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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) ILKOM Jurnal Ilmiah Jurnal Matematika UNAND Abdimas Toddopuli: Jurnal Pengabdian Pada Masyarakat Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika Jurnal Abdi Insani Square : Journal of Mathematics and Mathematics Education InPrime: Indonesian Journal Of Pure And Applied Mathematics Prima Abdika: Jurnal Pengabdian Masyarakat Journal of Fundamental Mathematics and Applications (JFMA) Journal of Mathematics and Applied Statistics Liquidity : Jurnal Ilmu Manajemen dan Bisnis Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat (JHP2M)
Muhammad Rifki Nisardi
Program Studi Ilmu Aktuaria FSAINS-UM Bulukumba
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Combined Truncated Spline and Fourier series in Nonparametric Biresponse Regression: A Case of Agricultural Productivity Husain, Hartina; Aristyarini, Rizki; Rahman, Andi Oxy Raihan Machikami; Rahmi, Nur; Nisardi, Muhammad Rifki
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i2.35319

Abstract

Agriculture plays a strategic role in supporting economic development and food security in Indonesia, particularly in South Sulawesi, one of the country’s primary rice-producing regions. Existing studies on agricultural productivity commonly rely on parametric or single-response models, which are less effective in capturing the nonlinear, locally varying, and interrelated characteristics of agricultural indicators. Addressing this research gap, the present study applies a biresponse nonparametric regression approach that integrates truncated splines and Fourier series to simultaneously model rice productivity and the food security index. This quantitative observational research uses secondary regional agricultural statistics, and the analytical procedure includes formulating the biresponse model, conducting diagnostic checks of key nonparametric assumptions, and estimating parameters using the Weighted Least Squares (WLS) method. Model selection was conducted using the Generalized Cross Validation (GCV) criterion, which indicated that rainfall was better approximated with truncated splines and extension workers with Fourier series. The optimal knot points were obtained at 1207.096 for rice productivity variable and 1207.556 for food security index variable, with one oscillation applied in the Fourier series and one knot for the truncated spline. The results show that the best model was obtained with the smallest Generalized Cross Validation (GCV) value of 21.38, a coefficient of determination of 94.85%, and a Mean Absolute Percentage Error (MAPE) of 9.68%. These results demonstrate the methodological advantage of the combined biresponse nonparametric model in accommodating complex data structures and provide actionable insights for policymakers in optimizing resource allocation, strengthening extension services, and enhancing food security strategies in South Sulawesi.
FRACTIONAL MATHEMATICAL MODELLING OF THE CORROSION RATE OF ALUMINUM 5083 IN A MARITIME ENVIRONMENT Muhammad Rifki Nisardi; Nur Rahmi; Muhammad Arkam Arifuddin; Hartina Husain; Kusnaeni Kusnaeni
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 3 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss3pp2117-2130

Abstract

Aluminum 5083 is one of the materials used for the construction of ship hulls due to its classification as a material with good corrosion resistance. Despite its high corrosion resistance, Aluminum 5083 remains susceptible to galvanic corrosion and pitting corrosion caused by marine environmental conditions. This study develops a mathematical model by adding chloride and passivation effects using fractional differential equations to describe the corrosion rate of Aluminum 5083. The model construction using a Fractional Differential Equation System (FDES) aims to capture memory effects to represent the complex corrosion dynamics accurately. Stability analysis of the fractional model shows that the system is locally asymptotically stable, with all eigenvalues satisfying the condition . Furthermore, a numerical solution approach using the PECE-PI method is employed to solve the model, demonstrating agreement between the simulation results and real-world corrosion phenomena. Involvement of different fractional orders α reveals an effect on the rates of increase and decrease in concentration for each variable. The smaller the value of fractional order α, the slower the concentration change process occurs.
A Hybrid Deep Learning–Machine Learning Approach for the Identification of Active Compounds in Blumea balsamifera (Sembung Leaves) Kusnaeni, Kusnaeni; Prihatin, Prihatin; Rahmatullah, Rahmatullah; Hafid, Mega Sartika; Nisardi, Muhammad Rifki; Nurmalasari, Nurmalasari; Andy B, Afif Budi
ILKOM Jurnal Ilmiah Vol 18, No 1 (2026)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v18i1.3195.165-179

