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Analysis of Weight Product (WP) Algorithms in the best Go Car Driver Recommendations at PT. Maranatha Putri Bersaudara Kurniawan, Roni; Windarto, Agus Perdana; Fauzan, M; Solikhun, Solikhun; Damanik, Irfan Sudahri
IJISTECH (International Journal of Information System & Technology) Vol 3, No 1 (2019): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (285.5 KB) | DOI: 10.30645/ijistech.v3i1.28

Abstract

This study aims to rank the best Go Car Driver. The problem arises because of the inaccuracy in giving value to the driver which results in the decision being given incorrectly so that the assessment tends to be subjective. This research was conducted at PT. Maranatha Putri Bersaudara. Sources of data obtained by observing, interviewing. The settlement method used is a decision support system with the Weight Producted method. The assessment criteria used are Performance (C1), Number of orders (C2), Rating (C3), Attitude (C4), Rating (C5) and Appearance (C6) where the alternatives used are 4 samples. The results obtained using the Weighted Product method are Alternative1 and Alternative4 which are recommended as the best go car driver with the assessment results of 0.0307 and 0.0272. It is expected that research results can be input to the relevant parties in recommending the best go car driver so as to minimize subjective judgment.
Peningkatan Nilai Akurasi Prediksi Algortima Backpropogation (Kasus: Jumlah Pengunjung Tamu pada Hotel berbintang di Sumatera Utara) Syahfitri, Devi; Windarto, Agus Perdana; Fauzan, M; Solikhun, S
Journal of Information System Research (JOSH) Vol 2 No 1 (2020): Oktober 2020
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

The research objective is to analyze and test whether the number of foreign tourist arrivals in Indonesia can be predicted using artificial intelligence techniques. The research data were obtained from the Indonesian Central Bureau of Statistics for the tourism category. The data used in the study is data on the number of tourist visits from 2003 - 2018. The artificial intelligence technique used in this study is the artificial neural network technique using the backpropagation method. The study will explore backpropagation parameters such as learning rate and network architecture where the results of the study are expected to help provide information for decision-makers to attract more foreign tourists to Indonesia because this has an impact on improving the economy in Indonesia. The research results show that from 4 architectural models tested (7-2-1, 7-5-1, 7-10-1 and 7-2-10-1) with a learning rate of 0.1; 0.01; 0.001; 0.2; 0.02; 0.002; 0.3; 0.03; and 0.003 where the 7-10-1 model with learning rate = 0.02 is obtained which is the best prediction model with the Root Mean Squared Error is 0.094 and the relative error is 4.49% +/- 10.21%. The accuracy of the truth obtained is 96%.
Sistem Pakar dengan Proses Forward Chaining pada Kulit Wajah Berminyak Syahputri, Indah; Windarto, Agus Perdana; Suhendro, Dedi; Irawan, Eka; Fauzan, M
Journal of Information System Research (JOSH) Vol 2 No 1 (2020): Oktober 2020
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

The research objective was to analyze oily facial skin using the forward chaining method and to build an expert system application that was able to provide accurate information about oily facial skin. Sources of data obtained by interviewing the owner of the House of Beauty who resides on Jl. Adam Malik, Pematangsiantar. The implementation of the expert system is a web application. The results showed that the system could be applied and analyzed oily facial skin using the forward chaining method, which was caused by various kinds of symptoms that attack everyone's facial skin, especially oily facial skin disease, based on the symptoms displayed by the user so that the expert system application could provide information about definition, treatment, and prevention, so as to help users in symptomatic symptoms and types of disease based on the symptoms that appear by the user.
Prediksi Jumlah Hasil Panen Sawit Menggunakan Algoritma Naive Bayes Ananda, Wahyu; Safii, M; Fauzan, M
TIN: Terapan Informatika Nusantara Vol 1 No 10 (2021): Maret 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Tujuan dari penelitian adalah untuk memprediksi jumlah hasil panen sawit dan memberikan masukan kepada pihak PTPN IV Dolok Sinumbah untuk lebih memperhatikan upaya dalam menghasilkan jumlah hasil panen sawit yang lebih meningkat setiap tahunnya. Untuk memprediksi jumlah hasil panen sawit metode yang digunakan algoritma Naive Bayes. Sumber data penelitian diperoleh dengan langsung dari instansi terkait. Sehingga diharapkan penelitian ini dapat membantu pihak pimpinan perusahaan dalam memprediksi meningkat atau menurunya produksi hasil sawit. Berdasarkan hasil penelitian yang dilakukan penulis menggunakan metode Naive Bayes pada prediksi meningkat secara manual menghasilkan nilai 7 record. Sedangkan Jumlah prediksi menurun secara manual menghasilkan nilai 5 record. Sehingga total Accuracy yang diperoleh sebesar 100%.
DETERMINATION OF EMPLOYEE JOB SATISFACTION PT BANK SYARIAH MANDIRI widya, ira; rasyid, arbanur; wandisyah, muhammad; fauzan, m
Journal Of Sharia Banking Vol 2, No 1 (2021)
Publisher : http://jurnal.iain-padangsidimpuan.ac.id/index.php/jsbanking/index

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Abstract

Fluctuations that occur in the number of employees at PT Bank Syariah Mandiri Gunung Tua Sub-Branch Office, which indicates employee dissatisfaction. The fluctuation that occurred was caused by several employees who applied for resignation for several reasons as well as employee dismissal due to not achieving the target. The formulation of the problem in this study is whether the influence of work environment, competence, and career development has an influence on employee job satisfaction. The aim is to determine whether there is an influence of these three variables on employee job satisfaction at PT Bank Syariah Mandiri Gunung Tua Sub-Branch Office. This research is a quantitative study with sampling using saturated samples with a sample size of 17. The data collection technique uses literature study, interviews, documentation and questionnaires. Data analysis techniques include instrument test (validity test, reliability test), classic assumption test (normality test, multicollinearity test, heteroscedasticity test), multiple linear regression analysis, hypothesis testing (determination coefficient test (R2), t test, F test). To simplify the data analysis process, this research was assisted by the SPSS version 23 program. The results of the t test showed that there was no influence of the work environment on employee job satisfaction, there was no influence between competence on employee job satisfaction, and there was an influence between career development on employee job satisfaction. Simultaneously there is an influence between work environment, competence, and career development on employee job satisfaction.