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All Journal Jurnal Ekonomi Kuantitatif Terapan dCartesian: Jurnal Matematika dan Aplikasi Media Statistika Indonesian Journal of Mathematics and Natural Sciences Gadjah Mada International Journal of Business Jurnal Sains Matematika dan Statistika Desimal: Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Limits: Journal of Mathematics and Its Applications International Journal of Computing Science and Applied Mathematics International Journal on Emerging Mathematics Education Zero : Jurnal Sains, Matematika, dan Terapan Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) ComTech: Computer, Mathematics and Engineering Applications Jurnal Linguistik Komputasional Imajiner: Jurnal Matematika dan Pendidikan Matematika KAIBON ABHINAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal Abdi Insani SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi) Journal of Science and Science Education Jurnal Akuntansi dan Keuangan Prosiding University Research Colloquium Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya d'Cartesian: Jurnal Matematika dan Aplikasi Limits: Journal of Mathematics and Its Applications
Didit Budi Nugroho
Universitas Kristen Satya Wacana
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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Using an LSTM Neural Network to Improve Symmetric and Asymmetric GARCH Volatility Forecast Rahmawanto, Setya Budi; Nugroho, Didit Budi; Trihandaru, Suryasatriya
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.24614

Abstract

Volatility forecasting is crucial for financial risk management, yet traditional models like GARCH struggle with nonlinearities and asymmetric effects. This study leverages Long Short-Term Memory (LSTM) neural networks to enhance symmetric and asymmetric GARCH models, addressing these limitations. By integrating LSTM with GARCH, GARCH-X, and Realized GARCH frameworks, we propose hybrid models (Baseline and Extended versions) to improve forecasting accuracy. Using daily data from FTSE 100, Nikkei 225, and S&P 500 indices (2000–2020), we compared hybrid models against traditional models. Results show that the Extended LSTM hybrid model outperforms both traditional GARCH-type models and the Baseline LSTM, capturing complex volatility patterns more effectively. The Extended model’s architecture, featuring ReLU, GRU, and dropout layers, mitigates over-smoothing and enhances responsiveness to market fluctuations. This research demonstrates LSTM’s potential to refine volatility forecasting, offering valuable insights for investors and risk managers.
Learning Algorithms of SVR, DTR, RFR, and XGBoost (Case Study: Predictive Maintenance of Fuel Consumption) Parhusip, Hanna Arini; Lea, Lea; Trihandaru, Suryasatriya; Nugroho, Didit Budi; Santosa, Petrus Priyo; Hariadi, Adrianus Herry
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.85657

Abstract

The most complex aspect of predictive maintenance (PdM) for heavy vehicles is accurately forecasting fuel consumption as it is both critical and challenging to achieve optimal efficiency while minimizing expenses. Overfitting and failure to capture the existing data's linear relationships seem to remain the most persistent issues with traditional methods. In order to achieve this, the following techniques were analyzed to choose the best fuel consumption forecaster: Support Vector Regression (SVR), Decision Tree Regression (DTR), Random Forest Regression (RFT), and XGBoost. The models were implemented and their performance measured using Mean Squared Error (MSE). The analysis revealed that SVR surpassed the others with a linear kernel (C=10) achieving the lowest MSE rates of 0.26, while DTR, RFR, and XGBoost earned significantly higher 3.375, 2.857, and 3.857 (MSEs). The other models lagged behind SVR because SVR was more effective in capturing linear relations and managing overfitting, a dominating issue with decision-tree based models. This points out another important aspect of predictive maintenance (PdM) : the appropriate machine learning technique plays a very important role in accurately predicting fuel consumption of heavy trucks, which improves precision and fuel efficiency.
Modern Ethnomathematics Mainstreaming through Mathematics Entrepreneurship Using Mathematical Ornaments Parhusip, Hanna Arini; Purnomo, Hindriyanto Dwi; Nugroho, Didit Budi; Sri Kawuryan, Istiarsi Saptuti Sri
International Journal on Emerging Mathematics Education IJEME, Vol. 5 No. 2, September 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijeme.v5i2.15118

