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Jurnal Forum Analisis Statistik
Published by Badan Pusat Statistik Provinsi Kalimantan Barat
ISSN : 28082605     EISSN : 28084497     DOI : -
Core Subject : Economy, Science,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance
Jurnal Forum Analisis Statistik (FORMASI) dikelola oleh Badan Pusat Statistik (BPS) Provinsi Kalimantan Barat sebagai wadah publikasi artikel ilmiah pejabat fungsional statistisi, akademisi dan praktisi bidang kajian statistika dan terapannya. Untuk menjaga kualitas dari artikel yang dipublikasikan oleh Jurnal FORMASI, kami senantiasa melakukan evaluasi berkala. Jurnal FORMASI saat ini berkomitmen untuk menerbitkan 2 terbitan jurnal setiap tahunnya, yaitu pada Juni dan Desember.
Arjuna Subject : Ilmu Ekonomi, Ekonometrika dan Keuangan (semua kategori) - Ilmu Ekonomi, Ekonometrika dan Keuangan (Lain-Lain)
Articles 43 Documents
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Negative Binomial Regression in Overcoming Overdispersion Poverty Data in Kalimantan Alvin Octavianus Halim; Nurfitri Imro'ah
Jurnal Forum Analisis Statistik Vol. 4 No. 1 (2024): Jurnal Forum Analisis Statistik (FORMASI)
Publisher : Badan Pusat Statistik Provinsi Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57059/formasi.v4i1.67

Abstract

Poverty is one of the problems that Indonesia still faces. Kalimantan Island has large naturalresources, but experiences inequality in the distribution of wealth in the region. In this study, data onthe number of poor people is used as the dependent variable. The independent variables include thepercentage of households that have access to non-PLN electricity (X1), access to proper drinking water(X2), proper sanitation (X3), non-own toilet facilities (X4), HDI (X5), Open Unemployment Rate (X6),average wages of informal workers and main employment (X7), population density per km2 (X8),monthly per capita food and non-food expenditure (X9), percentage of the population who have healthcomplaints and do not treat because there is no cost (X10), and percentage of the population aged 15years and above who do not have a diploma (X11) in 2023. A Poisson regression analysis is employed.The model accounts for the significance of every independent variable. The model was found to haveoverdispersion, which was resolved through negative binomial regression. The findings of the studyrevealed that the average wage of informal workers and primary employment, population density perkm2, monthly per capita food and non-food expenditure, the percentage of the population who havehealth complaints but do not treat them because there is no cost, and the percentage of the populationaged 15 years and older who do not have a diploma all have a significant impact on the magnitude ofthe number of people living in poverty on the island of Kalimantan.
Clustering of Regencies in Kalimantan Barat Based On Community Welfare Indicators Wahyudio Hariadi; Shantika Martha; Desa Ayu Natalia
Jurnal Forum Analisis Statistik Vol. 4 No. 1 (2024): Jurnal Forum Analisis Statistik (FORMASI)
Publisher : Badan Pusat Statistik Provinsi Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57059/formasi.v4i1.68

Abstract

Welfare is the capacity to meet all life's necessities to live decently, healthily, and productively. The objective of this study is to classify districts/cities in Kalimantan Barat Province according to indicators of community welfare. The data utilized include the percentage of impoverished individuals, gross regional domestic product, average years of schooling, expected years of schooling, and life expectancy. The procedure in this study commenced with a descriptive analysis of each variable, followed by the formation of an Euclidean distance matrix. After that, clustering with the centroid linkage method, in this case using the value of the silhouette coefficient to determine the optimal number of clusters formed. The clusters' outcomes are visible in the dendrogram. Cluster traits are identified based on the mean value of each variable within each cluster. The findings of the analysis indicate that Kota Pontianak enjoys high welfare, while the other thirteen districts are classified as having low welfare levels.
Model Spasial Data Panel dalam Menganalisis Faktor-Faktor yang Mempengaruhi Kemiskinan di Provinsi Kalimantan Barat: Spatial Data Panel Model in Analyzing Factors Affecting Poverty in Kalimantan Barat Province Hairil Al-Ham; Neva Satyahadewi; Nur Asih Kurniawati
Jurnal Forum Analisis Statistik Vol. 4 No. 1 (2024): Jurnal Forum Analisis Statistik (FORMASI)
Publisher : Badan Pusat Statistik Provinsi Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57059/formasi.v4i1.71

