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Journal of Mathematics and Scientific Computing With Applications
Published by Yayasan Pena Cendekia Insani
ISSN : 27985512     EISSN : 27985776     DOI : -
Core Subject : Education,
Mathematics
Journal of Mathematics and Scientific Computing With Applications is a broad-based journal covering all branches of computational or applied mathematics with special encouragement to researchers in theoretical computer science and mathematical computing. It covers all major areas, such as numerical analysis, discrete optimization, linear and nonlinear programming, theory of computation, control theory, theory of algorithms, computational logic, applied combinatorics, coding theory, cryptographic, fuzzy theory with applications, differential equations with applications. Journal features research papers in all branches of mathematics that have some bearing on the application to scientific problems, including areas of actuarial science, mathematical biology, mathematical economics, and finance.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 10 Documents
 1 
Search results for , issue "Vol. 5 No. 1 (2024)" : 10 Documents clear
APPLICATION OF THE FORWARD RECURSIVE EQUATION MODEL ON WASTE TRANSPORTATION ROUTES IN MEDAN JOHOR DISTRICT USING DYNAMIC PROGRAMMING ALGHORITHM Hanum, Syarifah; Azura, Maudya Nur; Sari, Dinda Permata; Husein, Ismail
Journal of Mathematics and Scientific Computing With Applications Vol. 5 No. 1 (2024)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v4i1.854

Abstract

Waste problems often occur in big cities such as Jakarta, Surabaya, Medan, Bandung, Yogyakarta and Semarang. Urban waste is waste produced by human activities in urban areas, including various types of materials such as plastic, paper, metal and organic materials. Therefore, waste needs to be collected, transported and disposed of immediately to prevent negative impacts on the environment. With the increase in population in urban areas, it is likely that the amount of waste will also increase. The solution that can be used to solve this problem is to optimize the distance using a dynamic programming model forward recursive equation algorithm. The application of dynamic programming can be used to solve various problems such as determining the shortest distance, optimal flow, task or resource scheduling, production planning, network optimization, and problems in research and development projects. Based on determining the optimal route for transporting waste in Medan Johor District using the dynamic programming algorithm forward recursive equation model, the total distance is 26,2km.
APPLICATION OF THE MONTE CARLO METHOD IN PREDICTING THE NUMBER OF BUDGET PROPOSALS ACCEPTED IN NORTH SUMATRA PROVINCIAL HEALTH OFFICE Harahap, Riska; Siahaan, Maharani Putri Adam; Widyasari, Rina
Journal of Mathematics and Scientific Computing With Applications Vol. 5 No. 1 (2024)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v4i1.873

Abstract

A budget is a planning tool regarding future expenditure and revenues, generally prepared for one year. The prediction simulation for approved budget proposals is an estimate of the calculation of the approval rate for approved proposals in the following year. This research uses the Monte Carlo method in solving problems. This method can be used in problems with nonlinear boundary conditions, namely prediction limits.the author uses a quantitative descriptive method, which is a form of research that focuses on the facts and characteristics of the research object by combining related variables. This research uses the Monte Carlo method uses random numbers and probability statistics to solve problems.The data used to predict the approved proposal budget is the budget proposal data that is approved each year. The following is one of the approved proposal data, namely the approved budget proposal data from 2021, 2022 and 2023 budget proposals received using the Monte Carlo Method which has been implemented at the North Sumatra Provincial Health Service with the simulation namely with an average percentage in 2022 of 84% and in 2023 by 76%. So with the successful application of the Monte Carlo Method to predict the number of budget proposals received at the North Sumatra Provincial Health Service for 2024 it will provide convenience for the North Sumatra Provincial Health Service to find out what the predicted number of budget .
POPULATION PREDICTION OF SIMALUNGUN DISTRICT USING THE LOGISTIC MODEL IN 2025-2030 Dora Latersia P, Egya; Jehan Maulana, Putri; Nada Utami, Destia; Rizki Hanafi, Muhammad
Journal of Mathematics and Scientific Computing With Applications Vol. 5 No. 1 (2024)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v5i1.978

Abstract

Population growth prediction is an important aspect in regional development planning, including in Simalungun Regency, which has complex demographic dynamics. Based on data from BPS, the population in Simalungun Regency is increasing every year, so a solution is needed to reduce the negative impact so that there is no population explosion. The solution that can be used to project the population in Simalungun Regency is to use a logistic growth model. This model is used to calculate the value of the growth rate and environmental carrying capacity (Carrying Capacity) using population data in Simalungun Regency in 2019-2023. The results obtained show that the environmental carrying capacity that limits the population in Simalungun Regency is 1,005,168.408 people. With the relative growth rate per year of the population in Simalungun Regency using the logistic model I is 3.46%. This model also projects the population in Simalungun Regency from 2025-2030. The population in 2025 amounted to 1,374,983 people until the year 2030 is estimated to amount to 1,476,292 people.
APPLICATION OF ANT COLONY OPTIMIZATION ALGORITHM ON DETERMINATION OF TRANSPORTATION FROM BELAWAN TO TUNTUNGAN CAMPUS Juliana; Juliani; Ramadhani, Akhiriyah; Widya, Ade; Farhan Zacky, M.
Journal of Mathematics and Scientific Computing With Applications Vol. 5 No. 1 (2024)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v5i1.979

