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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Agromet IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Techno.Com: Jurnal Teknologi Informasi CAUCHY: Jurnal Matematika Murni dan Aplikasi Lingua Jurnal Bahasa dan Sastra PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Ilmu Komputer dan Agri-Informatika Journal of the Indonesian Mathematical Society Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Seminar Nasional Informatika (SEMNASIF) Widyariset Indonesian Journal of Science and Technology Jurnal Sains Matematika dan Statistika Al-Jabar : Jurnal Pendidikan Matematika JOIV : International Journal on Informatics Visualization JURNAL SIMETRIK Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Matematika: MANTIK MAJALAH ILMIAH GLOBE Desimal: Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Zero : Jurnal Sains, Matematika, dan Terapan Teorema: Teori dan Riset Matematika Jambura Journal of Mathematics Jambura Geoscience Review SALINGKA Jurnal Matematika UNAND Building of Informatics, Technology and Science Sains, Aplikasi, Komputasi dan Teknologi Informasi Indonesian Journal of Electrical Engineering and Computer Science InPrime: Indonesian Journal Of Pure And Applied Mathematics Journal of Innovation Information Technology and Application (JINITA) Widyariset Jambura Journal of Biomathematics (JJBM) Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Journal of Mathematics: Theory and Applications Jurnal Pijar MIPA Jurnal Sains Terapan : Wahana Informasi dan Alih Teknologi Pertanian Journal of Applied Agricultural Science and Technology Milang Journal of Mathematics and Its Applications Jurnal Sintak Jurnal Matematika Integratif Al-Aqlu : Jurnal Matematika, Teknik dan Sains Indonesian Journal of Mathematics and Applications Jurnal Pendidikan Progresif Indonesian Journal of Mathematics and Natural Sciences MILANG Journal of Mathematics and Its Applications Majalah Ilmiah Bahasa dan Sastra International Journal of Computing Science and Applied Mathematics-IJCSAM
Sri Nurdiati
School Of Data Science, Mathematics, And Informatics, IPB University, Jl. Raya Darmaga Kampus IPB, Bogor, West Jawa, 16680, Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering 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 Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Physics Social Sciences Transportation Veterinary Other

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Evaluation of Best-Fit Probability Distribution Models for Monthly Rainfall in the Lake Toba Region Syukri Arif Rafhida; Sri Nurdiati; Retno Budiarti; Mohamad Khoirun Najib
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 2 (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.v9i2.25688

Abstract

Understanding rainfall's statistical distribution is crucial for effective water resource management, disaster mitigation, and climate adaptation in tropical regions. This study identifies the best-fit probability distributions for monthly rainfall in the Lake Toba region, Indonesia, based on long-term data from 34 rain gauge stations. Ten commonly used probability distributions were evaluated, with parameters estimated via Maximum Likelihood Estimation (MLE). The Kolmogorov-Smirnov (KS) test was applied to assess model goodness-of-fit at each station and month. Results indicate that the Generalized Extreme Value (GEV), Gamma, and Weibull distributions consistently provide the best fit for most stations and regencies, while Exponential and Inverse Gaussian distributions perform poorly. Spatial analysis reveals notable variation in best-fit models among regencies, emphasizing the influence of local topography and microclimate. These results highlight the need to select flexible probability models for hydrological planning and climate risk assessment in complex tropical regions. The findings provide valuable references for rainfall modeling and bias correction elsewhere.
Implementasi Metode Random Forest dan Support Vector Regression dalam Memprediksi Harga Cryptocurrency Ethereum Azizah Aulia Firdhasari; Lilis Sriwahyuni; Sri Nurdiati; Mohamad Khoirun Najib
Journal of Mathematics: Theory and Applications Vol. 8 No. 1 (2026): Volume 8 Nomor 1 Tahun 2026
Publisher : Program Studi Matematika Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/jomta.v8i1.6189

