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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Sains Dasar PYTHAGORAS: Jurnal Program Studi Pendidikan Matematika AKSIOMA JURNAL ILMIAH MATEMATIKA DAN TERAPAN Indonesian Journal of Applied Statistics MUST: Journal of Mathematics Education, Science and Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) MATAPPA: Jurnal Pengabdian Kepada Masyarakat Teorema: Teori dan Riset Matematika Journal of Education Technology Jambura Journal of Mathematics Jurnal Matematika UNAND Transformasi : Jurnal Pendidikan Matematika dan Matematika Jurnal Saintika Unpam : Jurnal Sains dan Matematika Unpam Mandalika Mathematics and Educations Journal ESTIMASI: Journal of Statistics and Its Application Majalah Ilmiah Matematika dan Statistika (MIMS) Jambura Journal of Mathematics Education Jambura Journal of Biomathematics (JJBM) Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Journal of Science and Technology JES-MAT (Jurnal Edukasi dan Sains Matematika) MATHunesa: Jurnal Ilmiah Matematika METIKS: Jurnal Teknik Mesin, Elektro, Informatika, Kelautan & Sains Pattimura International Journal of Mathematics (PIJMath) Jurnal Sintak Jurnal Multidisiplin Sahombu Jurnal Matematika Integratif Parameter: Jurnal Matematika, Statistika dan Terapannya Journal of Mathematics, Computation and Statistics (JMATHCOS) Bilangan: Jurnal Ilmiah Matematika, Kebumian dan Angkasa Algoritma: Jurnal Matematika, Ilmu Pengetahuan Alam, Kebumian dan Angkasa Indonesian Journal of Computational and Applied Mathematics
Agusyarif Rezka Nuha
Universitas Negeri Gorontalo
Agriculture, Biological Sciences & Forestry Arts Astronomy Automotive Engineering 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 Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Physics Transportation

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Journal : journal of mathematics computation and statistics jmathcos

 1 
Analisis Dinamik Model Predator-Prey dengan Efek Pemanenan Pada Populasi Ikan Nike (Awaous Melanocephalus) di Provinsi Gorontalo Usman, Nunung; Nento, Abdul Djabar; Hendri, Excel Muhammad; Biga, Azril Saputra; Sigar, Leidi; Nuha, Agusyarif Rezka
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.3461

Abstract

Gorontalo Province is one of the areas directly adjacent to Tomini Bay, which is known for its rich natural resources, especially in the fisheries sector such as Nike fish (Awaous melanocephalus). Nike fish is the main food commodity for people in the Gorontalo region. However, intensive fishing activities can pose an extinction threat to this species. This study aims to understand the dynamics of the Nike fish population using a predator-prey model that integrates the effects of harvesting on the prey population. The research process includes formulation of assumptions, model building, model validation, and data analysis through mathematical analysis and numerical simulation. The analysis showed that the model has four equilibrium points, each with different stability conditions. Numerical simulations showed that an increase in harvesting rate and natural mortality of prey, as well as a decrease in birth rate, could threaten the viability of the Nike fish population. Thus, appropriate management efforts are needed to maintain ecosystem balance and the sustainability of the Nike fish population. The calculation results show that the Nike fish production threshold in Gorontalo Province is 8.470.858 kg per year. However, the amount of Nike fish production in Gorontalo Province in 2023 only reached 56,75% of the threshold. This indicates that the production of Nike fish in Gorontalo can still be increased as long as the harvest limit is observed to prevent extinction.
Evaluation of the Adaptive Fuzzy Neuro Inference System and Fuzzy Model Time Series Markov Chains in Forecasting Crude Oil Prices Hinelo, Ikrar Prasetyo; Nuha, Agusyarif Rezka; Hasan, Isran K; Nasib, Salmun K; Abdussamad, Siti Nurmardia
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.6763

Abstract

The development of a country's economy is greatly influenced by global economic conditions, given the increasingly close links between countries through economic relations and international cooperation. One of the main factors in economic growth is international trade, particularly export and import activities. Crude oil is one of the most actively traded commodities. Given the highly volatile crude oil market, accurate price forecasts are crucial in economic and financial decision-making. This study compares the performance of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Fuzzy Time Series Markov Chain (FTSMC) in forecasting the price of West Texas Intermediate (WTI) crude oil using time series data from 2020 to 2024 with saturated sampling technique. The implementation of both methods is carried out through Matlab Online and R-Studio software, with results showing that ANFIS has higher accuracy than FTSMC, as evidenced by the Mean Absolute Percentage Error (MAPE) value of 1,8010% for ANFIS and 3,7567% for FTSMC. Further analysis shows that ANFIS with a triangular membership function as well as significant lags at lag 1, lag 3, lag 4, and lag 7 is able to produce more accurate predictions and match the trend of actual data. Therefore, ANFIS is recommended as a more effective method in forecasting WTI crude oil prices, which can provide valuable insights for policy makers and industry stakeholders.
Development of a Hybrid ARIMA–Fourier Series Model for Air Temperature Forecasting at the Gorontalo Climatology Station Suci Tilome; Isran K. Hasan; Agusyarif Rezka Nuha
Journal of Mathematics, Computations and Statistics Vol. 9 No. 1 (2026): Volume 09 Issue 01 (March 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcosv9i1.11462