Abstract

Poverty is a complex and multidimensional problem in many countries, including Indonesia, which includes a lack of access to economic resources, education and adequate health services. In 2023, the percentage of the poor people in West Kalimantan Province has decreased to 7.03%, while the target of the RPJMD for West Kalimantan Province is 6.92%. One of the efforts that can be made to overcome this problem is by determining the factors that influence poverty. This research focuses on modeling with a spatial panel econometric approach on the percentage of the poor population. With this modeling, time period effects and spatial effects can be obtained on the percentage of poor people in districts/cities in West Kalimantan Province. The factors analyzed consisted of four sectors, namely education, social, health and employment. The panel data regression model obtained from this study is random effect. Then, in testing spatial effects, the results obtained showed that there was spatial autocorrelation and spatial dependence on error. So the analysis was continued using the spatial error model-random effect (SEM-random effect). The influence between locations or in this case districts/cities is measured using the queen contiguity spatial weighting matrix. From the model formed, it was found that districts/cities that are close to each other have an influence on reducing the percentage of the poor population in West Kalimantan Province. There are two variables that have a significantly influence the percentage of poor people in West Kalimantan Province. The school participation rate has a positive effect, while the percentage of the working population in the labor force has a negative effect on the percentage of the poor.
Analisis Risiko Unit Value Komoditas Ekspor Kelapa di Kalimantan Barat: Risk Analysis of Unit Value of Coconut Export Commodities in West Kalimantan Maresha Widya Muliadiasti; Supandi Supandi; Evy Sulistianingsih
Jurnal Forum Analisis Statistik Vol. 4 No. 1 (2024): Jurnal Forum Analisis Statistik (FORMASI)
Publisher : Badan Pusat Statistik Provinsi Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57059/formasi.v4i1.72

Abstract

Coconut is one of the leading commodities in West Kalimantan that can produce throughout the year. Coconut is also one of the largest contributors to Regional Original Income (PAD) in West Kalimantan. Coconut export commodities and other processed products have increased exports to European Union countries. The unit value index is used to calculate the trade exchange rate by comparing the development of the export unit value index with the import unit value index. The unit value of each coconut commodity can be calculated by dividing the export value (US$) by the export volume (Kg) in each month. Value at Risk (VaR) is used to estimate the maximum loss experienced by investors in the capital market at a certain level of confidence. This study uses the VaR concept with the Cornish-Fisher method to estimate the losses of coconut exporters. Based on the results of the analysis, it can be concluded that with a 95% confidence level, coconut exporters in West Kalimantan Province will experience a loss of 362,602.9 US$/Kg if exporters export coconuts at 1,000,000 US$/Kg.
Distribusi Tenaga Kesehatan di Kalimantan Barat Menggunakan Metode Ward: Distribution of Health Workers in West Kalimantan Using the Ward Method Endah Saraswi; Hendra Perdana; Anis Fakhrunnisa
Jurnal Forum Analisis Statistik Vol. 4 No. 1 (2024): Jurnal Forum Analisis Statistik (FORMASI)
Publisher : Badan Pusat Statistik Provinsi Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57059/formasi.v4i1.73

Abstract

West Kalimantan's population has increased significantly in a fairly short period of time, with a growth of 11% in the last five years. The challenge in ensuring the welfare of the community, especially in the aspect of health. This study aims to fill the research gap by clustering regions using the Ward’s method to see if the distribution of health workers in West Kalimantan reflects and has an impact on the level of Life Expectancy (LE). The data utilized includes the number of health workers consisting of doctors, nurses, midwives, and nutritionists. The data was processed by calculating the ratio of population to the number of health workers in each region to provide a comprehensive picture of the distribution and availability of health workers in West Kalimantan. Cluster analysis method was used in this study. The results of the analysis show that the proportion of health workers and the LE level in West Kalimantan have a positive correlation. Based on Ward's dendrogram method, 14 districts/cities in West Kalimantan were divided into four clusters. Over a period of five years, there were seven areas that experienced cluster shifts, indicating the dynamics of health worker distribution. The government is advised to continue to pay attention to the distribution and availability of health workers in all regions in order to improve community welfare.
Penentuan Metode Cluster Hierarki Terbaik dengan Korelasi Cophenetic pada Pengelompokan Kabupaten/Kota di Indonesia Berdasarkan Variabel yang Memengaruhi Indeks Pembangunan Manusia: Determination of the Best Hierarchical Clustering Method with Cophenetic Correlation in the Clustering of Districts/Cities in Indonesia Based on Variables Affecting the Human Development Index Andini, Syarifah; Andani, Wirda; Kurniawati, Nur Asih
Jurnal Forum Analisis Statistik Vol. 4 No. 2 (2024): Jurnal Forum Analisis Statistik (FORMASI)
Publisher : Badan Pusat Statistik Provinsi Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57059/formasi.v4i2.83

