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Abstrak :
ABSTRACT
Pemerintahan Republik Indonesia memfokuskan pariwisata sebagai penghasil devisa utama untuk meningkatkan daya saing Indonesia. Selain itu, pada saat ini mulai terjadi pergeseran nilai ekonomis yang berawal dari Untuk meningkatkan daya saing, pemilik objek wisata dapat menciptakan memorable experience. Penelitian dilakukan dengan menggunakan pendekatan design thinking, yang difokuskan kepada pengunjung Galeri Indonesia Kaya. Berdasarkan wawancara dan pengamatan, ditemukan karakteristik, sifat, keinginan, dan kebutuhan pengunjung yang dipetakan dalam beberapa peta visual. Hasil dari penelitian ini adalah sebuah alat dan sebuah alur yang dapat meningkatkan interaksi pengunjung dengan objek, serta meningkatkan kunjungan kembali dan rekomendasi.

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ABSTRACT
Government of Indonesian Republic has focused its tourism as the main producer of its foreign exchange to increase their competitiveness in South East Asia. At the same time, nowadays, there is a phenomenon of economic value shift from commodities to experiences. To increase a country competitiveness, one can create a memorable experience in their attraction. This research is done with the design thinking approach that focused on the visitor of Galeri Indonesia Kaya. Based on empathy, it has been found the characteristic, behavior, needs, wants, and the trait of the visitor then mapped through various visual tools. The result of this research is an equipment and experience that can increase visitor rsquo s interaction with the attraction, which can result in increase in loyalty intention of revisit and recommend.

Abstrak :
Meningkatnya penggunaan internet di Indonesia memberikan dampak positif bagi perkembangan e-commerce di Indonesia dengan jumlah pengguna internet telah melakukan transaksi elektronik sebesar 63,5 . Dengan meningkatnya jumlah e-commerce B2C di Indonesia, diperlukannya strategi promosi yang tepat untuk mengetahui preferensi dan potensi pembelian untuk setiap konsumen sehingga dapat meningkatkan transaksi e-commerce tersebut. Web usage mining merupakan salah satu metode yang dapat mengolah data web log pengguna situs web e-commerce B2C menjadi informasi yang dapat digunakan untuk mengklasifikasi keputusan pembelian pengguna situs web. Kombinasi kategori produk pembelian yang tinggi oleh pengguna situs web e-commerce memerlukan teknik klasifikasi multi label yang dapat mengklasifikasi kombinasi pembelian secara bersamaan. Metode Label Powerset dengan algoritme Support Vector Machine SVM digunakan untuk mengklasifikasi keputusan pembelian pengguna situs web e-commerce. Seleksi fitur menggunakan Information Gain dan pemilihan parameter dengan menggunakan Grid Search terbukti dapat meningkatkan akurasi klasifikasi.

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The advance of internet usage in Indonesia has a positive impact on the development of e commerce in Indonesia where 63.5 of internet users have made online transactions. Along with e commerce B2C growth in Indonesia, it is necessary for an effective promotional strategy to know the preferences and potential purchases for each consumer with the result that to increase transactions. Web usage mining is a method having an ability to convert web log data into information used for purchase classification. The high combination of purchasing product categories by users of e commerce website required a multi label classification technique that could classify those combinations. Label Powerset method with Support Vector Machine SVM algorithm was applied to classify e commerce users purchases decision. The proposed feature selection with Information Gain and parameter selection using Grid Search could prove that they had an ability to enhance classification accuracy.

Abstrak :
Peningkatan persaingan dan kunjungan di situs web e-commerce shopping mall di Indonesia perlu disertai dengan meningkatkan strategi Customer Relationship Management CRM . Strategi yang bisa digunakan adalah peningkatan kualitas pelayanan, hal ini bisa di implementasikan melalui penyusunan sistem rekomendasi produk di situs web e-commerce tersebut. Untuk menyusun sistem tersebut, penggalian pola asosiasi produk dilakukan dengan memanfaatkan data web log yang berisi data navigasi dan pola kebiasaan pelanggan. Hal tersebut diakomodasi oleh metode web usage mining yaitu association rules. Algoritma yang digunakan adalah algoritma yang memberikan input asosiasi berdasarkan frekuensi item, yakni algoritma Apriori. Untuk menguji dan menyeleksi pola yang dihasilkan, objective interestingness measure dilakukan dan menghasilkan 25 luaran pola asosiasi.

