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INDONESIA
Jurnal Statistika dan Aplikasinya
Published by Universitas Negeri Jakarta
ISSN : -     EISSN : 26208369     DOI : https://doi.org/10.21009/JSA.041
Core Subject : Economy, Science, Education, Agriculture, Social,
Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Social Sciences Other
Jurnal Statistika dan Aplikasinya JSA is dedicated to all statisticians who wants to publishing their articles about statistics and its application. The coverage of JSA includes every subject that using or related to statistics.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 169 Documents
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Pemodelan Peluang Transisi Rantai Markov dengan Simulasi Monte Carlo Berdasarkan Multinoulli Distribution untuk Memprediksi Harga Indeks Saham Vieri Koerniawan; Andrew Nilsen; Febrina Puspa Sari; Muhammad Yahya Ayyasy; Sapto Wahyu Indratno
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06213

Abstract

Harga saham selalu berfluktuasi dari waktu ke waktu sehingga sulit untuk diprediksi. Prediksi terhadap fluktuasi harga saham memberikan dampak yang signifikan bagi perusahaan, investor maupun pemegang saham dalam mengambil keputusan terbaik untuk pilihan investasi yang memberikan profit maksimal. Beberapa negara mempunyai indeks saham yang secara umum menjadi ukuran untuk mengetahui pergerakan harga saham sahamnya. Indeks saham LQ45 dan IHSG dari Indonesia, S&P 500 milik Amerika Serikat, Nikkei 225 dari Jepang, serta Shenzhen dari China merupakan beberapa contoh indeks saham yang memiliki valuasi terbesar di dunia. Pemodelan peluang transisi rantai Markov adalah salah satu cara untuk memprediksi indeks harga saham. Pemodelan menggunakan rantai Markov ini efektif untuk dilakukan karena kemampuannya dalam memprediksi dengan model yang sederhana dibandingkan dengan model lainnya. Selanjutnya, digunakan metode Monte Carlo untuk memodelkan peluang transisi rantai Markov berdasarkan bangkitan nilai dari distribusi Multinoulli untuk memprediksi keadaan dan harga penutupan indeks saham untuk waktu yang akan datang. Disimpulkan bahwa dari kedua model antara rantai Markov dan regresi linear yang diterapkan pada data indeks saham IHSG, LQ45, Nikkei 225, Shenzhen, dan S&P 500, diperoleh bahwa model rantai Markov adalah yang paling memiliki keakuratan paling baik berdasarkan ukuran Mean Absolute Percent Error (MAPE).
Front Matter JSA Volume 6 Issue 2, December 2022 Journal Editor JSA
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06200

Abstract

Back Matter JSA Volume 6 Issue 2, December 2022 Journal Editor JSA
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06222

Abstract

Pemodelan Harga Cabai Indonesia dengan Metode Seasonal ARIMAX Faris Nasirudin; Abdullah Ahmad dzikrullah
Jurnal Statistika dan Aplikasinya Vol 7 No 1 (2023): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07110

Abstract

Chili is one of the plants favored by the people of Indonesia because Indonesian cuisine is famous for its spicy taste and spices in every food dish. The rise and fall of chili prices in the market are caused by chili farmers whose production decision-making processes are allegedly not handled and supported by a good production and price forecast. Therefore, analysis is needed to see the forecasting of chili prices in Indonesia in the future. The method that researchers use in forecasting in this study is the SARIMA and SARIMAX methods using the variables of rainfall, inflation, and google trend. The analysis shows that the SARIMAX method is the best model for predicting chili prices with a MAPE value of 6.889% compared to a MAPE SARIMA value of 7.630%.
Pemodelan Produk Domestik Regional Bruto Sektor Pertanian dan Penyaluran Kredit menggunakan Two Stage Least Square Prilyandari Dina Saputri; Pratnya Paramitha Oktaviana
Jurnal Statistika dan Aplikasinya Vol 7 No 1 (2023): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07101

