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All Journal Matematika: Jurnal Teori dan Terapan Journal of Geoscience, Engineering, Environment, and Technology Jurnal Riset Matematika Bandung Conference Series: Mathematics
Yurika Permanasari
Program Studi Matematika Fakultas MIPA Universitas Islam Bandung
Earth & Planetary Sciences Education Engineering Environmental Science Mathematics Physics Other

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Analysis of Disaster Vulnerability Areas in West Bandung Regency, West Java, Indonesia Usman, Dudi Nasrudin; Sukarsih, Icih; Permanasari, Yurika; Mildani, Deni; Widayati, Sri; Nuryahya, Himawan; Pulungan, Linda; Ramadhani, Rully Nurhasan
Journal of Geoscience, Engineering, Environment, and Technology Vol. 8 No. 4 (2023): JGEET Vol 08 No 04 : December (2023)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2023.8.4.10065

Abstract

Mineral resources, coal, and rock are one of the potentials possessed by Indonesia to be able to earn income from the mining sector. West Bandung Regency is one of the areas that have quite a lot of potential rock and mineral resources. The potential of this area is quite large, namely andesite rock, sand, limestone, and sandstone. Zeolite and others. On the other hand, the West Bandung area has a high potential and threat of being a disaster-prone. West Bandung Regency has the highest number of natural disasters occurring in the type of landslide disaster, which occurred 52 times in the period 2008-2016, or 68% of all disasters. Loss of economic value also occurs for mining material resources which are limited by the existence of a disaster zone. So it is necessary to carry out mitigation from the start to map disaster areas that have an impact on the distribution and existence of mining material resources. This study aims to identify and analyze the potential of rock resources in disaster-prone areas, so as to be able to prioritize conservation aspects for potential mining materials. The method used in this research is through literature study, mapping the potential of mining materials, mapping the potential of disaster-prone areas, processing of secondary data, and analysis using remote sensing. The results of this study are that the rocks in the West Bandung area are divided into groups of volcanic rocks, sedimentary rocks, and alluvial deposits. The volcanic rock group got a score of 3 because it was considered more prone to erosions than the sedimentary and alluvial rock groups which were scored 2 and 1. with a weighted level of disaster vulnerability. The zone of high disaster susceptibility is considered to have the highest probability of a disaster occurring. Therefore, in the final result, the overlap between the distribution of the potential for minerals and the zone of high disaster susceptibility results in a potential area for minerals that are relatively safe from disasters, both soil movement, and flooding. Potential mining resources in West Bandung Regency are Andesite basalt 1,860,412 ha (1.43%), Limestone 667.05 ha (0.50%), Sirtu 40,949.76 ha (31.35%%).
Pengaruh Learning Rate pada Artificial Neural Network terhadap Hasil Prediksi Cuaca Hujan Imran, Baihaky Muhammad; Yurika Permanasari
Jurnal Riset Matematika Volume 5, No.1, Juli 2025, Jurnal Riset Matematika (JRM)
Publisher : UPT Publikasi Ilmiah Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jrm.v5i1.6571

