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REKAYASA
Published by Universitas Trunojoyo Madura
ISSN : 02169495     EISSN : 25025325     DOI : https://doi.org/10.21107/rekayasa
Core Subject : Science, Agriculture, Engineering,
Agriculture, Biological Sciences & Forestry Computer Science & IT Electrical & Electronics Engineering Engineering Physics
This journal encompasses original research articles, review articles, and short communications, including: Science and Technology, In the the next year publication, Rekayasa will publish in two times issues: April and Oktober.
Arjuna Subject : -
Articles 517 Documents
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Analysis of the Use of Random Forest Models to Measuring the Quality of Indonesian Higher Education Institutions Wiyono, Masdar; Crysdian, Cahyo; Hariyadi, Mokhamad Amin; Abidin, Zainal; Almais, Agung Teguh Wibowo
Rekayasa Vol 18, No 3: Desember, 2025
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v18i3.32024

Abstract

This study investigates the performance of the Random Forest algorithm in measuring the quality of Higher Education Institutions (HEIs) in Indonesia. The current reliance on administrative evaluations and conventional accreditation processes often fails to capture the institutions’ actual performance comprehensively, indicating the need for a data-driven alternative. This research proposes the use of a Random Forest–based classification model to assess institutional quality based on relevant accreditation indicators. The RF-D model demonstrates optimal classification performance across three quality categories—Good, Very Good, and Excellent—with high precision, recall, and F1-scores for all classes. The Very Good category achieves a precision of 89% and a recall of 80%, while the Excellent category records the highest recall at 86%. Furthermore, the Area Under Curve (AUC) scores, which approach 1.0 for all categories, confirm the strong discriminative capability of the model. This study also highlights the influence of train–test data ratios on model stability. Extreme imbalances in data splitting can lead to overfitting or underfitting, emphasizing the importance of selecting an appropriate configuration during model development. Overall, the findings indicate that Random Forest, when optimized with suitable parameters, provides a more accurate, objective, and replicable approach for evaluating HEI quality in Indonesia. These results are expected to contribute to the development of a more transparent higher education assessment system and support data-driven decision-making among policymakers.
Optimasi Model Natural Rural Electrical Cooperation Agency Untuk Memprediksi Debit Aliran Bulanan di Sub DAS Lesti Suhartanto, Ery; Andawayanti, Ussy; Dara Lufira, Rahmah; Utami, Rizki Tri
Rekayasa Vol 18, No 3: Desember, 2025
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v18i3.31267

Abstract

Climate change and land use change in the Lesti Sub-DAS increase the risk of flooding and land degradation, requiring reliable flow predictions to support water resource management. However, the performance of the NRECA model in predicting monthly flows in this region is still not optimal because calibration-validation strategies and the use of environmental parameters have not been systematically studied. This study optimizes the NRECA model to predict monthly discharge for the period 2011-2020 in the Lesti sub-watershed by calibrating the GWF and PSUB parameters based on rainfall, evapotranspiration, and watershed morphometry data in three data division scenarios (70:30, 80:20, and 90:10 for calibration:validation). The results show that all scenarios produce excellent performance with calibration Nash-Sutcliffe Efficiency (NSE) values between 0.99491-0.99561 and correlation coefficients (R) between 0.99746-0.99785, while validation yielded NSE values between 0.89112-0.97227 and R between 0.49959-0.81520. The best scenario was obtained with a combination of 8 years of calibration and 2 years of validation, with NSE = 0.99561 and R = 0.99785 at the calibration stage, and NSE = 0.97227 and R = 0.81512 at the validation stage, indicating the model's ability to consistently represent monthly discharge variations. The similarity between the model discharge pattern and observations during the base and peak flow periods indicates that GWF optimization specifically improves the representation of base flow response. This study contributes by presenting an optimization-based calibration-validation scheme for the NRECA model, which can be used as a reference in conservation planning and reservoir operation management in watersheds with limited data.
Sustainable River Water Treatment Using Coffee Grounds: A Case Study on the Batanghari River Raudhatussya'rifah, Ra'ida; Heraningsih, Sarah Fiebrina; Alfernando, Oki; Widyastuti, Nita; Amelia, Dera; Meiyola, Nada Karima; Amanda, Nathasya Putri; Sakinah, Syarri; Ancel, Violetta Fanissa
Rekayasa Vol 18, No 3: Desember, 2025
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v18i3.31002

