Penerapan Kombinasi Metode Simple Additive Weighting (SAW) dan Rank Order Centroid (ROC) dalam Keputusan Pemberian Kredit

Silvilestari, Silvilestari

doi:10.30865/mib.v3i4.1509

Cited by 9 publications

(8 citation statements)

References 4 publications

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“…Peminjaman merupakan proses yang sangat penting bagi manajer kredit. Salah memilih penerima pinjaman akan mengakibatkan tagihan pinjaman tidak terbayar [11]. untuk menghindari itu, diperlukan suatu analisis data calon kreditu untuk menentukan apakah pinjaman layak atau tidak dan mengklasifikasikannya [7].…”

Section: A Pendahuluanunclassified

Optimalisasi Metode Naive Bayes Classifier Untuk Prediksi Persetujuan Kredit

Syakur,

Purwandi Putra,

Juliane

2024

ijcs

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Kredit adalah bentuk pembiayaan yang banyak orang ajukan ke bank atau perusahaan penyedia kredit. Dalam proses pengajuan kredit, dilakukan analisis untuk menentukan apakah kredit yang diajukan layak atau tidak. Penelitian ini bertujuan untuk membantu bank atau perusahaan penyedia kredit dalam melakukan persetujuan kredit dengan efektif dan akurat dalam menentukan status pengajuan. Penelitian ini menggunakan teknik data mining dan kumpulan dataset yang berasal dari kaggle.com. Terdapat 12 atribut dan 2 kelas yang digunakan dalam penelitian ini. Dalam penelitian ini, metode klasifikasi Naive Bayes dan optimasi kelompok partikel (PSO) digunakan. Prediksi persetujuan kredit dengan metode naïve bayes classifier menghasilkan nilai akurasi sebesar 80,00% dengan nilai AUC 0,884. Sebaliknya, prediksi persetujuan kredit dengan metode particle swarm optimization (PSO) menghasilkan nilai akurasi sebesar 96,67% dengan nilai AUC 0,69.

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Section: A Pendahuluanunclassified

Optimalisasi Metode Naive Bayes Classifier Untuk Prediksi Persetujuan Kredit

Syakur,

Purwandi Putra,

Juliane

2024

ijcs

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“…Saat memilih waitress restoran terbaik, pendekatan ROC adalah salah satu metode yang diterapkan guna menimbang setiap faktor. Berdasarkan tingkat prioritas masing-masing kriteria dilakukan pembobotan dengan menggunakan pendekatan ROC [31]. Standar yang digunakan untuk memilih pelayan restoran terbaik tercantum dalam Tabel 2.…”

Section: Penerapan Bobot Menggunakan Metode Rank Order Centroidunclassified

Pemilihan Waitress Resto Akul Terbaik Menerapkan Metode WASPAS dengan Pembobotan ROC

Soleha

Aldisa

Abdullah

2023

josh

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The restaurant is an area that serves culinary delights for public consumption and also has various services to make customers feel at home while eating. One of the factors that determines the success of a restaurant in the food industry is the quality of the waitress service. An employee who serves customers in a restaurant, cafe, dining room or hotel is known as a waitress. These are the people who will approach a client as they walk in to take their order, give them a menu, and be available if they need more. Because it generates data that can be used for administrative decisions such as promotion, training, awards and other assessments, selecting the best restaurant waiter is a very important process in management. The obstacle in choosing the best restaurant waitress is the difficulty for restaurant management to make decisions regarding the best restaurant waitress because of the large amount of data which results in a long processing time. The Weighted Aggregated Sum Product Assessment (WASPAS) approach and the Rank Order Centroid (ROC) weighting method are the two methods used in this study to apply a decision support system to the challenge of selecting the best restaurant waiter. In this study, a number of factors, including appearance, responsibility, discipline, teamwork, high initiative, and multitasking skills, were taken into consideration in selecting the best restaurant servers. The W8 alternative, Ratih Setyowati with a value of 0.9341, which has the right to be chosen as the best restaurant waitress, is the result of a ranking to choose the best restaurant waitress with the highest preference after applying the WASPAS method and ROC weighting.

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“…Berikut ada beberapa artikel terkait yaitu penelitian yang dilakukan oleh Silvi Lestari dkk (2019) tentang keputusan pemberian kredit menggunakan Metode SAW dengan hasil 0.69 diperoleh alternatif A 8 sebagai alternatif terbaik [9]. Penelitian lain dilakukan oleh Nursobah pada tahun 2021 mengenai pemilihan Perguruan tinngi Swasta di Kalimantan Timur dengan metode PSI [10].…”

Section: Pendahuluanunclassified

Optimalisasi Penerapan Metode TOPSIS dalam Penentuan Dosen Berprestasi

Purba,

Sitorus,

Syahrizal

2023

jieee

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The role of lecturers, especially for students, really determines the quality of the students themselves. Therefore, to create a quality future generation, qualified lecturers are also needed. However, currently there are many lecturers who only work as lecturers, but do not meet the criteria for a good lecturer. Giving awards to lecturers who excel is one of the efforts that can be done in order to create work motivation and increase the desire of every lecturer to become a lecturer who has good qualifications. However, the problem is to determine the best lecturers in a university, it will be very difficult if done manually. To make it easier for leaders to assess lecturers who deserve to be called achievers or not, a decision support system (SPK) is needed, where this SPK acts as a support for the leadership's reasons why the leader chooses someone as an outstanding lecturer. Decision Support System (DSS) is a system whose work uses a computer, where this system uses various methods which ultimately produce information in the form of a decision. the method used in this study is the TOPSIS method. The TOPSIS method is one of the DSS methods whose purpose is to produce an alternative with the highest value as an alternative recommendation. The results obtained in this study amounted to 0.5308 on behalf of Mesran as an alternative recommendation.

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Penerapan Kombinasi Metode Simple Additive Weighting (SAW) dan Rank Order Centroid (ROC) dalam Keputusan Pemberian Kredit

Cited by 9 publications

References 4 publications

Optimalisasi Metode Naive Bayes Classifier Untuk Prediksi Persetujuan Kredit

Optimalisasi Metode Naive Bayes Classifier Untuk Prediksi Persetujuan Kredit

Pemilihan Waitress Resto Akul Terbaik Menerapkan Metode WASPAS dengan Pembobotan ROC

Optimalisasi Penerapan Metode TOPSIS dalam Penentuan Dosen Berprestasi

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