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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknologi Informatika dan Komputer Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan SIGMA: Information Technology Journal Journal of Practical Computer Science (JPCS) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Agung Nugroho
Universitas Pelita Bangsa
Aerospace Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Journal : SIGMA: Information Technology Journal

 1 
Sistem Pakar Corrective Bay Penghantar Gardu Induk Mekarsari Karawang Dengan Metode Forward Chaining Agung Nugroho
Jurnal SIGMA Vol 12 No 2 (2021): Juni 2021
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

The need for electrical and technological energy at this time has grown so rapidly that electrical energy becomes one of the main needs in life. In the course of the substation itself in distributing power supply many disturbances that sometimes disrupt the distribution of electricity in factors such as equipment age and external factors such as lightning and so on. So in need of a system that can help in overcoming the disruption that occurred. The research method used is Quesioner methodology, Interview or Q & A, analysis which includes making flowcharts, and in system design include making State Transition Diagram (STD) and proposed proposal system design (Msukan Design, Process and Output). This study contains about the design of expert systems to find a solution of the disturbances that occur in the bay Deliver by diagnosing the symptoms that arise on the substation. This system is a new system design that is used to find the right disturbance solution, fast, and efficient. The author in this case designed the system by mengguanakan forward chaining method as for this application is made with PHP programming language and using MySQL Database. With this expert system is expected to mengefisiensikan various things such as communication, time and so forth in handling disruptions that occur. Keywords: Expert System, Disturbance, Indication
Mencegah Kredit Macet Dengan Analisa Kelayakan Pembiayaan Dengan Metode C4.5 Dan Naïve Bayes (Studi Kasus : Koperasi BMT UGT Sidogiri Cabang Cikarang) Agung Nugroho
Jurnal SIGMA Vol 11 No 2 (2020): Juni 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

The progress of the growth of MSMEs (Micro, Small and Medium Enterprises) in Indonesia from time to time which is increasingly rapid, resulting in an increase in the need for capital to develop their business. This is evidenced by the increasing number of credit or financing withdrawals from savings and loan cooperatives and BPRs (Rural Banks). The problem faced by savings and loan cooperatives, BPRs, or other financial institutions at this time in providing credit is the risk of late payments, repayments and even failure of credit payments. This problem occurs due to credit misuse and weak supervision both in the process of providing credit and in the implementation stage. The right solution to solve existing problems is by using data mining algorithms. The concept of data mining will make it easier to solve problems that are not optimal in cooperatives, the classification method is able to find models that differentiate concepts or data classes with the aim of making it easier to predict creditworthiness. The Naive Bayes algorithm and the C4.5 algorithm are considered to be able to predict future opportunities based on previous experiences. The author conducted research on the BMT UGT Sidogiri Cooperative with the title "Preventing bad credit by analyzing the feasibility of financing with the Naive Bayes and C4.5 methods". In this study the authors used 9 attributes as an assessment, namely: name, residence status, financing contract, income, ceiling, term of repayment, number of dependents, collateral. Testing is done using 520 data and 104 randomly selected testing data. From the results of tests carried out using Rapid Miner tools, it can be concluded that the accuracy level of the C4.5 algorithm is more accurate at 81.35%, while the Naive Bayes algorithm is 78.85%. Keywords : Credits, Classification, Accuracy, Naive Bayes, C4.5.
Sistem Pendukung Keputusan Pemilihan Hotel Di Jakarta Dengan Menggunakan Algoritma Naïve Bayes Agung Nugroho; Agus Safarudin
Jurnal SIGMA Vol 10 No 3 (2019): September 2019
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Jakarta has a nickname of a metropolitan city, but many residents are still confused about choosing a place to stay or just stop by as a place to rest. To determine the decision, the writer implements the Naïve Bayes algorithm. So that with the decision support system using the Naïve Bayes algorithm the writer can be sure and made easier in determining hotel selection in Jakarta. Keywords: Sistem Pendukung keputusan, Decision Support System, Naïve Bayes
Co-Authors Agus Safarudin Ahmad Rivaldi Ahmad Santoso Ahmad Turmudi Zy Ari Maulana Aswan S Sunge Aswan Supriyadi Sunge Donny Maulana Elkin Rilvani Ikhsan Romli Irfan Afriantoro Jamaludin Jamaludin Londong, Riko Reky Rusdi, Adi Septiawan Dwi Pramukti Supriadi, Asmadi Wahyu Hadikristanto Yoga Religia