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All Journal International Journal of Aviation Science and Engineering Electrician : Jurnal Rekayasa dan Teknologi Elektro
Puput budi wintoro
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Aerospace Engineering Automotive Engineering Control & Systems Engineering Electrical & Electronics Engineering Engineering Mechanical Engineering Transportation

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Systematic Comparison of Machine Learning Model Accuracy Value Between MobileNetV2 and XCeption Architecture in Waste Classification Syste Yessi Mulyani; Rian Kurniawan; Puput Budi Wintoro; Muhammad Komarudin; Waleed Mugahed Al-Rahmi
AVIA Vol. 4, No. 2 (December 2022)
Publisher : Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47355/avia.v4i2.70

Abstract

Garbage generated every day can be a problem because some types of waste are difficult to decompose so they can pollute the environment. Waste that can potentially be recycled and has a selling value is inorganic waste, especially cardboard, metal, paper, glass, plastic, rubber and other waste such as product packaging. Various types of waste can be classified using machine learning models. The machine learning model used for classification of waste systems is a model with the Convolutional Neural Network (CNN) method. The selection of the CNN architecture takes into account the required accuracy and computational costs. This study aims to determine the best architecture, optimizer, and learning rate in the waste classification system. The model designed using the MobileNetV2 architecture with the SGD optimizer and a learning rate of 0.1 has an accuracy of 86.07% and the model designed using the Xception architecture with the Adam optimizer and a learning rate of 0.001 has an accuracy of 87.81%.
Pemetaan Risiko Spasial Multi-Bencana Banjir dan Longsor Dengan Analisis Keputusan Multi – Kriteria pada Kabupaten Pesawaran Rizkima Akbar Setiawan; Trisya Septiana; Muhammad Nur Khawarizmi; Puput Budi Wintoro
Electrician : Jurnal Rekayasa dan Teknologi Elektro Vol. 20 No. 2 (2026)
Publisher : Department of Electrical Engineering, Faculty of Engineering, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/elc.v20n2.2938

Abstract

Kabupaten Pesawaran, Provinsi Lampung, memiliki kerentanan tinggi terhadap bencana hidrometeorologi akibat interaksi kompleks antara topografi, iklim, dan tutupan lahan. Penelitian ini mengembangkan model penilaian risiko multi-bencana (banjir dan longsor) dengan menggunakan Analisis Keputusan Multi-Kriteria (AKMK). Metode Entropi digunakan untuk menentukan bobot tiga parameter utama secara objektif: kemiringan lereng, intensitas curah hujan, dan tutupan lahan, guna mengurangi bias dan meningkatkan reprodusibilitas. Hasil pemetaan overlay berbobot menunjukkan bahwa 18% wilayah termasuk zona risiko tinggi banjir, terutama di daerah pesisir rendah, sementara 22% tergolong risiko tinggi longsor di kawasan berbukit dengan kemiringan >30°. Validasi dengan data kejadian bencana dari BPBD menunjukkan tingkat akurasi spasial sebesar 85%, membuktikan keandalan model. Peta risiko yang dihasilkan menjadi alat pendukung pengambilan keputusan yang efisien dan berbiaya rendah untuk perencanaan mitigasi bencana dan pengembangan tata ruang. Kerangka kerja ini memiliki potensi untuk direplikasi di wilayah lain dengan keterbatasan data, menawarkan pendekatan penilaian risiko yang efisien dan skalalabel.
Co-Authors Muhammad Komarudin Muhammad Nur Khawarizmi Mulyani, Yessi Rian Kurniawan Setiawan, Rizkima Akbar Trisya Septiana Waleed Mugahed Al-Rahmi