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All Journal Journal of Applied Data Sciences Sewagati
Putri, Endah Rokhmati Merdika
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The Model of Carbon Price Risk Prediction in European Markets Using Long Short-Term Memory- Geometric Brownian Motion Pradana, Yan Aditya; Mukhlash, Imam; Irawan, Mohammad Isa; Putri, Endah Rokhmati Merdika; Iqbal, Mohammad
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.536

Abstract

Accurate carbon market price prediction is one of the fundamentals in assessing the risks associated with carbon trading. Related studies on carbon price prediction were mainly focused on two major approaches: mathematical and/or machine learning models. Geometric Brownian Motion (GBM) is one of the mathematical models that can represent carbon price movements but requires modifying the sample size and the number of parameters for compiling the simulation numerically. Moreover, two critical parameters: (μ) mu and (σ) sigma need to be estimated to simulate the carbon price movements. In this study, the parameters μ and σ estimation are based on the average return value and standard deviation. However, if the carbon price movement is very volatile, we need to recognize its trend and characteristics by estimating the parameters precisely until there is no significant change (or stable) patterns. That is very expensive and may be intractable on high-dimensional data with less precise prediction. Therefore, we propose a hybrid model for carbon price prediction based on GBM with the parameter estimation using the Long Short-Term Memory (LSTM) model. The LSTM model was chosen because it has high accuracy in parameter estimation without losing the characteristics of the GBM stochastic model. Furthermore, Value at Risk (VaR) is utilized to measure the risk of carbon price volatility predictions. The simulation results showed the proposed model has higher prediction accuracy with a not-too-significant time difference, and the model is proven reliable in measuring future risks.
Penguatan Kompetensi Analitik dalam Layanan Publik di PT Jasamarga Transjawa Tol, Satelit-Surabaya Valeriana, Valeriana Lukitosari; Surjanto, Sentot Didik; Wardhani, Laksmi Prita; Putri, Endah Rokhmati Merdika; Safarina, Sena; Hakam, Amirul; Fadhilah, Helisyah Nur; Nabila, Galuh Putri; Nurviana, Asyira; Pratama, Fajar Wahyu; PL, Valentinus
Sewagati Vol 10 No 2 (2026): pre printed
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v10i2.8955

Abstract

Kemampuan analitik menjadi elemen penting dalam penguatan mutu layanan publik di era berbasis data. Pada sektor transportasi jalan tol, analisis yang tepat terhadap pendapatan, volume kendaraan, dan dinamika spasial wilayah berperan besar dalam menjaga kinerja operasional dan kepuasan pengguna. Kegiatan pengabdian masyarakat ini dilaksanakan sebagai sharing session antara tim akademik dari Matematika, Institut Teknologi Sepuluh Nopember (ITS) dan PT Jasamarga Transjawa Tol, Satelit–Surabaya. Kegiatan ini bertujuan mengenalkan teori, aplikasi, dan manfaat analisis peramalan dan spasial dalam konteks pengelolaan layanan publik. Model Autoregressive Integrated Moving Average (ARIMA) dibahas sebagai pendekatan untuk memprediksi pendapatan tol, sedangkan Generalized Space-Time Autoregressive (GSTAR) digunakan untuk memahami pola volume kendaraan antar gerbang tol. Selain itu, Geographically Weighted Negative Binomial Regression (GWNBR) dikenalkan untuk menganalisis pengaruh faktor spasial terhadap pembukaan lahan di sekitar akses tol. Pihak Jasamarga turut berbagi pengalaman mengenai kondisi lapangan, tantangan operasional, dan kejadian-kejadian yang memengaruhi kinerja layanan. Kegiatan ini memperkuat kolaborasi antara akademisi dan praktisi industri serta memberikan pemahaman bersama tentang potensi penerapan analisis data dalam peningkatan mutu layanan publik.
Co-Authors Daniel Happy Putra Hakam, Amirul Helisyah Nur Fadhilah Imam Mukhlash Mohammad Isa Irawan Nabila, Galuh Putri Nurviana, Asyira PL, Valentinus Pratama, Fajar Wahyu Safarina, Sena Sentot Didik Surjanto Valeriana, Valeriana Lukitosari Wardhani, Laksmi Prita YAN ADITYA PRADANA