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ANALISIS DALAM MENENTUKAN PRODUK BRI SYARIAH TERBAIK BERDASARKAN DANA PIHAK KETIGA MENGGUNAKAN AHP Putrama Alkhairi; Agus Perdana Windarto
CESS (Journal of Computer Engineering, System and Science) Vol 3, No 1 (2018): Januari 2018
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (593.568 KB)

Salah satu tujuan Bank BRI Syariah membuat layanan produk-produk dan jasa unggulan adalah untuk menghasilkan kegiatan perbankan yang berkualitas dan menunjang pelaksanan ekonomi dab stabilitas nasional ke arah peningkatan kesejahteraan masyrakat banyak. Banyak asumsi dan pendapat dari sejumlah kalangan tentang produk mana yang terbaik yang di keluarkan oleh BRI Syariah. Banyak kriteria dari produk - produk yang dapat dijadikan parameter sebagai kunci menjadi produk unggulan. Penelitian ini membahas tentang metode pengambilan keputusan di antara sekian banyak pilihan dengan menggunakan metode AHP (analytic hierarchy process). Model kasus yang digunakan adalah menentukan produk mana yang terbaik dri produk BRI Syariah berdasarkan Dana Pihak Ketiga. Penelitian menggunakan dua komponen komparasi yakni data riil BRI Syariah dan Observasi langsung, serta tiga kriteria yakni masalah Setoran awal, Biaya penutupan, dan Prospek fasilitas. Hasil dari penelitian ini menenujukan bahawa perhitungan yang dilakukan secara manual mampu memberikan perangkingan alternatif dari hasil perhitungan bobot nilai produk sesuai dengan metode (AHP). Dari hasil pengujian Tabungan Faedah BRI Syariah menunjukan yang menjadi produk BRI Syariah terbaik berdasarkan Dana Pihak Ketiga dengan nilai angka konsistensi eigen vektor 0,32201 yang lebih besar dari pada 0,19889 sebagai tempat kedua terbaik.

Penerapan Data Mining Untuk Menganalisis Kepuasan Pegawai Terhadap Pelayanan Bidang SDM dengan Algoritma C4.5 Putrama Alkhairi; Zakarias Situmorang
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 7, No 1 (2022): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v7i1.414

Employee satisfaction includes the difference between the level of importance and perceived performance or results, and is an alternative evaluation that exceeds employee expectations. There are 5 dimensions to measure service quality based on expectations and perceived performance by employees, namely career development, leadership in HR, policy and law enforcement, building a work atmosphere and providing salaries and rewards. Five dimensions are very influential in the progress of STIKOM Tunas Bangsa, using data mining methods can be found important trends for campuses. Employee satisfaction assessment is based on a questionnaire filled out by the employee. The results of the questionnaire were processed using the c4.5 algorithm. The c4.5 algorithm is a classification method and produces a decision tree. C4.5 turns large facts into decision trees that represent rules. Rules are easy to understand in natural language. Based on the results of the research that has been done, the use of the C4.5 algorithm can help the campus in improving services according to the results of the questionnaire. The results of the calculation, there are two variables satisfied employee questionnaire. Meanwhile, the employee questionnaire was not satisfied with the three variables. The highest gain value is the variable to build a work atmosphere with a value of 0.20619372. The indicator of the variable of building a work atmosphere that has the highest entropy value is a fairly good indicator with a value of 1. The total of questionnaires filled in are 65 questionnaires, 44 people stated they were satisfied and only 21 people said they were not satisfied.

Penerapan Data Mining Untuk Menganalisis Kepuasan Pegawai Terhadap Pelayanan Bidang SDM dengan Algoritma C4.5 Putrama Alkhairi; Zakarias Situmorang
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 7, No 1 (2022): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v7i1.414