Abstract

Green economy is a concept relating to economic development which aimed to improve people's welfare by paying attention to environmental conditions. One main pillar of a green economy is economic growth which can be calculated through GDP (Gross Domestic Product). Financial institutions can play an important role in raising economic growth through optimal credit allocation. This study aims to identify the causal relationship between credit allocation from financial institutions and regional economic growth (GRDP), particularly in the green industry sector. The causal relationship that influences each other between credit allocation and Gross Regional Domestic Product (GRDP) in the agricultural, hunting, forestry, and fisheries sectors can be analyzed using the simultaneous two stage least square equation. The variables that significantly affect credit allocation are the percentage of NPL and GRDP, while the variables that significantly affect GRDP are the area of agricultural land and credit allocation. A significant causal relationship between credit distribution and GRDP shows that financial institutions can play a role in raising the growth of the green sector economy through credit allocation, especially in the green sector.
Penerapan Analisis Jalur (Path Analysis) dalam Menentukan Faktor-faktor yang Mempengaruhi Angka Harapan Hidup di Wilayah Indonesia Bagian Tengah Cucun Wahyuni; Bagus Sumargo; Qorry Meidianingsih
Jurnal Statistika dan Aplikasinya Vol 7 No 1 (2023): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07107

Abstract

Path analysis is an analytical method used to analyze direct and indirect effects between variables. This study uses path analysis to identify the direct or indirect effect of factors that are thought to nfluence life expectancy in the central part of Indonesia. The data used is secondary data and was obtained from BPS in 2017. The result of the model fit test show that the resulting model has a chi-square p-value of 0.121, indicating that the mdel is fit. In addition, the RMSEA (Root Mean Square Error of Approximation) value obtained is 0.087, which indicates a relatively small level of approximation error. The CFI (Comparative Fit Index) value obtained is 0.951 and the TLI (Tucker-Lewis Index) value obtained is 0.990. The results of the analysis show that there is a significant direct effect between the per capita expendicture and the average length of schooling on life expectancy. In addition, the average length of school variable also has an indirect effects on life expectancy through the per capita expenditure variable. This indicates that education has a positive impact on increasing per capita expenditure and ultimately contributes to an increase in life expectancy.
Model Hibrid Harmonik, ARMA dan Outlier Curah Hujan di Surabaya, Malang dan Banyuwangi Heni Kusdarwati; Achmad Efendi; Luthfatul Amaliana
Jurnal Statistika dan Aplikasinya Vol 7 No 1 (2023): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07102

Abstract

The main factors affecting the climate in Indonesia are Monsoons, El Nino Southern Oscillation (ENSO) and sunspot cycles. Another influence is local characteristics, namely the geography and topography of each region. The harmonic model is an applied statistical model of Fourier series analysis. Because the harmonic model is a deterministic model with residuals that often still have autocorrelation, it is necessary to add a stochastic Autoregressive Integrated Moving Average (ARIMA) model. With the existence of 3 main factors that influence the climate in Indonesia with different seasonal periods, plus local influences, the bulk modeling with seasonal ARIMA, double S ARIMA is not enough so that a combination of harmonics, ARMA and Additive Outliers (AO) appears. The purpose of this study is to find the periodicity of rainfall and model rainfall time series data with hybrid harmonics, ARMA outliers. Periodogram analysis of monthly rainfall data for three cities in East Java shows a 1-year seasonal return period influenced by monsoons, an 11-year return period influenced by sunspots that cannot be detected. The monthly rainfall model for Surabaya is the 2nd order harmonic hybrid model, ARMA([1,9,11],0,0) and the outlier type
Analisis Faktor-Faktor yang Menjelaskan Kasus AIDS Provinsi Jawa Timur Menggunakan Model Geographically Weighted Logistic Regression (GWLR) Natasha Latifatu Soliha; Dian Lestari; Yekti Widyaningsih
Jurnal Statistika dan Aplikasinya Vol 7 No 1 (2023): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07104