Abstract

Modern ethnomathematics is proposed in this article by introducing curves and surfaces to objects based on commonly used mathematics. There are 2 types of objects, batik and ornament. The object is known as Batima, which means a mathematical motif made in a batik stamp. The same design can be used to design ornaments, souvenirs, accessories or other household items such as glasses, t-shirts and other materials. The formation of ethnomathematics is driven by entrepreneurial activities. The method starts with the expansion of the circular and spherical equations based on the variation of the power form which was originally 2 in the equation to be valued at random (say p). The other used equations are parametric equations, especially the hypocycloid which is extended to both curves and surfaces with spherical coordinates. In addition, derivative operators can be applied. Product manufacturing is carried out by at least 10 household businesses around Salatiga and Jogjakarta and its surroundings. In order to sustain the mainstreaming of modern ethnomathematics, entrepreneurial activities are carried out with existing materials through exhibitions and competitions that are followed. Likewise, the use of social media and marketplaces are explored to mainstream the modern ethnomathematics into society.
Learning geometry through surface creation from the hypocycloid curves expansion with derivative operators for ornaments Parhusip, Hanna Arini; Purnomo, Hindriyanto Dwi; Nugroho, Didit Budi; Kawuryan, Istiarsi Saptuti Sri
Desimal: Jurnal Matematika Vol. 4 No. 1 (2021): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v4i1.7385

Abstract

Geometry is one of the particular problems for students. Therefore, several methods have been developed to attract students to learn geometry. For undergraduate students, learning geometry through surface visualization is introduced. One topic is studying parametric curves called the hypocycloid curve. This paper presents the generalization of the hypocycloid curve. The curve is known in calculus and usually is not studied further. Therefore, the research's novelty is introducing the spherical coordinate to the equation to obtain new surfaces. Initially, two parameters are indicating the radius of 2 circles governing the curves in the hypocycloid equations. The generalization idea here means that the physical meaning of parameters is not considered allowing any real numbers, including negative values. Hence, many new curves are observed infinitely. After implementing the spherical coordinates to the equations and varying the parameters, various surfaces had been obtained. Additionally, the differential operator was also implemented to have several other new curves and surfaces. The obtained surfaces are useful for learning by creating ornaments. Some examples of ornaments are presented in this paper.
Improvement of Real-GJR Model using Jump Variables on High Frequency Data Nugroho, Didit Budi; Wulandari, Nadya Putri; Alfagustina, Yumita Cristin; Parhusip, Hanna Arini; Tita, Faldy; Susanto, Bambang
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 4 (2024): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i4.24294

Abstract

Volatility is a key indicator in assessing risk when making investment decisions. In the world of financial markets, volatility reflects the degree to which the value of a financial asset fluctuates over a given period. The most common way to measure the future loss potential of an investment is through volatility. Focusing on the Realized GJR (RealGJR) volatility model, which consists of return, conditional volatility, and measurement equations, this study proposes the RealGJR-CJ model developed by decomposing the exogenous variable in the volatility equation of RealGJR into continuous C and discontinuous (jump) J variables. The decomposition of exogenous variables makes the RealGJR-CJ model follow realistic financial markets, where the asset volatility is a continuous process with some jump components. As an empirical illustration, the models are applied to an index in the Japanese stock market, namely Tokyo Stock Price Index, covering from January 2004 to December 2011. The observed exogenous variable in the volatility equation of RealGJR models is Realized Volatility (RV), which is calculated using intraday data with time intervals of 1 and 5 minutes. Adaptive Random Walk Metropolis method was employed in Markov Chain Monte Carlo algorithm to estimate the model parameters by updating the parameters during sampling based on previous samples from the chain. From the results of running the MCMC algorithm 20 times, the mean of the information criteria of competing models is significantly different based on standard deviation and the result suggests that the model with continuous and jump variables can improve the model without jump. The best fit model is provided by RealGJR-CJ with the adoption of 1-minute RV data. 
WORKSHOP PERSIAPAN PEMBELAJARAN MATEMATIKA DENGAN BANTUAN PAKET PROGRAM KOMPUTER (GEOGEBRA/R) UNTUK MGMP MATEMATIKA SMA KABUPATEN SEMARANG JAWA TENGAH Setiawan, Adi; Parhusip, Hanna Arini; Nugroho, Didit Budi; Sasongko, Leopoldus Ricky; Rudhito, Andy; Utomo, Beni; Fernandez, Aloysius Joakim
Jurnal Abdi Insani Vol 12 No 2 (2025): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v12i2.2046