Employee satisfaction includes the difference between the level of importance and perceived performance or results, and is an alternative evaluation that exceeds employee expectations. There are 5 dimensions to measure service quality based on expectations and perceived performance by employees, namely career development, leadership in HR, policy and law enforcement, building a work atmosphere and providing salaries and rewards. Five dimensions are very influential in the progress of STIKOM Tunas Bangsa, using data mining methods can be found important trends for campuses. Employee satisfaction assessment is based on a questionnaire filled out by the employee. The results of the questionnaire were processed using the c4.5 algorithm. The c4.5 algorithm is a classification method and produces a decision tree. C4.5 turns large facts into decision trees that represent rules. Rules are easy to understand in natural language. Based on the results of the research that has been done, the use of the C4.5 algorithm can help the campus in improving services according to the results of the questionnaire. The results of the calculation, there are two variables satisfied employee questionnaire. Meanwhile, the employee questionnaire was not satisfied with the three variables. The highest gain value is the variable to build a work atmosphere with a value of 0.20619372. The indicator of the variable of building a work atmosphere that has the highest entropy value is a fairly good indicator with a value of 1. The total of questionnaires filled in are 65 questionnaires, 44 people stated they were satisfied and only 21 people said they were not satisfied.

PENGENALAN POLA KEMAMPUAN PELANGGAN DALAM MEMBAYAR AIR PDAM MENGGUNAKAN ALGORITMA NAÏVE BAYES P.P.P.A.N.W. Fikrul Ilmi R.H. Zer; Ela Roza Batubara; Putrama Alkhairi; Fazli Nugraha Tambunan; Rika Rosnelly
Jurnal TIMES Vol 10 No 2 (2021): Jurnal TIMES
Publisher : STMIK TIME

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (828.686 KB)

Dengan meningkatnya jumlah MBR (Masyarakat Berpenghasilan Rendah) yang masuk setiap tahunnya dimasing-masing wilayah di Pematansgsiantar, pihak PDAM Tirta Lihou berencana mencari alternatif solusi dalam menangani permasalahan kemampuan pelanggan dalam membayar tagihan air sehingga biaya opersional tetap bisa berjalan baik dan produksi dapat memenuhi kebutuhan masyarakat. Dalam menentukan alternatif untuk menentukan kemampauan masyarakat dalam membayar tagiahan air digunakan metode datamining. Dengan menggunakan teknik datamining khususnya klasifikasi menggunakan algoritma Naive Bayes dapat dilakukan prediksi terhadap kemampauan pelanggan dalam membayar tagihan air bersih berdasarkan data yang ada. Naive bayes adalah teknik prediksi probabilistik sederhana yang berdasarkan pada teorema Bayes dengan asumsi independensi (ketidak tergantungan) yang kuat. Berdasarkan hasil dari perhitungan menggunakan algoritma Naive Bayes, diperoleh hasil klasifikasi dari 30 alternatif yang digunakan, dimana terdapat 11 kelas mampu membayar tagihan dan 19 Tidak Mampu dengan total Accuracy yang diperoleh sebesar 70%. Dari hasil yang diperoleh,diharapkan penelitian ini dapat membantu pihak PDAM Tirta Lihou dalam menentukan lokasi yang layak dilakukan penaybungan sumber air untuk pelanggan yang memiliki prosfek baik dengan kemampuan untuk membayar tagihan air, sehingga dapat meminimalisir kerugian PDAM dan dapat memenuhi kebutuhan masyarakat. Penelitian ini juga diharapkan dapat menjadi referensi bagi peneliti selanjutnya yang berkaitan dengan pengguna algoritma yang digunakan.

Effect Effect of Gradient Descent With Momentum Backpropagation Training Function in Detecting Alphabet Letters Putrama Alkhairi; Ela Roza Batubara; Rika Rosnelly; W Wanayaumini; Heru Satria Tambunan
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2023): Articles Research Volume 8 Issue 1, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i1.12183

The research uses the Momentum Backpropagation Neural Network method to recognize characters from a letter image. But before that, the letter image will be converted into a binary image. The binary image is then segmented to isolate the characters to be recognized. Finally, the dimension of the segmented image will be reduced using Haar Wavelet. One of the weaknesses of computer systems compared to humans is recognizing character patterns if not using supporting methods. Artificial Neural Network (ANN) is a method or concept that takes the human nervous system. In ANN, there are several methods used to train computers that are made, training is used to increase the accuracy or ability of computers to recognize patterns. One of the ANN algorithms used to train and detect an image is backpropagation. With the Artificial Neural Network (ANN) method, the algorithm can produce a system that can recognize the character pattern of handwritten letters well which can make it easier for humans to recognize patterns from letters that are difficult to read due to various error factors seen by humans. The results of the testing process using the Backpropagation algorithm reached 100% with a total of 90 trained data. The test results of the test data reached 100% of the 90 test data.

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