Contemporary Mathematics and Applications (ConMathA)

Application of the ARIMA-GARCH Model for Forecasting Indonesia's Monthly Inflation Rate

Anisa, Ira Yudistira, Tony Yulianto — Thu, 27 Mar 2025 00:00:00 +0700

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%.

The Szeged Index and Padmakar-Ivan Index on the Zero-Divisor Graph of a Commutative Ring

Jinan Ambar, I Gede Adhitya Wisnu Wardhana, Abdurahim — Thu, 27 Mar 2025 00:00:00 +0700

The zero-divisor graph of a commutative ring is a graph where the vertices represent the zero-divisors of the ring, and two distinct vertices are connected if their product equals zero. This study focuses on determining general formulas for the Szeged index and the Padmakar-Ivan index of the zero-divisor graph for specific commutative rings. The results show that for the first case of ring, the Szeged index is exactly half of the Padmakar-Ivan index. For the second case, the Szeged index is consistently greater than the Padmakar-Ivan index. These findings enhance the understanding of how the algebraic structure of rings influences the topological properties of their associated graphs.

Determining Optimal Hierarchical Clustering by Combining Needleman Wunsch and Jukes Cantor Algorithms in Tuberculosis (TB) Disease Clustering

Hildatul Anizah, Tony Yulianto, Kuzairi, Ira Yudistira, Rica Amalia — Thu, 27 Mar 2025 00:00:00 +0700

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.

Voice-Based Emotion Identification Based on Mel Frequency Cepstral Coefficient Feature Extraction Using Self-Organized Maps and Radial Basis Function

Asrivatun Nikmah, Auli Damayanti, Edi Winarko — Thu, 27 Mar 2025 00:00:00 +0700

Speech recognition is one of the most popular research fields, one of which is about emotion identification. Voice-based emotion identification is carried out to determine the pattern of emotions using the depth analysis mechanism of voice signal development and feature extraction that carries the emotional characteristic parameters of the speaker's voice. Furthermore, the emotional characteristics of the speaker's voice are classified using an artificial neural network method to recognize patterns. In this study, emotion identification from voice signal data is classified into angry, sad, happy, and neutral emotions. The stages of voice-based emotion identification, including the feature extraction stage using the mel frequency cepstral coefficient, produce coefficient values, which will be used in the identification stage using the Self Organized Maps method on the Radial Basis Function.

Implementation of Mamdani Method Fuzzy System in Determining Final Semester Grades of UIN Walisongo Semarang Students

Arif Rezky Aprilianto, Budi Cahyono, Mohamad Tafrikan — Thu, 27 Mar 2025 00:00:00 +0700

Final semester grades are an important component for students to obtain a pass in completing a course. The program for determining final semester grades using fuzzy Mamdani can be used to facilitate the calculation of final semester grades. This research aims to determine the results of applying the Mamdani fuzzy system method in determining the final semester grades of students at UIN Walisongo Semarang. The Mamdani fuzzy system method was chosen as the method for calculating final semester grades along with MAPE (Mean Absolute Percentage Error) calculations. In accordance with the lecture contract for the computational mathematics course, several input variables were found to be used in the research, namely structured assignment grades (20%), independent assignment grades (30%), mid-semester exam grades (25%), and final semester exam scores (25%). The data is processed in several steps, namely creating fuzzy membership sets and functions, creating fuzzy rules, fuzzification, and defuzzification. After calculating with the Mamdani method fuzzy system, the next step is to calculate the MAPE value and display the results. The MAPE value obtained from research with 46 data was 2.074; This means that according to the MAPE criteria it produces accurate data. This proves that the Mamdani fuzzy system method can be applied to calculate students' final semester grades.