Judul: Pembuatan Modul Rekomendasi pada OpenCart Menggunakan Metode Item-Based Collaborative Filtering
Abstrak: This research aims to add a recommender module in OpenCart CMS. One of the method is item-based collaborative filtering that can reduce the execution time of calculation. This study uses adjusted cosine similarity to calculate the similarity between books, weighted sum method to calculate the books rate prediction, and mean absolute error to calculate recommendacy accuracy. In order to get the recommendation, user have to login and give ratings to the books. Then, adjusted cosine similarity calculates the similarity between books based on user’s rate. Based on the similarities between books, weighted sum method calculates the books rate prediction. Before a book is recommended to the user, type of book from the prediction are first matched with the type of book rated by the user. This research uses 300 books and 30 users. The result shows that only 17 users can get recommendations. Evaluation is conducted by analyzing the execution time and recommendacy accuracy. It is found that the execution time is 1.60 seconds and the mean absolute error is 0.15.
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Judul: Perancangan Sistem Rekomendasi Pembelian dan Manajemen Persediaan Produk Menggunakan Content Based Filtering dengan Pendekatan Sequential Pattern Mining
Abstrak: Toko Buku XYZ adalah salah satu toko buku besar yang ada di Indonesia. Saat ini, penjualan produk di Toko Buku XYZ terus meningkat sesuai dengan tren di masyarakat. Penjualan tinggi harus didukung oleh persediaan yang baik dan sesuai target. Barang yang dijual harus berdasarkan kebutuhan konsumen yang pada akhirnya bertujuan untuk mencapai penjualan tinggi. Toko Buku XYZ sebagai toko buku yang tergolong besar di Indonesia menyadari pentingnya mengetahui pola pembelian pelanggan yang ada pada periode tertentu. Karena seringkali para petugas pembelian (merchandiser) yang bertugas untuk melakukan kegiatan pembelian produk yang akan dijual kembali di toko tidak dapat melakukan pembelian yang pas. Hal ini mengakibatkan kosongnya stok barang yang seharusnya masih laku untuk dijual kembali. Tujuan penelitian ini adalah menemukan pola pembelian pelanggan dengan pendekatan sequential pattern mining, membangun model rekomendasi pembelian pada manajemen persediaan barang hingga membuat rancangan antarmuka dari model rekomendasi tersebut. Algoritme yang digunakan adalah algoritme SPADE (Sequential PAttern Discovery using Equivalent classes). Oleh sebab itu, penelitian ini diharapkan dapat memberikan hasil yang positif dan berguna bagi perusahaan. Dengan menggunakan pendekatan Sequential Pattern Mining, penelitian ini dapat mencari pola penjualan satu barang dalam kaitannya dengan barang lain. SPADE (Sequential Pattern Discovery menggunakan kelas Equivalence) adalah algoritme yang dapat digunakan untuk menemukan pola sekuensial dalam database besar. Data penjualan yang digunakan adalah dalam kurun waktu Juni sampai dengan Desember 2016. Produk yang dianalisis adalah produk buku. Hasil dari penelitian ini adalah rekomendasi bagi petugas pembelian hingga dibuatkan rancangan aplikasi rekomendasi untuk pembelian produk. Produk kategori Children’s Book menjadi kategori yang urutan pembeliannya paling banyak yaitu hingga mencapai 7-frequent sequence pada minimum support 0.001 daan support absolut 61. Hal ini membuktikan bahwa produk kategori ini sangat laris bahkan ada 61 pelanggan yang membeli produk dengan kategori ini hingga 7 kali pada tanggal yang berbeda di masa penelitian ini berlangsung. Ini berarti SPADE berhasil digunakan untuk memberikan rekomendasi pembelian sehingga petugas merchandiser bisa memastikan stok produk tersebut selalu tersedia untuk menghindari Lost Sales. Rancangan aplikasi yang dibuat terdiri dari 3 modul utama yaitu modul persediaan dimana pengguna bisa melihat persediaan produk, modul penjualan dimana pengguna bisa melihat penjualan produk, serta modul rekomendasi dimana pengguna bisa melihat rekomendasi produk dari data penjualan yang telah diolah menggunakan algoritme SPADE.
Keyword: Content Based Filtering, Rekomendasi, Sequential Pattern Mining, SPADE

Judul: Phylogeography and Species Limits in the Papuan White Snake (Micropechis ikaheka) (Reptilia: Serpentes: Elapidae)
Abstrak: Papua white snake, Micropechis ikaheka, has been distingushed into two subspecies M.i. ikaheka and M.i. fasciatus. However, due to lack of data on their morphology, distribution and ecology, both subspecies often ignored in scintific discussions and refers only byas , Micropechis ikaheka. This study was designed to document the differences between M.i. ikaheka and M.i fasciatus by using scales characteristics and reproductive organ or hemipenes. The study also examine, zoogeography, habitat, diet and cannibalism of both subspecies to better understanding the the ecology of one of the most venomous snakes in the world. This study consists of three topics with method and also different in the size samples, respectively. The first study is the histology and microtopography of the skin were studied using paraffin method and Scanning Electron Microscope (SEM). The second is the hemipenis were examined by following Myers and Cadle (2003), and Zaher and Prudente (2003). The third is the abdominal surgery was carried out to document diet type and the investigate phenomenon of cannibalism in the snake. Specimens for this study came from the collection from Museum Zoologicum Bogoriense (MZB) and Universitas Negeri Papua’s Laboratory (LZU). The research result also indicated that the markers of skin and hemipenis described the same structure and microornamentation in all M. ikaheka groups being compared. Based specimens examined morphological descriptions do not s support the further differentiation in Micropechis. In short, two markers that used in this study could not sufficiently indicate the differences in the level of species and subspecies of M. ikaheka. The study, however, were able to delineate zoogeography and skin color patterns, which fall into four groups: M. i. ikaheka; M. i. fasciatus. M. i. ssp. “intermediate”; and M. i. ssp “black”. This study also revealed that color variations did not overlap in their geographic distribution. It is therefore, it suggested that environmental factors may contribute to the skin color variations. It also assumed that habitat discontinuous and biogeography factors may also cause the loss of the connection between the original populations (vicarians) or follow colonization events (dispersal). The examined of 22 stomach contents of M. ikaheka shows this species is carnivorous, and prey on vertebrates such as amphibians, fish, reptiles, and Mammals. These snakes are opportunistic predators since they prey on all that can be captured, but mainly reptiles (61.5%), followed by mammals and fish (both 15.4%), and amphibians (7.7%). Although categorized as terrestrial animal, the diet study showed that M. ikaheka snakes often go into the water to hunt for fish (the sample from Yapen island), including eel (the sample from Aru island). Based on prey items indentified, there is evidence that M. ikaheka is cannibal. At this time, there still no record on reason for cannibalism, but it is assumed that cannibalism was due to competition between populations and means to control population.
Keyword: geographic variation, white snake, papua