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Pattimura International Journal of Mathematics (PIJMath)
Published by Universitas Pattimura
ISSN : -     EISSN : 28306791     DOI : https://doi.org/10.30598/pijmathvol1iss2year2022
Core Subject : Education,
Mathematics
Pattimura International Journal of Mathematics (PIJMath) is provided for writers, teachers, students, professors, and researchers, who will publish their research reports about mathematics and its is applications. Start from June 2022, this journal publishes two times a year, in May and November
Arjuna Subject : Matematika - Matematika Terapan
Articles 40 Documents
 1   2   3   4 
Forecasting Palm Oil Production in North Sumatera Using the Adaptive Neuro Fuzzy Inference System Method Sari, Riezky Purnama; Hidayati, Adinda Tri; Fairus, Fairus
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 1 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss1pp1-6

Abstract

Indonesia is an agricultural and maritime country because it is the country that has the largest agriculture and plantations in ASEAN. One of them is palm oil production, because palm oil is believed to not only be able to produce various types of butter, cooking oil or soap, but can also be a substitute for fuel oil. In the province of North Sumatra itself, oil palm is a crop that has potential and produces very high profits. Therefore, forecasting is used to determine future palm oil production results using the ANFIS method in order to increase or catalyze palm fruit. The data source used in this research comes from the Central Statistics Agency (BPS) of North Sumatra. The aim of this research is to determine the results of forecasting palm oil production in North Sumatra using the ANFIS model. So we got results from forecasting palm oil production in North Sumatra which experienced fluctuations throughout the period January 2023 to December 2024 with a forecasting accuracy level of 92% and a MAPE value of 12.778179% with MAPE criteria of 10% - 20% which was considered 'Good '. So it can be concluded that the forecasting results were carried out well and can be used for future forecasting.
Monte Carlo-Expected Tail Loss for Analyzing Risk of Commodity Futures Based on Holt-Winters Model Saputra, Wisnowan Hendy
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 1 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss1pp7-16

Abstract

Future, an agreement to buy or sell an asset at a certain price and a certain time in the future, is one of the market derivatives because the underlying assets influence the price of futures. In general, futures divide into financial futures and commodity futures. Each of the futures has different risks, so risk measures are needed to improve the effectiveness and efficiency of investment management. For example, we have the London Metal Exchange (LME) in the metal scope of commodity futures. Therefore, we propose the Holt-Winters Model for estimating commodity prices in this study. Hereafter, The Expected Tail Loss (ETL) with Monte Carlo process will use to analyze risk measures. We took six commodity futures in LME to implement the method as a sample, such as Zinc, Lead, Aluminum, Copper, Nickel, and Tin. Based on the analysis, each commodity has a different mean ETL value, where Nickel has the most significant risk with an ETL value of 0.036. This value means that the possibility of the expected loss to be borne by investors is 3.6%.
Classification of Poverty in Maluku Province using SMOTE-Random Forest Algorithm Damamain, Ferina L; Sinay, Lexy Janzen; Latupeirissa, Sanlly J; Bakarbessy, Lusye
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 1 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss1pp17-28

Abstract

Poverty is a complex issue. According to BPS publications, in 2023, the poverty line in Indonesia has reached 9.57%. Maluku is one of the provinces with a high poverty rate, reaching 16.23%. This research aims to classify poverty status in Maluku Province using the SMOTE-random forest algorithm. This research uses SUSENAS 2022 data, where the data is not balanced. SMOTE is used to overcome this problem. The best model obtained has an accuracy rate of 85.8%. The model is based on a training data proportion of 75% and testing 25%, with parameters m=4 and r=100. The critical factor that influences poverty status in Maluku Province is the number of households.
Damped Trend Exponential Smoothing and Holt-Winters in Forecasting the Number of Airplane Passengers at Kualanamu Airport Binoto, Rustham Michael; Sudarwanto, Sudarwanto; Santi, Vera Maya
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 1 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss1pp29-40

Abstract

Airplanes are one of the most frequently chosen modes of transportation by Indonesians today. Kualanamu Airport is one of the busiest airports in terms of the number of passengers. The number of airplane passengers often fluctuates, increasing and decreasing, so an analysis method is required to predict the number of passengers. This study uses the Double Exponential Smoothing Damped Trend and Multiplicative Holt-Winters models. The number of Kualanamu Airport domestic airplane passengers from January 2006 to December 2023 was used as research data. The best model is then used to forecast the number of Kualanamu Airport domestic airplane passengers for 12 periods from the last data used. The results showed that the Multiplicative Holt-Winters model with smoothing parameters and obtained smaller (Mean Absolute Error) MAE and (Mean Square Error) MSE values of 21415.556 and 961525264.508, compared to the Double Exponential Smoothing Damped Trend model with smoothing parameters,, and which obtained MAE and MSE values of 23612.461 and 1061042411.507 in predicting the number of domestic aircraft passengers at Kualanamu Airport. Forecasting accuracy for the next 12 periods using Holt-Winters Exponential Smoothing produces a MAPE value of 9.2%. It shows the accuracy of forecasting in the very good category.
Factor Analysis on Poverty in Kalimantan Island with Geographically Weighted Negative Binomial Regression Halim, Alvin Octavianus; Satyahadewi, Neva; Preatin, Preatin
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 1 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss1pp41-52

