Peramalan tingkat konsumsi gas pipa domestik di indonesia menggunakan metode neural network, arimax, dan multiple linear regression = Forecasting pipeline gas consumption rate in indonesia using neural network arimax and multiple linear regression method / Fitri Yulianti
Fitri Yulianti;
Farizal, supervisor; Rahmat Nurcahyo, supervisor; Djoko Sihono Gabriel, examiner; Yadrifil, examiner; Inaki Maulida Hakim, examiner
([Publisher not identified]
, 2013)
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ABSTRAK Penelitian ini bertujuan untuk memprediksi tingkat konsumsi gas pipa domestik diIndonesia menggunakan metode Neural Network, ARIMAX, dan Multiple LinearRegression (MLR). Peramalan dilakukan hingga periode Desember 2025 denganmenggunakan data historis tingkat konsumsi gas pipa domestik, inflasi, selisihharga minyak dan gas, serta selisih harga batubara dan gas periode Januari 2007sampai dengan September 2012 sebagai prediktor. Hasilnya metode ARIMAXmemberikan hasil yang paling akurat dengan nilai MAPE 3.89%. Metode NeuralNetwork memberikan hasil forecasting dengan nilai MAPE 6.34%, sedangkanmetode MLR mempunyai tingkat error terbesar dengan MAPE 8.39%. Kapasitasproduksi gas Indonesia cukup besar, tetapi jumlah gas yang dikonsumsi untukkeperluan domestik masih tergolong sedikit. Hasil forecasting ketiga metodemenunjukkan ke depannya tingkat konsumsi gas akan terus meningkat.Perbandingan antara hasil forecasting ketiga metode dan Neraca Gas Indonesiacukup besar. Hal ini menunjukkan meskipun Indonesia memiliki potensicadangan gas alam yang sangat melimpah, tetapi permintaan domestik belumterpenuhi secara maksimal. ABSTRACT This study aims to predict the level of domestic pipeline gas consumption inIndonesia using Neural Network, ARIMAX, and Multiple Linear Regression(MLR). Forecasting is done until the period of December 2025 using historicaldata of domestic pipeline consumption rate, inflation, the difference price of oiland gas, as well as the difference price of coal and gas from the period January2007 until September 2012 as predictor. The result ARIMAX method gives themost accurate results with the value of MAPE 3.89%. Neural Network methodgives forecasting result with MAPE 6.34%, while the MLR method has the largesterror rate with MAPE 8.39%. Indonesia gas production capacity is quite large, butthe amount of gas consumed for domestic use is still relatively small. The thirdmethod of forecasting results indicate the future gas consumption will continue toincrease. Comparison between the results of the three forecasting methods andNeraca Gas Indonesia is quite large. This shows even though Indonesia has veryabundant potential reserves of natural gas, but domestic demand has not been metmaximally. |
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Penerbitan : | [Place of publication not identified]: [Publisher not identified], 2013 |
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Bahasa : | ind |
Sumber Pengatalogan : | LibUI ind rda |
Tipe Konten : | text |
Tipe Media : | computer |
Tipe Carrier : | online resource |
Deskripsi Fisik : | xiii, 95 pages : illustration ; 28 cm + appendix |
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Lembaga Pemilik : | Universitas Indonesia |
Lokasi : | Perpustakaan UI, Lantai 3 |
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