Abstract

Abstract. Artificial Neural Network (ANN) is a machine learning method that mimics the way the human brain processes information. ANN has the ability to recognize patterns from complex and non-linear data, making it suitable for use in various applications, including weather prediction. In this study, ANN is used to predict rainfall based on a dataset consisting of 8 attributes, namely year, day, rainfall, surface pressure, air temperature, humidity, wind speed, and wind direction. This research aims to understand the ANN algorithm in processing data on rainy weather prediction. The model training process is carried out using weight update optimization through Adam Optimizer, which is designed to accelerate convergence and improve prediction accuracy. Stages in the training process include data processing, determining parameters such as learning rate, and evaluating model performance using BMKG daily observation data for 184 days. The feedforward propagation process uses linear, ReLU, and sigmoid functions, while backpropagation with Adam Optimizer adapts the weights based on the learning rate and gradient of the loss function. The results show that the algorithm for rainy weather prediction is built with the parameters of learning rate, activation function, weight, bias, and optimizer as the main conditions. Therefore, these parameters are very important in the ANN algorithm to process data for rainy weather prediction. Abstrak. Artificial Neural Network (ANN) merupakan salah satu metode pembelajaran mesin yang meniru cara kerja otak manusia dalam memproses informasi. ANN memiliki kemampuan untuk mengenali pola dari data yang kompleks dan tidak linear, sehingga cocok digunakan dalam berbagai aplikasi, termasuk prediksi cuaca. Dalam penelitian ini, ANN digunakan untuk memprediksi curah hujan berdasarkan dataset yang terdiri dari 8 atribut, yaitu tahun, hari ke, curah hujan, tekanan permukaan, suhu udara, kelembaban, kecepatan angin, dan arah angin. Penelitian ini bertujuan untuk memahami algoritma ANN dalam memproses data pada prediksi cuaca hujan. Proses pelatihan model dilakukan dengan menggunakan optimasi pembaruan bobot melalui Adam Optimizer, yang dirancang untuk mempercepat konvergensi dan meningkatkan akurasi prediksi. Tahapan dalam proses pelatihan meliputi pengolahan data, penentuan parameter seperti learning rate, dan evaluasi performa model menggunakan data hasil pengamatan harian BMKG selama 184 hari. Proses feedforward propagation menggunakan fungsi linear, ReLU, dan sigmoid, sementara backpropagation dengan Adam Optimizer yang mengadaptasi bobot berdasarkan learning rate dan gradien dari fungsi loss. Hasil penelitian menunjukkan bahwa algoritma untuk prediksi cuaca hujan dibangun dengan parameter learning rate, fungsi aktivasi, bobot, bias, dan optimizer sebagai kondisi utama. Oleh karena itu, parameter-parameter ini sangat penting dalam algoritma ANN untuk memproses data pada prediksi cuaca hujan.
Perbandingan Algoritma Dijkstra dan Bellman Ford dalam Menentukan Rute Terpendek Cafe Hopping Gheamelia, Dieva; Respitawulan, R; Permanasari, Yurika
Jurnal Riset Matematika Volume 5, No.2, Desember 2025, Jurnal Riset Matematika (JRM)
Publisher : UPT Publikasi Ilmiah Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jrm.v5i2.8297

Abstract

Abstrak. Penelitian ini bertujuan untuk membandingkan dua algoritma pencarian rute terpendek, yaitu Dijkstra dan Bellman-Ford, dalam konteks kegiatan cafe hopping di Kota Bandung. Dengan semakin maraknya minat masyarakat terhadap eksplorasi tempat-tempat kuliner seperti cafe, dibutuhkan sistem yang mampu memberikan rute tercepat dan terpendek agar kegiatan tersebut lebih efisien. Penelitian dilakukan dengan membangun model graf berarah berbobot dari beberapa lokasi cafe populer, menggunakan jarak antar titik sebagai bobot sisi. Implementasi algoritma dilakukan menggunakan Python di Google Colab. Hasil pengujian menunjukkan bahwa meskipun kedua algoritma menghasilkan rute dan jarak yang sama dari titik awal ke tujuan akhir, Algoritma Dijkstra memproses data lebih cepat karena tidak melakukan relaksasi berulang seperti Bellman-Ford. Namun, Bellman-Ford memiliki keunggulan dalam menangani graf dengan bobot negatif. Penelitian ini menyimpulkan bahwa pemilihan algoritma harus disesuaikan dengan karakteristik graf dan kebutuhan aplikasi. Rekomendasi untuk pengembangan selanjutnya mencakup penggunaan graf dua arah dan integrasi data waktu tempuh aktual agar solusi lebih relevan terhadap kondisi nyata di lapangan. Abstract. This study aims to compare two shortest path algorithms, namely Dijkstra and Bellman-Ford, in the context of cafe hopping activities in Bandung City. With the growing public interest in exploring culinary destinations such as cafés, a system that can determine the most efficient and shortest route is essential. The research was conducted by modeling a directed weighted graph based on several popular cafe locations, using the distance between each point as edge weights. The algorithms were implemented using Python on the Google Colab platform. The results show that although both algorithms produced the same route and distance from the starting point to the destination, Dijkstra's algorithm processed the data faster due to its single-pass nature, unlike Bellman-Ford which performs multiple relaxation steps. However, Bellman-Ford has the advantage of handling graphs with negative weights. This study concludes that the selection of an algorithm should align with the graph characteristics and application needs. Future development is recommended to include bidirectional graphs and real-time travel time data to ensure more practical and realistic solutions in real-world scenarios. 
Implementasi Perhitungan dengan Metode Garis Lurus dan Saldo Menurun Ganda Hastanti, Andrea Widhi; Rohaeni, Onoy; Permanasari, Yurika
Jurnal Riset Matematika Volume 5, No.2, Desember 2025, Jurnal Riset Matematika (JRM)
Publisher : UPT Publikasi Ilmiah Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jrm.v5i2.8461