Abstract

Transportation is an alternative used by everyone to get to a destination. In research, several alternative means of transportation can be used by students who live far from their campus. Students can determine the closest route to get to their campus. The campus we take is UINSU Campus IV. This research aims to overcome the transportation problems of students who live in the Belawan area and its surroundings. The research also used the ant colony optimization (ACO) algorithm method, with this method to make it easier to get the shortest route with a short time and the lowest cost or still standard with the distance. The ant colony optimization method is an algorithm inspired by the natural life of ants regarding ant habits in finding food. This research aims to get the shortest route and the optimal means of transportation used. In this study, it was found that the optimal means of transportation as well as distance, time, and cost were motorcycle transportation with a distance of 64.5km and the time required was 1 hour 4 minutes and the cost to be incurred was Rp. 40,000.00. This research uses Google Maps data to determine the distance of a location. Although the results are not optimal, it can be used as a solution for students in calculating the distance, time and cost to be used.
ANALYSIS OF THE BEST FERTILIZER SELECTION FOR CORN PLANTS USING THE MULTI-ATTRIBUTE UTILITY THEORY METHOD Sahrudin; Andini, Dwi; Malakiano Ritonga, Sandrina; Janurianty, Intan; Widya, Ade
Journal of Mathematics and Scientific Computing With Applications Vol. 5 No. 1 (2024)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v5i1.980

Abstract

Corn (Zea mays L.) is one of the most important food crops in the world, serving as a staple food for many countries, as well as a primary source of livestock feed and an industrial raw material. This research aims to determine the best fertilizer for corn plants (Zea mays L.) by applying the Multi-Attribute Utility Theory (MAUT) method, a systematic approach to multi-criteria decision making. This research was conducted in Rundeng District, Subulussalam City, Aceh, with three alternative fertilizers analyzed, namely NPK Mutiara, Urea, and Phonska. The criteria used include price, nutritional efficiency, and availability of fertilizer on the market, with weights for each criterion of 0.3, 0.5, and 0.2. The research results show that Phonska fertilizer has the highest global utility value of 0.895, making it the best choice based on the specified criteria. Phonska stands out for its optimal balance between affordable price, high nutritional efficiency and good availability on the market. Urea is in second place with a global utility value of 0.856, superior in terms of cheaper price, but lower efficiency than Phonska. Mutiara NPK, despite having the highest nutritional efficiency, only obtained a global utility value of 0.807 due to its higher price and lower availability. This research provides data-based guidance for farmers to choose the most suitable fertilizer, which is expected to increase corn crop productivity, reduce production costs, and support agricultural sustainability. By using the MAUT method, this research proves that a data-based approach can help make more rational decisions in the agricultural sector.
APPLICATION OF THE FORWARD RECURSIVE EQUATION MODEL ON WASTE TRANSPORTATION ROUTES IN MEDAN JOHOR DISTRICT USING DYNAMIC PROGRAMMING ALGHORITHM Hanum, Syarifah; Azura, Maudya Nur; Sari, Dinda Permata; Husein, Ismail
Journal of Mathematics and Scientific Computing With Applications Vol. 5 No. 1 (2024)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v5i1.854

Abstract

Waste problems often occur in big cities such as Jakarta, Surabaya, Medan, Bandung, Yogyakarta and Semarang. Urban waste is waste produced by human activities in urban areas, including various types of materials such as plastic, paper, metal and organic materials. Therefore, waste needs to be collected, transported and disposed of immediately to prevent negative impacts on the environment. With the increase in population in urban areas, it is likely that the amount of waste will also increase. The solution that can be used to solve this problem is to optimize the distance using a dynamic programming model forward recursive equation algorithm. The application of dynamic programming can be used to solve various problems such as determining the shortest distance, optimal flow, task or resource scheduling, production planning, network optimization, and problems in research and development projects. Based on determining the optimal route for transporting waste in Medan Johor District using the dynamic programming algorithm forward recursive equation model, the total distance is 26,2km.
APPLICATION OF THE MONTE CARLO METHOD IN PREDICTING THE NUMBER OF BUDGET PROPOSALS ACCEPTED IN NORTH SUMATRA PROVINCIAL HEALTH OFFICE Harahap, Riska; Siahaan, Maharani Putri Adam; Widyasari, Rina
Journal of Mathematics and Scientific Computing With Applications Vol. 5 No. 1 (2024)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v5i1.873

