Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Riset Statistika Jagratara: Journal of Disaster Research
Muhammad Zaky Arkananta
Unknown Affiliation
Humanities Decision Sciences, Operations Research & Management Environmental Science Mathematics Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Identifikasi Pola Spasial dan Temporal Daerah Potensi Kebakaran Hutan di Kota Singkawang Berbasis Sistem Informasi Geografis Muhammad Zaky Arkananta; Yahya Darmawan
Jagratara: Journal of Disaster Research Vol. 2 No. 1 (2024): Juni
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/jjdr.v2i1.141

Abstract

Singkawang City is one of the cities recorded as having experienced a relatively high impact of forest fires over the last 5 years. Although most forest fires are caused by natural factors, there are also impacts caused by human intervention as a serious trigger in increasing the frequency and intensity of forest fires in Singkawang City. This research aims to analyze the distribution pattern of areas prone to forest and land fires spatially and temporally in Singkawang City in 2018 - 2022 using a scoring and overlay method based on Geographic Information Systems (GIS). Some of the variables used in this research include rainfall, altitude, vegetation cover, and soil type. After the data processing process, it was continued with validation with fire point data in Singkawang City. Data analysis shows that there is significant variability in the number of hotspots from year to year, with the highest peak occurring in 2019. The results of this research show that the hotspots that occur are in accordance with the mapping of areas prone to forest fires. There is a positive correlation between the number of fire hotspots and the processing of areas prone to forest fires using scoring and overlay methods.
Perbandingan Model Prediksi Curah Hujan Kota Semarang Metode SARIMA dan Holt-Winter Muhammad Zaky Arkananta; Yahya Darmawan; Trianasari, Maria Evy; Widodo, Widodo; Widodo , Anton
Jurnal Riset Statistika Volume 5, No. 1, Juli 2025, Jurnal Riset Statistika (JRS)
Publisher : UPT Publikasi Ilmiah Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jrs.v5i1.6149

Abstract

Abstract. High rainfall in Semarang City often triggers hydrometeorological disasters such as floods and landslides. Therefore, accurate rainfall prediction is needed to support disaster mitigation in Semarang City. This study aims to compare the performance of two rainfall prediction models, namely Seasonal Autoregressive Integrated Moving Average (SARIMA) and Holt-Winter Exponential Smoothing. The data used are monthly rainfall data from 1991 to 2023 to make predictions and validate both models. The results of the study show that the SARIMA model is more accurate in predicting rainfall in Semarang City than the Holt-Winter Exponential Smoothing method. Evaluation metric values such as NRMSE, MAE, and MAPE show that SARIMA produces smaller prediction errors. Therefore, the SARIMA model is recommended as a more accurate method for predicting rainfall in Semarang City. It is hoped that this study can support efforts to adapt and mitigate hydrometeorological risks in Semarang City and its surroundings. Abstrak. Curah hujan yang tinggi di Kota Semarang sering kali memicu bencana hidrometeorologi seperti banjir dan tanah longsor. Oleh karena itu, diperlukan prediksi curah hujan yang akurat untuk mendukung mitigasi bencana di Kota Semarang. Penelitian ini bertujuan untuk membandingkan kinerja dua model prediksi curah hujan, yaitu SARIMA (Seasonal Autoregressive Integrated Moving Average) dan Holt-Winter Exponential Smoothing. Data yang digunakan adalah data curah hujan bulanan dari tahun 1991 hingga 2023 untuk membuat prediksi dan memvalidasi kedua model. Hasil penelitian menunjukkan bahwa model SARIMA lebih akurat dalam memprediksi curah hujan di Kota Semarang dibandingkan metode Holt-Winter Exponential Smoothing. Nilai metrik evaluasi seperti NRMSE, MAE, dan MAPE menunjukkan bahwa SARIMA menghasilkan kesalahan prediksi yang lebih kecil. Oleh karena itu, model SARIMA direkomendasikan sebagai metode yang lebih akurat untuk memprediksi curah hujan di Kota Semarang. Harapannya, penelitian ini dapat mendukung upaya adaptasi dan mitigasi risiko hidrometeorologi di Kota Semarang dan sekitarnya.
Co-Authors Trianasari, Maria Evy Widodo , Anton Widodo Widodo Yahya Darmawan