Judul: Multi-Depot Electric Vehicle Routing Problem with Time  Windows
Abstrak: Dunia sedang menghadapi masalah perubahan iklim yang salah satu penyebabnya adalah emisi gas rumah kaca. Emisi gas rumah kaca dapat dikurangi dengan menggunakan kendaraan listrik. Kendaraan listrik memiliki jarak tempuh yang terbatas. Oleh karena itu, perlu dilakukan penentuan rute optimal, salah satunya adalah penentuan rute kendaraan listrik multi-depot dengan time windows. Tujuan dari penelitian ini adalah memodelkan masalah penentuan rute kendaraan listrik multi-depot dengan time windows dalam model MDEVRPTW dan menyelesaikannya dengan mixed integer linear programming. Biaya yang diminimumkan meliputi biaya tetap kendaraan, biaya perjalanan, biaya pengisian daya, dan biaya penalti jika melanggar time windows. Kendaraan diperbolehkan melanggar time windows dengan toleransi waktu 5 menit dari time windows setiap lokasi. Model ini diimplementasikan dalam dua kasus yang dibagi menjadi lima skenario per kasus. Setiap skenario memiliki perbedaan dalam kapasitas baterai, kapasitas muatan, dan time windows pelanggan. Pada kasus pertama, kendaraan harus kembali ke depot asalnya, sedangkan pada kasus kedua, kendaraan bisa kembali ke depot terdekat. Solusi yang dihasilkan berupa rute kendaraan listrik yang meminimumkan total biaya untuk setiap skenario dan kasus, dan memenuhi semua kendala yang ditetapkan., The world is currently facing the issue of climate change, one of the causes is greenhouse gas emissions. Greenhouse gas emissions can be reduced by using electric vehicles. However, electric vehicles have a limited range. Therefore, it is necessary to determine the optimal route, one of which is the multi-depot electric vehicle routing problem with time windows. The aim of this research is to model the multi-depot electric vehicle routing problem with time windows in the MDEVRPTW model and solve it using mixed integer linear programming. The costs minimized in this problem include vehicle fixed costs, travel costs, charging costs, and penalty costs for violating time windows. Vehicles are allowed to violate time windows with a tolerance of 5 minutes. This model is implemented in two cases, each divided into five scenarios. Each scenario differs in vehicle battery capacity, vehicle load capacity, and customer time windows. In the first case, vehicles must return to their original depot, while in the second case, vehicles can return to the nearest depot. The result is the electric vehicle route that minimizes total costs for each scenario and case, and meets all the specified constraints.
Keyword: time windows, electric vehicle, MDEVRPTW, depot

Judul: Electric Vehicle Routing Problem with Soft Time Windows
Abstrak: Masalah perutean kendaraan listrik merupakan perkembangan dari masalah perutean kendaraan konvensional dengan karakteristik unik yang tidak dimiliki kendaraan konvensional. Masalah perutean kendaraan listrik dengan soft time windows memiliki beberapa fitur yang membuat model menjadi lebih fleksibel untuk diimplementasikan. Fitur tersebut antara lainnya adalah tersedianya stasiun pengisian daya kendaraan listrik umum (SPKLU) yang dapat dikunjungi kendaraan sebanyak yang diperlukan serta jumlahnya dapat disesuaikan. Model juga dapat menyesuaikan jumlah dan tipe kendaraan yang digunakan dalam sekali perutean. Tipe kendaraan listrik dapat berupa kendaraan homogen dengan kapasitas muatan dan baterai seragam ataupun heterogen dengan perbedaan kapasitas muatan dan baterai. Terdapat aturan soft time windows yang memberikan fleksibilitas waktu, memungkinkan kendaraan untuk melanggar aturan waktu dengan pemberian biaya penalti. Dalam mengimplementasikan model, tujuh kasus diuji dengan variasi jumlah kendaraan, kapasitas muatan dan baterai kendaraan, jumlah pelanggan dan SPKLU, dan aturan time windows. Penyelesaian masalah ini menggunakan metode eksak menghasilkan solusi optimum yang menciptakan rute perjalanan dengan biaya minimum sesuai dengan aturan soft time windows dan kendala lainnya., The electric vehicle routing problem is a development of vehicle routing problems with unique characteristics not found in conventional vehicles. The electric vehicle routing problem with soft time windows has several features that make the model flexible for implementation. These features include the availability and quantity of charging stations that vehicles can visit as needed can be adjusted. The model can also adapt the number and type of vehicles used in a single routing. Types of electric transport used in this model can be homogeneous with uniform cargo and battery capacity or heterogeneous with different load and battery capacity. There are soft time window rules that provide time flexibility, allowing vehicles to violate time rules with penalty costs. In implementing the model, we used seven cases with variations of number of vehicles, vehicle cargo capacity, vehicle battery capacity, the number of customers and charging stations, and time window rules. Solving this problem using an exact method results in an optimal solution that creates a travel route with minimum costs according to soft time window rules and other constraints.
Keyword: electric vehicle, SPKLU, time windows

Judul: Synthesis of Apatite - Chitosan Composite Using Duck Eggshell and Chitosan with Temperature and pH Control
Abstrak: Composite of apatite-chitosan was prepared by using chitosan as polymer matrix. Calcium phosphate was prepared from CaO and (NH4)2HPO4, which the ratio Ca : P had to be 1.67. Chitosan is produced by deacetilase from biopolymer chitin. Duck eggshell (95% CaCO3) as starting material was converted to be calcium oxide (CaO) through calcinations with temperature 1000oC for 5 hours. In-situ and ex-situ methods were prepared from apatite and chitosan (dissolved with acetate acid 2%). Calcium phosphate prepared for bone implantation, but it is too fragile and brittle to be implant into the body. So addition of chitosan can decrease crystalinity and increase mechanic characteristic (tougher). Composite apatite-chitosan was resulted by fast precipitation. Fast precipitation was held in a breaker glass with nitrogen atmosphere, under controlled temperature at 37oC and pH 7, in order to increase amount of hydroxyapatite. Precipitation with CaO which was dropped by (NH4)2HPO4. Hydroxyapatite and chitosan were appearing at samples with in-situ and ex-situ methods which indicating by peak matching of XRD (closed lattice parameter, crystal size), overlapping at FTIR spectra and supporting by SEM picture (homogenous and agglomerated particle). However, it still needs further research to examine biocompatibility osteoconductive degree of sample by in-vivo and in-vitro test.
Keyword: