Land and forest fire have been identified as one of the main problems contributing to forest biodiversity and Global Warming and well known as the phenomenon affected by El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). The total burned area becomes higher when either El Niño or positive IOD occur. This research aims to analyze and quantify the direct correlation of the Niño 3.4 and difference between west and east pole of IOD sea surface temperature anomaly (SSTA) to the burned area in Indonesia and the impact of ENSO and IOD of each category on the burned area. The correlation between spatial location with Niño 3.4 and difference IOD SST's will be analyzed using a heterogeneous correlation map. Meanwhile, the quantitative impact will be calculated based on the singular value decomposition analysis result to each year categories. The most significant impact of El Niño has occurred on Merauke following Kalimantan shows the strongest correlation between burned area and Niño 3.4 SST. However, the significant increase of burned area only occurred during very strong El Niño. Both areas can have double amount of burned area during peak fire in very strong El Niño. Moderate El Niño have the most diverse impact with the stronger one occurs on Kalimantan and Merauke. Weak El Niño can have a significant impact if occurred simultaneously with positive IOD. Even more, it can surpass the effect of a single Moderate El Niño. Meanwhile, the strongest IOD impact happened in the southern part of Sumatra.
Origin-Destination (O-D) Matrix describes people movement in a certain area. An O-D matrix is necessary for planning a good public transportation system. However, the exact values of O-D matrix are difficult to measure. There are several ways to estimate O-D matrix such as gravity model, gravity opportunity model, etc. In this study, gravity model was used to estimate the O-D matrix in Bogor city. The following assumptions were used to estimate the O-D matrix: (i) forces between two different zones are related to some existing parameters such as population, social-economic condition, etc. (ii) the people movements are influenced by accessibility from origin to destination, and the accessibility affected by distance, time, and/or cost.
Pendistribusian barang merupakan salah satu hal penting dalam suatu kegiatan produksi. Dalam proses distribusi, semua perusahaan mengharapkan agar dapat meminimumkan biaya pendistribusian. Kendala yang sering dihadapi dalam pendistribusian barang ialah penentuan rute yang harus dilewati oleh kendaraan pengirim barang tersebut. Banyak strategi yang bisa digunakan untuk mengatasi permasalahan distribusi, salah satunya dengan menggunakan jasa pengemudi sesekali. Dalam penentuan rute, setiap perusahaan memiliki kendala yang berbeda-beda, seperti jumlah kendaraan yang digunakan, kapasitas kendaraan dan permintaan konsumen, jarak antar konsumen, dan ada juga kasus dimana konsumen ingin dilayani sesuai dengan time windows yang dimilikinya. Masalah penentuan rute yang optimal dapat diselesaikan dengan model dalam optimasi yaitu Vehicle Routing Problem (VRP). Makalah ini bertujuan memformulasikan masalah pendistribusian pada model Vehicle Routing Problem Time Windows dengan pengemudi sesekali dalam menentukan rute optimal dimana tiap konsumen memiliki batasan waktu dengan menggunakan jasa pengemudi sesekali. Hasil VRP time windows dengan pengemudi sesekali menunjukkan bahwa model ini dapat digunakan untuk meminimalkan biaya pendistribusian.
<strong>Distribusi merupakan suatu proses penyaluran barang dari satu atau kumpulan produsen kepada konsumen</strong>. Dalam proses pendistribusian semua produsen mengharapkan untuk meminimumkan biaya pendistribusian. Oleh karena itu perlu diformulasikan suatu model dalam optimasi untuk meminimumkan biaya pendistribusian. Salah satu model yang telah diformulasikan adalah <em>vehicle routing problem</em> (VRP) dengan pengemudi sesekali untuk meminimumkan biaya pendistribusian di satu tempat produksi. Selanjutnya dalam makalah ini akan diformulasikan model VRP dengan pengemudi sesekali untuk dua tempat produksi, sehingga disebut <em>multi depot vehicle routing problem</em> (MDVRP) dengan pengemudi sesekali. Tujuan dari formulasi model (MDVRP) dengan pengemudi sesekali ini adalah untuk meminimumkan biaya pendistrbusian Penggunaan kendaraan milik pengemudi sesekali dalam model MDVRP dengan pengemudi sesekali menunjukkan bahwa model ini dapat digunakan untuk meminimalkan biaya pendistribusian pada dua tempat produksi. Berdasarkan hasil tersebut, model ini dapat digunakan untuk meminimumkan biaya pendistribusian untuk dua tempat produksi dan selanjutnya dapat dijadikan acuan untuk pengerjaan lebih dari dua tempat produksi.
El Nino-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) can reduce the amount of rainfall in Indonesia. The previous study found that ENSO and IOD derived from the OISST dataset have an association with hotspots in Indonesia, especially in southern Sumatra dan Kalimantan. But the correlation results are still too small, and the correlation strength between regions has not been analyzed. Therefore, this study quantifies the association of the estimated ENSO and IOD derived from the ERA5 dataset on hotspots in Indonesia based on a Heterogeneous Correlation Map (HCM) and analyzes the correlation strength between regions in Indonesia. We use a singular value decomposition method to quantify this HCM. Besides OISST, ERA5 is an estimation data often used for weather forecast analysis. Therefore, this study quantifies the association of the estimated ENSO and IOD derived from the ERA5 dataset on hotspots in Indonesia based on a Heterogeneous Correlation Map (HCM) and analyzes the correlation strength between regions in Indonesia. Based on variance explained and correlation strength, the hotspot in Indonesia is more sensitive to ENSO and IOD derived from ERA5 than OISST. Consequently, the ERA5 data more useful to statistical analysis that requiring a substantial correlation.
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