Abstract

Poverty is one of the problems still faced by Indonesia. The problem of poverty is a development priority because poverty is a complex and multidimensional problem. Therefore, to reduce poverty, it is necessary to know the factors that influence the number of people living in poverty. The influencing factors in each region are different due to the effects of spatial heterogeneity between regions such as geographical, economic, and socio-cultural conditions. This research considers spatial factors by using the Geographically Weighted Negative Binomial Regression (GWNBR) method on poverty-based regions in Kalimantan Island. This research uses eleven independent variables. The weighting function used is the Adaptive gaussian kernel because the adaptive kernel can produce the number of weights that adjust to the distribution of observations. The stage starts with descriptive statistics and checking multicollinearity. Then proceed with the formation of Poisson Regression, because the data used is enumerated data. Then check for overdispersion. If overdispersion is detected where the variance is bigger than the mean, then Negative Binomial Regression is continued. After that, it is tested for the presence or absence of spatial heterogeneity. If there is, proceed to find the bandwidth and Euclidean distance. After that, the graphical weighting matrix is searched. Then proceed with GWNBR modeling. The results of the analysis show that there are seven significant variables, including the percentage of households with the main source of lighting is non-state electricity company (PLN), average monthly net income of informal workers, population density for every square kilometer, monthly per capita expense on food and non-food essentials, percentage of people who have a health complaint and do not treat it because there is no money and percentage of population 15 years and above who do not have a diploma. Based on the categories of significant variables, six groups were formed in 56 districts/cities in Kalimantan Island.
Cayenne Pepper Price Forecast in Singkawang City Based on Rainfall using Transfer Function Model Maharani, Citra Cipta; Yundari, Yundari; Satyahadewi, Neva
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 2 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss2pp53-62

Abstract

Fluctuations in the price of cayenne pepper are a significant problem in Indonesia’s agricultural sector, especially in Singkawang City. Weather conditions, including rainfall are often the main factor affecting the production and distribution of cayenne pepper, causing price instability. This study aims to analyze the relationship between rainfall and the price of cayenne pepper, and build a forecasting model using a transfer function approach. In this study, the input series used is rainfall, while the output series is the price of cayenne pepper. The data used is secondary data obtained from the Central Statistics Agency in Singkawang City from January 2016 to December 2023. The data is analyzed through the stationarity stage, then the identification of the ARIMA model for the input series. After that, prewhitening and cross-correlation analysis were carried out to identify the parameter values and determine the noise series ARMA model. The results show that the transfer function model with parameters with ARMA noise series is the best model for forecasting the price of cayenne pepper. The results of forecasting the price of cayenne pepper in Singkawang City have a MAPE value of , so it can be concluded that the transfer function model is quite good at forecasting the price of cayenne pepper in Singkawang City with the highest forecasting result of IDR 61,899 in May 2024 and the lowest is IDR 32,206 in April 2024. This study focuses solely on the transfer function model because it is specifically designed to analyze the dynamic relationship between an input variable (rainfall) and an output variable (price). Other forecasting methods such as ARIMA or exponential smoothing only capture internal patterns within a single series and cannot represent the influence of external factors. Therefore, the transfer function approach is considered more appropriate for the purpose of this study.
Profile of Mathematical Connection Ability in Material Two-Variable Linear Equation System (SPLDV) In Grade IX SMP Siregar, Annisa Fachraini; Azzahra, Sevilla Tita; Widiati, Indah
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 2 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss2pp63-72

