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Jusak Irawan
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Rancang Bangun Sistem Pakar Diagnosis Penyakit Pada Sekitar Rahim Wanita Choirul Bariyah; Jusak Irawan; A.B Tjandrarini
Jurnal Sistem Informasi dan Komputerisasi Akuntansi (JSIKA) Vol 4, No 2 (2015)
Publisher : Jurnal Sistem Informasi Universitas Dinamika

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Abstract

The diseases around the woman's uterus is a fatal disease and causing death. But a lot of people underestimate the symptoms. The type of disease around the woman’s uterus have similar symptoms, it is difficult to know the type of disease that patients suffered. Therefore, patients need a doctor to consult about the disease around the woman's uterus. However, Patients often have trouble to consult a doctor because of limited working hours and cost limitations. In order to provide convenience consultation process, in this work, we build an expert system for diagnosing diseases around woman’s uterus using the certainty factor metho. The expert systems will diagnose any symptoms by providing certainty factor values at each symptom and the certainty factor value of answers. The new system will produce diagnosed diseases based on the some facts given by a user. The trial results showed that the system give accuracy diagnosis of 90%. It is examined by employing ten patients. This system also provide treatment advice based on the type of disease that suffered. However, the expert system for diagnosis of disease the woman's uterus can be accessed anytime and anywhere via website. 
RANCANG BANGUN APLIKASI PERAMALAN PENJUALAN MENGGUNAKAN METODE IMPROVED ELMAN (STUDI KASUS: UD DWI MULYA PLASTIK SIDOARJO) Chrisyanti Simbolon; Jusak Irawan; Tegar Heru Susilo
Jurnal Sistem Informasi dan Komputerisasi Akuntansi (JSIKA) Vol 5, No 7 (2016)
Publisher : Jurnal Sistem Informasi Universitas Dinamika

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Abstract

UD Dwi Mulya Plastik is a company that produces plastic ore based house appliances. To fulfill customer’s demand, it requires sales forecasting so it can reduce the risk of over production or under production. The sales is represented as time-series data. In this work, we utilized an Artificial Neural Network method that commonly called Improved Elman method to do forecasting of the time-series data. Based on our examination, it is shown that the smallest value of averaged MSE (0,29) as well as MAPE (12,69%) for ‘timba cor’ can be achieved by using learning rate of 0,50 and the number of input data 12. On the other hand, the smallest value of averaged MSE (0,011) as well as MAPE (15,23%) for ‘waskom’ can be achieved by using learning rate of 0,30 and the number of input data 12. It is commonly understood that the maximum value of MAPE to be categorized as good forecasting is 20%, hence, it is concluded that the Improved Elman method in this study is considered valid.
Rancang Bangun Sistem Pakar Identifikasi Penyakit Gigi Berbasis Web Dengan Menggunakan Metode Certainty Factor Mochammad Irfan; Jusak Irawan; Tania saskianti
Jurnal Sistem Informasi dan Komputerisasi Akuntansi (JSIKA) Vol 4, No 2 (2015)
Publisher : Jurnal Sistem Informasi Universitas Dinamika

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Abstract

This research is motivated by common dental diseases that are present among people. it is evident that people will visit dentist only when they experience serious problems with their teeth, this mainly because a lack of understanding against the dental disease and also expensive charge of dental checkup. therefore, in this study we build an application for diagnosing common dental disease. a web-based application that is available to be accessed freely. The purpose of this study is to build a expert system for identifying dental disease.The expert system utilized the certainty factor method as the inference engine. The reason behind this is  because this method is able to produce alternatives diagnosis (the output of the system comprises of some diagnosis results). It can be seen that certainty factor method is very suitable for expert system problem solving for disease diagnosis. This research was done by way of anamnesis process (giving a question to the user). The system produces a possibility of the diseases as well as causative factor and handling factor.This work has been tested by an expert using 30 times experiment. Based on our examination some result were obtained as follows: Firstly, the system gives similar results in reference  to the expert judgment of disease. Secondly, the system gives possibilities of the disease when we considered confidence level above 80%. Thirdly, the results were considered invalid when the diagnosis of the system didn’t match with the expert judgment
Co-Authors A. B. Tjandrarini Abd. Rasyid Syamsuri Chrisyanti Simbolon Mochammad Irfan Tania Saskianti Tegar Heru Susilo