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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 Jurnal Varian 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
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 Social Sciences Transportation Other

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Optimal Portfolio Risk Estimation Using Expected Shortfall of Jakarta Islamic Index (JII) Shares Lestari, Adika Risky; Sari, Devni Prima
Mathematical Journal of Modelling and Forecasting Vol. 2 No. 1 (2024): June 2024
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v2i1.19

Abstract

Forming an optimal portfolio using the Mean-Variance method with Downside Deviation as a measure of risk produces a good combination of assets. Before investing, estimating risk as a worst-case scenario is very important. Expected shortfall (ES) serves as a risk measure that takes into account the possibility of losses that exceed Value at Risk (VaR). This study aims to determine the optimal portfolio and compare ES and VaR at the 90%, 95%, and 99% confidence levels. This research data involves 3 stocks namely ACES, WIFI, and TLKM. Based on the results of the analysis conducted, the optimal combination of weights is ACES (19%), WIFI (10%), and TLKM (71%). Comparison of ES and VaR shows that the higher the level of confidence, the higher the VaR and ES values generated, so the greater the risk that will be borne by investors and the capital allocation used to cover these losses.
Analysis of Product Quality Control Using the Taguchi Method and Principal Component Analysis (PCA) at the Pabrik Tahu Alami Gulo, Trimodesman Hardinsyah; Sari, Devni Prima
Mathematical Journal of Modelling and Forecasting Vol. 2 No. 1 (2024): June 2024
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v2i1.22

Abstract

Indonesia's rapid economic growth in the global business sector has intensified competition among entrepreneurs, necessitating stringent control over product quality for companies to sustain their market position. This study utilizes the Taguchi method and Principal Component Analysis (PCA) to enhance quality control processes. The Taguchi method focuses on offline quality control with a single response, while PCA is employed for multiple responses. Experiments were conducted at Pabrik Tahu Alami, examining four factors: soybean rate, soaking time, boiling time, and whey water rate, each at three levels. The optimal combination determined was 3 kg of soybeans (level 1), 4 hours of soaking time (level 1), 20 minutes of boiling time (level 2), and 5 litres of whey water (level 2). These results provide a robust framework for optimizing product quality in similar production settings.
Earthquake Point Clustering in Sumatra Island using Spatio-Temporal Density-Based Spatial Clustering Application with Noise (ST-DBSCAN) Algorithm Putri, Muthiara Hazimah; Sari, Devni Prima
Mathematical Journal of Modelling and Forecasting Vol. 3 No. 1 (2025): June 2025
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v3i1.33

Abstract

Abstract. Earthquakes are one of the natural disasters that often occur in Indonesia, especially on the island of Sumatra. Earthquakes become a frightening spectre because they cannot be predicted when they will come, where they will be located, and how strong the vibrations are, so they often cause damage and casualties. To minimise losses due to earthquakes, it is necessary to divide areas easily affected by earthquakes. One method that can be used to divide these areas is clustering techniques. This study uses a clustering method, namely Spatio Temporal-Density Based Spatial Clustering Application with Noise (ST-DBSCAN), on the dataset of earthquake points on the island of Sumatra in 1917-2023. This method uses a spatial distance parameter (ε_1= 0.28), temporal distance parameter (= 180), and minimum number of cluster members (MinPts = 7) with a silhouette coefficient of 0.0991, resulting in 145 clusters with 15 large clusters and 4922 noises. The epicentres are primarily located in Siberut Island, Tanah Bala Island and its surroundings, the Indian Sea opposite Nias Island, the Sea around the Mentawai Islands, Enggano Island and its environs, Simaulue Regency, and Enggano Island and the Sea around it. The most common type of spatio-temporal pattern found is the occasional pattern type.
Forecasting Rainfall in Padang Panjang City Using Fuzzy Time Series Cheng Pratama, Tasya Putri; Sari, Devni Prima
Mathematical Journal of Modelling and Forecasting Vol. 3 No. 1 (2025): June 2025
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v3i1.35