Abstract

The world is heading towards the era of Society 5.0, which requires learning Mathematics as much as possible to be easy to understand and interesting for students. Technology-based visualization, such as the use of Geogebra, can help students understand Mathematics formulas better. Therefore, teachers who are members of the High School Mathematics MGMP need to have insight into the importance of technology-based learning as a strategy to improve teaching quality. This activity aims to open teachers' insights into visualization and technology-based Mathematics learning, and help them develop creative learning modules and tools. The activity method includes four meetings consisting of webinars and workshops. The first webinar contains an introduction to the importance of visualization-based learning; the second webinar provides training in using Geogebra/R onsite or hybrid; the third webinar trains the creation of learning modules; and the fourth webinar presents the theory of writing scientific papers and using Mendeley. The results show that teachers are able to make creative and interesting lesson plans and learning modules using Geogebra/R, and motivate students to learn Mathematics independently or in groups. Some of the modules produced have been tested at school, although none of the participants have succeeded in making papers ready for publication. This activity succeeded in improving the ability of teachers to utilize technology for learning Mathematics.
MATHEMATICAL SILVER FOR ENTREPRENEURIAL MATHEMATICS Parhusip, Hanna Arini; Nugroho, Didit Budi; Purnomo, Hindriyanto Dwi; Kawuryan, Istiarsi Saptuti Sri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (472.285 KB) | DOI: 10.30598/barekengvol16iss4pp1175-1184

Abstract

This article shows the result of entrepreneur mathematics by creating mathematical objects from silver. The objects discussed here are accessories to introduce undergraduate students to integrating several aspects of learning mathematics. These are learning geometry modernly, mathematical art, popularizing mathematics for society, introducing entrepreneurial values using mathematics, teamwork for achieving targets, and considering local heritage in mathematics. These aspects are blended into activity by creating designs and producing products based on the obtained designs. The particular product for this activity is creating silver accessories. The used research method is initiated by creating designs with the help of software where the surface equations are known. After the designs are obtained, the designs are communicated to the silver craftsman to be a partner in design testing and manufacturing of accessories products using the given designs. The size and the similarity of perceptions to the appearance of the design are discussed because the actual design is a three-dimensional image but expressed in objects to be two- dimensional objects. After productions are obtained, the accessories are managed to be promoted to the marketplace and social media as a form of entrepreneurial activity with materials starting from mathematics.
Model Regresi untuk Return Aset dengan Volatilitas Mengikuti Model GARCH(1,1) Berdistribusi Epsilon-Skew Normal dan Student-t Didit Budi Nugroho; Kristia Anggraeni; Hanna Arini Parhusip
Limits: Journal of Mathematics and Its Applications Vol. 17 No. 2 (2020): Limits: Journal of Mathematics and Its Applications Volume 17 Nomor 2 Edisi De
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Studi ini mendiskusikan dua perluasan dari model GARCH(1,1), yaitu AR(1)-GARCH(1,1) dan MA(1)-GARCH(1,1), yang diperoleh dengan cara menambahkan Autoregression tingkat 1 atau Moving Average tingkat 1 pada persamaan return . Untuk kasus ini, error dari return diasumsikan berdistribusi Normal, Skew Normal (SN), Epsilon Skew Normal (ESN), dan Student- t . Analisis terhadap model didasarkan pada pencocokan model untuk return dari indeks saham FTSE100 periode harian dari Januari 2000 sampai Desember 2017 dan indeks saham TOPIX periode harian dari Januari 2000 sampai Desember 2014. Model yang dipelajari diestimasi menggunakan metode GRG ( Generalized Reduced Gradient ) Non Linear yang tersedia di Solver Excel dan juga metode Adaptive Random Walk Metropolis (ARWM) yang diimplementasikan pada program Scilab. Hasil estimasi dari kedua alat bantu tersebut menunjukkan nilai-nilai yang hampir sama, mengindikasikan bahwa Solver Excel mempunyai kemampuan yang handal dalam mengestimasi parameter model. Uji rasio log- likelihood dan AIC ( Akaike Information Criterion ) menunjukkan bahwa model dengan distribusi ESN lebih unggul dibandingkan dengan model-model berdistribusi tipe normal lainnya untuk setiap kasus model dan data pengamatan, bahkan ini bisa mengungguli distribusi Student- t pada suatu model dan data pengamatan. Lebih lanjut, model-model dengan penambahan proses regresi di persamaan return menyediakan pencocokan yang lebih baik daripada model dasar, dimana pencocokan terbaik untuk kedua data pengamatan diberikan oleh model AR(1)-GARCH(1,1) berdistribusi Student- t .
Study on The Continuous-Jump Behavior of Asset Return Volatility Through The GJR Model Alfagustina, Yumita Cristin; Nugroho, Didit Budi; Tita, Faldy
Prosiding University Research Colloquium Proceeding of The 17th University Research Colloquium 2023: Bidang MIPA dan Kesehatan
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Generalized Auto-Regressive Conditional Heteroskeasticity (GARCH) is a model used to predict the volatility of returns. Volatility is a statistical measure of the movement of returns for securities (financial instruments that can only be traded through markets or securities companies) or certain market indices. Then the GARCH model was further developed into an asymmetric form, namely conditional volatility and returns have a relationship, namely the GJR model which is an abbreviation of the name (Glosten- Jagannathan-Runkle). This research focuses on the GJR-X by adding high-frequency exogenous variables in volatility process and on the GARCH-CJ which is a decomposition of the exogenous variable X, namely the continuous component C (Continuous) and the jump J (Jump). TOPIX data (Tokyo Stock Price Index) is the real data used in this study. To estimate the model parameters, the ARWM (Adaptive Random Walk Metropolis) method will be used with the MCMC (Markov Chain Monte Carlo) algorithm. First, it was found that the ARWM method is good at estimating parameters. Second, the AIC value of GJR-CJ was smaller than that of GJR-X, which means that GJR-CJ had better data fitting.
PENGABDIAN MASYARAKAT UNTUK PEMBELAJARAN CODING ARTIFICIAL INTELLIGENCE KEPADA SISWA SMP KRISTEN WONOSOBO Trihandaru, Suryasatriya; Parhusip, Hanna Arini; Kurniawan, Johanes Dian; Susanto, Bambang; Setiawan, Adi; Nugroho, Didit Budi
Jurnal Abdi Insani Vol 11 No 2 (2024): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v11i2.1536

