Article Per Year (5 Year)
p-Index From 2021 - 2026
0.702
P-Index
This Author published in this journals
All Journal Buletin Statistika dan Aplikasi Terkini
Magdalena Effendi
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Social Sciences

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI JUMLAH TIMBULAN SAMPAH DI PROVINSI JAWA TIMUR MENGGUNAKAN METODE RANDOM FOREST REGRESSION Alamsyah, Meuthia Nur Azizah; Sofia Dawani Silaban; Dave Agles Rizky Nor; Lalu Muhamad Rifani Fadli; Surya Puspita Sari; Magdalena Effendi
BESTARI BPS Kalimantan Timur Vol. 5 No. 2 (2025): Vol. 5 No. 02 (2025): Bestari 10th Edition
Publisher : BPS Kalimantan Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The issue of waste generation in East Java Province continues to rise in line with population growth and economic activities. This study aims to analyze socioeconomic factors influencing waste generation in 2024 using the Random Forest Regression (RFR) method. The dataset consists of secondary data from SIPSN and BPS, covering 38 districts and cities with five predictor variables: land area, population growth, population density, average expenditure per capita, and GRDP. The optimal model parameters were obtained at mtry = 2 and ntree = 500. The results indicate that GRDP and land area are the most influential factors based on the feature importance analysis. An R² value of 0.198 suggests that other unobserved variables also contribute to variations in waste generation. This study is expected to provide data-driven insights for local governments in formulating more effective and sustainable waste management policies.
PERAMALAN KUALITAS UDARA DI KOTA BALIKPAPAN BERDASARKAN INDIKATOR NILAI PM2.5 MENGGUNAKAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) Butar, Judah; Anastasya; Riswanty Margareth Malau; Galavinozky Roigabe Gumilang Rajaguguk; Surya Puspita Sari; Magdalena Effendi
BESTARI BPS Kalimantan Timur Vol. 5 No. 2 (2025): Vol. 5 No. 02 (2025): Bestari 10th Edition
Publisher : BPS Kalimantan Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kualitas udara merupakan indikator penting dalam menilai kondisi lingkungan karena berpengaruh langsung terhadap kesehatan manusia. Peningkatan aktivitas industri, transportasi, serta pembangunan infrastruktur di Kota Balikpapan seiring dengan pengembangan Ibu Kota Nusantara (IKN) berpotensi meningkatkan konsentrasi polutan udara, khususnya partikulat halus PM2.5. Penelitian ini bertujuan untuk menganalisis pola dan meramalkan konsentrasi PM2.5 di Kota Balikpapan. Penelitian ini menggunakan metode Autoregressive Integrated Moving Average (ARIMA) untuk memodelkan data deret waktu PM2.5 harian. Data yang digunakan mencakup periode Januari hingga September 2025 dengan total 273 observasi, yang dibagi menjadi 80% data training yaitu sebanyak 218 observasi dan 20% data testing sebanyak 55 observasi. Metode ARIMA dipilih karena kemampuannya dalam menangkap pola fluktuatif pada data deret waktu. Hasil penelitian menunjukkan bahwa model ARIMA(2,0,1) merupakan model terbaik untuk peramalan konsentrasi PM2.5 di Kota Balikpapan berdasarkan kriteria pemilihan model dan evaluasi kinerja peramalan. Model ini mampu merepresentasikan pola data historis dengan baik dan memberikan hasil peramalan yang cukup akurat pada data pengujian. Kesimpulan dari penelitian ini menunjukkan bahwa model ARIMA(2,0,1) dapat digunakan sebagai alat peramalan kualitas udara, khususnya konsentrasi PM2.5 di Kota Balikpapan, serta berpotensi mendukung pengambilan kebijakan dalam pengendalian pencemaran udara di wilayah tersebut.
Pemodelan PEMODELAN DAN PERAMALAN CURAH HUJAN DI BALIKPAPAN MENGGUNAKAN METODE ARIMAX: Studi Kasus Curah Hujan Kota Balikpapan Bulan Januari-Desember 2024 Septiansyah, Rifky; Hashifah Najma Zahra; Ananda Reza Putra Rahmadan; Sarah Katerina Simbolon; Surya Puspita Sari; Magdalena Effendi
BESTARI BPS Kalimantan Timur Vol. 5 No. 2 (2025): Vol. 5 No. 02 (2025): Bestari 10th Edition
Publisher : BPS Kalimantan Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The city of Balikpapan experiences high and fluctuating rainfall intensity, rendering it vulnerable to hydrometeorological disasters such as floods and landslides. Accurate rainfall forecasting is crucial for risk mitigation. This study aims to model and forecast daily rainfall in Balikpapan using the Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) method, considering environmental factors. This study utilizes daily data from the January-December 2024 period sourced from NASA POWER, encompassing the variables of rainfall, average temperature, air humidity, and wind speed. The data was analyzed using the Box-Jenkins approach, which includes stationarity tests, parameter estimation, and diagnostic checks. The results indicated that the data was not stationary in variance, necessitating a logarithmic transformation. The best-fit model, identified by the lowest AIC value (582.05), was ARIMAX (1, 0, 1). Analysis of exogenous variables identified that Air Humidity and Wind Speed significantly influence rainfall, whereas Average Temperature does not. The Ljung-Box diagnostic test confirmed that the model's residuals behave as white noise (p-value 0.2662). The model's forecasting evaluation yielded an RMSE of 9.9617. The model proved reasonably effective in capturing the general rainfall patterns, despite limitations in predicting extreme spikes. These findings can contribute a scientific basis to support early warning systems and disaster mitigation policies in Balikpapan.
Pengaruh Faktor Ekonomi dan Lingkungan terhadap Deforestasi di Indonesia Elfrida Eka Ayuningtyas; Muhammad Akmal Fadhillah; Nathania, Vanisa Azra; Surya Puspita Sari; Magdalena Effendi
BESTARI BPS Kalimantan Timur Vol. 5 No. 2 (2025): Vol. 5 No. 02 (2025): Bestari 10th Edition
Publisher : BPS Kalimantan Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Indonesia is one of the countries with the highest rate of deforestation in the world, influenced by various economic and environmental factors. This study aims to analyze the effect of Gross Regional Domestic Product (GRDP), forest area, population density, forest fires, and CO? emissions on deforestation in Indonesia during the 2018–2022 period using panel data regression analysis. Based on the Chow, Hausman, and Lagrange Multiplier tests, the Random Effects Model was identified as the most appropriate model to explain the relationships among variables. The results indicate that forest fires, forest area, and CO? emissions have a significant effect on deforestation, while GRDP and population density show no significant effect. Forest fires and CO? emissions positively influence deforestation, and forest area also shows a positive effect, indicating that provinces with larger forest coverage tend to record higher levels of deforestation. These findings suggest that environmental factors play a more dominant role than economic factors in determining the rate of deforestation in Indonesia.
Co-Authors Alamsyah, Meuthia Nur Azizah Ananda Reza Putra Rahmadan Anastasya Butar, Judah Dave Agles Rizky Nor Elfrida Eka Ayuningtyas Galavinozky Roigabe Gumilang Rajaguguk Hashifah Najma Zahra Lalu Muhamad Rifani Fadli Muhammad Akmal Fadhillah Nathania, Vanisa Azra Riswanty Margareth Malau Sarah Katerina Simbolon Septiansyah, Rifky Sofia Dawani Silaban Surya Puspita Sari, Surya Puspita