Abstract

Rainfall is essential in many areas of life, including agriculture, water resource management, and disaster mitigation.  Padang Panjang is one of the cities with high rainfall. Rainfall varies throughout the year, affecting agriculture and people's livelihoods. Therefore, accurate rainfall estimation is required to support effective planning and management. This study aims to forecast the amount of rainfall in Padang Panjang City from January 2020 to November 2024 using the fuzzy time series method of the Cheng model. The data is on the monthly rainfall amount from January 2020 to November 2024, obtained from the BMKG Padang Pariaman Climatology Station. The stages in the fuzzy time series Cheng model are forming the universe set, forming intervals, fuzzifying the data, analyzing Fuzzy Logical Relationship (FLR) and Fuzzy Logical Relationship Group (FLRG), determining the weight of the relationship, forecasting, and measuring the accuracy of predicting using Mean Absolute Percentage Error (MAPE). The forecasting results were validated using MAPE, with a value of 41%, which indicates that the model is feasible. The forecasting results for the following three periods are December 2024 high rainfall, January 2025 medium rainfall, and February 2025 high rainfall. This research shows that the fuzzy time series method of the Cheng model can be used as an alternative means of forecasting time series data.
Application of Seasonal Autoregressive Integrated Moving Average (SARIMA) Method in Forecasting Chicken Egg Prices in Indonesia Afifah, Wardah Hasna; Sari, Devni Prima
MUST: Journal of Mathematics Education, Science and Technology Vol 10 No 1 (2025)
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/must.v10i1.26370

Abstract

Chicken eggs are one of the widely known food commodities and are routinely used for daily food menus. Therefore, the price often fluctuates. So that the forecasting of chicken egg prices in Indonesia is very necessary so that the government can monitor price stability and plan future steps. The method that is suitable for this forecast is the Seasonal Autoregressive Integrated Moving Average (SARIMA). The results of data analysis using the SARIMA method show that the best model used for forecasting is SARIMA (2,1,3)(0,1,1)12. This model has a Mean Square Error value of 815267 and a Mean Absolute Percentage Error of 4% so it is good for forecasting. From this model, it is estimated that the price of broiler chicken eggs will tend to fluctuate and increase in the next 24 months, namely from January 2025 to December 2026. Keywords: price, chiken eggs, forcasting, sarima method.
Hierarchical Clustering of Education Indicators in Papua Island: A Ward’s Method Approach Prastika, Ifa; Sari, Devni Prima
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9740

Abstract

Education development aims to ensure inclusive, equitable education and increase learning opportunities for all Indonesian citizens. Papua Island is still not an island with a high education level; data on education indicators indicate this in each Regency / City on the island of Papua, with a value below the national average. Identifying districts/cities is needed to improve education, so clustering is carried out using the Ward method. This research aims to group and map regencies/cities on the island of Papua based on education indicators. The results of this study are expected to be a consideration and benchmark for the government in making decisions regarding education in districts/cities on the island of Papua, considering the region's characteristics. This is an applied research with the data type used, namely secondary data on education indicators in Papua Island in 2022. Data sources are obtained from the official website of the Central Bureau of Statistics of each province on the island of Papua. Four education indicators are taken into account in this research, namely the School Participation Rate (SPR), the Gross Enrollment Rate (GER), the Net Enrollment Ratio (NER), and the Average Years of Schooling (AYS), which are then detailed into 10 variables. The cluster analysis process uses Euclidean distance and cluster validation using the Dunn Index. The results showed that 3 clusters formed. Cluster 1 consists of 27 districts/cities; this first group is classified as a high level of education. Cluster 2 consists of 7 districts/cities with a medium level of education, and Cluster 3 has eight districts/cities with a low level of education—cluster results based on the highest Dunn Index validation value of 0.414.
DETERMINATION OF BANK INDONESIA SCHOLARSHIP RECIPIENTS USING NAÏVE BAYES CLASSIFIER Febri, Fera Malianis; Sari, Devni Prima
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1595-1604

Abstract

A scholarship is a grant given to students as financial aid for education. One of the most sought-after scholarships is the scholarship from Bank Indonesia. Currently, the selection process for Bank Indonesia scholarship recipients still involves verifying the completeness of the administrative documents of the prospective recipients. Manual administrative verification requires a long time for data processing and re-verification. Therefore, there is a need for a data classification system to assist in the decision-making process for Bank Indonesia scholarship recipients. This study aims to implement the naïve Bayes classifier method to classify Bank Indonesia scholarships accurately. The variables used include gender, semester, parental income, grade point average (GPA), achievement, organizational activity, and the number of dependents. This research found that the naïve Bayes classifier method for classifying Bank Indonesia scholarship recipients can be done accurately with an accuracy rate of 86,84%.
ANALYSIS OF THE RELATIONSHIP BETWEEN FACTORS THAT INFLUENCE USER SATISFACTION IN GOJEK USING THE FUZZY DEMATEL METHOD Putri, Elisa Ananda; Sari, Devni Prima
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp1349-1358

Abstract

Gojek is one of the most popular online transportation services in Indonesia. The success of Gojek is closely tied to user satisfaction. There are five factors influencing user satisfaction: service quality factor (A), price factor (B), ease of use factor (C), perceived benefit factor (D), and online servicescape factor (E). This research aims to identify which factors most significantly affect user satisfaction with Gojek services among students of the Mathematics Department at UNP. This study in applied research that is described using fuzzy DEMATEL and employs primary data obtained from questionnaire responses. The population of this study consists of students from the Mathematics Department at FMIPA UNP who enrolled in 2022, with a sample size of 75 students using the proportional random sampling technique. The results of this research indicate a significant relationship between the service quality factor (A) and price factor (B). With respective y coordinates of 0.583 and 2.074, the researcher can conclude that the price factor has the most significant influence on user satisfaction with Gojek among students of the Mathematics Department at FMIPA UNP in the 2022 cohort.
Regional Clustering in Sumatera Based on Walfare Indicators Using Fuzzy C-Means Putri, Rahma Dana; Sari, Devni Prima
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10103

Abstract

Welfare refers to a condition in which individuals have sufficient means to meet both physical and spiritual needs. In Indonesia, welfare is a national goal, yet Sumatra experiences the highest development disparity, contributing to unequal welfare distribution across regions. This study aims to cluster regions in Sumatra based on welfare indicators using the Fuzzy C-Means (FCM) method, analyze cluster characteristics, and provide policy recommendations for decision-makers. FCM is used because it accommodates uncertainty and allows each data point to belong to more than one cluster, making it suitable for welfare analysis. Cluster validity was tested using Partition Coefficient Index (PCI) and Silhouette Coefficient, both indicating that the optimal number of clusters is two. The results show that Cluster 1 consists of 62 regions with relatively higher welfare conditions, while Cluster 2 includes 92 regions with lower welfare characteristics. One notable member of Cluster 2 is Ogan Komering Ulu, with a high membership degree of 0.869. Recommended policies include improving access to clean water and healthcare, enhancing education, strengthening local economies, and delivering targeted social assistance to underdeveloped areas. For Cluster 1, sustainable development efforts should be maintained.
Rural Public Service Innovation: Database Training Using Google Apps and Microsoft Office as a Solution for Service Quality Improvement Zulvia, Yolandafitri; Sari, Devni Prima; Agustina, Dina
Pelita Eksakta Vol 7 No 1 (2024): Pelita Eksakta, Vol. 7, No. 1
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol7-iss1/225

Abstract

Innovation in public services is an important aspect in improving the quality of services to the community, especially at the village level. One innovation that is very relevant is the use of Google Apps and Microsoft Office.Pangkalan Koto Baru is one of the villages located in Lima Puluh Kota Regency, West Sumatra Province. From the initial survey conducted by the PKM team, several problems related to administrative services were found, including the lack of skills, knowledge and information and communication technology, data management and administrative information. For this reason, the PKM team conducted Database training activities using Google Apps and Microsoft Office to improve village administrative services. The method used is to provide training and assistance in building an integrated and effective system in managing data and information. This activity ended with an evaluation. Based on the results of observations and evaluations during the activity, there was an increase in the understanding and ability of village officials regarding the use of Google Apps and Microsoft Office to improve services to the community.
Co-Authors 1004, Anisa Abda Abda Adellia, Clara Febby Adhitya Ronnie Effendie, Adhitya Ronnie Afifah Humayrah Afifah, Wardah Hasna Anggraini, Fira Anis, Mei Syarah arsilla uswatunnisa Danardono Danardono Dedi Rosadi Deswita, Siska Dina Agustina 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 nur hafizah 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