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PERBANDINGAN METODE FUZZY TIME SERIES CHEN DAN METODE EXPONENTIAL SMOOTHING DALAM MEMPREDIKSI CURAH HUJAN DI KABUPATEN PAMEKASAN Tamam, Moh. Badrit; Kuzairi, Kuzairi; Yulianto, Toni; Faisol, Faisol; Yudistira, Ira; Amalia, Rica
Networking Engineering Research Operation Vol 9, No 2 (2024): Nero - November 2024
Publisher : Jurusan Teknik Informatika Fakultas Teknik Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/nero.v9i2.27986

Abstract

This research aims to predict rainfall in Pamekasan Regency, Madura, East Java, using two prediction methods: Fuzzy Time Series Chen and the Exponential Smoothing (ES) method, specifically Double Exponential Smoothing (DES). The data used in this study consists of monthly rainfall data from January 2011 to December 2023, covering a period of 13 years. The data was sourced from reliable records that regularly track rainfall in the region. In the analysis, both methods were applied to generate accurate predictions of rainfall patterns in Pamekasan Regency. Based on the calculations and performance evaluation, the best method for predicting rainfall in this region was found to be Double Exponential Smoothing Holt. This method uses two key parameters: alpha at 0.4 and beta at 0.6. After applying this method, a Mean Absolute Percentage Error (MAPE) of 1.479 was obtained, indicating a very low and acceptable level of prediction error. Therefore, it can be concluded that the Double Exponential Smoothing Holt method is an effective and accurate approach for predicting rainfall in Pamekasan Regency based on the historical data used..Keywords: Rainfall; Pamekasan Regency; Prediction; Chen's Fuzzy Time Series and Exponential Smoothing (ES) Method
Prediction of Divorce Data in Pamekasan District Based on Comparison of Exponential Smoothing and Moving Average Yudistira, Ira; Romlah, Siti; Yulianto, Tony; faisol, Faisol; Mardianto, M.Fariz Fadillah
Tensor: Pure and Applied Mathematics Journal Vol 5 No 2 (2024): Tensor: Pure and Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol5iss2pp67-78

Abstract

Divorce is a form of breakdown in domestic or marital relationships which is characterized by separation. Based on the Indonesian Statistics report, the number of divorce cases in Indonesia will reach 516,334 cases in 2022. This number is up 15.31% compared to the previous year of 447,743 cases. East Java is ranked second as the province with the highest divorce cases, namely 102,065 cases throughout 2022. To know the development of divorce in the future, forecasting is needed to determine when an event will occur, an increase in the divorce rate, so that we can prepare what will be done to overcome the spike. the divorce rate. In this research, the methods used to predict the number of divorce cases in Pamekasan Regency are the Exponential Smoothing and Moving Average methods. single exponential smoothing method for both divorce lawsuits and divorce divorces with MAD values ​​= 10.40539 and 15.3366868, MSE = 449.0276211 and 181.0038, MAPE = 22.1859129 and 23.84152 and SE values ​​= 21.57911661 and 13, 70064 with a value of α=0.12 for contested divorce and α=0.26 for talak divorce.
Application of the ARIMA-GARCH Model for Forecasting Indonesia's Monthly Inflation Rate Anisa; Yudistira, Ira; Yulianto, Tony
Contemporary Mathematics and Applications (ConMathA) Vol. 7 No. 1 (2025)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v7i1.60263

Abstract

Inflation is one of the important aspects that is used as a benchmark to see economic growth and economic conditions in each country. Inflation has resulted in increasing public expenditure in meeting basic needs. Inflation must be controlled to maintain the economic stability of a country, including Indonesia. Therefore, there is a need for a model that can forecast the inflation rate in Indonesia. The aim of this research is to create a model that can predict future inflation levels so that it can help the government in determining policies related to controlling inflation in Indonesia. The data used is monthly inflation data in Indonesia for 19 years from March 2007- October 2023 in percentage form. The forecasting model used in this study is the ARIMA-GARCH model. The ARIMA model is a time series model used to forecast future data based on past data. While GARCH is a time series model used to overcome heteroscedasticity in the ARIMA model. Inflation data will be modeled using the ARIMA model and then continued by modeling the residuals using the GARCH model if heteroscedasticity occurs in the ARIMA model residuals. Based on data analysis that has been done, the best model for inflation forecasting cases in Indonesia is the ARIMA (2,0,2) - GARCH (0,1) model with a MAPE value of 17.78%.
Determining Optimal Hierarchical Clustering by Combining Needleman Wunsch and Jukes Cantor Algorithms in Tuberculosis (TB) Disease Clustering Hildatul Anizah; Tony Yulianto; Kuzairi; Ira Yudistira; Amalia, Rica
Contemporary Mathematics and Applications (ConMathA) Vol. 7 No. 1 (2025)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v7i1.64172

Abstract

Tuberculosis (TBC) is an infectious disease affecting the respiratory system, caused by the bacterium Mycobacterium tuberculosis. Tuberculosis (TBC) remains a global concern, and to date, no country is completely free from TB. This disease continues to be one of the leading causes of mortality. Therefore, it is essential to categorize the spread of TBC. The percentage of identity in genetic codes will reveal the proportion of mutations. The percentage of identity in genetic codes will demonstrate that, although the symptoms caused by a disease may be quite similar, the protein sequences are not necessarily the same. In this study, the researchers employed the Hierarchical Clustering method, integrating the Needleman-Wunsch and Jukes-Cantor algorithms, resulting in two groups. The first group consists of 9 interconnected rows, while the second group consists of 7 interconnected rows.
Prediction of seawater salinity based on comparison of truncated spline estimators, Fourier Series and Kernel Faisol Faisol; M. Fariz Fadillah Mardianto; Ira Yudistira; Tony Yulianto; Sarmiatul Hasanah
Journal of Natural Sciences and Mathematics Research Vol. 9 No. 1 (2023): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.2023.9.1.12582

Abstract

Salinity is one of the factors that affect salt production. Salinity is defined as the level of saltiness or too much salt in water. The salt in question is a variety of ions dissolved in water, including table salt (NaCl). The higher the level of NaCl contained, the better the quality of the salt formed. This low quality causes Indonesia to import salt, both consumption salt and industrial salt. Because most of the quality of salt still does not meet the criteria of SNI. For this reason, it is necessary to predict the salinity of seawater to help determine the next steps or policies in improving the quality of salt in Indonesia, especially in the Madura area. This research is examined in the form of a nonparametric regression curve estimator with a truncated spline estimator approach, Fourier series and kernel. From the comparison results, the best model for predicting seawater salinity is the estimator of the Fourier series base sine cosine with an oscillation parameter (k) of 2 with a GCV value of 5.017987 and MSE and a coefficient of determination of 0.06299933 and 94.64373%. So the prediction results obtained in this study are close to accurate with MAPE values of 0.07225208%, MSE of 0.0001441417 and coefficient of determination of 99.99%.
Modeling the Spread of Hepatitis B Disease from the SEIR Model in East Java Using RKF 45 Na'malia, sakinun; Faisol, Faisol; Yulianto, Tony
Tensor: Pure and Applied Mathematics Journal Vol 6 No 1 (2025): Tensor: Pure and Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol6iss1pp1-12

Abstract

Hepatitis B is an infectious disease that has a major impact on public health, especially in East Java Province with a high prevalence of cases. This study aims to model the spread of Hepatitis B using the SEIR model (Susceptible, Exposed, Infected, Recovered) and solved numerically with the Runge-Kutta Fehlberg method (RKF45). Simulation results for 10 years showed that the susceptible population decreased from to individuals, while the exposed compartment increased from to . The infected population peaked at around individuals in year 2 and decreased to individuals, while the cured population continued to increase until it reached at the end of the period. The SEIR model with the RKF45 method proved effective in describing the dynamics of the spread of Hepatitis B mathematically and can be utilized as a predictive tool in supporting public health policy.
Penerapan Petri-Net Pada Model Gerakan Berjalan Walking Robot Berkaki Empat (Quadruped) Kuzairi, Kuzairi; Yulianto, Tony; Mardianto, M. Fariz Fadillah; Faisol, Faisol; Amalia, Rica
Zeta - Math Journal Vol 1 No 1 (2015): Mei
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (4219.834 KB) | DOI: 10.31102/zeta.2015.1.1.1-5