Abstract

Air temperature is a key climatic variable that reflects environmental conditions and influences various human activities. Recent observations indicate a persistent upward trend associated with global warming, leading to greater variability in climate patterns. These changes highlight the importance of forecasting methods that can accurately represent the characteristics of air temperature time series to support planning and decision-making. Reliable prediction is therefore essential for understanding climate dynamics and anticipating potential environmental impacts. This study proposes an air temperature forecasting approach using a hybrid Autoregressive Integrated Moving Average (ARIMA) and Fourier Series Analysis (FSA) model. The ARIMA component is applied to model trend behavior and temporal dependence, while FSA captures the remaining seasonal patterns in the ARIMA residuals. By integrating these two approaches, the hybrid model aims to improve forecasting accuracy in the presence of both stochastic and periodic components. The results show that the hybrid ARIMA–FSA model achieves good forecasting performance, with a Mean Absolute Error (MAE) of 0.56, a Root Mean Square Error (RMSE) of 0.66, and a Mean Absolute Percentage Error (MAPE) of 2.07%. These findings indicate that the proposed model effectively represents air temperature dynamics and can be considered a reliable alternative for climate forecasting applications
Adaptive ANFIS–PSO Model for Forecasting Bird’s Eye Chili Prices in Gorontalo Province Nur Siyam Djibu; Isran K. Hasan; Agusyarif Rezka Nuha
Journal of Mathematics, Computations and Statistics Vol. 9 No. 1 (2026): Volume 09 Issue 01 (March 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcosv9i1.11473

Abstract

Bird’s eye chili is one of the strategic food commodities in Indonesia with high price volatility and a significant contribution to food inflation, particularly in Gorontalo Province. The dynamic and nonlinear characteristics of bird’s eye chili prices often hinder accurate forecasting when using conventional methods, thereby requiring an adaptive approach capable of capturing complex data patterns. Therefore, this study applies an Adaptive Neuro-Fuzzy Inference System (ANFIS) optimized using Adaptive Particle Swarm Optimization (PSO) to improve the accuracy of bird’s eye chili price forecasting. This study utilizes daily bird’s eye chili price data in Gorontalo Province from 1 January 2019 to 31 October 2025, obtained from the National Strategic Food Price Information Center (PIHPS). The ANFIS model is optimized using adaptive PSO to obtain optimal parameter values that address local convergence problems and parameter sensitivity commonly encountered in conventional ANFIS models. Model performance is evaluated using the Mean Absolute Percentage Error (MAPE). The results indicate that the adaptive ANFIS–PSO model achieves a MAPE value of 17.4487% on the training dataset, which decreases significantly to 5.0741% on the testing dataset. The testing MAPE value below 10% demonstrates that the proposed model has excellent generalization capability in capturing bird’s eye chili price fluctuations. These findings confirm that adaptive PSO-based parameter optimization effectively enhances ANFIS performance in modelling nonlinear and highly volatile time series data. The proposed forecasting model can serve as a reliable analytical tool to support decision-making and regional food price stabilzation policies in Gorontalo Province.
Co-Authors Abdul, Nur Safitri Abubakar, Agung Sucipto Agung, Andi Aliwu, Randa Resvitasari Andi Agung Anggraini, Fitriana Anissa Dwi Wijayanti Aprina Manggarai Armayani Arsal Asriadi Asriadi Asriadi Asriadi Asriadi Asriadi Aswata Wisnuadji Ayyasy, Muhammad Yahya Bela Cintiya Samwan Bertu Rianto Takaendengan Biga, Azril Saputra Chasanah, Sri Istiyarti Uswatun Dewi Rahmawaty Isa Djibran, Fahrudin Djihad Wungguli Djuma, Clara Anggriani Eko Sulistyono Sulistyono Fajri Ikhsan Franky Alfrits Oroh Ghivahri Sidik Mokoagow Hasan S. Panigoro Hasan, Riyanto Hendri, Excel Muhammad Hinelo, Ikrar Prasetyo Husuna, Cabelita Ibrahim, Novita Ismail Djakaria Isran K Hasan Janna, Miftahul K. Nasib, Salmun Kai, Ferawati Kasim, Ranan Kundju, Adib Rizal La Ode Nashar La Ode Nashar Lailany Yahya Lailany Yahya Laita, Nazrilla Hasan Lasantu, Patra Lindrawati Abdjul Mahmud, Sri Lestari Melasarah Deswita Rahmadi Miftahul Huda Moh Dody Afandi Rauf Mohamad, Regina Mohammad Dwitiar Nalole Muhammad Ikhlas Muhammad Rifai Katili Nadiyyah, Ana Nento, Abdul Djabar Nina Valentika NISKY IMANSYAH YAHYA Novianita Achmad Novianita Achmad Nur Siyam Djibu NUR ’AIN SUPU Nursiya Bito Nurwan Nurwan Nurwan Nurwan NURWAN NURWAN Nurwan, Nurwan Pakaya, Revandi S. Rahman, Gusti Arviana Rahmi, Emli Rasmawati Rasmawati Rasyid, Kamelia Rauf, Moh Dody Afandi Resmawan Resmawan Rozikin, Muhammad Rusniwati S. Imran Salmun K. Nasib Saltina, Saltina Sari, Lia Nanda Sidik Susilo Sigar, Leidi Siti Nurmardia Abdussamad Sri Istiyarti Uswatun Chasanah Sri Istiyarti Uswatun Chasanah Sri Lestari Mahmud Sri Meylanti S. Ali Suci Tilome Sugito Mahendra Imran Syafrudin, Marisa Syarif Abdullah Taulia Damayanti Usfita Kiftiyani Usman, Nunung Usman, Sri Adiningsi B. Valentika, Nina Wafa, Moh. Shohibul Widyastutifajri Nuha Yazid Rukmayadi Zaqiyah, Arfatuz