Abstract

Blumea balsamifera (sembung) is a medicinal plant with well-documented antibacterial, anti-inflammatory, and analgesic properties. However, the systematic identification of its bioactive compounds remains a significant challenge due to the complexity and high dimensionality of LC–MS (Liquid Chromatography–Mass Spectrometry) data. This study aims to develop a robust computational framework for automated compound identification using a hybrid modeling approach.A hybrid model integrating Long Short-Term Memory (LSTM) and Extreme Gradient Boosting (XGBoost) was employed to enhance feature extraction and classification performance. The LSTM component was utilized to capture sequential dependencies in spectral data, while XGBoost performed optimized classification through gradient boosting. This integration enables efficient handling of complex spectral patterns and improves predictive accuracy.The proposed model achieved an accuracy of 91%, demonstrating strong performance in classifying and identifying bioactive compounds. Feature importance analysis identified several key compounds contributing to the model predictions, including Luteolin-7-methyl-ether, Umbelliferone, Blumeatin, Dihydroquercetin-7,4′-dimethylether, Chrysosplenol C, Blumealactone B, and Blumeaene E. These compounds are associated with known pharmacological activities, supporting the therapeutic relevance of B. balsamifera.The proposed hybrid LSTM–XGBoost framework provides an effective and scalable approach for LC–MS-based compound identification. This method reduces analytical complexity, enhances classification reliability, and offers a data-driven strategy for accelerating phytochemical research and bioactive compound validation
Sosialisasi Teknologi Tepat Guna: Stainless steel Sebagai Pengganti Plastik untuk Wadah Makanan dan Minuman Bagi UPT SMAS Al Iman Uluale Putri Mutia Monica; Suriyanto Bakri; Nurmalasari, Nurmalasari; Muhammad Rifki Nisardi; Syukrika Putri; Yusri Prayitna; Husain, Hartina; Kusnaeni, Kusnaeni; Muhammad Zhaky Putra; Dian Safitri
Abdimas Toddopuli: Jurnal Pengabdian Pada Masyarakat Vol. 7 No. 2 (2026): Volume 7, No 2, Juni 2026
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/00rq2x08

Abstract

Penggunaan wadah makanan berbahan plastik masih dominan di kalangan siswa SMA karena sifatnya yang praktis dan ekonomis. Namun, penggunaan berulang dan paparan panas berpotensi menyebabkan pelepasan mikroplastik yang berdampak pada kesehatan. Di sisi lain, stainless steel merupakan material alternatif yang memiliki ketahanan korosi tinggi, sifat higienis, serta umur pakai yang lebih panjang. Permasalahan utama yang dihadapi mitra adalah rendahnya pemahaman siswa mengenai risiko penggunaan plastik serta keunggulan stainless steel sebagai material yang lebih aman. Kegiatan pengabdian ini bertujuan meningkatkan literasi sains siswa melalui sosialisasi teknologi tepat guna. Metode yang digunakan meliputi pemaparan materi interaktif, diskusi, serta evaluasi melalui pre-test dan post-test. Hasil kegiatan menunjukkan adanya peningkatan pemahaman siswa terkait bahaya mikroplastik dan pentingnya pemilihan material yang tepat. Kegiatan ini berkontribusi dalam membentuk kesadaran siswa terhadap penggunaan material yang aman, higienis, dan berkelanjutan dalam kehidupan sehari-hari.
Co-Authors Amar, Muh Ikhsan Andy B, Afif Budi Antonin Robinet Aristyarini, Rizki Baehaqi Bakri, Suriyanto Chetehouna, Khaled Dian Safitri Dian Safitri Hafid, Mega Sartika Harianto Harianto Hartina Husain Herlambang, Dwicki Herlambang, Dwicky Hukmah Hukmah Hukmah Hukmah Hukmah HUkmah Hukmah, Hukmah Husain, Hartina Kasbawati Kasbawati Khaeruddin Khaeruddin Khaeruddin Khaeruddin Khaled Chetehouna Kusnaeni Kusnaeni Kusnaeni Kusnaeni Kusnaeni, Kusnaeni M, Suriani M. Yogi Riyantama Isjoni M.R, Andi Oxy Rayhan Muhammad Arkam Arifuddin Muhammad Zhaky Putra Nur Ahniyanti Rasyid Nur Rahmi Nur Rahmi Nurahmad, Muhammad Fadhil Nurlia Nurlia Nurmalasari Nurmalasari Nursamsi, Nursamsi Nurul Azizah Prayitna, Yusri Prihatin Prihatin, Prihatin Putra, Restu Ananda Putri Mutia Monica Rahman, Andi Oxy Raihan Machikami Rahmatullah Rahmatullah Raihan M.R, Andi Oxy Ramadhani, Dewi Citra Resky, Aprizal Robinet, Antonin Sasolo, Ryo Hartawan Sri Wahyuni Nurzak Subhan Khalifah Azis Sulma Sulma Sulma Sulma, Sulma Suriani M Suriani M Suriani M Suriani Suriani Syukrika Putri Syukrika Putri Ulfatun Hasanah Yusri Prayitna Yusrini, Yusrini Zaitun Zaitun Zaitun