Di Indonesia, terdapat beberapa pekerja sebagai petani sebagai matapencaharian karena kebutuhan pokok pada pangan dan memiliki lahan pertanian yang luas. Karena terdapat perbedaan  luas lahan pertanian dan hasil produksi pertanian, maka diperlukan klasterisasi pada data pertanian. Tujuan klastering adalah untuk mengidentifikasi suatu kelompok data dari populasi data untuk menghasilkan sifat-sifat dari data itu sendiri. Pada penelitian ini akan digunakan dua metode yaitu : algoritma K-Means dan algoritma Fuzzy C Means (FCM). Algoritma K-Means dan algoritma FCM dapat mengklaster beberapa kecamatan di kabupaten Lamongan berdasarkan luas lahan pertanian dan hasil produksi pertanian. Pada algoritma K-Means, titik pusat klaster diupdate sehingga menghasilkan jumlahan euclidean distance yang minimum. Pada algoritma FCM, derajat keanggotaan (the degree of membership) diupdate sehingga menghasilkan nilai fungsi objective yang minimum. Berdasarkan hasil simulasi, kedua metode tersebut dapat mengklaster beberapa kecamatan di kabupaten Lamongan berdasarkan luas lahan pertanian dan hasil produksi pertanian.

No abstract

Agriculture is a sector that has a significant role for the Indonesian economy. In Lamongan Regency, about 35.71 percent of the workers depends on the primary agricultural sector, so it is not surprising that the agricultural sector is the basis of growth, especially in rural areas. Agricultural development is oriented towards improving the welfare of farmers. One of the measurements the level of farmer welfare is by calculating the Farmer Exchange Rate. It is the relationship between the produce sold by farmers and the goods and services purchased by farmers. Seeing how important this Farmer Exchange Rate is, predicting the value of Farmer Exchange Rate in the following year will be very useful. The results of this value can be a benchmark to anticipate all situations in the following years and how to control the rising value of Farmer Exchange Rate so as to improve the welfare of the people of Lamongan. From the results of the analysis and discussion, food plants have a low NTP value, namely ?100 per month for a period of 3 years and have the highest Farmer Exchange Rate reduction in 2019 of 10.25%.

No abstract

The general goal of education is to develop Indonesian people completely in the sense that carried out education still maintain unity, diversity and develop individual’s ideals. Every citizen has the right to obtain education equally with excellence and a balance (equity) between the utilization (access) with achievement. The higher education system must be able to create a quality higher education that is also affordable by the people of Indonesia. A university leader must be in-line and lead a "quality revolution". All energy and attention are focused on the "quality revolution". For this reason, this paper will examine the Implementation of Higher Education Quality Management Systems. As a case study is that has implemented a Quality Management System. According to Law No. 12 of 2012 concerning Higher Education. Quality Higher Education is Higher Education that produces graduates who are able to actively develop their potential and produce Science and / or Technology that is useful for the Community, nation, and country. The government operates a higher education quality assurance system to get quality education. The Higher Education quality assurance system referred to consists of: a. internal quality assurance system developed by Higher Education; and b. external quality assurance system carried out through accreditation. Implementation of Quality Management Systems in Higher Education can produce Quality and Affordable Education.