Abstract

Artificial intelligence and the Internet of Things (AIOT) have been widely used by various activities, especially in the millennial generation. However, scientific technology has not been widely introduced in education. Additionally, schools experience a decline in student enrollment every year, so it is necessary to carry out innovative learning actions that can be introduced to the community through students. Innovation learning is demonstrated by providing coding lessons that students have never done before so that AIOT becomes part of the learning. Therefore, coding as a learning method is  introduced to junior students so they can get to know AIOT early. The method used is making a device called AIOT-kit with training to be able to directly monitor environmental parameters such as temperature and humidity. The Internet of Things was introduced, which uses ThinkSpeak as a dashboard for making observations. This device was made by students so that they could follow the process from making the AIOT-kit hardware and related coding to utilization. It is shown that AIOT-kit is not yet known to students, including how to code in it. AIOT is an urgent need to access developing related technology. This activity is part of the service team's efforts to make a positive contribution to the community and school environment. After carrying out this activity, there was a change in how students could make their own AIOT-kit devices while also coding. The school even received an award from the local government for the innovation activities carried out during that period.
Co-Authors A. Setiawan A.A. Ketut Agung Cahyawan W Adi Setiawan Agus Priyono Alfagustina, Yumita Cristin ALOYSIUS JOAKIM FERNANDEZ Anggita M Kusumawati Arisandi, Nia Lestari Atyanta Nika Rukmasari Bambang Susanto Beni Utomo Daivi Wardani, Daivi Daniel Eliazar Latumaerissa Dini Kurniawati E. D. Saputri, E. D. Erlina Prihatnani Faldy Tita Hanafi, Fika Maula Hanna Arini Parhusip Hariadi, Adrianus Herry Hariyanto, H Hindriyanto Dwi Purnomo Irfani, Nur Istiarsi Saptuti Sri Kawuryan Istiarsih Saputri Sri Kawuryan Kezia Natalia Putri Prasetia Kholil, Zaini Kristia Anggraeni Kurniawan, Johanes Dian Lea, Lea Lennox Larwuy Leopoldus Ricky Sasongko Leopoldus Ricky Sasongko Lydia Soepriyani Fallo Mince M. M. Rosely Nia Lestari Arisandi Obed Christian Dimitrio Pamungkas, Bintoro Ady Panjaitan, Lam P. Panjaitan, Lam Peter Prasetia, Kezia Natalia Putri Puspitasari, Agnes Dhika Putri, Zefania Sasongko Rahmawanto, Setya Budi Rebecca Rorimpandey Rorimpandey, Rebecca Rudhito, Andy Santosa, Petrus Priyo Sassongko, Leopoldus Ricky Sri Kawuryan, Istiarsi Saptuti Sri Suryasatriya Trihandaru Tundjung Mahatma Veny M Ningtyas Wijaya, Melina Tito Wulandari, Nadya Putri Yulius Pratomo