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<![CDATA[Sistem Pakar Diagnosa Penyakit Mata Menggunakan Metode Certainty Factor Berbasis Android ]]>
<![CDATA[Yogi Permana]]>;
<![CDATA[I Gede Pasek Suta Wijaya]]>;
<![CDATA[Fitri Bimantoro]]>
<![CDATA[ Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 1 No 1 (2017): Desember 2017 ]]>
Publisher : <![CDATA[Informatics Engineering Dept., Faculty of Engineering, University of Mataram ]]>
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DOI: 10.29303/jcosine.v1i1.11
<![CDATA[This entitled of research "Expert System Diagnosis Eye Diseases Using MethodCertainty Factor Based Android" is proposed due to the increased spread eye diseases thatis leads to blindness in Indonesia it is happened because of the limited facilities of eyehealth services in health centers and hospitals, as well as lack of eye doctor who canexamine the eye, making eye left untreated and can cause serious damage to the eye.Therefore, many people are already suffering from the early symptoms of blindnessletting untreated without properly treatment. The purpose of this study is to develop anexpert system that is capable of providing information about eye diseases along withsuggested solutions of the disease suffered by imitating the analysis of an eye doctor.The system is built using certainty factor method which is an algorithm that isimprove the uncertainty idea of an expert. This method is used to describe the level ofconfidence of experts on issues being addressed. This system is built by Ionic frameworkfor Android applications with PHP, HTML5 and AngularJS.The system is able to provide information about eye diseases through the processof diagnosis, that can be used for early treatment of eye diseases. The whole function ofthis expert system application already worked properly without any mistakes. Anddiagnostics accuracy rate of the system is 75% in the diagnosis process of 15 diseases and52 symptoms.]]>
<![CDATA[Steganografi Menggunakan Metode Pencocokan LSB dan Karakter Non-Breaking Space Sebagai Penanda Pesan ]]>
<![CDATA[Ulil Amri]]>;
<![CDATA[I Gede Pasek Suta Wijaya]]>;
<![CDATA[Fitri Bimantoro]]>
<![CDATA[ Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 1 No 1 (2017): Desember 2017 ]]>
Publisher : <![CDATA[Informatics Engineering Dept., Faculty of Engineering, University of Mataram ]]>
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DOI: 10.29303/jcosine.v1i1.18
<![CDATA[Keamanan sebuah informasi dalam sebuah jalur komunikasi merupakan salah satu aspek penting. Steganografi adalah salah satu metode yang digunakan untuk mengamankan suatu informasi. Tujuan penelitian ini adalah untuk mengembangkan metode steganografi yang baik digunakan pada media teks. Dalam penelitian ini, teknik yang digunakan untuk menyisipkan pesan rahasia pada media teks adalah dengan melakukan pencocokan LSB (Least Significant Bit) dan menggunakan karakter non-breaking space sebagai penanda pesan. Untuk mengevaluasi kualitas file teks hasil steganografi dilakukan pengujian nilai Peak Signal to Noise Rasio (PSNR), perhitungan skor Jaro-Winkler distance, pengujian dengan angket kuesioner, dan perhitungan nilai rasio kapasitas. Hasil pengujian memberikan nilai PSNR dengan selisih yang kecil, skor Jaro-Winkler distance dengan skor rata-rata lebih dari 0,8, nilai rata-rata Mean Opinion Score (MOS) 2,36 dan 1,79 untuk setiap parameter uji, dan nilai rasio kapasitas yang dihasilkan kurang dari 1%. Oleh karena itu, metode ini memiliki kemampuan yang cukup baik dalam menyembunyikan pesan tetapi memiliki daya tampung yang tergolong kecil]]>
<![CDATA[Pengenalan Wajah Untuk Sistem Kehadiran Menggunakan Metode Eigenface dan Euclidean Distance ]]>
<![CDATA[Fahmi Syuhada]]>;
<![CDATA[I Gede Pasek Suta Wijaya]]>;
<![CDATA[Fitri Bimantoro]]>
<![CDATA[ Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 2 No 1 (2018): Juni 2018 ]]>
Publisher : <![CDATA[Informatics Engineering Dept., Faculty of Engineering, University of Mataram ]]>
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DOI: 10.29303/jcosine.v2i1.74
<![CDATA[he development of Information Technology allows faces that are one part of identity that has been widely be used as biometric based security system. This research is a process of designing and making of identification system which is able to detect of human attended. This system implements: viola-jones, eigenface and euclidean distance methods. Viola-jones method is employed as face detection. Eigenface method is used to reduce the face image and to get the weight value. The euclidean distance is impemented as a classification method. The accuracy of this system against 30 register subjects and 15 unregistered subjects is 84%. This accuracy is obtained after the addition of preprocessing process and adaptive training model on the system. Therefore, this research concluded that viola-jones method is very good as face detection, however need to be added face correction process. Meanwhile, eigenface and euclidean distance methods provide good results to recognize face when many training faces are given. The more variations faces of subject are, the higher accuracy is given.]]>
