Judul: Integrasi Modul Pengelompokan Kode Program C Berdasarkan Struktur pada TOKI Learning Center
Abstrak: Manual detection of source code plagiarism requires a lot of time and effort. Therefore, a system that could help to detect plagiarism of programming assignment is required. The purpose of this research is to build a web application that implements clustering module of C program code based on the structure. The method used to build the system in this research is System Life Cycle. The result of this research is a web application that helps to detect plagiarism of programming assignment in TOKI Learning Center. The application has 3 clustering options, i.e., using clustering method, using the result of test case, and using the combined result of the test case with the clustering method. There are 5 methods of clustering used in the web application, i.e., K-means, bisecting Kmeans, single linkage, average linkage, and complete linkage. To help instructor determine a plagiarism, there are several conditions for consideration provided by the web application, i.e., clustering result, submission time, number of submissions, and the source codes.
Keyword: Bogor Agricultural University (IPB), web application, system life cycle, structure similarity, plagiarism detection, C programming

Judul: Pendeteksian Kemiripan Kode Program C dengan Algoritme KMedoids
Abstrak: Practice of plagiarism on program codes is more common and easier to do. Manual detection of plagiarism takes a lot of time and effort. The detection can be done by grouping program codes that have similar structures. This study intends to apply K-medoids algorithm on 4 C code program datasets to find similarities of code program and analyze clustering results. The experimental results show that the best clustering in dataset1 (If-Else Condition and Looping While) was obtained at k=10 with an average of dissimilarity 2.655, and 18.9% of students have the same group. In dataset2 (Looping While), the best clustering was obtained at k=9 with an average of dissimilarity 2.227, and 32.6% student assignments are in the same group. For dataset3, the assignments are divided into two clusters with an average of dissimilarty 0.719, and 87% of students assignments are in the same cluster. The best c lustering result on the dataset4 was obtained at k=6 with an average of dissimalrity 3.199, and 61% of students assignments are in the same group. The accuracy rate from clustering results is 93.28%
Keyword: similarity detection, K-Medoids algorithm, clustering, Bogor Agricultural University (IPB)

Judul: The Effects of Avocado Oil (Persea americana Mill.) as Hair Growth Promoters on Rats (Rattus novergicus)
Abstrak: Essential oils and carrier oils are commonly used as pharmacology cosmetics in promoting hair growth. Avocado oil is one of the carrier oils rarely discussed as a hair growth-promoting cosmetics as compared to other oils. This study determined the effects of avocado oil (Persea americana Mill.) as hair growth promoter on rats (Rattus norvegicus). A total of 6 rats were used and each rat was divided into 4 treatment areas: control, 1 smear a day, 2 smears a day, and 3 smears a day. The parameters are hair length and irritation reaction. Data were collected on day 6th, 9th, 12th and 15th. Descriptive analysis was initially performed to examine the trend of the data. Based on the trend of the data, the treatment of 1 smear a day showed a slight increase in hair length. Subsequently, ANOVA one-way and Tukey tests were conducted to determine the statistical significance of the results. The statistical analysis results indicated that avocado oil did not have a significant effect as a hair growth promoter. Furthermore, no signs of irritation were observed on the application site of the rats. In conclusion, while the descriptive analysis suggested 1 smear a day of avocado oil show effects as hair growth promoter, however the subsequent statistical analysis only support little significant effect.
Keyword: avocado oil, hair growth, irritation