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.

The development of retail business technology is related to the need for management to meet customer demands by using technology. To help make effective sales strategic decisions, it is necessary to optimize the use of information technology on existing sales transaction data. The transaction database that has been stored as a company archive asset can be used for processing information that is useful in increasing product sales and promotions. This study aims to provide an analysis related to the product sales pattern of PT. X in Sumbawa Besar city. PT. X is a retail company that sells distributes daily consumer goods. The algorithm used is Frequent Pattern – Growth which is one of the algorithms in data mining used to find relationships in large data based on the number of occurrences of these data relationships. The Association Rule Mining method can be used in the retail business field, known as Market Basket Analysis. The application used for testing is Rapidminer 9.10. The research stages include: data collection, data preparation, FP-Growth algorithm implementation, result analysis and conclusions. The results of the tests carried out resulted in 819 rules with a total of 85 rules. The results of grouping strong rules based on the combination and number of products that produce information that is expected to be used as recommendations to promote products with discount, cross-selling, up-selling, product bundling and other types of promotions to increase product sales.

COVID-19 has become a global pandemic that causes many deaths, so medical treatment for COVID-19 patients gets special attention, whether hospitalized or self-isolated. However, the problem in medical action is not easy, and the most frequent mistakes are due to inaccuracies in medical decision-making. Meanwhile, machine learning can predict with high accuracy. For that, or that's why this study aims to propose a data mining classification method as a machine learning model to predict the treatment status of COVID-19 patients accurately, whether hospitalized or self-isolated. The data mining method used in this research is the Random Forest (RF) and Support Vector Machine (SVM) algorithm with Confusion Matrix and k-fold Cross Validation testing. The finding indicated that the machine learning model has an accuracy of up to 94% with the RF algorithm and up to 92% with the SVM algorithm in predicting the COVID-19 patient's treatment status. It means that the machine learning model using the RF algorithm has more accurate accuracy than the SVM algorithm in predicting or recommending the treatment status of COVID-19 patients. The implication is that RF machine learning can help/replace the role of medical experts in predicting the patient's care status.

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.

Internet is one of the most important needs in human life. The need for the internet is increasingly crowded, making the world of education in Indonesia very enthusiastic about using it as a means of learning and learning. The use of the internet as a learning and learning tool makes it easier for educators (teachers) to interact with students (students) regardless of their position or distance. However, in meeting the need for a stable and fast internet, it is necessary to provide assistance on bandwidth management. In this assistance, one must be able to understand how much bandwidth is capable of optimizing internet connections for the learning and learning process at SMKN 1 Lingsar. In addition to these needs, it is important to know that bandwidth utilization is shared everywhere so that internet optimization for learning goes well. Therefore, optimal assistance aims to enable users to perform bandwidth management according to the stages of using mikbotam, so that monitoring of bandwidth usage can be carried out more optimally by SMKN 1 Lingsar. The mentoring method is carried out in 5 stages, namely planning, preparation, implementation, evaluation, and reporting. The results obtained from this service program are participants are able to perform bandwidth management according to the stages that have been given.

The impact of the Covid 19 pandemi, which began in 2020, has changed almost all aspects of life, especially teaching and learning activities. Teaching and learning activities which are generally carried out face-to-face, during this pandemi, were implemented online or online using the internet media. The use of the internet among ustadz, ustadzah and students of SD IT Ulul Albab is not an obstacle, especially as children in this era grow up with the internet which has become an important part of the surrounding environment and the internet is easily accessed at home, school and other public facilities. From every facility obtained from the internet, of course, it produces 2 sides that are positive and negatif, and to reduce the negatif impact of activities that involve the internet, there is a need for assistance, direction and socialization of the internet in a healthy and safe manner.         In the service that was carried out at SD IT Ulul Alabini, it was given assistance and socialization to ustadz and ustadzah in representing healthy internet access which would then be passed on to their students. From this service, an evaluation was also carried out by distributing questionnaires related to the results of the socialization carried out in conveying the material, that the participants of this service gained added value to utilize the internet media in a healthy manner as a learning tool for 89% of the participants who attended.