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All Journal Bulletin of Multi-Disciplinary Science and Applied Technology
Budi Serasi Ginting
STMIK Kaputama, Binjai
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Other

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Sistem Pakar Diagnosa Penyakit Kelapa Sawit Dengan Menggunakan Metode Certainty Factor Hidayatullah Hidayatullah; Budi Serasi Ginting; Achmad Fauzi
Bulletin of Multi-Disciplinary Science and Applied Technology Vol 1 No 5 (2022): Agustus 2022
Publisher : Forum Kerja Sama Penddikan Tinggi (FKPT)

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Abstract

Computer development is very important in information notification and data processing, computer development can also play a role in analyzing the symptoms of problems that occur. Oil palm plantations are currently growing in Indonesia and almost all of oil palm is grown throughout the archipelago. Oil palm plants are very beneficial for humans because oil palm fruit as a palm oil-producing plant and palm kernel is one of the prima donna of plantation crops which is a source of non-oil and gas foreign exchange for Indonesia. Because of the importance of oil palm resulting in increased production. However, there is an imbalance in the production of oil palm fruit due to the lack of understanding of the farmers to overcome the diseases that attack oil palm plants. It takes an expert system that will incorporate all expert knowledge in a system so that it can diagnose diseases in oil palm anytime and anywhere. The Certainty factor (CF) method is a method to prove whether a fact is certain or uncertain in the form of a metric that is usually used in expert systems. This method is very suitable for expert systems that diagnose something that is not certain. Based on the results of the CF calculation, the highest value was in the type of palm root rot disease with a value of 97.29%. From the results obtained, the system diagnoses the oil palm tree diagnosed with palm root rot disease.
Data Mining Pengelompokan Pengajuan Kredit Pensiun Pada Bank Sumut Menggunakan Metode Clustering (Studi Kasus : PT. Bank Sumut Cabang Binjai) Alma Alawiyah Gultom; Budi Serasi Ginting; Magdalena Simanjuntak
Bulletin of Multi-Disciplinary Science and Applied Technology Vol 1 No 6 (2022): Oktober 2022
Publisher : Forum Kerja Sama Penddikan Tinggi (FKPT)

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Abstract

PT. Bank SUMUT Binjai branch is one of the financial institutions that provides several products offered to retirees such as retirement savings and pension loans. Most of the information is only seen as archives that are not used and can be destroyed at any time. This is a wrong view, because with proper and clever handling, these data can be processed and manipulated by data mining, so that later they can be used to produce useful information in making a decision. Data mining can help companies explore new knowledge by processing existing data with clustering methods and using the K-Means algorithm. From the credit application data, several criteria/variables will be taken, including the basic salary variables, allowances and loan guarantees (collateral) used. The data is processed with the Matlab program to produce a cluster center and the relationship between variables is obtained by the group with the highest value. The use of data mining techniques is expected to provide knowledge that was previously hidden in the data warehouse so that it becomes valuable information. The calculation that has been done is that the number of members of group 1 is 141 data, the number of members of group 2 is 90 data and the number of members of group 3 is 148 data. With the results centroid 1: 2.5319, 1, 1.5319, centroid 2: 5.2222, 3.5556, 1.9889 and centroid 3: 4,3286,1.8295, 2.1818.
Co-Authors Alma Alawiyah Gultom Fauzi, Achmad Hidayatullah Hidayatullah magdalena simanjuntak