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Management the Potential Data on Web Site For Communicating Research In Social and environment Issues Yendra, Rado
Indonesian Council of Premier Statistical Science Vol 4, No 1 (2025): February 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/icopss.v4i1.35853

Abstract

This paper focus on Management the Potential Data On Web Site For Communicating Research In Social and Environment Field with a special focus to produce some research on education and climate issue. It discusses the potentials and challenges of Internet data for social and environmet and presents a selection of the relevant literature to establish the wide spectrum of topics, which can be reached. Such data represent a large and increasing part of everyday life, which cannot be measured otherwise. They are timely, perhaps even daily following the factual process, they typically involve large numbers of observations, and they allow for flexible conceptual forms and experimental settings. In this paper, the data from website be managed to produce some academic article. Internet data can successfully be applied to a very wide range of climate issues including forecasting (e.g. of rainfall, wind speed, and the like)  and detecting education issues  (e.g. spatial analysis for relation a number of male and female students and test score mathematic and foreign lenguages subjects) ,Our article reviews the current attempts in the literature to incorporate Internet data into the mainstream of scholarly empirical research and guides the reader through this Special Issue. We provide some insights and a brief overview of the current state of research.
A Rainfall Model Comparison by Using Stochastic Neyman-Scott Rectangular Pulse (NSRP) and Bartlett-Lewis Rectangular Pulse (BLRP) Yendra, Rado; Rahmadeni, Rahmadeni; Desvina, Ari Pani
Journal of Ocean, Mechanical and Aerospace -science and engineering- Vol 53 No 1 (2018): Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse)
Publisher : International Society of Ocean, Mechanical and Aerospace -scientists and engineers- (ISOMAse)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (181.455 KB) | DOI: 10.36842/jomase.v53i1.48

Abstract

Lately, a climatic change has affected the uncertain occurrence of the rain process that implicates several difficulties in estimating flood disaster. The matter will certainly give the big problem to urban areas. Two stochastic-rain models which use the hourly rainfall data, Neyman-Scott Rectangular Pulse (NSRP) and Bartlett-Lewis Rectangular Pulse (BLRP), are a better way to identify the pattern of the rain events. Five rain characteristics represented by NSRP model’s parameter and six characteristics represented by BLRP model’s parameter will be used in identifying the rain pattern which is represented by the some rain statistics such as the probability and average of the hourly and daily rainfall. Two statistical rain models will predict the statistical value. This research using the data on 39-year rainfall per hour (1970-2008) from Alorsetar rain station has showed. It has been proved that some statistic models such as the statistical values which are generated by both models are very similar to those of observation statistics or statistics values which are generated from data.
Forecasting of Average Air Temperature in the City of Pekanbaru Using the Holt-Winters Method Yendra, Rado; Marizal, Muhammad; Ramadhani, Hilvania
Indonesian Council of Premier Statistical Science Vol 4, No 2 (2025): August 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/icopss.v4i2.37868

Abstract

Global climate change causes significant fluctuations in air temperature, including in the city of Pekanbaru, therefore, a predictive system is needed that can help the government and the community in dealing with climate impacts, one of which is through air temperature forecasting. This study aims to forecast the average air temperature in Pekanbaru City using the Holt-Winters Exponential Smoothing method, which is known to be effective in capturing seasonal patterns and trends. The data used is monthly average air temperature data from 2017 to 2024 obtained from BMKG. The analysis was carried out using an addictive approach and model evaluation was carried out based on the Mean Absolute Percentage Error (MAPE) value. The results show that the best model is obtained on a parameter with a MAPE value of 2.684. This model is then used to forecast the air temperature in 2025, which is predicted to decrease gradually. The results of this forecast are expected to be a reference in planning and decision-making related to climate change mitigation in the Pekanbaru area
Optimalisasi Tahapan Pembiayaan Debitur pada PT. Bank Riau Kepri Syariah Bengkalis Duri Hangtuah Menggunakan Metode Pert Yendra, Rado; Ummi, Tengku Fahmil
Indonesian Council of Premier Statistical Science Vol 3, No 1 (2024): February 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/icopss.v3i1.31751

Abstract

Perbankan adalah lembaga keuangan yang kegiatan usahanya mengumpulkan dana dari masyarakat dan menyalurkannya kembali dana tersebut kemasyarakat, serta memberikan jasa-jasa bank lainnya. Tujuan dari penelitian ini adalah bahan pertimbangan dalam menentukan keputusan untuk mengoptimalkan waktu penyelesaian kegiatan, guna mencapai waktu sesuai atau waktu yang diharapkan. Penelitian ini didasarkan pada deskripsi kuantitatif dan jenis datanya digunakan adalah sekunder. Data tersebut didapatkan dari perusahaan. Metode yang digunakan adalah metode Project Evaluation and Review Technique (PERT). Penelitian tersebut menghasilkan perhitungan waktu normal 515,36 menit dan perhitungan PERT 498,33 menit sehingga didapat selisish 17,03 menit. Dengan probabilitas 0,4801, yang dikonversikan pada tabel Z = 0,09 sama dengan 0,5199 yang berarti memiliki peluang sebesar 48,01% proyek kegiatan selesai dalam kurun waktu 498,33 menit
Peramalan Jumlah Produksi Bawang Merah, Cabai Besar dan Cabai Rawit di Provinsi Riau dengan Metode Holt-Winter Multiplicative Rahayu, Ade Nur; Yendra, Rado
Indonesian Council of Premier Statistical Science Vol 3, No 2 (2024): August 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/icopss.v3i2.32232

Abstract

Penelitian ini berfokus pada peramalan jumlah produksi bawang merah, cabai besar, dan cabai rawit di Provinsi Riau menggunakan metode Holt-Winters Multiplicative. Penelitian dilakukan di Dinas Pangan Tanaman Pangan dan Hortikultura Provinsi Riau, dengan menganalisis data sekunder dari tahun 2021 hingga 2023. Metode Holt-Winters Multiplicative dipilih karena kemampuannya menangani data dengan pola musiman yang kompleks dan tidak stasioner. Hasil analisis menunjukkan bahwa model terbaik untuk bawang merah memiliki nilai Mean Absolute Percentage Error (MAPE) sebesar 196.167%. Untuk cabai besar, model terbaik memiliki nilai MAPE sebesar 14.808%. Sedangkan untuk cabai rawit, model terbaik memiliki nilai MAPE sebesar 11.094%. Peramalan menunjukkan bahwa produksi bawang merah akan mengalami fluktuasi dengan peningkatan dan penurunan di bulan-bulan tertentu pada tahun 2024. Penelitian ini menyimpulkan bahwa metode Holt-Winters Multiplicative efektif untuk peramalan data produksi cabai besar dan cabai rawit, namun kurang akurat untuk bawang merah. Diperlukan metode peramalan yang lebih kompleks seperti ARIMA atau teknik pembelajaran mesin untuk meningkatkan akurasi peramalan bawang merah. Penelitian ini memberikan rekomendasi untuk peningkatan metodologi peramalan dalam studi lanjutan