Abstract

The Batanghari River is increasingly contaminated by organic and inorganic pollutants resulting from intensive human activities, posing significant risks to both ecosystems and public health. This study evaluates the potential of spent coffee grounds—a low-cost, eco-friendly organic waste—as a biosorbent to purify the river water, specifically focusing on the removal of soluble contaminants measured by Total Dissolved Solids (TDS). The coffee grounds were prepared via thermal activation (110 °C for 30 min) and systematically tested in a batch adsorption system using dosages of 1, 2, and 3 grams to determine the optimal dosage for water quality improvement. The treatment demonstrated high efficacy across multiple water quality parameters. The adsorbent achieved an outstanding turbidity removal efficiency of 91.96%, effectively eliminating suspended particles. The optimal reduction in TDS was recorded at 4.9 mg/L using the 3-gram dosage, confirming success against soluble contaminants. Concurrently, the pH level increased from 6.65 to 8.16 at the 2-gram dose, reflecting improved water neutrality, and physical observations confirmed the murky, foul-smelling water became visibly clearer and odorless. Isotherm analysis revealed that the adsorption process is governed by the Langmuir model, confirming a favorable monolayer adsorption mechanism. This is evidenced by a maximum adsorption capacity (Qmax) of 10.50 mg/g and a separation factor (RL) of 0.21. These results robustly establish spent coffee grounds as a highly accessible and sustainable solution for environmental remediation, offering a viable pathway for restoring river water quality while utilizing agricultural waste. 
Optimasi Kinerja Thermoelectric Generator (TEG) melalui Analisis Distribusi Kalor dan luaran Listrik dengan Variasi Sirip Penukar Panas Atmoko, Nugroho Tri; Jamaldi, Agus; Ulikaryani, Ulikaryani; Pisti Cikarge, Ghia
Rekayasa Vol 18, No 3: Desember, 2025
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v18i3.30546

Abstract

The utilization of waste heat from conventional gas stoves as electrical energy represents an effort to improve household energy efficiency. Thermoelectric generator (TEG) technology enables the direct conversion of thermal energy into electrical energy without moving components. This study aims to investigate the performance of TEGs in harnessing waste heat from gas stoves through the application of various heat-sink fin configurations to enhance thermal absorption. Three types of fins—long fins, short fins, and random fins—were employed as heat exchangers and mounted on a modified stove enclosure. Four TEG modules were connected in series and tested to measure operating temperatures and the resulting electrical output. The findings indicate that fin configuration significantly influences heat distribution and TEG performance. The random fin model demonstrated the highest heat absorption capability, reaching 94.112 J/s, thereby increasing the temperature gradient across the TEG modules. Consequently, the random fin model also produced the highest electrical output, generating 3.369 Watts, outperforming the other fin designs. These results highlight the critical role of fin geometry in optimizing heat transfer within TEG systems. In conclusion, the random fin configuration is the most effective heat exchanger design for TEG applications on gas stoves, as it enhances heat absorption efficiency and delivers greater electrical power output. This finding offers important potential for further development of self-sustaining energy systems in household appliances.
The Effect of Online Dictionary Use and Learning Motivation on Senior High School Students’ Reading Comprehension in English Pujiastuti, Nanik; Gunawan, Wawan; Syahria, Nukmatus
Rekayasa Vol 18, No 3: Desember, 2025
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v18i3.32124

