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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL ILMIAH MATEMATIKA DAN TERAPAN KOMPUTIKA - Jurnal Sistem Komputer Parameter: Journal of Statistics MULTIPLE: Journal of Global and Multidisciplinary Tadulako Science and Technology Journal Jurnal Pustaka Cendekia Hukum dan Ilmu Sosial Khazanah Journal: Economics, Muamalah dan Entrepreneurship
Rais
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Journal : Tadulako Science and Technology Journal

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Linear Trend Regression Analysis On Gold Forecasting For Investment In Indonesia During The Covid-19 Pandemic Nursyahraini Husen; Rais; Lilies Handayani
Tadulako Science and Technology Journal Vol. 3 No. 1 (2022): TADULAKO SCIENCE AND TECHNOLOGY JOURNAL
Publisher : LPPM Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/sciencetech.v3i1.15999

Abstract

Linear trend regression is also known as straight line trend, is a form of linear trend, that is trend whose variable X is (Time Period) highest rank one. The purpose of this study is to look at the model and predict the amount of gold prices during the COVID-19 pandemic in Indonesia using the linear trend regression method. The results obtained for the model of the total price of gold during the COVID-19 pandemic in Indonesia are Y = 623584.1 + 6129.1X + . As for forecasting the amount of gold prices for investment during the COVID-19 pandemic in Indonesia for the next 6 months using the linear trend regression method, it increases every month, it can be concluded that gold is suitable for investment because the price tends to rise, especially during the Covid-19 pandemic in Indonesia.
Grouping Districts / Cities in Central Sulawesi Province Based on Poverty Indicators Using the Fuzzy Geographically Weighted Clustering -Artificial Bee Colony Method Nafiul Agristya; Rais; Iman Setiawan
Tadulako Science and Technology Journal Vol. 2 No. 2 (2022): Tadulako Science and Technology Journal
Publisher : LPPM Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/sciencetech.v2i2.17301

Abstract

Introduction: Poverty is the main problem that is the focus of attention of the government in Indonesia. In general, poverty is a person's inability to meet basic basic needs in every aspect of life. Cluster analysis is a solution to map this problem. Method: Fuzzy Geographically Weighted Clustering-Artificial Bee Colony (FGWC-ABC) is one clustering method that is an integration of classical fuzzy clustering methods and geodemographic elements. Artificial Bee Colony is a metaheuristic algorithm that is used as a global optimization to increase cluster accuracy. Artificial Bee Colony can efficiently and effectively solve various function optimization problems in various cases. Result and Discussion: The research results obtained 3 optimum clusters with each cluster characteristic relatively different based on poverty indicators. Cluster 1 with low poverty, cluster 2 with high poverty, and cluster 3 with moderate poverty. Conclusion: By using the IFV validity index, 3 optimum clusters were obtained with different characteristics of each cluster based on its indicators. Cluster 1 consists of three regencies/cities with low poverty status, cluster 2 consists of seven regencies/cities with high poverty status, and cluster 3 consists of six regencies/cities with moderate poverty status.
Co-Authors A. Melantik Rompegading Abdul Basit Agus Mohamad Soleh Andi Ferosita Sustrisno Andi Hendra Syam Budi Susetyo Fadjriyani Fajri, M Fiskia, N Gamayanti, Nurul Fiskia Hartayuni Sain Imam Hanafi Iman Setiawan Jamidun Jassinca Chrissma Audina Krisdianto, A H Lilies Handayani Lukman Maliku, E T Mohammad Fajri Musnar Indra Daulay Nafiul Agristya Nur'Eni Nursyahraini Husen Sain, H Setiawan, Iman Shadri Suryanto, Wiwit Very Kurnia Bakti, Very Kurnia