Abstract

Selama ini sudah banyak robot diproduksi baik dalam skala kecil maupun besar untuk membantu manusia dalam mengerjakan pekerjaan sehari-hari manusia sesuai dengan fungsi masing-masing. Akan tetapi, fungsi-fungsi tersebut akan dapat berjalan dengan baik apabila komponen-komponen yang mendukung pada robot dapat berjalan dengan baik, seperti salah satunya adalah cara gerak berjalan robot. Di sini, peneliti lebih menekankan gerak jalan robot empat kaki yang menggunakan walking, karena yang banyak umum digunakan dan kesulitannya juga lumayan dibandingkan robot berjalan dengan dua kaki. Maka dengan menggunakan aljabar max plus akan diperoleh model gerak jalan robot walking tersebut yang sesuai dengan yang diharapkan.
Aplikasi SVM Classifier dalam Pengenalan Target IR (infrared) Amalia, Rica; Kuzairi, Kuzairi; Yulianto, Tony; Mardianto, M. Fariz Fadillah; Faisol, Faisol
Zeta - Math Journal Vol 1 No 1 (2015): Mei
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2775.426 KB) | DOI: 10.31102/zeta.2015.1.1.6-9

Abstract

Dalam tulisan ini, support vector machine diusulkan dalam pengenalan target IR. Metode grid digunakan untuk memilih parameter yang tepat dari SVM untuk menghindari over-fitting yang disebabkan pemilihan parameter yang tidak tepat. Kami menggunakan citra pemantauan IR tambang batubara untuk melihat kemampuan pengenalan target IR oleh SVM. Fitur dan kategori citra pemantauan IR tambang batubara diberikan. Hasil eksperimen menggambarkan bahwa akurasi pengenalan target IR oleh SVM adalah 100%. Jadi, SVM adalah metode pengenalan target IR yang sangat baik.
Aplikasi Jaringan Hebb dalam Pengenalan Huruf Faisol, Faisol; Amalia, Rica; Kuzairi, Kuzairi; Yulianto, Tony; Mardianto, M. Fariz Fadillah
Zeta - Math Journal Vol 1 No 1 (2015): Mei
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (4078.798 KB) | DOI: 10.31102/zeta.2015.1.1.10-14

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Pengenalan pola secara automatis adalah masalah yang banyak menyita perhatian sekarang ini, baik pengenalan pola wajah, sidik jari, tulisan tangan maupun pola karakter hasil cetakan. Yang menjadi alasan penelitian adalah kemampuan untuk mengenali secara efektif dengan menggunakan pola contoh yang sedikit. Satu pendekatan yang menunjukkan hasil yang menjanjikan dalam pengenalan pola adalah dengan menggunakan jaringan saraf tiruan. Jaringan saraf tiruan telah dikembangkan sebagai generalisasi model matematik dari pembelajaran otak manusia. Jaringan saraf tiruan algoritma Hebb Rule adalah salah satu algoritma pelatihan paling sederhana untuk jaringan syaraf tiruan secara umum. Dalam penelitian ini, jaringan saraf dilatih dengan menggunakan 7 karakter huruf besar, yakni A, B, C, D, E, J, dan K. Hasil pengujian menunjukkan bahwa metode Hebb masih memiliki keterbatasan dalam pengenalan pola karena ada input pola yang ditraining yang tidak bisa dikenali pada saat proses testing.
Perancangan Bejana Tekan Berdimensi Satu dengan Menggunakan Metode Elemen Hingga Yulianto, Tony; Faisol, Faisol; Amalia, Rica; Kuzairi, Kuzairi; Mardianto, M. Fariz Fadillah
Zeta - Math Journal Vol 1 No 1 (2015): Mei
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (5063.042 KB) | DOI: 10.31102/zeta.2015.1.1.15-21

Abstract

Salah satu metode numerik yang digunakan untuk menyelesaikan persamaan differensial biasa adalah metode elemen hingga, dalam paper ini diberikan simulasi penerapan metode tersebut untuk menyelesaikan masalah nilai batas kususnya untuk mengukur besar defleksi dari bejana tekan. Diberikan pula perbandingan galat dari dua cara perhitungan, yaitu metode elemen hingga dengan metode beda hingga yang pernah diteliti sebelumnya. Hasilnya menunjukkan bahwa perhitungan dengan caraelemen hingga lebih baik dibandingkan denganbeda hingga.