Abstract

This study was conducted to determine the mathematical connection abilities of ninth-grade junior high school students in learning mathematics on the subject of Two-Variable Linear Equation Systems (SPLDV). This study used a qualitative method with a descriptive approach, which aims to understand phenomena in depth through direct observation. The study was conducted at a junior high school in Riau, with a sample of 12 ninth-grade students who had studied the topic of Systems of Linear Equations with Two Variables (SPLDV). The sampling technique used in this study was purposive sampling, selecting three students for further analysis based on the following criteria: (1) students with high mathematical connection skills (all indicators met), (2) students with moderate mathematical connection skills, and (3) students with low mathematical connection skills. The instruments used in this study consisted of a written test and an interview guide. The written test comprised three essay questions designed to measure students' mathematical connection skills in the SPLDV material. The results and discussion of this study showed that 6 students had high mathematical connection skills, 2 students had moderate mathematical connection skills, and 4 students had low mathematical connection skills
Forecasting the Stock Price of PT. Dayamitra Telekomunikasi with Single Input Transfer Function Model Arsanti, Resti; Satyahadewi, Neva; Martha, Shantika
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 2 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss2pp87-96

Abstract

The unpredictable movement of stock prices is often a challenge for investors, so it requires a deeper understanding and consideration of various factors before making investment decisions. One of the factors that affect stock price movements is trading volume. Therefore, this study uses a single input transfer function model to forecast the daily closing stock price of PT. Dayamitra Telekomunikasi, with the closing stock price as the output variable and the stock trading volume as the input variable. The transfer function is a forecasting model that integrates ARIMA with multiple regression analysis, allowing modeling not only based on the values of the output variables, but also considering the influence of the input variables. ARIMA model estimation is performed on the input series for the prewhitening process, then the order of the transfer function is determined using cross-correlation plots, as well as model diagnostic tests to ensure its feasibility. Model accuracy is calculated to evaluate its performance in forecasting. The data used in this study are daily data from the period July 5, 2022 to October 9, 2024. The transfer function model obtained has an order of (2,0,0), with a MAPE value of 1.09%, which indicates that the model has good accuracy. Based on the forecasting results, it is estimated that there will be a decrease in the share price of PT. Dayamitra Telekomunikasi Tbk for the next five periods
Comparison of Single Net Premium of Unit Linked Endowment Life Insurance using Annual Ratchet Method and Black Scholes Model Idilla, Leona; Satyahadewi, Neva; Martha, Shantika
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 2 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss2pp73-86

Abstract

Annual Ratchet is an indexing method. Black Scholes is a model used to determine option. The purpose of this study is to compare the results of single net premium of unit-linked endowment life insurance using the Annual Ratchet method and the Black Scholes Model. The data used in this study are data on the daily closing share price of PT Telkom Indonesia (Persero) Tbk for the period December 20, 2021 to December 20, 2022, Bank Indonesia interest rates and the 2019 Mortality Table. In this study, a comparison is made between the Annual Ratchet method and the Black-Scholes model to calculate the net single premium of unit-linked endowment life insurance for a 30-year-old male insured. The results show that the premium calculated using the Annual Ratchet method is greater than the premium from the Black-Scholes model, which is Rp 8,725,000. This is due to the additional protection feature in the Annual Ratchet method, which provides a minimum guaranteed investment value, thus increasing the premium value to be paid.
Estimation of Inpatient Health Insurance Premiums using the RP-2000 Table with Medical Cost Projection Scenario Satyahadewi, Neva; Perdana, Hendra; Tamtama, Ray
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 2 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss2pp97-104

Abstract

Inpatient health insurance serves as an essential form of financial protection to mitigate the risk of loss arising from hospitalization costs. This study aims to estimate inpatient health insurance premiums by combining the Indonesian Mortality Table IV and the RP-2000 Combined Healthy Table to determine age-specific hospitalization probabilities. Methodologically, this research employs a quantitative actuarial modeling approach based on life table techniques and expected present value calculations, using secondary data from the Indonesian Mortality Table IV, the RP-2000 Combined Healthy Table, and published information on medical inflation in Indonesia. The numerical illustrations are obtained through spreadsheet-based actuarial calculations. In addition to age, the premium calculation incorporates the interest rate, the insured’s gender, and cost components such as inpatient care, surgery, and intensive care unit (ICU) treatment so that the premium structure aligns with the coverage provided. A scenario of rising hospital costs due to medical inflation, assumed at 13% per year, is also included to obtain more realistic and economically relevant premium estimates. A case study is conducted for a 30-year-old participant with a two-year coverage period, offering benefits of an inpatient daily allowance of IDR 300,000 (maximum 40 days), surgical expenses up to IDR 3,000,000, miscellaneous hospital care up to IDR 7,000,000, and an ICU allowance of IDR 600,000 per day (maximum 15 days). The analysis results show monthly premiums of IDR 113,341 for male participants and IDR 121,904 for female participants, where the difference is attributed to higher hospitalization risks among females. Age variation analysis indicates that premiums increase with age, while interest rate variation analysis shows that higher interest rates result in lower premiums due to the discounting effect. These findings support the need for a dynamic actuarial approach to setting more accurate and sustainable health insurance premiums

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