Abstract

AIDS is the most chronic phase of HIV infection which can weaken the immune system. In 2020, East Java Province is a province which has the most HIV infections and in the third place for the highest total number of AIDS cases in Indonesia. The purpose of this research is to build a model using Geographically Weighted Logistic Regression (GWLR), and to work out the grouping results of regencies/cities using K-means Clustering Analysis. The variables used in this research are Gini Ratio, L Index of Per Capita Expenditure, Gender Ratio, Dependency Ratio, Gender Development Index, and The Number of Pos Pelayanan KB Desa. The proportion levels of AIDS cases are categorized into 2 categories based on cut-point which has been specified, which 0 as the category of low level with the proportion of AIDS cases is less than 0.0006 and 1 as the category of high level with the proportion of AIDS cases is more than or equal to 0.0006. Parameter estimation for GWLR is using Maximum Likelihood Estimation (MLE) method with Fixed Gaussian as weighted kernel function and optimum bandwidth is determined using Akaike's Information Criterion Corrected (AICc). Z-Score of the most suitable model will be grouped using K-means Clustering Analysis, with Z-score is parameter estimator divided by standard error. Grouping results indicates cluster 1 members tend to be regencies/cities that have gender ratio and dependency ratio as significant variables, meanwhile cluster 2 members tend to be regencies/cities that have only dependency ratio as significant variable.
Analisis Faktor-Faktor yang Menjelaskan Pengimplementasian Nilai-Nilai Utama (Corevalues) AKHLAK pada Karyawan di PT TASPEN (Persero) Mohammad Zahran Pratomo; Yekti Widyaningsih; Dian Lestari
Jurnal Statistika dan Aplikasinya Vol 7 No 1 (2023): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07103

Abstract

The development of the global economy is currently entering the era of Industry 4.0. Industry 4.0 cannot be faced only with technological development, but must involve social dynamics in it. Every company and agency must create a strategy in dealing with this era, including Badan Usaha Milik Negara (BUMN) by establishing main values that become the reference for the behavior of all human resources in BUMN. These core values consist of Trustworthy, Competent, Harmonious, Loyal, Adaptive, and Collaborative (AKHLAK). In practice, AKHLAK has not been implemented properly, even though the corevalues of AKHLAK need to be implemented by all human resources in BUMN. This study examines the significant factors explaining the implementation of AKHLAK core values on PT TASPEN (Persero) employees and to examine the profile of employees who have implementation core values high and low are based on significant factors. The factors used in this study are work motivation, work environment, employee welfare, socialization, employee commitment, religiosity, work stress, age, gender, education level, and years of service. The methods used in solving this research problem are the Partial Least Square (PLS) method and the Classification and Regression Tree (CART) method. The data used is primary data of 209 PT TASPEN (Persero) employees taken using purposive sampling. The results showed that work motivation, socialization, religiosity, and education level can significantly explain the implementation of AKHLAK. The profile of employees who have a high level of implementation of AKHLAK are employees with high level of religiosity, high work motivation, for all categories of educational levels, and work stress levels. The profile of employees who have a low level of implementation of AKHLAK are employees who have low religiosity and work motivation.
Aplikasi Model ARIMA dalam Peramalan Data Harga Emas Dunia Tahun 2010-2022 Mohammad Abror Gustiansyah; Akbar Rizki; Berliana Apriyanti; Kenia Maulidia; Raffael Julio Roger Roa; Oksi Al Hadi; Nabila Ghoni Trisno Hidayatulloh; Wiwik Andriyani Lestari Ningsih; Andika Putri Ratnasari; Yenni Angraini
Jurnal Statistika dan Aplikasinya Vol 7 No 1 (2023): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07108

Abstract

Gold investment is one of the favorite investments during the Covid-19 pandemic because the price of gold is relatively volatile but shows an increasing trend. Savvy investors investing in gold need to be able to predict future opportunities. Therefore, price estimation is needed to develop a buying and selling strategy to maximize profits. The Autoregressive Integrated Moving Average (ARIMA) model is a suitable method for predicting time series data, so the best ARIMA model will be applied for forecasting world gold prices. The best ARIMA model is selected based on the Akaike Information Criterion (AIC) and Mean Absolute Percentage Error (MAPE) criteria. Monthly world gold price data for 146 periods are applied in this study and will be used to predict gold prices for the following six periods. ARIMA (0,1,1) is the best model obtained from the analysis results, with AIC and MAPE values of 1264.731 and 11.972%, respectively. Forecasting results show that world gold prices will increase for the next periods.

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