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ESTIMASI: Journal of Statistics and Its Application
Published by Universitas Hasanuddin
ISSN : 2721379X     EISSN : 27213803     DOI : http://dx.doi.org/10.20956/ejsa
Core Subject : Education,
Mathematics
ESTIMASI: Journal of Statistics and Its Application, is a journal published by the Department of Statistics, Faculty of Mathematics and Natural Sciences, Hasanuddin University. ESTIMASI is a peer – reviewed journal with the online submission system for the dissemination of statistics and its application. The material can be sourced from the results of research, theoretical, computational development and all fields of science development that are in one group.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 107 Documents
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Pengelompokan Produksi Daging Sapi Menurut Provinsi di Indonesia Tahun 2017-2022 dengan Menggunakan Metode K-Means Ningsih, Diah Restu
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 1, Januari, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i1.26988

Abstract

Demand for beef is a commodity that will continue to increase. In addition to nutritious milk and protein-rich meat, cows are very beneficial to humans. The consumption trend of Indonesians which continues to increase every year also shows this. However, adequate beef production, both in terms of quality and quantity, has not been sufficient to meet the increasing demand for beef. As a result, beef production has not been evenly distributed in all Indonesian provinces. This study aims to apply the K-Means Cluster method to group provinces and determine the characteristics of the clusters formed based on the level of beef production in Indonesia in 2017-2022. With this research, it can be input to the government and the people of Indonesia so that they can handle policies for regions that are included in the low cluster as an increase in the equity of beef production. This study clustered 3 groups. The results obtained were 10 provinces included in the low cluster, 21 provinces included in the medium cluster and 3 provinces included in the high cluster.
Analisis Hasil Tanaman Perkebunan (Kopi Dan Teh) Menggunakan Regresi Linear Hamidah, Isna
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 2, Juli, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i2.26989

Abstract

Plantation crops are an agricultural sub-sector which also plays an important role in boosting the country's economy, one of which is coffee and tea. However, it is known from the Statistics Indonesia that data shows that the production of plantation crops has decreased, this is caused by one of the factors, namely due to the reduced area of plantation land caused by changes in the conversion of plantation land. The purpose of this study was to determine the influence of land area on the production of plantation crops with linear regression. The results of the study with linear regression analysis show that the variable area of land simultaneously or partially can affect the production of plantation crops, especially coffee and tea plant.
Penerepan Analisis Diskriminan Kuadratik Robust Pada Klasifikasi Desa Asnidar, Asnidar; Ilyas, Nirwan; Raupong, Raupong
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 2, Juli, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i2.27002

Abstract

Discriminant analysis is a method used in separating objects into different groups and allocating objects into a predetermined group. Discriminant analysis is bound by the assumption that the mean vector for each group is different, the data is normally distributed multivariate and the covariance variance matrix between groups is the same. If there is a covariance variance matrix between different groups, then quadratic discriminant analysis is used for the classification process. However, sometimes it is found that data contains outliers, so a robust estimator is used, namely the Minimun Covariance Determinant with the fast-MCD algorithm. Therefore, robust quadratic discriminant analysis can be used to classify 128 villages and 48 sub-districts in Wajo district. It was found that 106 villages were correctly classified into village groups and 22 villages were misclassified into sub-district groups and 35 sub-districts were correctly classified as sub-district groups and 13 sub-districts were misclassified into village groups and produced an accuracy of classification results of 80.11%.
Pengelompokkan Daerah Rawan Demam Berdarah (DBD) di Jawa Timur Menggunakan Metode K-Means Auditiyah, Cellyn
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 2, Juli, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i2.27091

