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All Journal J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Journal of Mathematics Education and Science
Cheryl Ayu Melyani
Universitas Islam Indonesia
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics

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PERAMALAN INFLASI DI INDONESIA MENGGUNAKAN METODE AUTOREGRESSIVE MOVING AVERAGE (ARMA) Cheryl Ayu Melyani; Atsila Nurtsabita; Ghaitsa Zahira Shafa; Edy Widodo
Journal of Mathematics Education and Science Vol. 4 No. 2 (2021): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (424.789 KB) | DOI: 10.32665/james.v4i2.231

Abstract

A good inflation rate for a country is an inflation rate that has a low and stable value so that able to realize fast and controlled economic growth. Forecasting can be one of the steps that can provide an overview of the value of inflation in Indonesia for the government or related agencies to formulate and maintain inflation stability in Indonesia. In this study, a forecasting analysis was carried out to determine the prediction of inflation in Indonesia in 2021 using the Autoregressive Moving Average (ARMA) method. From the results of the research that has been done, the best model to predict this case is using the ARMA model (3,0,0) because it produces the smallest AIC value of 0.2373 and the smallest RMSE of 7.81. From this model, the results of forecasting inflation rates for the months of May to December 2021 are also obtained with a range of 0.1% to 0.3%. The graphic pattern of the predicted results follows the actual data line pattern, which means that this model is good to use. Abstrak Tingkat inflasi yang baik bagi suatu negara adalah tingkat inflasi yang memiliki nilai yang rendah dan stabil, sehinga mampu mewujudkan pertumbuhan ekonomi yang cepat dan terkendali. Peramalan dapat menjadi salah satu langkah yang dapat memberikan gambaran nilai inflasi di Indonesia bagi pemerintah atau badan yang terkait untuk menyusun dan mempertahankan kestabilan inflasi di Indonesia. Dalam penelitian ini, dilakukan analisis peramalan untuk mengetahui prediksi angka inflasi di Indonesia tahun 2021 menggunakan metode Autoregresif Moving Average (ARMA). Dari hasil penelitian yang telah dilakukan, model terbaik untuk meramalkan kasus ini yaitu menggunakan model ARMA (3,0,0) karena menghasilkan nilai AIC paling kecil yaitu 0.2373 dan RMSE terkecil sebesar 7.81. Dari model tersebut juga didapatkan hasil peramalan angka inflasi untuk bulan Mei hingga Desember 2021 dengan kisaran 0.1% hingga 0.3%. Pola grafik dari hasil prediksi mengikuti pola garis data aktual yang berarti bahwa model ini baik untuk digunakan.
Hotel Recommendation System with Content-Based Filtering Approach (Case Study: Hotel in Yogyakarta on Nusatrip Website) Cheryl Ayu Melyani
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 15 No 1 (2022): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (401.884 KB) | DOI: 10.36456/jstat.vol15.no1.a5375

Abstract

The increasing of Covid-19 pandemic has hampered people's activities, often causing stress if they are only stay at home continuously. This has led to an increasing trend of staycations or holiday activities in the city itself by renting a hotel. Hotel rental technology has begun to be transferred with the existence of OTA (Online Travel Agent). The existence of various kinds of hotels with various kinds of facilities that makes people feel confused in choosing which hotel to occupy. To help overcome this, the researchers tried to create a recommendation system to help prospective hotel residents choose the hotel according to their choice. In addition, it can also assist companies in increasing hotel room reservations through its website. In this study, researchers will build a hotel recommendation system in Yogyakarta at one of the OTAs in Indonesia using Content-Based Filtering Methods, weighting text data using Term Frequency-Inverse Document Frequency (TF-IDF) Methods and measuring document similarity using Cosine Similarity Methods. Based on the results of the Good Karma Yogyakarta hotel recommendations as a test example, 10 similar hotels were obtained, namely Happy Buddha Yogyakarta – Hostel, Nextdoor Homestay, Hotel Puspita, OYO 426 Hotel Gading Resto, Omah Jegog Homestay, Prawirotaman Homestay, RedDoorz near Prawirotaman, Ayodhya Garden Hostel Yogyakarta by HOM, Bringin House Yogyakarta, and House 24 Yogyakarta with cosine similarity values 0.956666513, 0.946570717, 0.917459394, 0.912534877, 0.886439718, 0.88221982, 0.881775275, 0.875845794, 0.872030219, and 0.871514859.
Co-Authors Atsila Nurtsabita Edy Widodo Ghaitsa Zahira Shafa