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Tessy Octavia Mukhti
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LPPM Universitas Negeri Padang, Jalan Prof. Dr. Hamka, Air Tawar Barat, Kota Padang, Sumatera Barat 25131
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UNP Journal of Statistics and Data Science
Published by Universitas Negeri Padang
ISSN : -     EISSN : 2985475X     DOI : 10.24036/ujsds
Core Subject : Science, Education, Social,
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences
UNP Journal of Statistics and Data Science is an open access journal (e-journal) launched in 2022 by Department of Statistics, Faculty of Science and Mathematics, Universitas Negeri Padang. UJSDS publishes scientific articles on various aspects related to Statistics, Data Science, and its application. Articles can be in the form of research results, case studies, or literature reviews. All papers were reviewed by peer reviewers consisting of experts and academicians across universities.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 6 Documents
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Search results for , issue "Vol. 1 No. 1 (2023): UNP Journal of Statistics and Data Science" : 6 Documents clear
Modeling Open Unemployment Rate in West Sumatera Province Using Truncated Spline Regression Aprilla Suhada; Syafriandi; Dodi Vionanda; Fadhilah Fitri
UNP Journal of Statistics and Data Science Vol. 1 No. 1 (2023): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (937.841 KB) | DOI: 10.24036/ujsds/vol1-iss1/3

Abstract

The Open Unemployment Rate (TPT) is an indicator used to measure the unemployment rate in the labor force which shows the percentage of the number of job seekers to the total workforce. In 2020 West Sumatra Province occupies the eighth position as the largest contributor to unemployment in Indonesia, this is a problem for the West Sumatra Provincial government. To deal with the unemployment problem, it is necessary to analyze the factors that are thought to affect the open unemployment rate in West Sumatra Province using truncated spline regression on the grounds that the data pattern between the response variables and each predictor variable does not form any pattern. Several factors are thought to influence the open unemployment rate, namely population, labor force participation rate, average length of schooling, dependency ratio. Based on the results of the analysis, the best model for modeling the open unemployment rate in West Sumatra Province is the truncated spline regression using three knot points with a GCV value of 0.061762. Variables that have a significant effect are population, labor force participation rate, average length of schooling and dependency ratio with a coefficient of determination of 99.97%.
Comparison K-Means and Fuzzy C-Means Methods to Grouping Human Development Index Indicators in Indonesia Belia Mailien; Admi Salma; Syafriandi; Dina Fitria
UNP Journal of Statistics and Data Science Vol. 1 No. 1 (2023): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (798.41 KB) | DOI: 10.24036/ujsds/vol1-iss1/4

Abstract

The Human Development Index (HDI) is an important indicator to measure the success of efforts to improve people's quality of life. The increase in the human development index in Indonesia is not accompanied by an even distribution of the human development index in every district/city in Indonesia. To facilitate the government in making policies and plans in overcoming the uneven HDI in Indonesia, it is necessary to group districts/cities in Indonesia based on HDI indicators. This study discusses the use of the K-means and Fuzzy C-Means algorithms with a total of 4 clusters. The grouping results obtained summarize that most districts/cities in Papua Island have low HDI indicators. The achievement of the HDI indicator in the medium category on the K-Means and Fuzzy C-Means methods is the same, spread across all major islands in Indonesia. However, the Nusa Tenggara Islands generally have a medium HDI indicator achievement. The achievements of the HDI indicators with high categories in the K-Means and Fuzzy C-Means methods are mostly found on the islands of Sumatra, Java, Kalimantan, and Sulawesi. The achievement of the HDI indicator in the very high category in the K-Means and Fuzzy C-Means methods is found in provincial capitals in several provinces in Indonesia as well as in big cities in Indonesia. The results of this study indicate that the S_DBW index and C_index values of the Fuzzy c-means method are smaller than the K-Means method, namely 2.312 and 0.105.
Forecasting Shallot Prices in West Sumatra Province Using the Fuzzy Time Series Method of the Singh Model and the Cheng Model Huriati Khaira; Fadhilah Fitri; Nonong Amalita; Dony Permana
UNP Journal of Statistics and Data Science Vol. 1 No. 1 (2023): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (807.7 KB) | DOI: 10.24036/ujsds/vol1-iss1/7