Abstract

Tropical diseases are common in areas with tropical and subtropical climates. As a country with a tropical climate, Indonesia is vulnerable to various tropical diseases. A large number of tropical diseases can occur in the temperate climate zone, differing only in the frequency with which they are affected. Dengue hemorrhagic fever is a tropical disease in Indonesia. DHF occurs as a result of infection with the dengue virus which is transmitted through the bite of the female Aedes aegypti mosquito. The high prevalence of DHF in East Java requires a data collection process to identify areas that are frequently infected with DHF. Therefore, we need a clustering system that can help classify areas that often experience DHF cases. This study aims to find out which districts/cities have the predominant cases of dengue fever. The clustering method used is K-Means clustering. Based on the research conducted, 2 clusters were obtained with a silhouette coefficient  value of 0.76. Cluster 1 covers 36 districts/cities and is an area with a low level of vulnerability to dengue fever, while cluster 2 covers 2 districts/cities and is an area with a high level of vulnerability to dengue fever.
Pemodelan Produk Domestik Regional Bruto (PDRB) di Indonesia Periode 2018-2021 dengan Analisis Regresi Data Panel Kesuma, Ahmad Rizky; Rinanda, Farikah Ayu; Astafira, Ilyas; Afriani, Nur; Fadlirhohim, Rizki Dwi; Lestari, Tri Septi Ayu; Sifriyani, Sifriyani
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 2, Juli, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i2.27522

Abstract

High and sustainable economic growth is the main condition or a must for the continuity of economic development and increased welfare. GRDP is defined as the total added value generated by all business units in an area. The analytical method used in this study is panel data regression analysis. Panel data regression is used to observe the relationship between one dependent variable and one or more independent variables. This study aims to determine the panel regression model of Gross Regional Domestic Product (GDP) in Indonesia for the period 2018 to 2021 and to find out whether the domestic investment investment variable and the cooperative business volume variable affect GRDP in Indonesia for the 2018-2021 period. The results obtained in this study are that the best panel regression model for modeling GRDP is the FEM model and the variable Domestic Investment Investment and Cooperative Business Volume are variables that have a significant effect on the GRDP variable in Indonesia for the 2018-2021 period.
Pendekatan Neural Network dalam Peramalan Jumlah Penduduk Kota Semarang dengan Menggunakan Metode Backpropagation Kuntarini, Agustin Absari Wahyu
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 2, Juli, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i2.28112

Abstract

The city of Semarang is one of the metropolitan cities that has a fairly dense population. During the years 2010-2021 the City of Semarang has a population fluctuation. It is necessary to make predictions of population data in order to plan the development in the City of Semarang can be better planned and can regulate the fluctuation of population in the future. In this study, the results of the prediction of the population of the City of Semarang were analyzed using the Neural Network approach with the backpropagation method. After training and testing, the best architectural model was obtained with 2 neurons on the input layer, 2 neurones on the hidden layer and 1 neuron on the output layer. Based on the results of the best architectural model, the MSE score was 9.39749 x 10-6 and the average MAPE value was 0.884552461%. The evaluation result with the MAPE value is very accurate because it is < 10%. In this study, the results of the forecast of the population of the city of Semarang in 2022-2025 consecutive are 1,863.121 people, 1,878.634 people, 1.891.865 people, and 1,902.947 people.
Pemodelan Faktor-Faktor yang Mempengaruhi Kasus Stunting di Sulawesi Selatan Menggunakan Geographically Weighted Regression Putri, Siti Choirotun Aisyah; Salsabila, Afifah; Suardi, Shafira; Mutmainnah, Mutmainnah; Aswi, Aswi
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 2, Juli, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i2.30142

