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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Civilla : Jurnal Teknik Sipil Universitas Islam Lamongan Jurnal Publikasi Ekonomi dan Akuntansi
Salwa Nabilah
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering

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Environmental Impact of C Excavation Mining Activities in Banyakan District Romadhon Romadhon; Salwa Nabilah
Civilla : Jurnal Teknik Sipil Universitas Islam Lamongan Vol 6, No 2 (2021): September
Publisher : Litbang Pemas - Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/cvl.v6i2.720

Abstract

C Excavation mining activity in Banyakan District, Kediri Regency has been going on for a long time. It is needed to support the creation of good infrastructure and become one of the foundations for development progress, but in its implementation it must pay attention to the preservation of the natural environment. This study uses descriptive analysis method with a quantitative approach, and uses survey and interview methods for data collection. Afterward, the survey data were analyzed by non-parametric test using the free K-sample test, validity and reliability tests, and quantitative analysis using the Analytical Hierarchy Process (AHP) method. Thereafter, with expert recommendations, a strategy for managing the impact was developed. The results of the discussion found that environmental damage due to C excavation activities that often occur and has a major impact in Tiron Village, Banyakan District, includes damage to road infrastructure, air pollution due to material transport vehicle traffic, and loss of rural feel. Therefore, all parties must work together to overcome this, several responses that can be taken to deal with these impacts include all parties having to allocate special funds for road infrastructure improvements, policies from the government that are in favor of the community and the environment, and reclamation of mining former lands to restore a rural feel and good air quality standards
Pengaruh Kualitas Pelayanan dan Keragaman Produk Terhadap Kepuasan Konsumen pada Jaya Mart Kabupaten Pelalawan Salwa Nabilah; Endang Sutrisna
Jurnal Publikasi Ekonomi dan Akuntansi Vol. 5 No. 3 (2025): September : Jurnal Publikasi Ekonomi dan Akuntansi (JUPEA)
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jupea.v5i3.4019

Abstract

Currently, one of the growing business sectors is the retail industry. The retail industry has undergone a significant transformation in recent decades, moving from traditional retail to more complex and diverse modern retail. This study aims to determine the effect of service quality, product diversity on customer satisfaction at Jaya Mart Pelalawan Regency. This research uses quantitative methods. The sampling technique is non-probability sampling using incidental/accidental sampling with a sample size of 99 respondents. The data obtained was processed using SPSS software version 25. The results of this study are: (1) service quality has a significant effect on customer satisfaction, (2) product diversity has a significant effect on customer satisfaction, (3) service quality and product diversity have a significant effect on customer satisfaction.
Sea Land Segmentation of East Java’s North Coast Using Landsat 9 and ResNet50 Nafiiyah, Nur; Ilyas; Rifky Aisyatul Faroh; Salwa Nabilah; Nur Azizah Affandy
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 2 (2026): April 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i2.7435

Abstract

Coastal regions are among the most vulnerable ecosystems due to the combined impacts of natural processes and human activities. Climate change, population growth, and coastal development accelerate shoreline dynamics, increasing the need for accurate and efficient coastal monitoring. Satellite-based remote sensing, combined with deep learning techniques, provides a promising solution for large-scale and continuous shoreline analysis. This study proposes a deep learning–based approach for coastal land–sea segmentation using the ResNet50 architecture applied to Landsat 9 OLI imagery of the North Coast of East Java, Indonesia. The dataset consists of multispectral images processed into 224×224 pixel tiles, accompanied by manually generated ground truth segmentation maps. Two optimization strategies, Adam and Stochastic Gradient Descent (SGD), are evaluated to determine the most effective optimizer for improving segmentation performance. Experimental results demonstrate that the Adam optimizer outperforms SGD across multiple training epochs, achieving the highest segmentation accuracy with mean Intersection over Union (IoU) and Dice coefficient values of 0.888 and 0.934, respectively. These findings indicate that optimizer selection significantly influences the performance of ResNet50-based coastal segmentation. The proposed approach shows strong potential for supporting automated and large-scale coastal monitoring applications using medium-resolution satellite imagery.
Co-Authors Endang Sutrisna Ilyas Nafiiyah, Nur Rifky Aisyatul Faroh Romadhon Romadhon