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An increasing of competition and visitors on e commerce shopping mall websites in Indonesia, need to be accompanied by improving Customer Relationship Management strategy. A strategy that can be used is improving the quality of services, it can be implemented through the preparation of product recommendation system on the e commerce website. To compile the system, pattern recognition of product association is conducted by utilizing weblog data which contains navigation data and customer behavior pattern. It is accommodated by web usage mining method that is association rules. The algorithm applied is an algorithm that provides input association based on item frequency, i.e Apriori algorithm. To test and select the resulting pattern, objective interestingness measure was performed and yields 25 outcomes of the association pattern.

Abstrak :
ABSTRACT
Peningkatan jumlah pengguna internet mendorong organisasi, perusahaan, dan lembaga lain untuk berinteraksi dengan publik melalui berbagai media online. Situs website adalah contoh saluran informasi online yang digunakan oleh kelompok organisasi yang memungkinkan para pengunjung melakukan pencarian informasi didalamnya. Website SIMAK adalah website milik Universitas Indonesia yang mendistribusikan informasi mengenai cara masuk Universitas Indonesia. Ekstraksi pola perilaku pengunjung pada website SIMAK penting dilakukan untuk mengetahui tren terhadap pencarian informasi dan pengaksesan tampilan halaman yang terdapat di laman website. Hal ini dilakukan untuk meningkatkan kualitas website SIMAK dalam hal kemudahan aksesibilitas pengguna yang lebih baik. Namun, pola penggalian di website SIMAK belum pernah dilakukan sebelumnya. Sementara itu, website SIMAK merupakan salah satu website yang paling banyak dikunjungi oleh publik. Penelitian ini dilakukan dengan menggunakan pattern mining, salah satu aplikasi pengekstraksian pola pencarian informasi yang dilakukan oleh pengunjung website untuk mengetahui pola perilaku pengunjung melalui situs website SIMAK. Data web log pengunjung website SIMAK selama bulan Februari, Maret, dan April digunakan dalam penelitian ini sebagai representasi tingginya aktivitas website dalam kurun waktu satu tahun menggunakan teknik association rules. Hasil pengolahan data kategorisasi umum menunjukkan bahwa terdapat satu pola aturan unik pada bulan Februari dan Maret, dan tiga pola aturan unik di bulan April. Selain itu, pada data berkategorisasi khusus terdapat delapan pola aturan unik di bulan Februari, tiga pola aturan unik di bulan Maret dan enam pola aturan unik di bulan April. Aturan pola yang ditemukan ini menggambarkan pola perilaku pengunjung dalam melakukan pencarian informasi melalui situs website SIMAK.

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ABSTRACT
The increasing amount of internet usage encourages organizations, companies, and other institutions to engage with the public through various online media. Website is an example of online information channel for those institutions, enabling the visitors to search detailed information. SIMAK Website is a website owned by the Universitas Indonesia that distributes information on getting through Universitas Indonesia. Extracting pattern of website visitors behavior is important to find out the trend on information searching and page accessing. Thus, the website can be improved to have better accessibility and user performance. However, the extracting pattern in the SIMAK website is not often conducted while this website is one of the highest number vistitors. This study was conducted using pattern mining, one of the applications of web usage mining, to find out patterns and trend of visitors behavior in information searching through SIMAK website. Visitors web log data of the SIMAK website in February, March, and April was processed by association rules method as those three months have the highest number of visitors activities in accessing website information in a year. The results show that general categorized data have one unique pattern in February and March, and three unique patterns in April. Meanwhile, the distinctive categorized data have eight unique patterns in February, three unique patterns in March, and six unique patterns in April. The rules patterns found describe the visitors behavior which may occur due to the information search on SIMAK website.

Abstrak :
Practical web analytics for user experience teaches you how to use web analytics to help answer the complicated questions facing UX professionals. Within this book, you'll find a quantitative approach for measuring a website's effectiveness and the methods for posing and answering specific questions about how users navigate a website. The book is organized according to the concerns UX practitioners face. Chapters are devoted to traffic, clickpath, and content use analysis, measuring the effectiveness of design changes, including A/B testing, building user profiles based on search habits, supporting usability test findings with reporting, and more. This is the must-have resource you need to start capitalizing on web analytics and analyze websites effectively.

Abstrak :
This book is the second of three volumes that illustrate the concept of social networks from a computational point of view. The book contains contributions from a international selection of world-class experts, concentrating on topics relating to security and privacy (the other two volumes review Tools, Perspectives, and Applications, and Mining and Visualization in CSNs). Topics and features : presents the latest advances in security and privacy issues in CSNs, and illustrates how both organizations and individuals can be protected from real-world threats; discusses the design and use of a wide range of computational tools and software for social network analysis; describes simulations of social networks, and the representation and analysis of social networks, with a focus on issues of security, privacy, and anonymization; provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology.