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All Journal Jurnal IPTEK INDONESIAN JOURNAL OF APPLIED PHYSICS Zero : Jurnal Sains, Matematika, dan Terapan Jurnal Pengabdian Masyarakat Asia KUBIK: Jurnal Publikasi Ilmiah Matematika Enthusiastic : International Journal of Applied Statistics and Data Science MATHunesa: Jurnal Ilmiah Matematika UNP Journal of Statistics and Data Science RENATA Jurnal Pengabdian Masyarakat Kita Semua Indonesian Journal of Applied Mathematics Parameter: Jurnal Matematika, Statistika dan Terapannya TeknoKreatif: Jurnal Pengabdian kepada Masyarakat JPEMAS: Jurnal Pengabdian Kepada Masyarakat Indonesian Actuarial Journal
Indah Gumala Andirasdini
Department Of Actuarial Science, Institut Teknologi Sumatera, 35365. Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Other

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Comparative Modeling of Pineapple Production Using Gaussian GLM and Random Forest Regression Radot MH Siahaan; Indah Gumala Andirasdini; Fuji Lestari; Dwi Mahrani; Amalia Listiani
ZERO: Jurnal Sains, Matematika dan Terapan Vol 10, No 1 (2026): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v10i1.28721

Abstract

This study aims to conduct a comparative modelling of pineapple production at PT Great Giant Pineapple (GGP) using Gaussian GLM as parametric statistical approach and Random Forest Regression method as machine learning based on monthly data from 2014 to 2022. Multicollinearity testing and distribution fitting were conducted to validate the Gaussian assumption. For the Random Forest Regression, hyperparameters were optimized by tuning the number of trees (ntree) and the number of predictors at each split (mtry) with model stability evaluated using Out-of-Bag (OOB) error. The Gaussian GLM achieved a MAPE of 8.41% (R² = 0.106) for the GP3 clone and 11.27% (R² = 0.149) for the F180 clone. Random Forest Regression produced a testing MAPE of 9.28% (R² = 0.144) for GP3 and 12.11% (R² = 0.105) for F180. While both models achieved low prediction error based on MAPE, they differed in identifying influential variables and showed limited explanatory power as indicated by low R² values. The Gaussian GLM identifies air pressure as significant for both clones and rainfall for F180 clone, while Random Forest consistently identifies rainfall as the most influential predictor. These findings confirm the complementary strengths of parametric and machine learning approaches in supporting climate-based production planning and risk mitigation.
Density Functional Theory (DFT) Study on Molecular Interaction between H2O and Graphene Daffa Hadyan Akmal; Amrina Mustaqim; Indah Gumala Andirasdini; Septia Eka Marsha Putra
Jurnal IPTEK Vol 30, No 1 (2026): May
Publisher : LPPM Institut Teknologi Adhi Tama Surabaya (ITATS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.iptek.2026.v30i1.8094

Abstract

Graphene has attracted significant attention as an anode material due to its high surface area and unique electronic properties. This study explores the adsorption behavior of H₂O molecules on graphene using Density Functional Theory (DFT) with the van der Waals density functional (vdW-DF). Various molecular orientations (zero-leg, one-leg, and two-leg) and adsorption sites (top, bridge, hollow) were analyzed. The results show that the most stable configuration is the two-leg orientation at the hollow site, with an adsorption energy of -0.123 eV. The findings suggest that the stability of the adsorbed system is governed more by the interaction between hydrogen atoms and the carbon surface than by the oxygen atom. All stable structures are characterized by adsorption distances between 2.8 and 3.2 A. The interaction is classified as physisorption due to its low energy and minimal charge transfer. These results are consistent with previous studies, confirming the key role of molecular orientation and adsorption site in determining the adsorption behavior of H₂O on graphene.
Peningkatan Literasi dan Kompetensi IoT Siswa SMK Dharmapala Panjang Listra Yehezkiel Ginting; Ahmad Suaif; Amrina Mustaqim; Nike Dwi Grevika Drantantiyas; Septia Eka Marsha Putra; Christio Revano Mege; Indah Gumala Andirasdini
JPEMAS: Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 2 (2026): JPEMAS: Jurnal Pengabdian Kepada Masyarakat
Publisher : Yayasan Pendidikan Tanggui Baimbaian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71456/adc.v4i2.1758

Abstract

Kegiatan pengabdian kepada masyarakat ini dilatarbelakangi oleh masih terbatasnya pemahaman dan keterampilan siswa SMK dalam menguasai teknologi Internet of Things (IoT) serta belum optimalnya pembelajaran berbasis praktik yang sesuai dengan kebutuhan industri di era digital. Tujuan kegiatan ini adalah untuk meningkatkan literasi teknologi, pemahaman konsep, dan keterampilan praktis siswa melalui pelatihan dan penerapan IoT berbasis pendekatan STEM (Science, Technology, Engineering, and Mathematics). Metode yang digunakan meliputi ceramah, diskusi interaktif, praktik langsung perakitan sistem IoT sederhana, serta evaluasi melalui pretest dan posttest terhadap 88 siswa jurusan kelistrikan SMK Dharmapala Panjang. Hasil kegiatan menunjukkan peningkatan signifikan pada seluruh indikator pemahaman, yaitu pemahaman implementasi IoT meningkat dari 43 menjadi 88 peserta (51,14%), komponen sistem IoT dari 55 menjadi 85 peserta (34,09%), jaringan komunikasi IoT dari 23 menjadi 84 peserta (69,32%), serta langkah pembuatan proyek IoT dari 22 menjadi 88 peserta (75,00%). Selain itu, peserta mampu merakit dan mengoperasikan sistem pengendalian lampu berbasis IoT menggunakan mikrokontroler secara mandiri. Hasil ini menunjukkan bahwa pendekatan pelatihan yang mengintegrasikan teori dan praktik secara langsung efektif dalam meningkatkan kompetensi teknis dan literasi digital siswa, sehingga kegiatan ini berkontribusi dalam mendukung penguatan pendidikan vokasi yang adaptif terhadap perkembangan teknologi dan kebutuhan dunia kerja.
Density Functional Theory (DFT) and Quasi Harmonic Approximation (QHA) on Isotope effect of Methane Absorbed on Ag(111) Surface Septia Eka Marsha Putra; Indah Gumala Andirasdini
INDONESIAN JOURNAL OF APPLIED PHYSICS Vol 14, No 1 (2024): April
Publisher : Department of Physics, Sebelas Maret University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijap.v14i1.71754

Abstract

We investigated the isotope effect of methane (CH4) on Ag(111) using van der Waals density functional and the quasi-harmonic approximation.In this study, we combined two methods to investigate the nuclear quantum effect in methane adsorption on an Ag(111) surface. We obtained that the adsorption potential energies of CD4on fcc Ag(111) surfaces are shallower than those of CH4, whereas the equilibrium distances from the surface are larger.The similiar finding also observed in our previous study, however, Ag(111) gives smaller energies.It is found that the similar softening of the C-H bond pointing toward the surface is the cause of the isotope effect. This softening leading to lowering the vibrational frequency and large zero-point energy difference between CH4and CD4. 
Forecasting and Financial Risk Analysis Using ARIMA Intervention Model: A Case Study on JMAS Tbk Rina Yuliantika; Indah Gumala Andirasdini
Indonesian Actuarial Journal Vol. 2 No. 1 (2026): Indonesian Actuarial Journal
Publisher : Persatuan Aktuaris Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65689/iajvol2no1pp013-023

Abstract

The capital market is characterized by high volatility, making accurate forecasting and risk measurement essential for investment decision-making. This study aims to apply the Autoregressive Integrated Moving Average (ARIMA) intervention model and the Value at Risk (VaR) approach for stock prices forecasting and finansial risk analysis.The data consist of monthly stock prices of PT Asuransi Jiwa Syariah Jasa Mitra Abadi Tbk (JMAS) from January 2018 to December 2025. The ARIMA intervention model is applied to identify and quantify structural changes caused by external shocks, particularly the COVID-19 pandemic. The results indicate that the ARIMA (1,2,0) intervention model is the most appropriate model, with a step intervention function reflecting a sudden and permanent impact on stock price movements. The model satisfies diagnostic assumptions and demonstrates good forecasting accuracy, with a Mean Absolute Percentage Error (MAPE) of 13.01%. Forecasting results for January to March 2026 show that stock prices are expected to remain relatively low, indicating a slow post-pandemic recovery. Financial risk is measured using the Cornish-Fisher Value at Risk (VaR) approach at a 95% confidence level. The estimated VaR is -0.4245 indicating a maximum potential loss of 42.45% over a one-month period. This high level of risk reflects extreme market conditions during the COVID-19 period, which significantly increased volatility. This study contributes to financial analysis by integrating intervention-based time series modeling with risk measurement in a unified framework.
EKSPLORASI HUBUNGAN KATEGORI VOLUME PERDAGANGAN DAN VOLATILITAS HARGA SAHAM IHSG MENGGUNAKAN ANALISIS KORESPONDENSI Indah Andirasdini
MATHunesa: Jurnal Ilmiah Matematika Vol. 14 No. 02 (2026)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v14n02.p64-71