Abstract

Reading competence is fundamental to students’ intellectual and personal development, particularly in acquiring foreign language proficiency. This study examined the effects of online dictionary use and learning motivation on English reading comprehension among secondary school students. Employing a quasi-experimental quantitative design with comparative and correlational approaches, 131 tenth-grade students from SMAN 1 Madiun participated. Data were collected using a standardized reading comprehension test and a validated 30-item motivation questionnaire. Results showed that online dictionary use and learning motivation were both positively correlated with reading comprehension (r = 0.797 and r = 0.980, respectively; p 0.001). Two-way ANOVA revealed significant main effects of online dictionary use (F = 106.919, p 0.001, η² = 0.457) and learning motivation (F = 5.943, p = 0.016, η² = 0.045), with no significant interaction effect (p = 0.133). These findings highlight the importance of integrating digital tools and motivational strategies to strengthen English reading comprehension.
The Impact of Fintech on Financial Inclusion in Emerging Economy of Major Cities in Indonesia Ernawaty, Lisa; Mujanah, Siti; Fianto, Achmad Yanu Alif
Rekayasa Vol 18, No 3: Desember, 2025
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v18i3.31933

Abstract

This study investigates the impact of financial technology (FinTech) adoption on financial inclusion in emerging economies using Structural Equation Modeling–Partial Least Squares (SEM-PLS). Data were collected through a survey of 450 respondents from three emerging city (Surabaya, Makassar, and Medan) to measure the relationships among FinTech accessibility, financial literacy, trust in digital platforms, and financial inclusion. The measurement model showed good reliability and validity, with Cronbach’s Alpha ranging from 0.84 to 0.90 and Average Variance Extracted (AVE) above 0.60. Structural model results indicated that FinTech accessibility (β = 0.35, p 0.01) and financial literacy (β = 0.29, p 0.01) have significant positive effects on financial inclusion. Trust in FinTech platforms also contributed positively (β = 0.21, p 0.05) and acted as a mediator between FinTech accessibility and financial inclusion (indirect β = 0.11, p 0.05). The model explained 62% of the variance in financial inclusion (R² = 0.62), suggesting strong explanatory power. These findings confirm that FinTech innovations not only improve access to financial services but also enhance their effective use when combined with higher trust and literacy levels. The study contributes to the digital finance literature and provides practical recommendations for policymakers to promote inclusive growth.
Analisis Pengaruh Tata Guna Lahan Terhadap Perubahan Karakteristik Hidrograf Banjir di Sub DAS Sungai Negara Kota Amuntai Awaludin, Muhammad Syahli Roby; Amal, Nilna
Rekayasa Vol 18, No 3: Desember, 2025
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v18i3.31612

Abstract

Seasonal flooding in Amuntai City, located in the downstream area of the Negara Sub-watershed, has become increasingly frequent, with land-use change identified early as one of the main contributing factors. This study aims to model flood hydrographs under the land-use conditions of 2006, 2015, and 2022, and to analyze the impact of land-use conversion on the characteristics of flood hydrographs. The modeling was carried out using HEC-HMS with rainfall inputs distributed hourly using the Mononobe Method and the Alternating Block Method (ABM). Hydrological parameters, including Curve Number (CN), initial abstraction, and imperviousness, were obtained through spatial analysis using QGIS. The results indicate that land-use change has a direct influence on the hydrological response of the sub-watershed, as reflected by an increase in peak discharge from 115.9 m³/s in 2006 to 120.8 m³/s in 2015 (a 4.23% rise), and a more substantial increase to 136.4 m³/s in 2022 (a 12.91% rise from 2015, or 17.7% from 2006). In addition, acceleration of the time to peak (Tp) and shortening of the time base (Tb) were observed, indicating increased surface runoff due to reduced soil infiltration capacity as built-up areas expanded. These findings affirm that land-use conversion significantly contributes to heightened flood vulnerability in downstream areas. This study also highlights the need for more complete observational hydrograph data to enhance model accuracy in future research, and encourages the use of alternative modeling to obtain more comprehensive insights in support of sustainable watershed management strategies.

Page 52 of 52 | Total Record : 517

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