Abstract

Abstrak. Penentuan nilai objek sewa yang sesuai dengan prinsip-prinsip syariah merupakan aspek penting dalam transaksi keuangan Islami. Penelitian ini ditujukan kepada sebuah implementasi model berbasis Python yang dapat digunakan untuk menghitung nilai sewa objek secara akurat dan sesuai dengan ketentuan syariah. Dengan memanfaatkan bahasa pemrograman Python, penelitian ini menyusun algoritma yang mengintegrasikan metode penilaian syariah seperti metode garis lurus dan metode Saldo Menurun Ganda yang diakui dalam keuangan Islam. Tujuan dari penelitian ini adalah untuk mengetahui metode mana yang paling berpengaruh terhadap laba perusahaan dan untuk mengetahui metode mana yang efektif dipilih oleh perusahaan. Berdasarkan penelitian ini, metode garis lurus memiliki keuntungan yang tidak terlalu besar dan pada beban penyusutan tidak terlalu besar pada tiap tahunnya, sedangkan pada metode saldo menurun dari segi keuntungan memang besar akan tetapi pada beban penyusutan juga besar pertahunnya, maka akan berpengaruh pada tarif sewa kepada yang akan menyewa. Abstract. Determining the value of a leased asset in accordance with Sharia principles is an important aspect of Islamic financial transactions. This study focuses on a Python-based implementation model that can be used to accurately calculate the lease value of an asset in compliance with Sharia regulations. By leveraging the Python programming language, this research develops an algorithm that integrates Sharia valuation methods such as the straight- line method and the double declining balance method, both recognized in Islamic finance. The aim of this study is to identify which method has the greatest impact on the company’s profit and to determine which method is effectively preferred by the company. Based on the research findings, the straight-line method yields moderate profit and relatively low annual depreciation expenses, whereas the double declining balance method results in higher profits but also incurs higher annual depreciation expenses, which in turn affects the rental rates charged to lessees.
Co-Authors Abdul Kudus Aditia Rahmat Tulloh Angga Aditya Pratama Anneke Iswani A Annisa Melinia Rahayu Desy Pitriyani Didi Suhaedi Dinda Salsabilla Nur Aliana Dudi Nasrudin Usman Erwin Harahap Erwin Harahap Farid H Badruzzaman Farid H Badruzzaman Farid Hirji Badruzzaman Gheamelia, Dieva Hastanti, Andrea Widhi Icih Sukarsih Imran, Baihaky Muhammad Ismi Fadhillah Kiki Mulkiya Linda Pulungan Luthfiani Yasyifa M Yusuf Fajar M Yusuf Fajar M Yusuf Fajar Marlina, Emas Mildani, Deni Muhammad Iqbal Mubarok Nuryahya, HimawaN Onoy Rohaeni Onoy Rohaeni Ramadhani, Rully Nurhasan Ravi A. Salim Respitawulan, R Sindi Sri Sofiyani Sri Widayati