The aim of the research is to map clusters on Indonesia’s national food security during the Covid-19 Pandemic. Where food security is a condition for the fulfillment of food for the state up to individuals, which is reflected in the availability of sufficient food, both in quantity and quality, safe, diverse, nutritious, equitable, and affordable and does not conflict with the religion, beliefs and culture of the community, to be able to live a healthy, active, and productive life in a sustainable manner. The data source used is secondary data from the Central Statistics Agency (abbreviated BPS). The data consists of monthly per capita expenditure in urban and rural areas by province and group of goods (rupiah) consisting of 33 data records (2011-2018). The group of goods used is expenditures used for food costs. The data mining method used is k-medoids which are part of the clustering. Cluster mapping uses 2 labels namely C1: labels with high food security and C2: labels with low food security. The results of the k-medoids method calculation concluded that 19 provinces were in C1 cluster and 14 provinces were in C2 cluster. From these results it is stated that 42% of Indonesia still has low food security as evidenced by the fulfillment of higher food needs than non-food. These regions are West Sumatra, Riau, Bangka Belitung Islands, Riau islands, DKI Jakarta, West Java, Banten, Bali, Central Kalimantan, South Borneo, East Kalimantan, North Sulawesi, West Papua and Papua.
School as one of the processes for implementing formal education is required to carry out the learning process optimally to produce quality students. Regarding the research process carried out to predict the graduation rate of SMA Nurul Falah students by using the decision tree method. The data used in this study are student data using the criteria for student names, majors, average report cards from semester one (I), two (II), three (III), four (IV), five (V), and the average value of the National Standard School Examination (USBN). The data is then managed using Rapidminer 5.3 software to make it easier to predict student graduation rates. The application of data mining is used to predict the graduation rate by using the decision tree method and C4.5 algorithm as a supporter as well as to find out information on the graduation rate of Nurul Falah High School students. This study aims to predict student graduation rates in order to get useful information and the school can make policies in the coming year.
This activity is to provide assistance to the group of Lancang Kuning University lecturers, especially to the lecturers participating in the Phase I lecturer certification in 2020. The service team will explain the techniques and methods of collection starting with explaining the functions of the Sister application (www.sister.unilak.ac.id ) for lecturers both lecturer certification participants and certified lecturers. Certification participants must enter their personal data, educational history, functional position history, education implementation history, research history, service history and other supporting data. All participants explained the rules in the process of inputting data, especially the maximum size of data that can be input up to a quick trick in order to be able to input data themselves on the application. Of the 10 faculties at Lancang Kuning University, 72 lecturers can continue at stage D3 to stage D4. Whereas at stage D5 only 51 lecturers were able to proceed because of the selection process for the assessment of the system. The dedication team made WAG in guiding the data system input process in the framework of the certification process. This is done so that they can monitor and assist if there are obstacles in the certification process.
Sistem Pendukung Keputusan (SPK) adalah sebuah system yang dapat membantu pimpinan / owner dalam proses pengambilan keputusan dengan menggunakan metode perhitungan berdasarkan kriteria-kriteria penilaian. SPK bukan sebuah tool pengambil keputusan tetapi hanya sebuah alat perbandingan dalam pengambilan keputusan. Keputusan Fakultas Terbaik di Universitas Lancang Kuning adalah proses penilaian fakultas dari beberapa aspek kriteria yang dapat membantu pimpinan / badan penjamin mutu dalam penilaian dengan tujuan agar terciptanya persaingan antar fakultas aspek penilaian. Penelitian yang akan dilakukan denga menggunakan perbandingan hasil penilaian dengan menggunakan metode Smart dan Moora. Hasil keputusan dari masing-masing metode akan dilihat keefektivitasan dalam proses penilaian hingga menjadi sebuah keputusan. Didalam masing-masing metode menggunakan kriteria sama atau berbeda, hal itu tergantung dari pada nilai bobot dari masing-masing kriteria yang dinilai. Hasil ini bisa menjadi acuan bagi Universitas Lancang Kuning dalam mengevaluasi penilaian Fakultas Terbaik berdasarkan aspek penilaian.
Pada penelitian ini menjelaskan tentang Penerapan Decision Support System Dalam Menentukan Dosen Terbaik Prodi PG PAUD Menggunakan Metode AHP. Hasil penelitian ini dapat menjadi rujukan dan rekomendasi untuk dosen terbaik di Program Studi Pendidikan Guru Pendidikan Anak Usia Dini (PG-PAUD) Fakultas Keguruan Ilmu Pendidikan (FKIP) Universitas Lancang Kuning. Terdapat setidaknya ada 5 kriteria yang digunakan pada DSS ini diataranya adalah pendidikan, jabatan fungsional, pangkat / golongan, sertifikasi dosen dan jurnal ilmiah. Seluruh kriteria diambil dari data dosen yang dipublish secara online / daring. Outpun penelitian ini adalah dosen terbaik yang menjadi rekomendasi kepada pimpinan FKIP atau ketua prodi PG PAUD dalam melakukan evaluasi sumber daya. Luaran dari penelitian ini adalah sebuah jurnal yang diterbitkan pada jurnal nasional.
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