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INDONESIA
Jurnal Matematika Sains dan Teknologi
Published by Universitas Terbuka
ISSN : 14111934     EISSN : 24429147     DOI : -
Core Subject : Education, Agriculture,
Agriculture, Biological Sciences & Forestry Mathematics Other
Merupakan media informasi dan komunikasi para praktisi, peneliti, dan akademisi yang berkecimpung dan menaruh minat serta perhatian pada pengembangan Matematika, ilmu pengetahuan dan teknologi. Diterbitkan oleh Lembaga Penelitian dan Pengabdian kepada Masyarakat, Universitas Terbuka.
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "vol. 25 no. 2 (2024)" : 5 Documents clear
Analysis of the Impact of Energy Consumption and Economic Performance on Carbon Dioxide Emissions in Indonesia Using Error Correction Mechanism Abigail Brenda Padhang Pasorong Randa; Arlita Dwina Firlana Sari; Emily Azizaida Budikusuma; Yuniar Yudhi Tirana; Nasrudin Nasrudin
Jurnal Matematika Sains dan Teknologi Vol. 25 No. 2 (2024)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v25i2.6879.2024

Abstract

Lately, Indonesia has been intensively developing its domestic economy. Industrial development began to be started, which attracted investors to invest. However, this massive economic development is causing an increase in CO2 emissions. This study intends to capture the effects of primary energy consumption per capita and economic performance represented by Gross Domestic Product (GDP), Foreign Direct Investment (FDI), and International Trade Openness on CO2 emissions in Indonesia from 1990–2022, in the short-run and long-run, using Error Correction Mechanisms (ECMs) analysis. In the long-run, energy consumption and GDP significantly affect CO2 emissions in Indonesia. Meanwhile, in the short-run, only energy consumption and Error Correction Term (ECT) have a significant effect on CO2 emissions. Moreover, from the ECT coefficient, it is known that the speed of adjustment to return to equilibrium is 95.08% in the first year after the shock.
Application of teh Hybrid Singular Spectrum Analysis – ARIMA Model for Indonesia's Inflation Rate (2018-2023) Sri Rahayu; Aswi Aswi; Muhammad Fahmuddin Sudding
Jurnal Matematika Sains dan Teknologi Vol. 25 No. 2 (2024)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v25i2.7982.2024

Abstract

This research aims to determine the results and accuracy of forecasting inflation rates in Indonesia using Hybrid Singular Spectrum Analysis (SSA) – Autoregressive Integrated Moving Average (ARIMA). Hybrid SSA-ARIMA combines two time series methods to increase forecasting accuracy, especially for economic data that contains trend and seasonal components. The data used is data on the national consumer price inflation rate (Y-on-Y) for the period January 2018 to December 2023. The forecast accuracy obtained by the MAPE value for Singular Spectrum Analysis was 56.26797%, and Hybrid SSA-ARIMA was 18.88851%. This shows that Hybrid SSA-ARIMA has better forecasting capabilities than Singular Spectrum Analysis in predicting the inflation rate in Indonesia.
Application of The Fuzzy Ruey Chyn Tsaur Method to The Time Series Data: (Case Study: Total Exports in East Kalimantan from January 2018 to May 2021) Indah Ayu Kartika Putri; Ika Purnamasari; Suyitno
Jurnal Matematika Sains dan Teknologi Vol. 25 No. 2 (2024)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v25i2.6505.2024

Abstract

Markov chains are stochastic processes in which current events depend only on events one step back. The transition probability matrix shows the probability of movement between states in a Markov chain process. The transition likelihood matrix can be used to help forecast future changes. This research has the purpose of forecasting using the fuzzy Ruey Chyn Tsaur method combined with the Markov chain concept. In this study, the determination of interval length was carried out using Sturges and averages based. The results showed that the value of MAPE based on Sturges (5.95%) is lower than the value based on the average (6.02%). In June 2021, forecasting of the total exports was obtained at USD 1,687.17 million for the Sturges method and USD 1,728 million for average based.
Route Optimization in Asymmetric Capacitated Vehicle Routing Problem (ACVRP) Model using Tabu Search Algorithm (Case Study: Car Oil Distribution of PT. Kencana Central Mobil) Thedorus Junjun; Mariatul Kiftiah; Fransiskus Fran
Jurnal Matematika Sains dan Teknologi Vol. 25 No. 2 (2024)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v25i2.6575.2024

Abstract

PT. Kencana Central Mobil is an automotive workshop that distributes oil to nine regular customers spread across Pontianak and its surroundings. The route from the depot to the customer and between customers has a different length, because when making a round trip using different roads. From this information, the author conducted observations in the field to measure the distance between customers with the help of the Avanza application. Thus, the problem in this company is included in the Asymmetric Capacitated Vehicle Routing Problem. The ACVRP model is a problem where the route from location  to  is not the same as the route from location  to . Based on the problems that have been explained, this study uses the Tabu Search algorithm to solve it. The Tabu Search algorithm works by moving from one route to another, so that when related to a problem the company can find a trip by choosing the shortest route. There are six steps in solving this problem, namely determining the initial route, finding alternative routes by swapping two node positions so that the routes that can be formed each iteration are  routes (nine is the number of customers), choosing the best route among alternative routes, determining the new best route, updating the tabu list and checking the stopping criteria. From the calculation results, there is a difference in the distance traveled from the initial route which is 63.16 km long, while when calculated using the Tabu Search Algorithm, it can be seen that the tabu search criteria stops at the 7th iteration with a route length of 50.26 km so that it differs by 12.9 km from the initial route. The length of the route is optimal because it has the shortest route length of all the literature that has been traced.
Estimating The Probability of Depression in Adolescent Based on Internal Family Factors using Binary Logistic Regression and Naïve Bayes Muhammad Hasan Sidiq Kurniawan; Achmad Fauzan
Jurnal Matematika Sains dan Teknologi Vol. 25 No. 2 (2024)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v25i2.10312.2024

Abstract

Depression is a common mental health issue affecting approximately 300 million people globally, with severe cases potentially leading to death. Adolescents with depression are reported to have a 30-fold increased risk of suicide compared to other age groups, making early identification and intervention in this age group essential. Internal family factors play a crucial role in influencing adolescent mental health, including variables such as family type, parenting style, residence status, birth order, and parental occupation. This study aims to identify which internal family factors significantly impact the likelihood of depression and to estimate the probability of depressive episodes in adolescents. By understanding these factors, preventive measures can be better tailored to reduce adolescent depression in the future. The data utilized in this study is primary data obtained through a sampling process employing the simple random sampling method applied to first-year university students. A binary logistic regression model was employed to analyze the significance of each family-related factor. Findings indicate that parenting style and parental occupation are among the most significant factors associated with adolescent depression. The novelty of this study lies in the exploration of internal family factors that are rarely examined comprehensively in previous research, such as the effects of family type, birth order, and parental occupation. Additionally, the study adopts a dual-method approach, combining logistic regression and Naive Bayes, to provide a robust and comparative analysis of predictive accuracy. Probability estimates were conducted using both binary logistic regression and Naive Bayes methods. Results from these analyses suggest that a democratic parenting style tends to foster more stable mental health in adolescents, while adolescents with parents employed in the private sector or similar occupations face a higher likelihood of depression. Both methods demonstrated high predictive accuracy, with 96.31% for logistic regression and 96.93% for Naive Bayes.

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