To find out the problems faced in the teaching performance assessment process by utilizing the Technique For Order Preference method by Similiarity to Ideal Solution (TOPSIS), to manage the processing of Teacher data is a more optimal consideration. By using the (TOPSIS) method as a basis for processing teacher performance assessment data. This can allow the system to provide an assessment in accordance with the quality of each teacher and is expected to facilitate decision making in the assessment of Teacher's performance. The Technique For Order Preference by similiarity to Ideal Solution has been running well and can result in a weighting of assessment criteria and clear and fast information compared to manual calculations so SD Negeri Kebalen 07 can use it as a tool for making appropriate decisions.
Student academic achievement is a very important matter for all school parties that are directly or indirectly related, especially for Depok Tourism Vocational School, student academic achievement is one of the benchmarks in the success of education. Currently, the process of determining student achievement from the academic side of the Depok Tourism Vocational School is still using a manual system, so it takes a long time to determine the assessment of student academic achievement, because there are quite a lot of student data recording. In addition, it is still less relevant because it has not used the right calculation method, resulting in inaccurate calculations. This research uses the Technique For Order Preference by Similarity to Ideal Solution (TOPSIS) method, because this method is a simple concept and easy to understand and to help the optimal decision-making process to solve practical decision problems. The results of the research using the Technique For Order Preference by Similarity to Ideal Solution (TOPSIS) method found that students with the name Akmal Adnanto got the first rank with the highest preference value of 0.760.
PT. Mayer Indah Indonesia is engaged in the production of goods, where the most important part to prepare the needs for production needs is the purchasing department, but in the purchasing section it is difficult to determine which items must be bought a lot, are and few in meeting the demand requirements of each part because of the needs goods for production are very unpredictable, eventually causing some goods demand not to be fulfilled because the goods are out of stock. To solve the problems experienced by the purchasing part, datamining using clustering algorithm is k-means method, where the initial stages determine the centroid randomly and do the first iteration calculation and determine the new centroid from the first iteration, then the second iteration calculation is done, because the results of the first and second iterations in the smallest layout of the three groups, the calculation stops. The results obtained by using the ink purchase data seen from the three attributes of incoming goods, items purchased and stock of goods, making it easier and help the purchasing department in classifying items that must be purchased a lot, medium and little.
It is an advantage for the bank, in this case, the Bank Mandiri Dramaga1 Bogor Unit, because of the increasing credit activity in banks, it is necessary to have an assessment in credit as consideration for prospective customers before the bank decides to accept or reject a prospective customer request. So it is necessary to develop a method that can assist and facilitate the bank in making decisions quickly and accurately. The basis for decision making is based on the criteria for determining who is eligible or not to receive a loan. To assist in determining whether someone is eligible or not to receive a loan, a decision support system is needed using fuzzy logic and applying the Tsukamoto method. The Lending Decision Support System was created to assist and facilitate the bank in making decisions to provide alternatives if a prospective customer applies for credit is accepted or not.
Credit is the provision of money or equivalent claims, based on agreements or agreements on loans between banks and other parties which require the borrowing party to repay the debt after a certain period of time with the amount of interest, compensation or profit sharing. From the credit customer data available at BSM KCP Kemang Pratama still has Non Performing Financing (NPF) or Bad Credit.In analyzing a credit sometimes an analyst does an inaccurate analysis, so there are some customers who are less able to make credit payments, resulting in bad credit. So the researchers conducted an analysis using the C4.5 decision tree algorithm and Rapid Miner application for determining credit worthiness. From the analysis of credit customer data using the C4.5 decision tree algorithm method, the feasibility of credit recipient customers is very effective and produces a value of accuracy on Rapid Miner 5.3 of 80%, Precision of 100% and Recall of 0% so as to minimize the risk.Abstrak -Kredit merupakan penyediaan uang atau tagihan yang dapat disamakan dengan hal itu, berdasarkan persetujuan atau kesepakatan pinjaman-pinjaman antara bank dengan pihak lain yang mewajibkan pihak peminjam untuk melunasi utangnya setelah jangka waktu tertentu dengan jumlah bunga, imbalan atau pembagian hasil keuntungan. Dari data nasabah kredit yang ada pada BSM KCP Kemang Pratama masih memiliki Non Performing Financing (NPF) atau Kredit Macet. Dalam menganalisa sebuah kredit terkadang seorang analis melakukan analisa tidak akurat, sehingga ada beberapa nasabah yang kurang mampu dalam melakukan pembayaran kredit, dan pada akhirnya mengakibatkan kredit macet. Peneliti melakukan analisis menggunakan algoritma decision tree C4.5 dan aplikasi Rapid Miner untuk penentuan kelayakan pemberian kredit. Dari analisis data nasabah kredit menggunakan metode Algoritma decision tree C4.5 menghasilkan kelayakan nasabah penerima kredit sangat efektif dan menghasilkan nilai akurasi pada Rapid Miner 5.3 sebesar 80%, Precision sebesar 100% dan Recall sebesar 0% sehingga dapat meminimalisir resiko yang terjadi. Kata kunci-Kredit, Algoritma C4.5, Rapid Miner, Nilai Akurasi
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