Abstract

Capaian Indeks Pembangunan Manusia di Indonesia pada tahun 2023 mencapai 73,55 poin menunjukkan bahwa angka tersebut berada pada kategori tinggi. Akan tetapi, jika ditinjau berdasarkan wilayah kabupaten/kota, maka terjadi ketimpangan terhadap wilayah pembangunan. Ketimpangan ini bisa dilihat berdasarkan perbedaan capaian Indeks Pembangunan Manusia pada enam wilayah kabupaten/kota di Provinsi DKI Jakarta yang masuk dalam kategori tinggi dan sangat tinggi, sementara Provinsi Papua mendominasi pada kategori rendah. Hal tersebut menunjukkan bahwa terjadi ketimpangan pembangunan manusia pada wilayah kabupaten/kota di Indonesia. Penelitian yang dilakukan ini bertujuan untuk membantu merancang strategi yang lebih tepat sasaran untuk meningkatkan kualitas hidup masyarakat, baik di daerah dengan Indeks Pembangunan Manusia dengan kategori rendah maupun di daerah dengan Indeks Pembangunan Manusia dengan kategori tinggi melalui pendekatan yang berbasis pada kesamaan kondisi wilayah sosial ekonomi masing-masing wilayah. Analisis dalam penelitian ini memanfaatkan data yang mencakup Umur Harapan Hidup, Harapan Lama Sekolah, Rata-rata Lama Sekolah, Pengeluaran Riil per Kapita yang Disesuaikan, Tingkat Pengangguran Terbuka, dan Upah Minimum. Penelitian ini menentukan analisis cluster hierarki terbaik menggunakan korelasi Cophenetic lalu menentukan jumlah cluster optimum menggunakan package NbClust pada software RStudio. Hasil dari penelitian tersebut yaitu diperoleh metode terbaik yang digunakan ialah metode Average Linkage yang terbagi menjadi 5 cluster berdasarkan karakteristik wilayah pembangunan manusia.
Utilization of the ARIMA Model for Predicting the Value of Coconut Export in Kalimantan Barat Marda, Marda; Imro'ah, Nurfitri; Novita, Irene
Jurnal Forum Analisis Statistik Vol. 4 No. 2 (2024): Jurnal Forum Analisis Statistik (FORMASI)
Publisher : Badan Pusat Statistik Provinsi Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57059/formasi.v4i2.87

Abstract

The manufactured coconut classified under HS code 08011100 is available in either shredded or dried form. In 2022, this variety of coconut is projected to account for 8.68% of the export value of manufactured coconuts in Indonesia. While West Kalimantan has not yet achieved the status of the largest coconut exporter in Indonesia, coconut remains the primary commodity in the plantation sub-sector and significantly contributes to the Regional Original Income (PAD) of West Kalimantan Province. West Kalimantan, with a potential coconut plantation area of 94,204 ha and a growing array of processed coconut products, stands poised to enhance the value of its coconut exports. This study seeks to examine prospective market conditions by predicting the export value of coconuts in shredded or dried form, serving as a foundational strategy for enhancing the value of coconut exports. The ARIMA (Autoregressive Integrated Moving Average) model is employed to forecast the value of coconut exports (HS 08011100) for the upcoming 4 periods. During the process of identifying the best model, the ARIMA model (2,1,1) was selected, yielding a MAPE value of 26.63%. This indicates that the forecasts for coconut export values (HS 08011100) remain acceptable. The estimated coconut export value serves as a valuable planning reference for stakeholders aiming to enhance future coconut exports.
Analysis of the Effect of Population, Average Years of Schooling, and Per Capita Expenditure on Income Inequality among 14 Regencies/Cities in Kalimantan Barat Province Ihsan, Muhammad Nurul; Tamtama, Ray; Supandi, Supandi
Jurnal Forum Analisis Statistik Vol. 4 No. 2 (2024): Jurnal Forum Analisis Statistik (FORMASI)
Publisher : Badan Pusat Statistik Provinsi Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57059/formasi.v4i2.89

