Judul: Customer Relationship Management Untuk Penetapan Strategi Penjualan Menggunakan Teknik Association Rules Mining
Abstrak: Business competition is the most important factor to develop a marketing system for a more effective and efficient marketing system in an industry. Customer Relationship Management (CRM) is a marketing Management system which can be a solution to face an increasingly competitive business. CRM includes cross-up selling, analysis of affinity products, and bundling of products that can be used as an alternative solution in marketing strategy system in an industry. Revenue of a company can be improved through cross selling where sale the additional product with the major products. Customer Relationships can improve customer satisfaction. This research discusses an analysis of sales transaction data from an agro-industrial company with tires products using Association Rules Mining technique. The result from this work shows the strategy of sales can be made using value of support, confidence and improvement. Determining of sales strategy makes to sell products which have complementary products with a value is higher than the base product and have confidence level> 50%. It shows that sell in up-selling (offering products that have higher prices of basic products) also can be done.
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Judul: Preferensi layanan pelanggan berbasis CRM (Customer Relationship Management) dengan pendekatan apriori dan bond
Abstrak: Market basket analysis discovers association pattern in retail transaction data. Association rules mining is a method of data mining that aims to find a set of items that frequently occur together. Apriori algorithm is an algorithm to find pattern of association that is used for market basket analysis (MBA). Cross-selling is a part of the CRM (customer relationship management), which sells the main products with additional products recommended. Cross-selling should be analyzed based on transaction data by using data mining concepts. The analysis process involves the extraction of information from customer transaction that includes what products they buy, customer buying behavior etc. RFM analysis (Recency Frequency Monetory) is a marketing technique to analyze customer buying behavior. Mining association rules based on steps of RFM measurement, analyzes relationship and customer loyalty on products to get good recommendations to increase the company's revenue . Apriori algorithm is usually used for the MBA. In this study, besides a’priori we add a minimum measurement bond correlation, which shows the close relationship between products. With the addition of the bond measure, it would be easier to select products for cross-selling and reduce processing time. Result of this research is a hypothesis cross-selling marketing strategy that is customer service preferences; providing good recommendations to improve customer loyalty and increase the company's revenue . The proposed method is applied to sales transactions of spare parts of central AC company as dataset in the case. Results of this study showed 9 rules which can be used to determine the cross-selling sales strategy, taking into account the highest value of improvement (lift), confidence, bond and support. Recommendations for cross-selling strategy is composed by sets of rules measure from four parameters above. The proposed products for cross-selling based on the results of association rules mining and measurement bond are oil filter, maintenance kit, filter kit, separator kit, G roto inject oil, air filter, oil separator and chemical. The results also indicate the relationship between products and to get the best customer loyalty recommendation to the company. Results of the analysis is customers with the highest RFM that give more benefits for the company. Company is advised to maintain customer satisfaction and customer loyalty, to offer cooperation for service contracts, and to offer reselling (customers involved in selling products). It is recommended to maximize RFM analysis by taking into account geographical segmentation of the customers.
Keyword: association rules mining, bond measure, CRM (customer relationship management), cross-selling, data mining

Judul: Penapisan Hepadnavirus Secara Serologik Dan Molekuler Pada Monyet Ekor Panjang (Macaca Fascicularis) Di Habitat Ex-Situ
Abstrak: Penemuan infeksi virus hepatitis B (VHB) monyet ekor panjang (Macaca fascicularis) di Pulau Mauritius pada tahun 2013 merupakan temuan baru yang menunjukan bahwa penyakit ini dapat menginfeksi jenis satwa primata dari famili Cercopithecidae. Temuan tersebut hanya dilaporkan pada M. fascicularis yang berada di benua Afrika, sehingga menjadi alasan dilakukannya investigasi pada M. fascicularis asal Indonesia. Untuk mendapatkan gambaran keadaan tersebut, sampel darah M. fascicularis diambil dari berbagai lokasi habitat ex-situ. Uji penapisan terhadap antigen permukaan virus hepatitis B (Hepatitis B surface antigen, HBsAg) dilakukan pada 95 sampel plasma dan serum M. fascicularis yang berasal dari penangkaran, pusat penyelamatan satwa, dan topeng monyet. Upaya pemeriksaan DNA VHB dilakukan pada sampel yang menunjukan hasil seropositif terhadap HBsAg. Uji penapisan menunjukan bahwa sebanyak 11 dari 95 (11.6%) sampel reaktif terhadap HBsAg. Antigen permukaan virus hepatitis B lebih banyak ditemukan pada monyet di pusat penyelamatan satwa dan topeng monyet (55%) dibandingkan dengan satwa penangkaran (45%). Hasil seropositif HBsAg pada sampel M. fascicularis yang diperiksa dengan teknik ELISA menggunakan kit HBsAg manusia mengindikasikan adanya kemiripan protein antigen permukaan VHB manusia dengan yang ditemukan pada M. fascicularis, karena antibodi monoklonal yang digunakan dalam uji ELISA pada penelitian ini bersifat spesifik mengikat HBsAg manusia. Meskipun uji PCR terhadap sampel tersebut tidak menunjukkan adanya DNA VHB, hasil seropositif HBsAg mengindikasikan bahwa M. fascicularis dapat terinfeksi VHB atau virus yang mirip VHB secara alami.
Keyword: virus hepatitis B, monyet ekor panjang, habitat ex-situ