Abstract

Shallots are one of the leading spices that are widely used by humans as food seasoning and traditional medicine. The price of shallots always fluctuates which can affect the buying and selling of consumers and producers. Therefore, forecasting is used as a reference to be able to predict the price of shallots in the future and can provide convenience to the public for the condition of shallot prices in the next period. The forecasting method used is the fuzzy time series (FTS) method. FTS is a method whose forecasting uses data in the form of fuzzy sets sourced from real numbers to the universe set on actual data. Forecasting models used in this study are Singh's FTS model and Cheng's model. The data used is monthly data on shallot prices in West Sumatra Province for the period January 2018 to March 2022. The results obtained in this forecast are the Singh model FTS has a smaller MAPE value of 4.41% with a forecasting accuracy value of 95.59 %. This means that Singh's FTS model is better at predicting the price of shallots in West Sumatra Province.
Time Series Modeling on Stock Return at PT. Telecommunication Indonesia Tbk. Hana Rahma Trifanni; Dony Permana; Nonong Amalita; Atus Amadi Putra
UNP Journal of Statistics and Data Science Vol. 1 No. 1 (2023): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (750.274 KB) | DOI: 10.24036/ujsds/vol1-iss1/8

Abstract

One of the time series data modeling is the ARMA model which assumes constant volatility. However, in economic and financial data, there are many cases where volatility is not constant. This results in the occurrence of heteroscedasticity problems in the residuals, so a GARCH model is needed. In addition to heteroscedasticity, another problem with residuals is the asymmetric effect or leverage effect. For that we need asymmetric GARCH modeling. This study aims to compare the accuracy of the ARMA, GARCH, and asymmetric GARCH models. This research is an applied research. The data used is daily stock return data from February 2020 to February 2022 as many as 488 data. The results showed that the best model in modeling stock return volatility is ARMA(0,1). The accuracy of this model is very good with MAD value of 0,0018644 and RMSE value of 0,0025352.
Adding Exogenous Variable in Forming ARIMAX Model to Predict Export Load Goods in Tanjung Priok Port Elvina Catria; Atus Amadi Putra; Dony Permana; Dina Fitria
UNP Journal of Statistics and Data Science Vol. 1 No. 1 (2023): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (892.487 KB) | DOI: 10.24036/ujsds/vol1-iss1/10

Abstract

The main idea of world maritime has been launched by the Indonesia’s Government through the development of inter-island connectivity, namely a logistics distribution line system using cargo ships with scheduled routes. However, in terms of inter-island sea transportation connectivity using sea transportation, the number of ships used for loading and unloading activities at Tanjung Priok in 2020 reached 11,876 units, which number decreased by 12.6% compared to the previous year, this figure was not sufficient for transportation of Indonesian loading and unloading goods (exports). This condition is important to note because the implementation of sea transportation, especially for sea toll transportation, if it cannot reach all regions, will cause freight transportation in some areas to be limited and regional economic growth cannot be distributed evenly. The purpose of this study is to predict the number of goods loaded (exported) at the Port of Tanjung Priok, by establishing an export forecasting model. Exogenous variable in the form of the Indonesian Wholesale Price Index. After analyzing the data, the order of the ARIMA model (5,1,1) was obtained as a parameter to estimate the ARIMAX model. From the ARIMAX model (5,1,1), the model's accuracy rate is 13.25% which is quite feasible to use to predict the total export cargo for the period January 2021-December 2021. Forecasting results show better fluctuations than in 2020.
Grouping The Districts in Sumatera Region Based on Economic Development Indicators Using K-Medoids and CLARA Methods Retsya Lapiza; Syafriandi; Nonong Amalita; Dina Fitria
UNP Journal of Statistics and Data Science Vol. 1 No. 1 (2023): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (795.074 KB) | DOI: 10.24036/ujsds/vol1-iss1/13

Abstract

Inequality in economic development is an economic problem that is often felt by developing countries. In Indonesia, one of the regional areas that has not yet experienced equal distribution of economic development is the regencies/cities of the Sumatera Region. This study aims to determine regional groups and compare the results of grouping with the K-Medoids and CLARA methods. The K-Medoids and CLARA methods are non-hierarchical methods that are strong against outliers. While the best selection method is done by comparing the silhouette coefficient. The results obtained in this study using the K-Medoids and CLARA methods with 2 groups being better than forming 3 groups. The K-Medoids method resulted in cluster 1 as many as 59 districts/cities and cluster 2 as many as 95 districts/cities. Meanwhile, the grouping of districts/cities using the CLARA method with 2 groups resulted in cluster 1 as many as 74 districts/cities and cluster 2 as many as 80 districts/cities. From the comparison of the two methods, the silhouette coefficient values using the K-Medoids and CLARA methods are 0.13 and 0.15 respectively. Therefore, the CLARA method with 2 groups gave better cluster results

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