Abstract

In the implementation of economic development, Indonesia as a developing country is faced with complex problems in the implementation of economic development that is currently being carried out, namely the problem of inequality in income distribution. In West Kalimantan Province itself, regional economic development still needs special attention, in order to narrow the possibility of regional income inequality. One important aspect of economic development is improving the standard of living of the people. Improvements from social, educational and economic aspects must be made. In this research, data variables will be used that represent these aspects, namely population, average years of schooling, and per capita expenditure, which will then be identified using panel data regression analysis with best estimation modeling to determine the influence of these variables. on the Gini Ratio figure as a measuring variable of income inequality between 14 districts/cities in West Kalimantan Province from 2012 to 2023. Panel data regression in this research is used as an analytical tool using the best estimation modeling, namely the Fixed Effect Model (FEM). From the results of the analysis carried out, it was found that population size has a significant influence on the Gini Ratio figure. Meanwhile, the average years of schooling and per capita expenditure do not have a significant influence on the Gini Ratio or income inequality in West Kalimantan Province.
Peramalan Inflasi Kota Pontianak dengan Metode Seasonal Autoregressive Integrated Moving Average Aulia, Alwa; Huda, Nur'ainul Miftahul; Rofatunnisa, Sifa
Jurnal Forum Analisis Statistik Vol. 4 No. 2 (2024): Jurnal Forum Analisis Statistik (FORMASI)
Publisher : Badan Pusat Statistik Provinsi Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57059/formasi.v4i2.99

Abstract

One measure of regional economic stability that is always interesting to discuss is inflation, as it has a major impact on economic growth, external balance, competitiveness, interest rates, and even income distribution. Inflation is a term that refers to a consistent rise in the prices of goods and services over a period of time. This rise in prices can lead to a decrease in the purchasing power of money. To solve this problem, it is necessary to make predictions to forecast the value of inflation in the future. This research uses the Seasonal Autoregressive Moving Average method to forecast Pontianak City inflation from January 2025 to December 2025. The data used in this research comes from BPS Pontianak City. The best model is determined from the accuracy test with MAPE value. Based on the results of the analysis conducted, the ???????????????????????? (6,0,4)(2,1,1)6 model is the best model for forecasting inflation in Pontianak City with a MAPE value of 2.02%.
Metode Holt-Winter Exponential Smoothing untuk Memprediksi Nilai Tukar Petani di Provinsi Kalimantan Barat: Holt-Winter Exponential Smoothing Method to Predict Farmer Exchange Rates in West Kalimantan Province Fidianty, Fadilla; Perdana, Hendra; Rofatunnisa, Sifa
Jurnal Forum Analisis Statistik Vol. 5 No. 1 (2025): Jurnal Forum Analisis Statistik (FORMASI)
Publisher : Badan Pusat Statistik Provinsi Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57059/formasi.v5i1.95

Abstract

Kegiatan bertani yang dilakukan manusia adalah untuk memenuhi kebutuhan pangan. Tidak hanya berkontribusi untuk memenuhi kebutuhan pangan, tetapi juga menjadi pendorong untuk membangun suatu pedesaan. Sektor pertanian adalah sektor perekonomian yang memiliki peran besar terhadap pembangunan negara berkembang. Salah satu indikator yang berperan dalam evaluasi pembangunan pertanian adalah Nilai Tukar Petani (NTP). Besarnya kontribusi sektor pertanian sehingga diperlukan penentuan kebijakan yang tepat, salah satunya menggunakan metode peramalan. Metode peramalan yang digunakan pada penelitian ini adalah Holt-Winter Exponential Smoothing. Tujuan dilakukannya penelitian ini adalah untuk meramalkan NTP pada Januari 2024 sampai dengan desember 2024, dan melihat apakah metode ini tepat dalam meramalkan NTP. Ketepatan peramalan dilihat dari nilai Mean Absolute Percentage Error (MAPE) terkecil yang sesuai dengan klasifikasi nilai MAPE. Hasil analisis yang didapatkan dengan parameter optimal yang digunakan adalah alfa = 0,953014, beta = 0,08162, dan gamma = 0,99 , parameter tersebut didapatkan setelah dilakukan solver data. Nilai MAPE yang didapatkan dengan parameter tersebut sebesar 1,12%. Metode ini bisa menjadi rujukan untuk meramalkan NTP ke depannya. Untuk penelitian selanjutnya, disarankan menggunakan metode peramalan yang lain, agar dapat diketahui metode mana yang mendapatkan hasil terbaik.

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