Abstract

Perkembangan cryptocurrency menjadikan Ethereum (ETH) sebagai salah satu aset digital penting, namun pergerakan harganya sangat volatil karena dipengaruhi oleh berbagai faktor fundamental dan eksternal. Kondisi tersebut menyebabkan prediksi harga close ETH menjadi permasalahan utama karena akurasi peramalan sangat menentukan analisis dan pengambilan keputusan berbasis data. Penelitian ini bertujuan membangun serta membandingkan model prediksi harga close Ethereum menggunakan Random Forest dan Support Vector Regression (SVR) untuk forecasting 30 hari ke depan. Data yang digunakan berupa harga harian Ethereum periode 1 Januari 2020 hingga 30 Desember 2024 dari Yahoo Finance, kemudian dilakukan pra-pemrosesan, standarisasi, dan pembagian data train-test 80:20 dengan menjaga urutan waktu. Feature engineering dibagun dari harga close melalui MA 7, EMA 7, dan lag return 7, serta diterapkan exponential smoothing untuk mengurangi noise. Model Random Forest dan SVR dioptimasi menggunakan Grid Search CV, kemudian dievaluasi menggunakan metrik MAPE. Hasil tuning menunjukkan konfigurasi terbaik Random Forest adalah max depth = 10 dan total estimator = 90. Konfigurasi terbaik SVR adalah kernel linear dengan C = 10, ε = 0.5, dan γ = scale. Evaluasi MAPE menunjukkan Random Forest lebih unggul dengan MAPE train 1,37% dan test 2,04%, sedangkan SVR menghasilkan MAPE train 5,83% dan test 2,22%. Secara keseluruhan, kedua model memberikan akurasi prediksi yang sangat baik, namun Random Forest menunjukkan kinerja lebih stabil dan akurat pada data pengujian. Model Random Forest kemudian digunakan untuk forecasting harga close ETH 30 hari ke depan sebagai estimasi jangka pendek yang cenderung stabil dan mengikuti tren data pengujian.
ANALISIS PERFORMA YOLOV8 PADA DETEKSI KEMATANGAN BIJI KOPI DENGAN BERBAGAI KONFIGURASI PELATIHAN: Performance Analysis of YOLOv8 in Coffee Seed Detection with Various Training Configuration Roma Rio Simbolon; Muhammad Faza Hanifan; Mohamad Khoirun Najib; Elis Khatizah; Sri Nurdiati
Al-Aqlu: Jurnal Matematika, Teknik dan Sains Vol. 4 No. 2 (2026): Juli 2026
Publisher : Yayasan Al-Amin Qalbu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59896/aqlu.v4i2.570

Abstract

Coffee is a strategic plantation commodity in Indonesia, whose quality is strongly influenced by fruit maturity at harvest. However, maturity assessment in the field is still largely conducted manually, leading to subjectivity and low efficiency. This study aims to analyze the performance of YOLOv8 in detecting three coffee fruit maturity levels—unripe, semi-ripe, and ripe—and to evaluate the impact of different training configurations on model performance. The experiments were conducted using the public “Coffee Cherry” dataset from Kaggle, consisting of 432 images with 1000 bounding box annotations. Several configurations were evaluated, including YOLOv8 variants (n, s, m), image sizes, batch sizes, number of epochs, and data augmentation techniques based on HSV color space, object scaling, and mixup. The results show that YOLOv8s provides the best balance between detection accuracy and computational efficiency. The optimal configuration was achieved using an image size of 416, batch size of 8, and 30 epochs, with augmentation improving recall and mAP@50, particularly for challenging classes. Nevertheless, limited dataset size and diversity remain the main constraints affecting performance. Overall, YOLOv8 demonstrates strong potential for coffee fruit maturity detection under real-world conditions.
Numerical Solution of 2D Advection-Diffusion for River Pollutant Transport using the Finite Element Method Muhamad Adzka Rizkia; Rahma Alya Zahrani; Zelisha Pitriatuz Zahra Fauzi; Foky Michelin; Najwaa Alifya Azka; Faiza Mayla Sabita; Mualim Arya Ilyas Wiradinata; Ferdy Aliansyah Hasyim; Mochamad Tito Julianto; Sri Nurdiati; Mohamad Khoirun Najib; Syukri Arif Rafhida
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 2 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i2.42814

