With k-medoids algorithm, it often takes many iterations to cluster a large dataset, that is, the k-medoids algorithm cannot achieve the optimal performance. Based on cluster validity, this paper tries to optimize the clustering performance of k-medoids algorithm, using the purity algorithm. Specifically, the medoids value was determined by the purity value, and cluster validity was measured with the Davies Bouldin Index (DBI) on the Iris Dataset and the Death/Birth Rate Dataset. The results show that the cluster validity of the proposed purity k-medoids algorithm was better than the conventional k-medoids algorithm. The conventional k-medoids converged in an average of 8.7 iterations on the Death Birth Rate Dataset and 13.2 on the Iris Dataset. By contrast, the purity k-medoids algorithm only needed 2 iterations on either dataset. Therefore, the purity k-medoids algorithm can effectively minimize the number of iterations in the clustering of large datasets.

Proses clustering dengan algoritma K-Means pada dataset yang memiliki banyak atribut akan mempengaruhi besarnya jumlah iterasi. Pada penelitian ini, metode Information Gain digunakan untuk mereduksi atribut dataset. Dataset yang telah direduksi atribut akan dilanjutkan proses clustering dengan K-Means. Dataset yang dianalisis pada penelitian ini adalah data Hepatitis C Virus yang diperoleh dari UCI Machine Learning Repository, dengan 29 atribut dan 1385 jumlah data. Hasil penelitian ini menunjukkan bahwa rata-rata jumlah iterasi yang diperoleh dari 10 kali pengujian dengan menggunakan K-Means konvensional diperoleh rata-rata sebesar 32 iterasi, sedangkan K-Means dengan reduksi atribut diperoleh rata-rata sebesar 27.7 iterasi. Nilai validitas cluster dihitung menggunakan Davies-Bouldin Index (DBI). Nilai DBI pada K-Means konvensional sebesar 2.1972, sedangkan DBI pada K-Means yang telah direduksi 1 atribut sampai 5 atribut diperoleh nilai rata-rata DBI masing-masing sebesar 2.0290, 1.8771, 1.8641, 1.8389, dan 1.8117.

Algoritma Honey Encryption dan algoritma Blowfish merupakan dua buah algoritma kriptografi yang dapat digunakan dalam proses enkripsi dan dekripsi. Honey Encryption merupakan salah satu algoritma yang masih baru dalam ilmu kriptografi, untuk itu perlu dilakukan analisis kinerja algoritma tersebut pada proses enkripsi dan dekripsi. Berdasarkan studi perbandingan yang telah dilakukan diperoleh hasil bahwa jika ditinjau proses enkripsi dan dekripsinya, algoritma Honey Encryption jauh lebih efektif dan efisien dibandingkan dengan algoritma Blowfish dari segi keamanan dan tingkat kompleksitas enkripsi dan dekripsinya.

The management of Land and Building Certificates at Universitas Malikussaleh is still using a manual library in Biro Perlengkapan which contains some problem whereas it can be burned accidentally refers to fire case in 2017 in Rektorat Building at Universitas Malikussaleh. Given the problem faced by the staff in Biro Perlengkapan, the authors idea is to create a database-based data processing system, the authors designed an integrated information system which be able to anticipated such problem in the future and saving time to collecting important certificates such Land and Building Certificates at Universitas Malikussaleh and protecting them with Honey Encryption algorithm. The information system based on desktop and works as a client-server system. The result  of this research provide that the honey encryption algorithm can protect the data and it can solve the problem in management system of land and building certificates.

The scholarship program held to ease the burden of students in taking the study period, especially in terms of costs. This research conducted at SMP Negeri 7 Sawang – Paya Gaboh in Sawang sub-district, Kabupaten Aceh Utara. This research discusses the provision of educational scholarships from the government of Kabupaten Aceh Utara for students. Therefore, the researcher intends to offer a solution to determine the scholarship recipients at SMP Negeri 7 Sawang by applying the Profile Matching method to find the criteria for receiving the scholarship. The purpose of this research is to design and build a system to determine students who are entitled to receive the scholarships by applying the Profile Matching method based on core data and secondary factors. The implementation of the results of the criteria for the scholarship recipients will be processed using the Profile Matching method. It will produce an output that later assist the selection team in finding the scholarship recipients. The results of the research indicate that the use of the Profile Matching algorithm in finding scholarship recipients works according to the expected categories. The student with the highest score on rank is the first alternative that deserves to be the recipient of the government scholarship aid of Kabupaten Aceh Utara. The system is builtand implemented using PHP programming language.