Wisata lokal saat ini berpotensi untuk dikembangkan sebagai salah satu sumber pendapatan daerah dengan mendayagunakan sumber daya yang dapat memberikan sumbangan bagi pembangunan ekonomi pada suatu daerah tersebut. Kota Sidamanik merupakan kota yang mempunyai banyak wisata alam yang masih alami. Dan juga suasana alam yang indah dikelilingi perkebunan teh yang sangat menarik perhatian para wisatawan lokal maupun asing. Dalam hal ini terkadang banyak para wisatawan bingung untuk menentukan wisata mana yang akan mereka kunjungi untuk dapat menyesuaikan keinginan mereka, mengingat beberapa wisata yang ada di kota sidamanik. Penelitian ini menggunakan Metode MAUT (Multi-Attribute Utility Theory) untuk merekomendasikan destinasi wisata lokal yang ada di kota Sidamanik. Pengolahan nilai menggunakan metode Maut akan menghasilkan nilai rangking. Hasil dari penelitian ini yaitu rekomendasi destinasi tujuan wisata lokal di Kota Sidamanik adalah wisata Bah Biak. Hasil nilai yang di peroleh dari wisata lokal Bah Biak adalah 0,847 dan menempati nilai tertinggi dari keempat wisata lokal yang ada di Kota Sidamanik Kab. Simalungun Provinsi Sumatra Utara.

The Indonesian tourism sector currently contributes approximately 4% of the total economy. In 2019, the Indonesian Government wants to increase this figure to double to 8% of PDB (Produk Domestik Bruto), a target that implies that within the next 4 years, the number of visitors needs to be doubled to approximately 20 million tourists. This study discusses the Application of Clustering in Grouping the Number of Foreign Tourist Visits by Nationality and Month of Arrival by the K-Means Method. The source of this research data was collected based on data on the number of foreign tourist visits produced by the National Statistics Agency. K-Means clustering is one of the data mining techniques that gives a description of an item's cluster. The purpose of this study is to classify the number of foreign tourists in Indonesia. The results of this study are grouping the number of foreign tourist visits grouped by two clusters (high and low), high clusters of 4 countries and low clusters of 87 countries. Countries that are included in the lower clusters can be used for the Government of Indonesia in terms of improving existing facilities in tourist attractions so that visiting tourists will increase in the future.

Posyandu (Integrated Service Post) is one form of Community-based Health Efforts (UKBM) carried out with the community, to empower and provide facilities to the community to obtain health services for mothers, infants and toddlers. The Posyandu program is an effort to reduce the impact of the economic crisis on reducing the nutritional status of maternal and child health. This study discusses the grouping of the number of active posyandu based on provinces in Indonesia. The method used in the research is Data mining with the K-Means Clustering algorithm. By using this method the data obtained can be grouped into several clusters. This study uses secondary data, namely data obtained from intermediary media recorded on the website of the Indonesian Ministry of Health with the url address https://www.depkes.go.id/. The results obtained in this study are grouping the number of active posyandu grouped into 2 clusters, the highest cluster and the lowest cluster. There are 3 provinces included in the highest cluster and there are 31 provinces included in the lowest cluster. From the results of this study, it will be found that the provinces that get the lowest cluster in the number of active posyandu in Indonesia, It is hoped that this research can provide input to the relevant government, to pay more attention to the provinces in Indonesia which have the lowest cluster to activate the posyandu program in the province. Because posyandu is very important for children's health. If the child has never done a posyandu then he or she will not receive nutritional intake according to the child's needs.