Abstract

A budget is a planning tool regarding future expenditure and revenues, generally prepared for one year. The prediction simulation for approved budget proposals is an estimate of the calculation of the approval rate for approved proposals in the following year. This research uses the Monte Carlo method in solving problems. This method can be used in problems with nonlinear boundary conditions, namely prediction limits.the author uses a quantitative descriptive method, which is a form of research that focuses on the facts and characteristics of the research object by combining related variables. This research uses the Monte Carlo method uses random numbers and probability statistics to solve problems.The data used to predict the approved proposal budget is the budget proposal data that is approved each year. The following is one of the approved proposal data, namely the approved budget proposal data from 2021, 2022 and 2023 budget proposals received using the Monte Carlo Method which has been implemented at the North Sumatra Provincial Health Service with the simulation namely with an average percentage in 2022 of 84% and in 2023 by 76%. So with the successful application of the Monte Carlo Method to predict the number of budget proposals received at the North Sumatra Provincial Health Service for 2024 it will provide convenience for the North Sumatra Provincial Health Service to find out what the predicted number of budget .
POPULATION PREDICTION OF SIMALUNGUN DISTRICT USING THE LOGISTIC MODEL IN 2025-2030 Dora Latersia P, Egya; Jehan Maulana, Putri; Nada Utami, Destia; Rizki Hanafi, Muhammad
Journal of Mathematics and Scientific Computing With Applications Vol. 5 No. 1 (2024)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v5i1.978

Abstract

Population growth prediction is an important aspect in regional development planning, including in Simalungun Regency, which has complex demographic dynamics. Based on data from BPS, the population in Simalungun Regency is increasing every year, so a solution is needed to reduce the negative impact so that there is no population explosion. The solution that can be used to project the population in Simalungun Regency is to use a logistic growth model. This model is used to calculate the value of the growth rate and environmental carrying capacity (Carrying Capacity) using population data in Simalungun Regency in 2019-2023. The results obtained show that the environmental carrying capacity that limits the population in Simalungun Regency is 1,005,168.408 people. With the relative growth rate per year of the population in Simalungun Regency using the logistic model I is 3.46%. This model also projects the population in Simalungun Regency from 2025-2030. The population in 2025 amounted to 1,374,983 people until the year 2030 is estimated to amount to 1,476,292 people.
APPLICATION OF ANT COLONY OPTIMIZATION ALGORITHM ON DETERMINATION OF TRANSPORTATION FROM BELAWAN TO TUNTUNGAN CAMPUS Juliana; Juliani; Ramadhani, Akhiriyah; Widya, Ade; Farhan Zacky, M.
Journal of Mathematics and Scientific Computing With Applications Vol. 5 No. 1 (2024)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v5i1.979

Abstract

Transportation is an alternative used by everyone to get to a destination. In research, several alternative means of transportation can be used by students who live far from their campus. Students can determine the closest route to get to their campus. The campus we take is UINSU Campus IV. This research aims to overcome the transportation problems of students who live in the Belawan area and its surroundings. The research also used the ant colony optimization (ACO) algorithm method, with this method to make it easier to get the shortest route with a short time and the lowest cost or still standard with the distance. The ant colony optimization method is an algorithm inspired by the natural life of ants regarding ant habits in finding food. This research aims to get the shortest route and the optimal means of transportation used. In this study, it was found that the optimal means of transportation as well as distance, time, and cost were motorcycle transportation with a distance of 64.5km and the time required was 1 hour 4 minutes and the cost to be incurred was Rp. 40,000.00. This research uses Google Maps data to determine the distance of a location. Although the results are not optimal, it can be used as a solution for students in calculating the distance, time and cost to be used.
ANALYSIS OF THE BEST FERTILIZER SELECTION FOR CORN PLANTS USING THE MULTI-ATTRIBUTE UTILITY THEORY METHOD Sahrudin; Andini, Dwi; Malakiano Ritonga, Sandrina; Janurianty, Intan; Widya, Ade
Journal of Mathematics and Scientific Computing With Applications Vol. 5 No. 1 (2024)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v5i1.980

Abstract

Corn (Zea mays L.) is one of the most important food crops in the world, serving as a staple food for many countries, as well as a primary source of livestock feed and an industrial raw material. This research aims to determine the best fertilizer for corn plants (Zea mays L.) by applying the Multi-Attribute Utility Theory (MAUT) method, a systematic approach to multi-criteria decision making. This research was conducted in Rundeng District, Subulussalam City, Aceh, with three alternative fertilizers analyzed, namely NPK Mutiara, Urea, and Phonska. The criteria used include price, nutritional efficiency, and availability of fertilizer on the market, with weights for each criterion of 0.3, 0.5, and 0.2. The research results show that Phonska fertilizer has the highest global utility value of 0.895, making it the best choice based on the specified criteria. Phonska stands out for its optimal balance between affordable price, high nutritional efficiency and good availability on the market. Urea is in second place with a global utility value of 0.856, superior in terms of cheaper price, but lower efficiency than Phonska. Mutiara NPK, despite having the highest nutritional efficiency, only obtained a global utility value of 0.807 due to its higher price and lower availability. This research provides data-based guidance for farmers to choose the most suitable fertilizer, which is expected to increase corn crop productivity, reduce production costs, and support agricultural sustainability. By using the MAUT method, this research proves that a data-based approach can help make more rational decisions in the agricultural sector.

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