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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

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

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%.

Spline Nonparametric Regression Model for Local Revenue in Central Sulawesi Mohammad Fajri; Eka Rizky Wulansari; Ayu Anggraeni; Mufitatul Annisa
Parameter: Journal of Statistics Vol. 1 No. 2 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Local Own-source Revenue (LOR) is all regional revenue that comes from the region's original economic resources. It is very important to identify it by researching and determining the Regional Local Own-source Revenue (LOR) by properly researching and managing the source of revenue so as to provide maximum results. Central Sulawesi Province itself has Local Own-source Revenue (LOR) in the Regional Revenue and Expenditure Budget of the 2018 Budget Year has reached Rp1 trillion. The increase or decrease in growth of local revenue is influenced by the amount and type of tax, levies collected by local governments and the lack of incentives for the management apparatus to carry out tax collection and levies. This study uses spline regression analysis because the data of the Local Own-source Revenue (LOR) in Central Sulawesi in 2018 does not have a pattern so that it fits perfectly with that method. Then after processing the data obtained the results of spline nonparametric regression modeling using the optimal knots point obtained from the minimum GCV value. The best spline nonparametric regression model is written as follow . It can be concluded that in Central Sulawesi in 2018 the lowest Local Own-source Revenue (LOR) value was Banggai Laut Regency with 21,776 billion rupiahs and the highest Local Own-source Revenue (LOR) value was Palu City at 267,402 billion rupiahs.

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

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

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

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

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.

Fuzzy Clustering Algorithm to Catching Pattern of Change in District/City Poverty Variables Before and The Beginning of The Covid-19 Pandemic in Sulawesi Island Raditya Novidianto; Rini Irfani
Parameter: Journal of Statistics Vol. 1 No. 2 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

The first goal of the SDGs is to end poverty in any form. The COVID-19 pandemic has greatly affected several economic indicators, especially absolute poverty, especially in Sulawesi Island, which has increased poverty indicators, leading to the movement of values between districts/cities. The grouping will show similar characteristics of absolute variable poverty. By the Fuzzy method clustering, each observation has a degree of membership so that from the degree of membership can be identified which areas have vulnerable to move from one cluster to another. Grouping using fuzzy algorithms will get an overview of districts of concern to the government during the pandemic so that the variable indicators of absolute poverty do not worsen due to the pandemic. Comparison with the absolute variables of poverty in 2019 and 2020 in the headcount index (P0), Poverty Gap Index (P1), and Poverty Severity Index (P2) in districts/cities on the island of Sulawesi based on silhouette coefficients shows that optimum clusters formed as many as 2 clusters, with a coefficient of 0.57 and 0.60 respectively. Cluster 1 has characteristics including areas with absolute poverty rates that tend to be more prosperous than cluster 2 in the 2019 and 2020 data groups on the island of Sulawesi. The fuzzy algorithm detects areas prone to displacement from cluster 1 to cluster 2, namely Bombana, Bone, Sangihe Islands, South Konawe, and Siau Tagulandang Biaro in 2019 and Bombana, Bone, Sangihe, and Maros Islands in 2020. The COVID-19 pandemic in March 2020 has not had much impact on the macro indicators of poverty seen in the transfer of membership from 2019 to 2020, which only occurred to 3 districts that changed, namely bolaang mongondouw and konawe selatan from cluster 1 to cluster 2 and Maros from cluster 2 to cluster 1.

Implementation of Constant Elasticity of Substitution Function and Data Envelopment Analysis: Productivity and Technical Efficiency of Large Industry Creative Economy in Craft Subsector Indonesia Khusnudin Tri Subhi Zuhoran; Budiasih
Parameter: Journal of Statistics Vol. 1 No. 2 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Indonesia has undergone a transformation from agriculture to the manufacturing industry in 1971-1997. In the 2001-2015 period there was de-industrialization in developed countries. Likewise, Indonesia which shows a decrease in the contribution of GDP and manufacturing sector workforce to the economy. However, deindustrialization in Indonesia is premature / too fast. One of the policies to overcome this problem is with attention to the creative industry. With the existence of the creative industry, it can achieve several SDGs goals, namely the 8th goal, namely decent work and economic growth, the creative economy can increase economic growth, create jobs and increase exports (UNCTAD, 2010). However, the creative industry GDP growth that is below the RPJMN target is thought to indicate low productivity of the creative industry. According to IBS data, the craft sub-sector creative industry has a low production value. To see productivity can use technical efficiency. This study aims to evaluate the technical efficiency of creative industry in the craft sub-sector as well as to analyze the trend of variables that affect technical judgments. The method used is the CES production function and Data Envelopment Analysis. The results show that industries that have high total production factor values have a tendency to have high technical efficiency values as well. Furthermore, those arranged according to technical categories and binary logistic regression are used to determine trend variables that affect technical judgments. The technical efficiency of the craft, significantly by wages, investment status and company scale.

Expenditure Per Capita Model with Spatial Small Area Estimation Ahmad Risal
Parameter: Journal of Statistics Vol. 1 No. 2 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Indonesia is one of many countries around the world that attempt to suffer from high poverty rates. Since, poverty information in a certain area is a point of interest to researchers and policy makers. One problem faced is for the development program to be carried out more effectively and efficiently, it is necessary to have data availability up to the micro-scale. The technique used to reach the goal is Small Area Estimation (SAE). Fay-herriot (FH) model is one method on Small Area Estimation. Since, the SAE techniques require “borrow strength” across neighbor areas so thus Fay-Herriot model approach was developed by integrating spatial information into the model. This method known as Spatial Fay-Herriot Model (SFH) or Spatial Empirical Best Linear Unbiased Prediction (SEBLUP). This study aims to compare MSE of direct estimation, FH, and SFH Model to see which method gives the best result in estimating expenditure. The MSE value of the estimated SFH is smaller than direct estimation and FH, but it does not significant. It means adding spatial information in the small area estimation model does not give a better prediction than the simple small area estimation which is takes account the area as a specific random effect.

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
Iman Setiawan

Contact Email
npl.untad@gmail.com

Phone
+6281282206923

Journal Mail Official
jparameter.untad@gmail.com

Editorial Address
Jl. Soekarno Hatta No.KM. 9, Tondo, Mantikulore,Kota Palu, Sulawesi Tengah 94119

Location
Kota palu,

Sulawesi tengah

INDONESIA

Abstract

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Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Iman Setiawan

Contact Email npl.untad@gmail.com

Phone +6281282206923

Journal Mail Official jparameter.untad@gmail.com

Editorial Address Jl. Soekarno Hatta No.KM. 9, Tondo, Mantikulore,Kota Palu, Sulawesi Tengah 94119

Location Kota palu, Sulawesi tengah INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Iman Setiawan

Contact Email
npl.untad@gmail.com

Phone
+6281282206923

Journal Mail Official
jparameter.untad@gmail.com

Editorial Address
Jl. Soekarno Hatta No.KM. 9, Tondo, Mantikulore,Kota Palu, Sulawesi Tengah 94119

Location
Kota palu,

Sulawesi tengah

INDONESIA