often face challenges in handling multiple assessment criteria and large volumes of applicant data. This study proposes a Data-Driven Decision Support System (DSS) for scholarship selection in Deli Serdang Regency based on Multi-Criteria Analytics. The system integrates academic and non-academic indicators, including Grade Point Average (GPA), family income, academic achievements, organizational involvement, attendance records, and extracurricular activities. A quantitative approach was employed using student data collected from higher education institutions in Deli Serdang. Multi-criteria analysis was applied to evaluate and rank scholarship candidates according to predefined weighting schemes. The results demonstrate that the proposed system effectively identifies eligible candidates while improving consistency, transparency, and decision accuracy. Furthermore, the data-driven framework reduces subjective bias and supports evidence-based scholarship allocation. The study concludes that the proposed DSS can serve as a reliable tool for educational institutions and local governments in optimizing scholarship selection processes and promoting equitable access to educational opportunities.

A RAG and Reciprocal Rank Fusion-Based Chatbot for New Student Admission (SPMB) Information Services at SMK Muhammadiyah 1 Wonosobo

2026-06-29T16:47:32+00:00

The New Student Admission (SPMB) information service at SMK Muhammadiyah 1 Wonosobo faces a high volume of inquiries—987 registrants were recorded in 2025—handled through seven official channels limited to working hours, resulting in repetitive questions and inconsistent answers. This study aims to develop a Natural Language Processing (NLP)-based chatbot using the Retrieval-Augmented Generation (RAG) and Reciprocal Rank Fusion (RRF) methods to automate the SPMB information service on the school’s official website. The system was built using the Prototype development method. The designed RAG pipeline adds three retrieval-enhancement mechanisms on top of naive RAG, namely query expansion, RRF with an asymmetric 4:1 weighting, and cross-encoder reranking, with Gemini 3 Flash Preview as the answer generator and a knowledge base of 44 official school text documents. Testing was conducted through Black Box Testing and RAGAS evaluation measuring faithfulness, answer relevancy, and context precision. Black Box Testing of 17 scenarios achieved a 100% functional success rate. RAGAS evaluation on the full (Enhanced) configuration obtained faithfulness 0.9812, answer relevancy 0.9146, and context precision 0.7991. Compared to the Baseline configuration, answer relevancy increased by 12.40% and context precision by 14.16%, while faithfulness remained in the “Very Good” category. This study concludes that applying these three techniques positively contributes to document relevance and the answer quality of the SPMB information chatbot.