Abstract

Pollutant dispersion in rivers is governed by advection, diffusion, and the physical characteristics of the channel. This paper models two-dimensional pollutant transport using the advection-diffusion equation and solves it numerically with the Finite Element Method (FEM) under five scenarios: constant flow with a single pollutant source, flow that follows a meandering channel, constant flow with two sources, the presence of a rock obstacle, and an irregular river domain. Simulations are implemented in Mathematica through domain construction, mesh generation, and a Finite Element-based numerical solution. The results show that flow velocity is the primary driver of plume movement, while diffusion smooths concentration gradients. Comparative analysis across the five scenarios demonstrates that obstacle-containing and irregular domains produce the widest plume spreading and the strongest concentration deformation compared to the straight-channel case. Peak concentrations also decrease more rapidly in multi-source and irregular-flow scenarios due to enhanced mixing and plume interaction. Physical obstacles and channel irregularities generate loacal recirculation zones and plume deviation, producing more realistic pollutant transport behavior than simplified channer models. These findings highlight the importance of geometry-aware flow representations for understanding river pollutant transport in numerical modelling studies.
Co-Authors AA Gede Rai Gunawan Aaron August Vincent Soelaiman Abisha, Nicholas Ade Irawan Ade Irawan Agah D. Garnadi Agung Widyo Utomo Agus Buono Aldri Frinaldi Alifah, Nayla Nur Alifah, Rifdah Nur Alika Azka Shapira Amalia, Rizki Nurul Amanah, Ayu Amanda Nabila Anak Agung Gede Rai Gunawan Andriani, Rizka D. Annisa Annisa Annisa Permata Sari, Annisa Permata Antika, Ester Ardhana, Muhammad Reza Ardhasena Sopaheluwakan Ardhasena Sopaheluwakan Ardhasena Sopaheluwakan Ardiyani, Evi Aufa Ghifada Aulia Rizki Firdawanti Ayu Amanah Aziz, Muhammad Farhan Azizah Aulia Firdhasari Bib Paruhum Silalahi Blante, Trianty Putri Cece Sumantri Chairunisa, Ghevira David Vijanarco Martal Deni Suwardhi DEWI RAHMAWATI Dezvini Muthmainnati Vidia Edi Santosa Ekaputri, Dhea Endar Hasafah Nugrahani Eragilang Muhammad Hastapatria Ester Antika Fahren Bukhari Fahren Bukhari Fahren Bukhari Faiqul Fikri Faiza Mayla Sabita Fajar Delli Wihartiko Farah Annisa Tri Sundari Fathia Rahmaisty Fatmawati, Linda Leni Fauzan, Muhammad Daryl Ferdy Aliansyah Hasyim Foky Michelin Ginting, Dini Tri Putri Br Hanief, Hafzal Hany Savitry Harley Dearmanson Girsang Hasafah Nugrahani, Endar Heliza Rahmania Hatta, Heliza Rahmania Hendri Irwandi Henny Nuraini Henriyansah Herlambang, Karen Hilmi, Kautsar I Gusti Putu Purnaba I Wayan Mangku Iftar Hendry Imas Sukaesih Sitanggang Imni, Salsabila F. Indra Jaya Irman Hermadi Irman Hermadi Irmanida Batubara Jauhari, Muhammad Fakhri Karlisa Priandana Kasiyah M. Junus Kautsar Hilmi Khairuna Putri Gunawan Khatizah, Elis Khoerunnisa, Nazwa Komariah . Lana Syakina Lilik Budi Prasetyo LILIK BUDIPRASETYO Lilis Sri Wahyuni Lilis Sriwahyuni Linda Leni Fatmawati Lizzilmi Syarifatuz Zaimah M. Syamsul Maarif Maliha Qonita Maman Turjaman Marimin Marimin Mas’oed, Teduh W. Maulia, Syammira Dhifa Mirlan Sujana Mirza Farhan Azhari Mochamad Tito Julianto Mohamad Khoirun Najib Mohammad Khoirun Najib Mualim Arya Ilyas Wiradinata Muhamad Adzka Rizkia Muhamad Syukur Muhammad Adam Tripranoto Muhammad Faza Hanifan Muhammad Fikri Isnaini Muhammad Ilyas Muhammad Reza Ardhana Muhammad Tito Julianto Muhammad Zidane Bayu Mukhlis Mukhlis Mukhlis Mukhlis Muliawan Sebastian, Denny Nadhifa Zahra Ghaisani Nadhira Maulida Hayani Nadiyah, Fadilah Karamun Nisaa Najib, Mohamad K. Najib, Mohamad Khoirun Najwaa Alifya Azka Nandika Safiqri Naura Dalta Indriyani Nerissa Patrice Manuella NGAKAN KOMANG KUTHA ARDHANA Nicholas Abisha Niswati, Za'imatun Noval Nur Fallahi, Putri Afia Nur Nabila Nurwegiono, Muhammad Nuzhatun Nazria Pandu Septiawan Pratama, Yoga Abdi Prihasuti Harsani Putri, Renda S. P. Rachma Fauziah Krismayanti Rafhida, Syukri Arif Rahma Alya Zahrani Redytadevi, Tita Putri REFI REVINA Retno Budiarti Rika Kusumawati Rizkian Agung Jamaesa Rohimahastuti, Fadillah Roma Rio Simbolon Ruben Harry Valentdio Salsabila, Fitra Nuvus Salsabilla Rahmah Salsabilla, Fitra Nuvus Sanjaya, Wardah Septian Dhimas Shelvie Nidya Neyman Sitanggang, Imas S. Solikin Solikin Sony Hartono Wijaya Sopaheluwakan, Ardhasena Sri Hartati Sri Mulatsih Srihadi Agungpriyono Sriwahyuni, Lilis Suci Nur Setyawati SUHARINI, YUSTINA SRI Sukmana, Ihwan SYAHID AHMAD MUKRIM Sya’adah, Syifa Noer Syukri Arif Rafhida Syukri Arif Rafhida Talenta Parfaibya Mahenindra Tri Rapani Febbiyanti Tri Rapani Febbiyanti Trianty Putri Blante Triwulandari, Raden Roro Carissa Usmany, Rendy Valentdio, Ruben Harry Verry Riyanto Vicky Zilvan Wigawijayanti Wigawijayanti Wisnu Ananta Kusuma Yandra Arkeman Yasin Yusuf Yeni Herdiyeni Yoga Abdi Pratama Zelisha Pitriatuz Zahra Fauzi