<![CDATA[Sistem Pakar Diagnosa Gangguan Mental pada Anak dengan Metode Dempster Shafer ]]>
<![CDATA[dina hastari]]>;
<![CDATA[Fitri Bimantoro]]>
<![CDATA[ Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 2 No 2 (2018): Desember 2018 ]]>
Publisher : <![CDATA[Informatics Engineering Dept., Faculty of Engineering, University of Mataram ]]>
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DOI: 10.29303/jcosine.v2i2.106
<![CDATA[Gangguan mental adalah kondisi yang mempengaruhi pikiran, perasaan, suasana hati dan perilaku manusia pada semua usia termasuk anak-anak. Untuk mendapatkan kesimpulan, penelitian ini menggunakan metode Dempster Shafer. Setiap data gejala memiliki nilai keyakinan sebagai nilai awal untuk mendapatkan kesimpulan dalam metode Dempster Shafer. Tes yang digunakan dalam penelitian ini adalah black box, perhitungan teoritis, akurasi, laboratorium dan kuesioner. Hasil tes black box yang dilakukan oleh 3 responden mahasiswa menunjukkan sistem berjalan dengan baik. Perbandingan perhitungan teoritis dan perhitungan pada sistem memberikan hasil yang sama. Pengujian laboratorium dan pengujian akurasi dari 40 kasus memberikan hasil yang sama sekitar 95%. Selain itu, aplikasi ini juga telah diuji oleh para pakar dan masyarakat langsung untuk menilai apakah sistem sudah berjalan dengan baik atau tidak. Berdasarkan parameter MOS (Mean Opinion Score), sistem telah bekerja dengan baik dengan skor 4,44 dari skala 5.]]>
<![CDATA[Implementasi Modifikasi Kompresi Run-Length Encoding pada Steganografi ]]>
<![CDATA[Suwardiman Suwardiman]]>;
<![CDATA[Fitri Bimantoro]]>
<![CDATA[ Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 2 (2020): December 2020 ]]>
Publisher : <![CDATA[Informatics Engineering Dept., Faculty of Engineering, University of Mataram ]]>
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DOI: 10.29303/jcosine.v4i2.109
<![CDATA[RLE is one of the methods to compress data, however it has disadvantages that the compressed data may become twice larger as the original size. Therefore, in this research RLE will be modified to solve the problem. In the experiment we tested 3 file format i.e. JPG, PNG and BMP. The testing on JPG and PNG shows that conventional RLE method is not able to compress all images because it obtained negative compression ratio with an average compression ratio about -97.4%, Meanwhile the compression with RLE modification shows that the all image successfully compress with an average compression ratio about 0.31%. The testing on BMP shows the conventional RLE method successfully compress 5 files out of 11 tested images with average compression ratio about -25.4%, Meanwhile the compression with modified RLE successfully compress all tested images with average compression ratio about 22.4 %.]]>
<![CDATA[Predict A Person's Personality Based On The Shape of Handwriting of The Letters "i", "o", and "t" Using The Levenberg Marquardt Backpropagation Method ]]>
<![CDATA[Annisa Mujahidah Robbani]]>;
<![CDATA[I Gede Pasek Suta Wijaya]]>;
<![CDATA[Fitri Bimantoro]]>;
<![CDATA[Heri Wijayanto]]>
<![CDATA[ Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 5 No 2 (2021): December 2021 ]]>
Publisher : <![CDATA[Informatics Engineering Dept., Faculty of Engineering, University of Mataram ]]>
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DOI: 10.29303/jcosine.v5i2.178
<![CDATA[The literature shows that Graphology is common and relatively useful in our life. For example, as one of the job requirements. Professional organizations hire a professional handwriting analyst called Graphologist to analyze the characteristic traits of the candidates by identified their handwriting. However, the accuracy of handwriting analysis depends on how skilled the graphologist is, two graphologists which predict the same handwriting may give us a different result of the prediction. To improve the accuracy, we develop a system that can automatically predict a person’s personality based on the shape of the handwriting of the letters "i", "o", and "t" using the Levenberg Marquardt Backpropagation method. Based on this research we got the maximum accuracy by using 2 hidden layers. We got 71,42% of accuracy for the letter “i”, 76,92% of accuracy for the letter “o”, and 60% of accuracy for letter the “t”.]]>
<![CDATA[Pengenalan Pola Tulisan Tangan Suku Kata Aksara Sasak Menggunakan Metode Moment Invariant dan Support Vector Machine ]]>
<![CDATA[Riska Yulianti]]>;
<![CDATA[I Gede Pasek Suta Wijaya]]>;
<![CDATA[Fitri Bimantoro]]>
<![CDATA[ Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 3 No 2 (2019): December 2019 ]]>
Publisher : <![CDATA[Informatics Engineering Dept., Faculty of Engineering, University of Mataram ]]>
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DOI: 10.29303/jcosine.v3i2.181
