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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics LEMMA: Letters Of Mathematics Education MUST: Journal of Mathematics Education, Science and Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING Eksakta : Berkala Ilmiah Bidang MIPA Pelita Eksakta Majalah Ilmiah Matematika dan Statistika (MIMS) Journal of Applied Data Sciences Journal of Science and Technology MATHunesa: Jurnal Ilmiah Matematika Journal of Mathematics UNP Mathematical Journal of Modelling and Forecasting Journal of Statistics and Data Science

Devni Prima Sari

Universitas Negeri Padang

Author-ID : 5650761

Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Transportation Other

Published : 41 Documents Claim Missing Document

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VARIASI PEMBAYARAN ANUITAS DENGAN POLA DERET ARITMATIKA Sari, Devni Prima
JURNAL LEMMA Vol 1, No 1 (2014): LEMMA : Letters of Mathematics Education
Publisher : Universitas PGRI Sumatera Barat

Anuitas adalah rangkaian pembayaran atau penerimaan dalam jumlah tertentu yang dilakukan secara berkala pada jangka waktu tertentu. Konsep anuitas dapat dimulai dengan ketersedian sejumlah dana yang digunakan untuk membayar angsuran dalam suatu jangka waktu sampai dana tersebut habis. Pembayaran anuitas biasanya dilakukan dalam jumlah tetap setiap tahunnya. Oleh karena itu penulis mencoba menganalisa secara matematika mengenai nilai sekarang dan nilai akhir dari pembayaran anuitas yang dilakukan berbeda setiap tahunnya, baik pembayaran naik maupun turun dengan skema pembayaran anuitas mengikuti pola deret aritmatika. Pembayaran anuitas yang seperti ini bisa dijadikan pilihan bagi para annuitant.

K-means and bayesian networks to determine building damage levels Devni Prima Sari; Dedi Rosadi; Adhitya Ronnie Effendie; Danardono Danardono
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.11756

Many troubles in life require decision-making with convoluted processes because they are caused by uncertainty about the process of relationships that appear in the system. This problem leads to the creation of a model called the Bayesian Network. Bayesian Network is a Bayesian supported development supported by computing advancements. The Bayesian network has also been developed in various fields. At this time, information can implement Bayesian Networks in determining the extent of damage to buildings using individual building data. In practice, there is mixed data which is a combination of continuous and discrete variables. Therefore, to simplify the study it is assumed that all variables are discrete in order to solve practical problems in the implementation of theory. Discretization method used is the K-Means clustering because the percentage of validity obtained by this method is greater than the binning method.

Discretization methods for Bayesian networks in the case of the earthquake Devni Prima Sari; Dedi Rosadi; Adhitya Ronnie Effendie; Danardono Danardono
Bulletin of Electrical Engineering and Informatics Vol 10, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i1.2007

The Bayesian networks are a graphical probability model that represents interactions between variables. This model has been widely applied in various fields, including in the case of disaster. In applying field data, we often find a mixture of variable types, which is a combination of continuous variables and discrete variables. For data processing using hybrid and continuous Bayesian networks, all continuous variables must be normally distributed. If normal conditions unsatisfied, we offer a solution, is to discretize continuous variables. Next, we can continue the process with the discrete Bayesian networks. The discretization of a variable can be done in various ways, including equal-width, equal-frequency, and K-means. The combination of BN and k-means is a new contribution in this study called the k-means Bayesian networks (KMBN) model. In this study, we compared the three methods of discretization used a confusion matrix. Based on the earthquake damage data, the K-means clustering method produced the highest level of accuracy. This result indicates that K-means is the best method for discretizing the data that we use in this study.

Comparison of Portfolio Mean-Variance Method with the Mean-Variance-Skewness-Kurtosis Method in Indonesia Stocks Dina Agustina; Devni Prima Sari; Rara Sandhy Winanda; Muhammad Rashif Hilmi; Dina Fakhriyana
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 23 No. 02 (2022): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

In this paper, we compare the optimal portfolio weight of mean-variance (MV) method with mean-variance-skewness-kurtosis (MVSK) method. MV is a method to get weight on a portfolio. This method can be developed into the method of MVSK with attention to the higher-order moment of return distribution; skewness and kurtosis. In determining the weight of portfolio is also important to consider the skewness and kurtosis of return distribution. This method of considering the aspect of skewness and kurtosis is called the MVSK method with the aim of maximizing the level of return and skewness and minimizing the risks and exceeding of kurtosis. The result indicate that the optimal portfolio return of all methods is MVSK method with minimize variance priority.