Abstract

Pasar modal merupakan elemen penting dalam perekonomian, di mana volume perdagangan dan pergerakan harga saham menjadi indikator utama untuk memahami dinamika pasar. Penelitian ini bertujuan untuk mengeksplorasi hubungan antara kategori volume perdagangan dan kategori volatilitas Indeks Harga Saham Gabungan (IHSG) periode 1 Januari 2024–31 Desember 2025. Metode yang digunakan adalah Analisis Korespondensi, yang diawali dengan pengolahan data historis harian, perhitungan volatilitas berbasis rentang harga harian, kemudian dikategorikan menggunakan pendekatan kuantil (33% dan 66%) menjadi tiga kelompok: rendah, sedang, dan tinggi, penyusunan tabel kontingensi. Hubungan awal antar variabel diuji menggunakan uji Chi-Square, kemudian dipetakan dalam ruang berdimensi rendah melalui dekomposisi singular value decomposition (SVD). Hasil menunjukkan bahwa nilai Chi-Square signifikan pada taraf 5%.Visualisasi peta korespondensi memperlihatkan bahwa volume besar cenderung berhubungan dengan volatilitas tinggi, volume sedang berasosiasi dengan volatilitas sedang, dan volume kecil berasosiasi dengan volatilitas rendah. Temuan ini menunjukkan bahwa secara kategorikal, aktivitas volume memiliki pola keterkaitan terhadap tingkat volatilitas pasar pada periode pengamatan.
Conditional Covariance Estimation Using CCC-GARCH for Markowitz Portfolio Optimization Indah Andirasdini; Delila Anggraini Siringo Ringo
UNP Journal of Statistics and Data Science Vol. 4 No. 3 (2026): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol4-iss3/544

Abstract

The time-varying volatility and heteroskedasticity of stock returns require appropriate volatility modeling for portfolio construction. This study aims to model stock return volatility using the Constant Conditional Correlation Generalized Autoregressive Conditional Heteroskedasticity (CCC-GARCH) and apply the estimated conditional covariance matrix to optimal portfolio construction based on the Markowitz model. The study employs daily returns of seven sector-representative stocks listed in the LQ45 Index from February 2020 to August 2025. The analysis consists of ARMA-GARCH modeling to estimate the conditional volatility of individual stock returns, CCC-GARCH estimation to obtain the conditional covariance matrix, and portfolio optimization using the Markowitz model. Portfolio performance was evaluated using the Sharpe Ratio. The results indicate that all stock returns exhibit heteroskedasticity, with the ARMA-GARCH(1,1) model providing the best volatility specification for each stock. The CCC-GARCH-based conditional covariance matrix produced an optimal portfolio with an expected return of 0.00041210, a portfolio variance of 0.00011439, and a Sharpe Ratio of 0.02103415. These findings show that the CCC-GARCH model provides a more representative estimate of portfolio risk and supports optimal portfolio construction under dynamic market conditions.
Co-Authors Ahmad Suaif Aliem, Dien Manarul Amrina Mustaqim Amrina Mustaqim Ayu Sofia Azzanina, Nanda Baiti, Putri Isnaini Cahyaning Berliana Ratam, Aldila Nur Indah Christio Revano Mege Daffa Hadyan Akmal Delila Anggraini Siringo Ringo Dewi, Karina Sylfia Dila Tirta Julianty Dila Tirta Julianty Dwi Mahrani Fuji Lestari Fuji Lestari Gustina K. S, Annisa Hevita Irwan, Sri Efrinita Josepa , Tiffany Audrey Listiani, Amalia Listra Yehezkiel Ginting Marisa Marisa Muklas Rivai Nike Dwi Grevika Drantantiyas Paiz Jalaludin Radot MH Siahaan Rahman, Alrafiful Ratih Suryaningsih Rina Yuliantika Rivai, Muklas Rosni, Rosni Saputra, Desta Septia Eka Marsha Putra Septia Eka Marsha Putra Septia Eka Marsha Putra Simarmata, Gabriel Camoranesa Yulita, Tiara