<![CDATA[The research of Javanese and Balinese ancient script have been done by some researches. However, the researches still have problems, such as image scaling, noise reduction and image transformation. This research implemented moment invariant and support vector machine to solve these problems especially on Sasak ancient script. The input data used in this research was 2700 handwritten Sasak ancient script. The testing was done to know the effect of thinning and the number of feature by using zoning on the classification performance. Accuracy is used as performance indicator. The highest average accuracy is 89.76%, on the second scenario, the average accuracy obtained is 92.52%.]]>
<![CDATA[Analisis Efektifitas Metode Weighted Product dan TOPSIS dalam Mendiagnosa Serangan Asma ]]>
<![CDATA[Ade Ragil Purwandani]]>;
<![CDATA[Ario Yudo Husodo]]>;
<![CDATA[Fitri Bimantoro]]>
<![CDATA[ Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 3 No 1 (2019): June 2019 ]]>
Publisher : <![CDATA[Informatics Engineering Dept., Faculty of Engineering, University of Mataram ]]>
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DOI: 10.29303/jcosine.v3i1.185
<![CDATA[To diagnose asthma attack we use Weighted Product and TOPSIS method to analyze the data. The lack of Weighted Product for the expert system is there are no cost and benefit for the criteria. We use combined it with TOPSIS to determining an alternative preference based on the ideal positive and ideal negative solution. WP methods have advantages where it has an initial weight which is TOPSIS don’t have. Combining the two methods aims to determine the effectiveness of the method. We use 40 data test on two different experts and compare it with our proposed method in this research. The result shows that, for the first expert, we gain accuracy for Weighted Product, TOPSIS and combined of WP and TOPSIS are 12,5%, 12,5%, and 60% respectively and for the second expert, we gain 30%, 30%, and 70%. Its show that the combined methods are better used compared to the WP and TOPSIS methods.]]>
<![CDATA[Sistem Pakar Diagnosa Penyakit Kulit pada Manusia dengan Metode Dempster Shafer ]]>
<![CDATA[Anita Rosana MZ]]>;
<![CDATA[I Gede Pasek Suta Wijaya]]>;
<![CDATA[Fitri Bimantoro]]>
<![CDATA[ Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 2 (2020): December 2020 ]]>
Publisher : <![CDATA[Informatics Engineering Dept., Faculty of Engineering, University of Mataram ]]>
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DOI: 10.29303/jcosine.v4i2.285
<![CDATA[Skin is the broadest organ in the human body that covers the entire surface of the body and acts as a support for human life. Because of its outermost location, the skin is often attacked by various diseases. This research aims to build an expert system to diagnose 10 types of skin diseases caused by viruses, fungi, bacteria, and parasites based on the knowledge of 3 experts using the Dempster Shafer method to obtain conclusions of skin diseases. Each symptom of skin disease has a value of belief that is used to calculate conclusions in the Dempster Shafer method. Expert system applications that are built can run Android-based smartphones. Testing techniques used in this research are black-box testing, theoretical calculations, system accuracy and MOS (Mean Opinion Score). Comparison of the calculation on the system has been appropriate based on the theoretical calculations. System accuracy testing in 30 sample cases resulted in an accuracy of 90%, but if it was seen as a subsection of expert diagnosis, it resulted in a system accuracy of 92.22%. MOS testing on 30 respondents results in a MOS value of 4.24 from a scale of 5 which shows that the system is proper to use and categorized into a good system.]]>
<![CDATA[Sistem Pakar Diagnosis Penyakit pada Ayam dengan Menggunakan Metode Dempster Shafer ]]>
<![CDATA[Salsabila Putri Rajani Said]]>;
<![CDATA[I Gede Pasek Suta Wijaya]]>;
<![CDATA[Fitri Bimantoro]]>
<![CDATA[ Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 1 (2020): June 2020 ]]>
Publisher : <![CDATA[Informatics Engineering Dept., Faculty of Engineering, University of Mataram ]]>
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DOI: 10.29303/jcosine.v4i1.286
<![CDATA[Chicken is one type of poultry that has many benefits, so the chicken can be an option for livestock. This research was conducted to create an expert system that helps provide information to farmers about poultry diseases, especially broilers. This expert system is built on the Android platform and uses the Dempster Shafer calculation method to get the diagnosis of chicken disease. The data used in this study consisted of 38 symptoms and 10 diseases data which were limited to diseases caused by bacteria and viruses. Each symptom has the value of belief given by 3 veterinarians. This study used four types of testing in the form of black-box testing, questionnaire testing, theoretical testing, and accuracy testing. The results of the accuracy testing of the 30 cases given are 92.22% and the system accuracy is 93.33% if the system diagnosis results are assumed to be valid because it is a subsection of expert diagnosis. For questionnaire testing using the MOS, parameters obtained 4.58 results from a scale of 5, as well as theoretical calculation tests that get the same calculation results between the results of expert diagnoses and system diagnoses. Based on the test results, the system built is good and appropriate.]]>