Optimasi Produksi Tanaman Padi dan Jagung di Kabupaten Pesisir Selatan Menggunakan Metode Fungsi Penalti Eksterior Emmelia Safani; Devni Prima Sari
Journal of Mathematics UNP Vol 5, No 3 (2020): Journal Of Mathematics UNP
Publisher : UNIVERSITAS NEGERI PADANG

Abstract — Planted area, harvested area, and the average production of rice and maize in Pesisir Selatan Regency in 2010-2018 fluctuated, thus affecting agricultural conditions and the economy of the community and government. Therefore, it is necessary to have an optimal planting area, harvest area, and average production of rice and maize. The purpose of this study was to determine the form of a mathematical model and the results of the solution to optimize the production of rice and maize in Pesisir Selatan Regency with the exterior penalty function method. This research method explains the basic concept of the n-order polynomial regression method for the mathematical model of nonlinear programming problems and solving nonlinear programming problems with the exterior penalty function method. The exterior penalty function method converts a constrained nonlinear problem into a constrained one. The data used are secondary data obtained from the publication of the Puasat Statistics Agency for Pesisir Selatan Regency in 2010-2018. The optimal result of the exterior penalty function method for rice plant area is 66.667 Ha, the planted area of maize is 16.667 Ha, and the average total production of rice and maize is 236,56 Kw/Ha. Keywords — Production of Rice and Corn, Polynomial Regression Method, Exterior Penalty Function Method.

Perhitungan Dana Tabarru’ Asuransi Syariah Menggunakan Hukum Mortalita Makeham dengan Metode Cost of Insurance Riri Indriani; Devni Prima Sari
Journal of Mathematics UNP Vol 5, No 2 (2020): Journal Of Mathematics UNP
Publisher : UNIVERSITAS NEGERI PADANG

Abstract — Tabarru’ funds in Islamic insurance is a number of funds that are used to help each other between insurance participants. In the fund management mechanism with savings element, Tabarru’ funds have a percentage of payment of 5%. Whereas in the management of funds without savings, it is not known how much the percentage must be paid to the company, so that it will cause confusion for customers. In this research, we will discuss how to calculate the tabarru’ funds using the cost of insurance method. This calculation involves the probability of death based on the Makeham mortality table. Makeham Mortality Tables can be arranged by estimating parameters using the least squares method. obtained parameters A, B and C, respectively for men, namely 0.05822, 0.00158 and 1.08394, while for women namely 0.04418, 0.00152 and 1.08400. So the amount of tabarru’ funds that must be paid by someone aged x that is,Keywords — Tabarru’ funds, Makeham Mortality Law, Least Squares Method, Cost of Insurance Method

Disaster Mitigation Efforts Using K-Medoids Algorithm and Bayesian Network Devni Prima Sari; Media Rosha; Dedi Rosadi
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 23 No. 03 (2022): Eksakta: Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol23-iss03/304

Disaster mitigation is a series of efforts to reduce disaster risk. One of the disaster mitigation efforts is the supervision of the implementation of spatial planning. Knowing the level of damage to buildings in a region in the event of a disaster can supervise the implementation of spatial planning. To predict the level of damage to buildings in an area, we can use the Bayesian network (BN). There are several types of BN based on the variable type; discrete, continuous, and hybrid BN. A discrete BN is a model in which all the variables involved are discrete. Therefore, if there is a continuous variable, it is necessary to discretize the variable. In this paper, modifications are made to the algorithm commonly used in the clustering process to be used in the discretization process. The algorithm used is the K-Medoids algorithm, where this algorithm uses existing data as a representative of the cluster center. Then, the BN model and the K-Medoids algorithm were used to determine the level of damage to buildings due to the earthquake that occurred in West Sumatra in 2009. From 25,000 house damage data used in this study, we obtain an accuracy rate is 95.17%.

