Judul: Pengelompokan kode program c berdasarkan kemiripan struktur menggunakan metode hierarchical agglomerative clustering
Abstrak: Tujuan penelitian ini adalah mengimplementasikan algoritme hierarchical agglomerative clustering untuk membantu pendeteksian penjiplakan pada kode program c secara otomatis dan membandingkan hasil penelitian dengan penelitian sebelumnya menggunakan metode iterasi k-means otomatis dan bisecting k-means. Data yang digunakan dalam penelitian ini sebanyak 386 kode program c yang terdiri atas 4 dataset. Metode yang digunakan single linkage, complete linkage, dan average linkage. Hasil clustering yang dilakukan menunjukkan eksekusi waktu metode single linkage sebesar 1.7220 detik dengan jumlah cluster 14 dan ri sebesar 0.9706, eksekusi waktu metode complete linkage sebesar 1.7500 detik dengan jumlah cluster 10 dan ri sebesar 0.8560, dan eksekusi waktu metode average linkage sebesar 1.7400 detik dengan jumlah cluster 14 dan ri sebesar 0.9546. Hasil penelitian ini menunjukkan adanya perbaikan waktu eksekusi clustering dari penelitian sebelumnya yang menggunakan metode iterasi k-means sebesar 8.41 detik dan metode bisecting k-means sebesar 4.69 detik
Keyword: hierarchical clustering, kode program c, pendeteksi penjiplakan

Judul: Pendeteksian Penjiplakan Kode Program C dengan Bisecting K-means
Abstrak: Plagiarism of source codes assignments is a widespread problem in academic institutions. Manual plagiarism detection is time and energy consuming. Therefore, a system that can help detecting this plagiarism is needed. The detection can be done by grouping similar source codes based on their structure. This method is used in previous research by using automatic K-means iterations algorithm. That algorithm, although produced decent clusters, had a long execution time. The purpose of this research is to improve the time efficiency and clusters result quality by using bisecting K-means algorithm. The results showed a significant improvement in execution time from 11.68 seconds to 6.64 seconds. Bisecting K-means also produced fewer clusters with slightly better Rand Index than K-means iterations. Furthermore, experiments using 2-gram to 6-gram showed that 4-gram resulted in the best performance
Keyword: 

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