Judul: Pengoptimuman Proses Antar Jemput Barang Menggunakan Kendaraan Listrik
Abstrak: Sebuah perusahaan logistik perlu menentukan rute yang optimal untuk meminimalkan biaya operasional dalam pendistribusian produk. Permasalahan pendistribusian ini, khususnya antar jemput barang secara simultan dapat diselesaikan dengan Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD). Peralihan kendaraan konvensional ke kendaraan listrik merupakan salah satu upaya perusahaan dalam mengurangi gas emisi rumah kaca. Pada penelitian ini akan menyelesaikan permasalahan proses antar jemput barang menggunakan kendaraan listrik yang dimodelkan dengan Electric Vehicle Routing Problem with Simultaneous Pickup and Delivery (EVRPSPD). Kendaraan listrik yang digunakan pada model ini memiliki keterbatasan daya sehingga perlu mengisi daya pada Battery Swapping Station (BSS). Selanjutnya, model akan diimplementasikan pada berbagai macam kasus berbeda yang diselesaikan menggunakan metode eksak dengan bantuan software Lingo 18.0. Hasil yang diperoleh berupa rute distribusi yang optimal dengan meminimumkan jarak serta kendaraan listrik yang mengunjungi BSS untuk pengisian ulang daya., A logistic company needs to determine the optimal route to minimize operational costs in product distribution. This distribution problem, especially the simultaneous pickup and delivery of goods can be solved using the Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD). The transition from conventional vehicles to electric vehicles is one of efforts carried-out by company in reducing greenhouse gas emission. This research aims to solve the pickup and delivery process problem using electric vehicles, modeled as the Electric Vehicle Routing Problem with Simultaneous Pickup and Delivery (EVRPSPD). The electric vehicles used in this model have limited power and need to recharge at a Battery Swapping Station (BSS). Furthermore, the model will be implemented in various different cases using an exact method with the assistance of Lingo 18.0 software. The results obtained include an optimal distribution route by minimizing the distance traveled and the electric vehicles visiting the BSS for recharging.
Keyword: battery swapping, VRPSPD, electric vehicle, route optimization

Judul: Masalah Perutean Kendaraan Listrik Multi-Perjalanan dengan Keberadaan Stasiun Penukaran Baterai
Abstrak: Dengan meningkatnya kesadaran terhadap emisi gas rumah kaca, masyarakat lebih cenderung menggunakan kendaraan listrik dalam berbagai layanan distribusi. Masalah rute pendistribusian dapat diselesaikan dengan menggunakan Electric Vehicle Routing Problem (EVRP). EVRP merupakan perluasan dari VRP klasik dengan kendala keterbatasan kapasitas baterai sehingga kendaraan listrik diharuskan mengunjungi stasiun penukaran baterai dalam perjalanan. Pada makalah ini akan dijelaskan tentang Multiple Trips Electric Vehicle Routing Problem (MTEVRP) dengan keberadaan Stasiun Penukaran Baterai Kendaraan Listrik Umum (SPBKLU). Kendaraan listrik dapat melakukan lebih dari satu kali perjalanan dalam memenuhi permintaan tiap lokasi. Fungsi objektifnya bertujuan meminimumkan konsumsi energi baterai pada kendaraan listrik serta meminimumkan jarak tempuh, di mana kedua hal tersebut berbanding lurus dengan biaya pengiriman maka dengan meminimumkan kedua hal tersebut secara otomatis dapat meminimumkan biaya pengiriman. Permasalahan ini akan diselesaikan dengan metode eksak yaitu Integer Linear Programming., In connection with the increasing awareness of greenhouse gas emissions, people are more inclined to use electric vehicles in various distribution services. The distribution route problem can be solved using the Electric Vehicle Routing Problem (EVRP). EVRP is an extension of the classic VRP with the constraint of limited battery capacity so that electric vehicles are required to visit recharging stations on the way. In this study, we will explain the Multiple Trips Electric Vehicle Routing Problem with Battery Swapping Stations. The electric vehicle can make more than one trip to fulfill the demand of each location. The objective function is minimizing the electric vehicle's battery energy consumption and the travel distance, both of which are directly proportional to the shipping cost, so minimizing these two things can automatically minimize the shipping cost. This problem will be solved with an exact method: Integer Linear Programming.
Keyword: battery swapping stations, electric VRP, exact method, multiple trips, MTEVRP

Judul: Durability of Specific Immunoglobulin (Ig) Y Againts Influenza and Covid-19 in Sunscreen
Abstrak: The benefit of specific immunoglobulin Y (Ig Y) as an active ingredient in personal care products such as sunscreen has not been properly studied. Our study aims to evaluate the reliability of specific IgY against influenza and the COVID-19 virus in a sample sunscreen product. Specific IgY influenza and COVID-19 viruses were inserted in the sample sunscreen at two concentrations of 0.1% and 0.25%. Three treatments were observed: control (C) sunscreen without IgY, treatment 1 (T1) sunscreen with 0.1% IgY, and treatment 2 (T2) sunscreen with 0.25% IgY. Organoleptic observations were carried out to monitor changes in aroma, color, and texture, and sunscreen sampling was done every week for 6 weeks. The durability of IgY was evaluated using an enzyme-linked immunosorbent assay (ELISA) and a neutralization assay. Organoleptic observation from weeks 1 to 6 showed consistency in its aroma, color, and texture. Enzyme-linked immunosorbent assay and neutralization assay (NA) results of the T1 and T2 groups showed negative results except for sample T1 at week 5, which showed a positive result in the Influenza A ELISA. Based on the results, it seems that IgY concentrations of 0.1% or 0.25% were not optimal. However, this negative result might be due to low concentration of the IgY and the presence of beeswax, which inhibits IgY and causes it to dissolve in distilled water, thus preventing it from being detected in the assay.
Keyword: Immunoglobulin Y, Sunscreen, Influenza, COVID-19, Biological Activity