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All Journal Seminar Nasional Hasil Penelitian LP2M UNM Parameter: Jurnal Matematika, Statistika dan Terapannya Journal of Mathematics, Computation and Statistics (JMATHCOS)
Kaito, Nurlaila
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Peramalan Jumlah Kedatangan Wisatawan Mancanegara di Sulawesi Selatan Menggunakan Model ARFIMA Sukarna; Abdy, Muhammad; Aswi; Kaito, Nurlaila
Journal of Mathematics, Computations and Statistics Vol. 5 No. 2 (2022): Volume 05 Nomor 02 (Oktober 2022)
Publisher : Jurusan Matematika FMIPA UNM

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Abstract

Tourism is a potential and strategic asset to encourage the development of a region, especially for areas that have potential tourist objects. Exchange rates, inflation, and geography influence foreign tourist visits to an area. What may be unexpected is the increase in the number of tourists, which makes tourist workers have difficulties in providing the best services, and vice versa if there is a sudden drop, it will increase the number of unemployed. Therefore, we need a scientific study of forecasting that can provide information on the number of tourists. The ARFIMA model is an ARIMA whose differencing value is a fraction. The main goal of this research is to discover the best ARFIMA model to predict the number of foreign tourist arrivals in South Sulawesi. From the data of foreign tourists in South Sulawesi from 2015 to 2020, the result of this research is the AIC value of 710.44 for ARFIMA([1,8],d,0) with. The average difference between the actual and forecasted data in the out sample data for the two models is 38.6667 points. Therefore, the two models can still be classified as the best for forecasting foreign tourists from South Sulawesi. It depends on who applied this models into this cases.
Implementasi Tingkat Berpikir Van Hiele Sebagai Solusi Masalah Geometri Pada Siswa Kelas VIII SMP Negeri 26 Makassar Mulbar, Usman; Sanusi, Wahidah; Side, Syafruddin; Kaito, Nurlaila; Farhan, Muhammad
Seminar Nasional LP2M UNM SEMINAR NASIONAL 2024 : PROSIDING EDISI 9
Publisher : Seminar Nasional LP2M UNM

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Abstract

Penelitian ini bertujuan untuk mengeksplorasi implementasi tingkat berpikir Van Hiele sebagai solusi dalam menghadapi masalah geometri pada siswa kelas VIII di SMP Negeri 26 Makassar. Berdasarkan teori Van Hiele, siswa akan melalui lima tingkatan berpikir dalam memahami geometri, yang meliputi: visualisasi, analisis, deduksi informal, deduksi, dan rigor. Penelitian ini menggunakan pendekatan kualitatif eksploratif, dengan data yang dikumpulkan melalui observasi, wawancara, dan tes yang disesuaikan dengan tingkatan berpikir Van Hiele. Hasil penelitian menunjukkan bahwa sebagian besar siswa berada pada level 2 (deduksi informal), di mana mereka mampu memahami definisi abstrak tentang bangun datar serta mengenali hubungan antar bangun. Namun, hanya sebagian kecil siswa yang mampu mengaitkan hubungan-hubungan tersebut dengan baik. Temuan ini menekankan pentingnya penyesuaian metode pembelajaran geometri dengan tingkat berpikir siswa untuk meningkatkan pemahaman dan kemampuan pemecahan masalah geometri. Selain itu, penelitian ini menemukan bahwa kemampuan matematika dan perbedaan gender tidak secara signifikan mempengaruhi proses pemecahan masalah, tetapi kemampuan matematika yang lebih tinggi cenderung menghasilkan pemecahan masalah yang lebih efektif. Kata kunci: Van Hiele, Geometri, Pemecahan Masalah, Tingkat Berpikir
Hybrid ARIMA-GARCH Model with Walk-Forward Method On LQ45 Stock Price Forecasting Kaito, Nurlaila; Annas, Suwardi; Alimuddin, Alimuddin
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 2 (2025): Parameter: Jurnal Matematika dan Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv4i2pp249-260

Abstract

Stock investment offers returns but also risks, such as potential capital losses due to declining stock prices. To mitigate these risks, investors use forecasting models, and one common approach is time series forecasting. The ARIMA model captures linear patterns in data, while the GARCH model handles time-varying volatility. This study uses a hybrid ARIMA-GARCH model with the Walk-Forward method to predict the daily closing prices of LQ45 index stocks from January 2022 to May 2024, utilizing data from Yahoo Finance. The Walk-Forward approach divides the data into 80% training and 20% testing, ensuring the model is tested on unseen data for more realistic evaluation. The process includes fitting the ARIMA model to stock return data, testing for heteroscedasticity, and building the hybrid ARIMA-GARCH model. The best model, ARIMA(1,0,0) – GARCH(1,1), was selected based on the lowest AIC value of -3004.88 for ARIMA and -6.83 (AIC) and -6.78 (BIC) for GARCH. This research contributes to stock forecasting by applying high-frequency data and the Walk-Forward validation method, offering a more accurate assessment of the model’s performance. It also enriches time series analysis methodology in the Indonesian stock market by combining ARIMA and GARCH models, optimizing model parameters using AIC and BIC criteria for stock price prediction.
Co-Authors Aswi, Aswi Muhammad Abdy Muhammad Farhan Sukarna Suwardi Annas Syafruddin Side Usman Mulbar Wahidah Sanusi