Garuda - Garba Rujukan Digital

Article Per Year (5 Year)

All

Jurnal Aplikasi Statistika & Komputasi Statistik

jurnalasks
Website

Published by Politeknik Statistika STIS

ISSN : 20864132 EISSN : 26151367 DOI : -

Core Subject : Science, Education,

Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

Redaksi menerima karya ilmiah atau artikel penelitian mengenai kajian teori statistika dan komputasi statistik pada bidang ekonomi dan sosial dan kependudukan, serta teknologi informasi. Redaksi berhak menyunting tulisan tanpa mengubah makna subtansi tulisan. Isi jurnal Aplikasi Statistika dan Komputasi Statistik dapat dikutip dengan menyebutkan sumbernya.

Arjuna Subject : -

Articles 6 Documents

Search results for , issue "Vol 8 No 1 (2016): Journal of Statistical Application " : 6 Documents clear

Analisis Statistik dalam Pendugaan Curah Hujan Studi Kasus di DAS Ciliwung Hulu Wahyu Samsudin
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 8 No 1 (2016): Journal of Statistical Application & Statistical Computing
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS

Determining for distribution of rainfall is a very important part in determining the plans of rainfall in a region. This study used daily rainfall data in 1992-2009 from three rainfall stations,namely Gunung Mas, Citeko and Gadog. Thiessen polygon method is used to determine the average rainfall region. The distribution of rainfall is determined by using statistical analysis with Chi-Square test. Based on the results of distribution suitability testing by using Chi-Square (χr2) with significance (α) we obtained χr2 value of 6.50 while the χr2 table is 7.185. Since the calculated χr2< χr2 table, then the Gumbel distribution is eligible. So that the distribution pattern of the right to Ciliwung upstream is the Gumbel distribution. The amount of planned rainfall-plant the upstream Ciliwung watershed based on the Gumbel distribution for the return period of 2, 5, 10, 25, 50, and 100 years, respectively are 70.98 mm, 88.98 mm, 99.55 mm, 113.93 mm , 124.59 mm and 135.18 mm.

Penerapan Model Inferensi Bayesian dengan Variational Bayesian Principal Component Analysis (VBPCA) dalam mengatasi Missing Data Analisis Komponen Utama Ricky Yordani
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 8 No 1 (2016): Journal of Statistical Application & Statistical Computing
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS

In standard Principal Component Analysis (PCA) comes one problem in addressing the set of incomplete data. The standard PCA procedure on incomplete data is to eliminate (listwise deletion procedure) or using the mean of the variable, this procedure may result in loss information from these observations. Another method used is to integrate Expectation Maximization (EM) to the method of Probabilistic Principal Component Analysis (PPCA). But PPCA can produce overfitting response prediction. In this study discussed the Variational Bayesian Principal Component Analysis (VBPCA) which is a method of development of PPCA method by incorporating prior information from the distribution of the principal components of the model parameters. From the simulation studies by eliminating the data through the concept of missing at random (MAR), obtained results that the value of the correlation scores principal components complete data with the principal component score predicted results PPCA method is superior when compared with VBPCA, as well as to the value of the correlation scores for the various percentages are generally incomplete data. However, judging from the size of a match between the response to predictions by the size normalized root mean square error of prediction (NRMSEP) VBPCA method produces better than PPCA.

Pelacakan Gangguan Kereta Komuter Melalui Twitter Crawling Lya Hulliyyatus Suadaa
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 8 No 1 (2016): Journal of Statistical Application & Statistical Computing
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS

Nowadays, Twitter is a very popular social media, especially in Indonesia. Tweets can be used as a data source to explore information. PT KAI (Kereta Api Indonesia) Commuter Jabodetabek (Jakarta, Bogor, Depok, Tangerang, Bekasi) (PT KCJ) has an official account, Twitter @CommuterLine, to disseminate information related to commuter train. One of important information regularly published in @CommuterLine account are information about commuter train intrusion. PT KCJ uses specific tweet format and certain hashtag to inform people about the intrusion. Intrusion information that is usually published is time of the intrusion, name of the station, train number and train line. #InfoLintas and #InfoLanjut hashtag are used to easier tweet searching. Information extraction processes are adopted to automatically extract commuter train intrusion information from @CommuterLine account Twitter. The statistical analysis about commuter train tweets are visualized in tables and graphs. A prototype system in the form of mobile application is developed to track commuter train intrusion based on the result of the information extraction.

Analisis Hubungan Produk Domestik Bruto dan Ekspor Indonesia dengan Threshold Vector Error Correction Model Gama Putra Danu Sohibien
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 8 No 1 (2016): Journal of Statistical Application & Statistical Computing
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS

One of the approaches that can be used to analyze the relationship between export and GDP is by using Vector Error Correction Model (VECM). In VECM, the relationship between deviation and short-term dynamics is considered to have a linear pattern. However, the pattern of it may not be linear in various economic circumtances. A A Modelwhich can be used when the relationship pattern between deviation and short-term dynamics is not linear is Threshold Vector Error Correction Model (TVECM). According to the in sample residual, TVECM with 3 regimes is better than other models (VAR, VECM, and TVECM with 2 regimes). According to out sample residual, TVECM with 2 regimes is the better than other models (VAR, VECM, and TVECM with 3 regimes).

Pengelompokkan Wilayah Bencana Endemi Demam Berdarah Dengue di Jawa Timur dengan Fuzzy Geographically Weighted Clustering - Particle Swarm Optimization Fikri Handoko Putra; Robert Kurniawan
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 8 No 1 (2016): Journal of Statistical Application & Statistical Computing
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS

DHF is a disease that is a public health problem and is endemic in almost all districts / cities in East Java. The disease is transmitted through the bite of Aedes aegypti and Albopictus. There is currently no anti-viral drugs and vaccines to prevent dengue fever, then to break the chain of transmission, vector control is considered most appropriate at this time, but because the vector is widespread, it is necessary to control the success of the total coverage (covering the whole area) so that mosquitoes can not be multiply. This research was proposed to investigate of classify the endemic regions in East Java based factor that causes dengue vector control can be focused on certain areas that have the highest potential of dengue fever in East Java. This research was used a method FGWC-PSO to classify areas in East Java with the approach of some of the factors associated with an increase in dengue disease. The data will be used is from the publication of the East Java in Figures In 2013, East Java Provincial Health Profile in 2012, and Indonesian Disaster Data and Information in East Java in 2012. Overall, causes the highest number of dengue fever in some areas in East Java province, namely:

Error Correction Mechanism (ECM) Analysis for Identifying Factors that Influence Tax Income in Indonesia Sugiarto -; Merisa Widyasari
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 8 No 1 (2016): Journal of Statistical Application & Statistical Computing
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS

The under necessity of taxpayer number and the low of tax ratio in Indonesia indicate about small tax base revenue. it is contrary to the large population size that should have great potential against the tax. Theoritically, the tax revenue in the country are affected by various factors including Foreign Direct Investment (FDI), Gross Domestic Product (GDP), exports, and imports. This study aimed to analyze the influence of foreign investment (PMA), Gross Domestic Product (GDP), exports and imports to tax revenues in Indonesia in the long term and short term. The analytical method used in this study is Error Correction Mechanism (ECM) with study period 1984-2013. The study results show that in the long term, FDI, export, and import have significant positive impact on tax revenues, while the GDP has no significant positive effect on tax revenue. In the short term, FDI, GDP, export, and import have significant positive impact on tax revenue in Indonesia. The study result can be imply to the imports selection, improving the quality of exported goods and facilitate administration services of investment is the main point to increase tax revenues.

Page 1 of 1 | Total Record : 6

Filter by Year

2016 2016

Filter By Issues

All Issue Vol 17 No 2 (2025): Jurnal Aplikasi Statistika & Komputasi Statistik Vol 17 No 1 (2025): Jurnal Aplikasi Statistika & Komputasi Statistik Vol 16 No 2 (2024): Jurnal Aplikasi Statistika & Komputasi Statistik Vol 16 No 1 (2024): Jurnal Aplikasi Statistika & Komputasi Statistik Vol 15 No 2 (2023): Journal of Statistical Application and Computational Statistics Vol 15 No 1 (2023): Journal of Statistical Application and Computational Statistics Vol 14 No 2 (2022): Journal of Statistical Application and Computational Statistics Vol 14 No 1 (2022): Jurnal Aplikasi Statistika dan Komputasi Statistik Vol 13 No 2 (2021): Jurnal Aplikasi Statistika dan Komputasi Statistik Vol 13 No 1 (2021): Jurnal Aplikasi Statistika dan Komputasi Statistik Vol 12 No 3 (2020): Jurnal Aplikasi Statistika dan Komputasi Statistik Edisi Khusus Vol 12 No 2 (2020): Journal of Statistical Application and Computational Statistics Vol 12 No 1 (2020): Journal of Statistical Application and Computational Statistics Vol 11 No 2 (2019): Journal of Statistical Application and Computational Statistics Vol 11 No 1 (2019): Journal of Statistical Application and Computational Statistics Vol 10 No 2 (2018): Journal of Statistical Application and Computational Statistics Vol 10 No 1 (2018): Journal of Statistical Application and Computational Statistics Vol 9 No 2 (2017): Journal of Statistical Application and Computational Statistics Vol 9 No 1 (2017): Journal of Statistical Application and Computational Statistics Vol 8 No 2 (2016): Journal of Statistical Application and Computational Statistics Vol 8 No 1 (2016): Journal of Statistical Application & Statistical Computing Vol 7 No 2 (2015): Journal of Statistical Aplication and Statistical Computing Vol 7 No 1 (2015): Journal of Statistical Application and Computational Statistics More Issue

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
-

Contact Email
-

Phone
-

Journal Mail Official
-

Editorial Address
-

Location
Kota adm. jakarta timur,

Dki jakarta

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name -

Contact Email -

Phone -

Journal Mail Official -

Editorial Address -

Location Kota adm. jakarta timur, Dki jakarta INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
-

Contact Email
-

Phone
-

Journal Mail Official
-

Editorial Address
-

Location
Kota adm. jakarta timur,

Dki jakarta

INDONESIA