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All Journal Jurnal Absis : Jurnal Pendidikan Matematika dan Matematika Jurnal Pengabdian Masyarakat (JAPAMAS)
Hanifa Mardiatun Nasution
Universitas Islam Negeri Sumatera Utara
Religion Computer Science & IT Education Library & Information Science Mathematics Social Sciences

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Analisis Spasial dan Temporal Data Kejadian Bencana Banjir dengan Model Generalized Space Time Autoregressive Integrated Moving Average (GSTARIMA) Hanifa Mardiatun Nasution; Hendra Cipta
Jurnal Absis: Jurnal Pendidikan Matematika dan Matematika Vol. 6 No. 1 (2023): Jurnal Absis
Publisher : Program Studi Pendidikan Matematika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/absis.v6i1.2171

Abstract

The Generalized Space-Time Autoregressive Integrated Moving Average (GSTARIMA) is a model used to model time series data that exhibits spatial dependencies among its locations as well as temporal dependencies. GSTARIMA is applied in various economic contexts, including analyzing exports and imports, exchange rates, production, inflation, and rainfall. This research aims to develop the best GSTARIMA model and utilize it to forecast rainfall in the Medan Belawan District. The GSTARIMA model combines temporal and geographical aspects by adjusting parameters for each observed location. The data used in this study consists of monthly rainfall data for the Medan Belawan District, obtained from the Maritime Class II Meteorological Station in Belawan, spanning from January 2020 to December 2022. The identification of Autoregressive (AR) and Moving Average (MA) orders was performed through the analysis of the Autocorrelation Matrix (MACF) and Partial Autocorrelation Matrix (MPACF). This study employed a spatial order of 1, along with an inverse distance weighting matrix and cross-correlation normalization. Parameter estimation used the generalized least squares (GLS) method. The research results indicate that the GSTARIMA model (2,0,0) with the inverse distance weighting matrix achieved the lowest Mean Absolute Percentage Error (MAPE) rate, specifically at 1.0170. Thus, this model is considered the best for forecasting rainfall in the Medan Belawan District.
Implementasi Metode NWC (North West Corner) Untuk Menentukan Alokasi Waktu Optimal Dalam Penggunaan Aplikasi DJP (Direktorat Jenderal Pajak) Online Taslima Dewi; Hanifa Mardiatun Nasution; Nur Manda Sari; Rina Filia Sari; Elis Citra Purnama Purba; Shopia
Jurnal Pengabdian Masyarakat Vol. 2 No. 1 (2023): Juni 2023
Publisher : Unity Academy

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Abstract

Practical Work (KP) is a direct job training program that is implemented from higher education institutions to students in the work environment, which aims to improve skills and provide experience to students. The problem that occurs at the KP is the lack of BKKBN employees in managing time to upload data in the DJP online application. Therefore, the practitioner tries to use the NWC (North West Corner) method to optimize the time for uploading data in the DJP online application. By using the NWC (North West Corner) method, the optimal time allocation needed for BKKBN employees to upload data in the DJP online application is to make it more efficient, namely 3.72 hours/day.
Co-Authors Elis Citra Purnama Purba Hendra Cipta Nur Manda Sari Rina Filia Sari Shopia Taslima Dewi