ANALISIS K-MEDOIDS CLUSTERING PADA EPISENTRUM GEMPA BUMI DI PROVINSI SUMATERA BARAT DAN SEKITARNYA Jeri Jefrianto; Devni Prima Sari
Journal of Mathematics UNP Vol 7, No 2 (2022): Journal Of Mathematics UNP
Publisher : UNIVERSITAS NEGERI PADANG

Sumatra is located along the confluence line of the Indo-AustralianPlate and the Eurasian plate, which has high seismic activity. Theisland of Sumatra is prone to earthquakes which pose a considerabledanger, and one of the provinces on this island that is prone toearthquakes is the Province of West Sumatra. So it is necessary tostudy each earthquake characteristic in the Province of West Sumatraand its surroundings using K-Medoids Clustering analysis.Earthquake data used is tectonic earthquake data from December 1970to September 2021 with attributes: latitude, longitude, and magnitude.In this study, several clusters were tried, namely K=2, K=3, K=4, andK=5 using the Euclidean Distance. The most optimum cluster is K=2of 0.448072 using the Silhouette coefficient validation test, theepicenter was at 99.290E and -1.050S with a magnitude of 5.38 on theSR for the first group and the second group produced an epicenter at101.150E and -3.440S with a magnitude of 5.36 SR.

Analisis Risiko Investasi Saham Tunggal Syariah dengan Value at Risk (VaR) Menggunakan Simulasi Monte Carlo Afifah Humayrah; Devni Prima Sari
Journal of Mathematics UNP Vol 8, No 1 (2023): Journal Of Mathematics UNP
Publisher : UNIVERSITAS NEGERI PADANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/unpjomath.v8i1.13375

Investment is an activity to hold a number of funds with the aim of gaining future profits, one of which is by investing in the Islamic capital market. Islamic capital market instruments that can be used are shares. Stocks are known to have the characteristics of high risk and high return, not only bringing high profits but also carrying high risks. One of the measuring tools that can be used to measure risk is Value at Risk because it can estimate the maximum possible loss that can occur on a single asset at a certain level of confidence. The purpose of this study is to estimate the optimal risk obtained by using Value at Risk with Monte Carlo Simulation. The data used in this study is the closing price of shares of PT Telekomunikasi Indonesia, Tbk which is listed in the Jakarta Islamic Index (JII). Based on research using initial investment funds of 100,000,000.00, IDR the value of Value at Risk is -3,620,898.95 IDR at an error level of 1%, -2,709,707.70 IDR at an error level of 5% and -2.120.418.85 IDR at an error level of 10. %.

ANALISIS METODE ARIMA PADA PERAMALAN NILAI EKSPOR SUMATERA BARAT irwandi irwandi; Devni Prima Sari
Journal of Mathematics UNP Vol 6, No 4 (2021): Journal Of Mathematics UNP
Publisher : UNIVERSITAS NEGERI PADANG

The movement of the export value of the province of West Sumatra every month experiences a fluctuating condition and tends to decline. Exports are very important for the economy in a region. The decline in the value of exports allows a decrease in the amount of production of goods which can result in weakening economic growth in the region. The non-constant export value needs to be analyzed so that it can be used as an indicator for the West Sumatra government in taking policies that maximize export value, such as increasing competence and skills to produce products that are able to compete in the export market. So it is necessary to forecast the export value of the province of West Sumatra so that the government can take some planning in the future. This study aims to determine the form of the forecasting model and the results of forecasting the export value of West Sumatra for the period January 2021 to December 2021. The forecasting method used is the ARIMA method. The results show that the ARIMA (2,1,0) model is a suitable model for predicting the export value of West Sumatra, with the model Y_t=0,00131+0,5265Y_(t-1)+0,1705Y_(t-2)+0,3030Y_(t-3)+e_t.

Co-Authors 1004, Anisa Adellia, Clara Febby Adhitya Ronnie Effendie, Adhitya Ronnie Afifah Humayrah Afifah, Wardah Hasna Anggraini, Fira arsilla uswatunnisa Danardono Danardono Dedi Rosadi Deswita, Siska Dina Agustina Dina Agustina, Dina Dina Fakhriyana Emmelia Safani Fadhilah Fitri Febri, Fera Malianis Filfiqri, Hamimatul Gulo, Trimodesman Hardinsyah Gusvira Widuri irwandi irwandi Jayawarsa, A.A. Ketut Jeri Jefrianto Lestari, Adika Risky Media Rosha Medika, Amelia Nurul Miftha Delinda Muhammad Rashif Hilmi Pepi Novianti Prastika, Ifa Pratama, Tasya Putri Puja Ermiati Putri, Elisa Ananda Putri, Muthiara Hazimah Putri, Rahma Dana Putriyana Nursal Rara Sandhy Winanda Riri Indriani Rohadatul Aisy Sadli, Wanda Hamidah Soleha, Annisa Sumita, Nurmaya Tessy Octavia Mukhti Tri Rahmayani Ulfasari Rafflesia Wardana, Yuni Yolandafitri Zulvia

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