One of the strategic plans of the developing universities in obtaining new students is forming a partnership with surrounding high schools. However, partnerships made does not always behave as expected. This paper presented the segmentation technique to the previous new student admission dataset using the integration of recency, frequency, and monetary (RFM) analysis and fuzzy c-means (FCM) algorithm to evaluate the loyalty of the entire school that has bound the partnership with the institution. The dataset is converted using the RFM approach before processed with the FCM algorithm. The result reveals that the schools can be segmented, respectively, as high potential (SP), potential (P), low potential (CP), and very low potential (KP) categories with PCI value 0.86. From the analysis of SP, P, and CP, only 71 % of 52 school partners categorized as loyal partners.
Program Studi S1 Teknik Informatika yang bernaung dibawah Sekolah Tinggi Manajemen Informatika dan Komputer (STMIK Bumigora Mataram), sebagai program studi dengan jumlah peminatnya mendominasi keluarga besar STMIK Bumigora Mataram. Seiring dengan bertambahnya mahasiswa disertai dengan padatnya operasional yang dijalankan oleh civitas akademik sehingga mendorong pihak internal untuk mampu mendukung fungsi bisnis dengan menyelaraskan strategi bisnis dan teknologi yang digunakan. Pencapaian sebuah keselarasan teknologi informasi dengan bisnis yang dijalankan oleh STMIK Bumigora Mataram, sehingga dirancanglang sebuah arsitektur enterprise yang mampu menghasilkan sebuah Blue Print yang dilengkapi dengan sebuah Framework TOGAF sehingga mampu menganalisis arsitektur bisnis secara lengkap dan menyeluruh untuk periode waktu jangka panjang.
The Madrasah Head who has good ability will give the best performance for the Madrasa he leads so that the Madrasa has good quality so that it can create a generation that is smart and has good character and good religion. One of the efforts of the Ministry of Religion of the Republic of Indonesia Mataram City Office to always maintain and improve the quality of Madrasah heads in the City of Mataram is to provide an assessment to choose the best Madrasah head so that all Madrasah heads in the City of Mataram have the motivation to always improve their quality. The design and manufacture of systems in this study use the waterfall methodology. This study uses the Exponential Comparison Method (MPE) which is one of the methods of the Decision Support System (SPK) used to determine the priority order of alternative decisions with multi criteria. The results of this assessment are to get the best Madrasah head ranking table in the city of Mataram based on the results of the system calculation, where these results can already be used by the Ministry of Religion of the Republic of Indonesia Mataram City Office as a consideration in determining the best Madrasa head in the city of Mataram. The conclusion of this study is the construction of a system that is able to produce the best level of Madrasah head assessment in the city of Mataram which can then be used to help the Ministry of Religion of the Republic of Indonesia Mataram City Office in making the decision to determine the best Madrasah head in the city of Mataram effectively and efficiently.
Culinary business using carts selling various kinds of heavy food, light and drinks, is favored by many people to just fill their stomachs, gather with friends and even family. Culinary businesses or culinary destinations like this are known as Angkringan which are increasingly mushrooming in the millennial generation. Angkringan Waru, located in Tanjung Bias, is a gathering destination for all people to enjoy a relaxed atmosphere on the beach. Angkringan Waru provides 85 types of menus for its customers, the many menus often confuse customers in choosing snacks while enjoying the beachside atmosphere. Starting from these problems, data mining techniques are used with the Frequent Pattern Growth (Fp-Growth) algorithm to recommend items in producing a menu package consisting of 1 snack item and 1 drink item. The dataset used is transaction data from Angkringan Waru as many as 870 transactions, the resulting output is a menu package recommendation rule and implemented in a web for Angkringan Waru. The Fp-Growth Data Mining Application by providing a minimum support value of 20% and Confident 50% with a lift ratio > 1 produces 57 rules or menu package recommendations that will be offered to Angkringan Waru customers. The results of the application in the form of 57 menu package recommendations are then used as recommendations for Angkringan Waru customers, where these menus are the favorite menus of customers at Angkringan Waru.
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