Peramalan Dan Analisa Hubungan Konsumsi Energi Listrik Dengan Indikator Ekonomi Dan Sosial Di Jawa Timur Dengan Multivariate Time Series Analysis

Farih, Imaduddin (2023) Peramalan Dan Analisa Hubungan Konsumsi Energi Listrik Dengan Indikator Ekonomi Dan Sosial Di Jawa Timur Dengan Multivariate Time Series Analysis. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kondisi ekonomi sangat penting untuk mendapatkan perhatian. Pertumbuhan ekonomi merupakan salah satu indikator kesejahteraan masyarakat disuatu wilayah. Indonesia merupakan negara kepulauan dimana setiap wilayah memiliki kondisi sosial, budaya, dan geografis yang berbeda-beda sehingga kondisi perekonomian tingkat Nasional belum dapat menggambarkan secara utuh kondisi perekonomian disetiap daerah. Dari kondisi tersebut maka analisis yang lebih spesifik di level Daerah sangat diperlukan. Pendapatan Domestik Regional Bruto PDRB merupakan salah satu indikator perekonomian di level Daerah, namun terdapat variabel lain yaitu konsumsi energi dan populasi yang dianggap sebagai faktor lain yang saling berpengaruh. Pemahaman atas hubungan antar variabel melalui proses pemodelan kuantitatif dapat dijadikan referensi bagi Pemerintah Daerah dan Pihak-pihak terkait dalam perencanaan strategis terkait ekonomi, sosial dan ketersediaan energi listrik. Penelitian ini difokuskan pada suatu Regional tertentu dimana Jawa Timur dipilih menjadi wilayah observasi dengan struktur data time series dari periode 1991 hingga 2021. Pada penelitian ini digunakan analisis multivariate time series dengan metode pemodelan Vector Autoregressive (VAR) melalui beberapa tahapan pengujian seperti stasioneritas, residual, kausalitas, dan akurasi untuk mendapatkan bentuk model optimal. Dari proses analisis yang telah dilakukan, diperoleh hasil bahwa pertumbuhan konsumsi listrik berpengaruh terhadap pertumbuhan PDRB tetapi tidak sebaliknya (kausalitas searah). Hal ini menunjukkan bahwa kebijakan terkait ketersediaan energi listrik dan penggunaan energi listrik akan dapat memberikan pengaruh positif terhadap pertumbuhan PDRB. Selanjutnya dari model yang dihasilkan didapatkan nilai peramalan untuk beberapa tahun kedepan.
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Economic conditions are very important to get attention. Economic growth is an indicator of people's welfare in a region. Indonesia is an archipelagic country where each region has different social, cultural and geographical conditions so that the economic conditions at the National level cannot fully describe the economic conditions in each region. From these conditions, a more specific analysis at the regional level is needed. Gross Regional Domestic Income GRDP is an indicator of the economy at the regional level, but there are other variables such as energy consumption and population which are considered as other factors that influence each other. An understanding of the relationship between variables through a quantitative modeling process can be used as a reference for the Regional Government and related parties in strategic planning related to the economy, social and availability of electrical energy. This research is focused on a particular region where East Java was chosen to be the observation area with time series data from 1991 to 2021. In this study, multivariate time series analysis was used using the Vector Autoregressive (VAR) modeling method through several stages of testing such as stationarity, residuals, causality, and accuracy to obtain the optimal model. Refer to analysis process that has been carried out, the result is that the growth in electricity consumption affects GRDP growth but not vice versa (unidirectional causality). This shows that policies related to the availability of electrical energy and the use of electrical energy will be able to have a positive influence on GRDP growth. Furthermore, from the resulting model obtained forecasting values for the next few years.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Macroeconomics, Multivariate, Time series, Vector Autoregression Makroekonomi, Multivariate Time series, Vector Autoregression
Subjects:	H Social Sciences > HA Statistics > HA30.3 Time-series analysis Q Science > QA Mathematics > QA278 Cluster Analysis. Multivariate analysis. Correspondence analysis (Statistics)
Divisions:	Interdisciplinary School of Management and Technology (SIMT) > 61101-Master of Technology Management (MMT)
Depositing User:	Imaduddin Farih
Date Deposited:	09 Feb 2023 05:37
Last Modified:	09 Feb 2023 05:37
URI:	http://repository.its.ac.id/id/eprint/96514

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