Abstract

One of the prevalent nutritional issues affecting toddlers worldwide is stunting. Several studies on stunting cases have been conducted in Indonesia. However, modeling using the Geographically Weighted Regression (GWR) method in South Sulawesi has not been carried out. This study aims to identify the variables that affect the incidence of stunting in each district in South Sulawesi based on spatial modeling using the GWR method. Data on the number of stunting cases, the pproportion of low-birth-weight infants, the percentage of under-five who are malnourished, the percentage of proper drinking water, and the percentage of poor people in South Sulawesi in 2020 were used. The results show that the GWR model has an  value of 86.64%, which is higher than that of the global regression model. The factors that influence the percentage of stunting based on the GWR modeling results are the percentage of under-five who are malnourished and the percentage of proper drinking water. The findings of this study are anticipated to help the government address the issue of stunting in South Sulawesi. Early prevention may then be implemented.
Penerapan Path Analisis untuk Mengetahui Pengaruh Layanan Keluarga Berencana dan Indeks Pembangunan Manusia pada Penggunaan Metode Kontrasepsi Jangka Panjang dan Fertilitas di Indonesia Sari, Nurul Puspita; Munir, Ahmad; AT, M.Ramli; Iskandar, Madris
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 1, Januari, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i1.31227

Abstract

The efficacy of nationwide population control initiatives in Indonesia ought to be uniformly dispersed throughout all provinces. The decentralization policies implemented by each local government and regional differences in characteristics have, nevertheless, resulted in substantial discrepancies in TFR across all provinces in Indonesia. The efficacy of long-acting contraceptives is widely acknowledged as the primary prerequisite for mitigating the pace of population growth. In addition to reducing the TFR, the government has established goals for the equitable distribution of family planning programs across Indonesia. The implementation of family planning programs in an equitable manner will impact the birth rate reduction. The objective of this research is to examine the potential impact of contextual elements on fertility reduction via contraceptive methods in Indonesia. The findings of this research indicate that the proportion of women utilizing long-acting contraceptive methods has the most significant impact on TFR reduction in Indonesia, at -0.562. In contrast, the HDI and the number of family planning villages each have an influence of -0.12 and -0.36, respectively, on TFR reduction.
Analysis of Women’s Poverty in Maluku Province Daud, Jumerti; Pulubuhu, Dwia Aries T; Hasniati, Hasniati
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 1, Januari, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i1.31236

Abstract

The Sustainable Development Goals (SDGs) aim to end poverty in all its forms everywhere and provide a gender-sensitive policy framework. Limited access to resources causes women to be more vulnerable to poverty and contributes to economic disadvantages, known as the feminization of poverty. Maluku Province is the fourth poorest province in Indonesia by 2022, with a poverty rate of 15.97 percent. The percentage of poor households headed by women is 7.03 percent, an increase of 0.83 percentage points from 2021. This research identifies the relationship between households headed by women and poverty in the Maluku Province. Secondary data were obtained from the National Socioeconomic Survey 2022 by the Central Bureau of Statistics. The sample size included 822 households headed by women. Binary logistic regression analysis was used in this study. The research found that area of residence, number of household members, education level, and employment sector significantly affected women's poverty status in Maluku. Furthermore, women's poverty was higher among rural residents. The findings highlight that the number of household members with family planning programs, better education, and government policies providing assistance for better agriculture can alleviate household poverty.
Modeling Exchange Rate of Naira to Euro with the APLSTAR-GARCH model Effiong, Benjamin .A.; Okereke, Emmanuel .W.; Omekara, Chukwuemeka .O.; Acha, Chigozie .K.; Akpan, Emmanuel .A.
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 2, Juli, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i2.31904

Abstract

Application of the asymmetric power logistic smooth transition autoregressive (APLSTAR) model proposed by [1] to naira/Euro exchange rate spanning from January, 2006 to April, 2021, which is a nonlinear  macroeconomic time series was considered. The APLSTAR model was justifiably fitted to the series and the fit of the APLSTAR model compared with the fits of the competing models revealed that the APLSTAR model fits the data exchange rate of naira to Euro better than the other asymmetric STAR models. Lagrange Multiplier tests for autoregressive conditional heteroscedastic (ARCH) effects were carried out and there was no substantial evidence to reject the presence of ARCH effects in the set of residuals used. Hence, we compared hybrid smooth transition autoregressive-generalized ARCH (STAR-GARCH) models using model evaluation criteria. On balance, the APLSTAR-GARCH (0, 1) model outperforms the other models under consideration.

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