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All Journal Jurnal Nasional Holistic Science EDUCTUM: Journal Research
Lubis, Muhammad Shadri Ismaun
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Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Prediction of Increase in House Prices Using Newton's Divided Difference Method Hutapea, Risca Octaviyani; Sinaga, May Rani Tabitha; Lubis, Muhammad Shadri Ismaun; Aqil, Muhammad Fachri
Holistic Science Vol. 4 No. 3 (2024): Jurnal Nasional Holistic Science
Publisher : Lembaga Riset Mutiara Akbar NOMOR AHU-0003295.AH.01.07 TAHUN 2021

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/hs.v4i3.771

Abstract

This research predicts house price increases using Newton's Divided Difference Method based on historical datasets from the Melbourne Housing Snapshot (2016–2017). A pattern of rising home prices that is consistent with a linear trend is revealed by preliminary investigation. By building an interpolation polynomial using Newton's Divided Difference Method, home prices in 2025 are predicted to be AUD 1,753,391.53. This technique works well for spotting upward price trends in data that is continuously distributed linearly. These results offer crucial information to help with strategic choices in market research and real estate investing. This approach may accurately simulate the link between year (an independent variable) and house prices (a dependent variable) by using Newton polynomials. The impact of market demand and other economic factors on sharply rising property prices is reflected in these projections.
Spatial Analysis of Earthquake Distribution Patterns in North Sumatera in 2022 Using Moran's Test and Moran Scatter Plot Mapping Hutapea, Risca Octaviyani; Sinaga, May Rani Tabitha; Lubis, Muhammad Shadri Ismaun; Aqil, Muhammad Fachri
EDUCTUM: Journal Research Vol. 4 No. 2 (2025): Eductum: Journal Research
Publisher : Lembaga Riset Mutiara Akbar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/ejr.v4i2.1006

Abstract

This study aims to analyze the spatial distribution patterns of earthquake occurrences in North Sumatra during 2022 using spatial statistical approaches, namely the global Moran’s I autocorrelation test and Local Indicators of Spatial Association (LISA), visualized through a Moran Scatter Plot. The data used in this study are secondary data obtained from the official earthquake catalog released by the Meteorology, Climatology, and Geophysics Agency (BMKG), including information on geographic location, time of occurrence, magnitude, and depth of earthquakes. The analysis was conducted using R and QGIS software, applying three types of spatial weighting: inverse distance, k-nearest neighbors (KNN), and adaptive Gaussian kernel functions. The results of the Moran’s I test revealed significant global spatial autocorrelation, indicating that earthquakes with similar magnitudes tend to cluster geographically. In contrast, the LISA analysis showed that most points did not exhibit significant local spatial association, although a few clusters of high-high, low-low, high-low, and low-high types were identified. These findings confirm the presence of spatial patterns in the distribution of earthquakes in North Sumatra, which are relevant for supporting mitigation efforts and spatially-based disaster management planning.
Co-Authors Aqil, Muhammad Fachri Hutapea, Risca Octaviyani Sinaga, May Rani Tabitha