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Parameter: Journal of Statistics
Published by Universitas Tadulako
ISSN : -     EISSN : 27765660     DOI : https://doi.org/10.22487/27765660.2021.v1.i2
Core Subject : Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics
Parameter: Journal of Statistics is a refereed journal committed to original research articles, reviews and short communications of Statistics and its applications.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 6 Documents
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Search results for , issue "Vol. 1 No. 1 (2021)" : 6 Documents clear
Cross-correlation Analysis Between Sea Surface Temperature Anomalies and Several Climate Elements in The Indian Ocean Fanny Oktaviani; Miftahuddin; Ichsan Setiawan
Parameter: Journal of Statistics Vol. 1 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (321.653 KB) | DOI: 10.22487/27765660.2021.v1.i1.15354

Abstract

Climate change can create a considerable impact in Indonesia. Aceh province is a province located on the island of Sumatra and it are located around in the Indian Ocean. Aceh Province has a considerable impact of climate change caused by the Sea Surface Temperature Anomalies (SSTA). The SSTA in the Indian Ocean is a parameter that can affect climatic conditions in Indonesia. The SSTA changes can cause an extreme climate change on earth. There are several climate elements affected by SSTA including air temperature, rainfall, wind speed, solar radiation, and relative humidity. One of the methods used to look at SSTA's relationship with some climate elements is the Cross-Correlation method. The climate data used in this study was a daily time series data. The purpose of this study is to find out SSTA's relationship with some climate elements. The results showed that using the Pearson correlation, the highest relationship was SSTA and the air temperature was 0.45. Meanwhile, the lowest relationship was SSTA and the rainfall was -0.05. Similarly, the Cross-Correlation method where the highest relationship was SSTA and the air temperature was 0.469, and the lowest close relationship was SSTA and the rainfall was -0.075.
Forecasting Bitcoin Price Based on Blockchain Information Using Long-Short Term Method Kinanti Dhea Larasati; Arum Handini Primandari
Parameter: Journal of Statistics Vol. 1 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (394.37 KB) | DOI: 10.22487/27765660.2021.v1.i1.15389

Abstract

Since its founding in 2008, Bitcoin (financial code: BTC) has emerged as a digital currency in market cap and continues to attract investors and policymakers' attention. In recent years, BTC has high price volatility, a substantial increase in 2016, followed by a significant decline in 2018. Unlike stock markets, BTC is open for 24x7 dan has no closing period. It means everyone can trade it for any time. However, this flexibility carries investment risk. This research attempts to forecast BTC's price by considering the blockchain's information to minimize the risk. We employ Long-Short Term Memory (LSTM), the artificial Recurrent Neural Network (RNN) architecture. Its model can avoid long-term problems. The data used is BTC's price and blockchain information data from August 4, 2018, to January 21, 2020. The model with 20 neurons and 500 epochs has the smallest MSE value. Then a prediction has an accuracy rate of 91.07%.
Intervention Model Analysis The Number of Domestic Passengers at Sultan Hasanuddin Airports Andi Ferosita Sustrisno; Rais; Iman Setiawan
Parameter: Journal of Statistics Vol. 1 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (384.479 KB) | DOI: 10.22487/27765660.2021.v1.i1.15436

Abstract

Domestic passengers are objects whose travel / flight transportation services only cover the domestic area. The increase or decrease in the number of domestic passengers is usually influenced by the occurrence of intervention. This research uses the intervention analysis. Intervention analysis is the time series analysis to model data that is determined by the presence of an intervention. Intervention analysis is one of the time series analysis to model data that are affected by the occurrence of a particular event in a short period of time, such as accidents, natural disasters, and promotions. This research is used to establish intervention model with pulse function of passengers of domestic Sultan Hasanuddin Airport. The result of the research were obtained the model Seasonal ARIMA .There were 6 intervention times during 2006 - 2018, by entering the intervention order b = 0, s = 0, and r = 1 based on the smallest AIC value is -303,66 with MAPE value is 6,1023.
Forecasting Of Crude Palm Oil By Using Fuzzy Time Series Method (Study Case : PT. Buana Mudantara Plantation) Rasna; I Wayan Sudarsana; Desy Lusiyanti
Parameter: Journal of Statistics Vol. 1 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (765.159 KB) | DOI: 10.22487/27765660.2021.v1.i1.15442

Abstract

PT. Buana Mudantara is a company engaged in palm oil production. The production of oil palm at this company varies every period, so the problem that often occurs is insufficient supply and demand. Therefore, it is necessary to forecast future oil palm production. The method used in this research is the Fuzzy Time Series method which has advantages, among others, that the calculation process does not require a complicated system, so it is easier to develop and can solve the problem of forecasting historical data in the form of linguistic values. This method provides a level of accuracy calculated using the MAPE (Mean Absolute Percentage Error) of . The results show that the forecasting of the amount of oil palm production in November 2019 - March 2020 is respectively ton, ton, ton, tons and tons
The Influence of Climate Factors on Cocoa Productivity in Sulawesi, 2019 Marta Sundari; Pardomuan Robinson Sihombing
Parameter: Journal of Statistics Vol. 1 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (306.556 KB) | DOI: 10.22487/27765660.2021.v1.i1.15444

Abstract

Cocoa is one of the plantation commodities that has an important role in Indonesia's economic activity and is one of Indonesia's export commodities which is quite important as a source of foreign exchange and oil and gas. Sulawesi Island is one of the cocoa-producing islands in Indonesia. This study aims to determine a spatial regression model between the average cocoa productivity per month with the average drinking temperature per month, the average monthly rainfall and the average length of sunshine per month and the climatic factors that affect cocoa productivity in Sulawesi. The best model estimation uses the AIC value; the best model has the smallest AIC value. In this study, the SARMA spatial regression model is the best model with the specified criteria.
Discriminant Analysis to Predict Workers Wanted to Find Other Job Muhammad Faiz El Haq; Pardomuan Robinson Sihombing
Parameter: Journal of Statistics Vol. 1 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (644.469 KB) | DOI: 10.22487/27765660.2021.v1.i1.15445

Abstract

This study aims to produce a model function that can predict whether a worker wants to find another job or not by looking at demographic characteristics such as age and job characteristics such as length of work in the main job, working hours during the past month, and income received. The variables observed were age, length of work in the primary position, working hours during the past month, and income. The dependent variable is the desire to find another job. The research sample used secondary data, namely the results of the 2017 National Labor Force Survey (SAKERNAS) conducted by the Central Statistics Agency of Padang Panjang City. Based on the analysis results, the discriminant function contains significant Age and income variables with a negative correlation for age and a positive correlation for income.

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