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Journal : Proceeding of the Electrical Engineering Computer Science and Informatics

Implementation of Winnowing Algorithm for Document Plagiarism Detection Nurissaidah Ulinnuha; Muhammad Thohir; Dian Candra Rini Novitasari; Ahmad Hanif Asyhar; Ahmad Zaenal Arifin
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (375.112 KB) | DOI: 10.11591/eecsi.v5.1599

Abstract

Plagiarism prevention efforts are being evolved in various sector. Designing and developing plagiarism checker applications is the purpose of this paper. Specifically by knowing the percentage of similarity between the original document and the test document. Winnowing algorithm is used because it can detect plagiarism in documents up to sub-section of the document. In this paper using three validators consisting of computational mathematicians, software engineering experts, and users to test the feasibility of the application. Experiment using several scenarios, the result of the equation using winnowing algorithm is 90.12%.
Optimal ANFIS Model for Forecasting System Using Different FIS Deasy Adyanti; Dian Candra Rini Novitasar; Ahmad Hanif Asyhar; Fajar Setiawan
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (356.341 KB) | DOI: 10.11591/eecsi.v5.1617

Abstract

Adaptive Network Based Fuzzy Inference System (ANFIS) using time series analize is one of intelligent systems that can be used to predict with good accuracy in all fields like in meteorology. However, some research about forecasting has less emphasis on the structure of the FIS ANFIS. Thus, in this paper, the optimization of the ANFIS model for predicting maritime weather is carried out by analyzing the appropriate initialization determinations of the three fuzzy Inference structures ANFIS which includes FIS structure 1 (grid partition), FIS structure 2 (subtractive clustering) and FIS structure 3 (fuzzy c-means clustering). In this paper, the variable input used are two hours (t-2) and one hour (t-1) before, and data at that time (t), and the output of this system is the prediction of next hour, six hours, twelve hours and next day of variable ocean currents velocity (cm/s) and wave height (m) using the three FIS ANFIS approaches. Based on the smallest goal error (RMSE and MSE) of the three FIS ANFIS approaches used to predict the ocean currents speed (velocity) and wave height, the model is best generated by subtractive clustering. It can be seen that subtractive clustering produces the smallest RMSE and MSE error values of other FIS structure.
Automated Diagnosis System of Diabetic Retinopathy Using GLCM Method and SVM Classifier Ahmad Zoebad Foeady; Dian Candra Rini Novitasari; Ahmad Hanif Asyhar; Muhammad Firmansjah
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (605.455 KB) | DOI: 10.11591/eecsi.v5.1630

Abstract

Diabetic Retinopathy (DR) is the cause of blindness. Early identification needed for prevent the DR. However, High hospital cost for eye examination makes many patients allow the DR to spread and lead to blindness. This study identifies DR patients by using color fundus image with SVM classification method. The purpose of this study is to minimize the funds spent or can also be a breakthrough for people with DR who lack the funds for diagnosis in the hospital. Pre-processing process have a several steps such as green channel extraction, histogram equalization, filtering, optic disk removal with structuring elements on morphological operation, and contrast enhancement. Feature extraction of preprocessing result using GLCM and the data taken consists of contrast, correlation, energy, and homogeneity. The detected components in this study are blood vessels, microaneurysms, and hemorrhages. This study results what the accuracy of classification using SVM and feature from GLCM method is 82.35% for normal eye and DR, 100% for NPDR and PDR. So, this program can be used for diagnosing DR accurately.
Co-Authors Abdulloh Hamid Abdulloh Hamid Adam Fahmi Khariri Adelia Damayanti Adyanti, Deasy Ahmad Hanif Asyhar Ahmad Hanif Asyhar Ahmad Hidayatullah Ahmad Lubab Ahmad Yusuf Ahmad Zoebad Foeady Ahmad Zoebad Foeady Alvin Nuralif Ramadanti Arifin, Ahmad Zaenal Aris Fanani Aris Fanani Chalawatul Ais Deasy Adyanti Dewi Sulistiyawati Dilla Dwi Kartika Dina Zatusiva Haq Dina Zatusiva Haq Diva Ayu Safitri Nur Maghfiroh Elen Riswana Safila Putri Evi Septya Putri Fahriza Novianti FAJAR SETIAWAN Fajar Setiawan Fajar Setiawan Fajar Setiawan Fajar Setiawan Faris Mushlihul Amin Ferryan, Dhandy Ahmad Firmansjah, Muhammad Foeady, Ahmad Zoebad Galuh Andriani Ganeshar B.D. Prasanda Gede Gangga Wisnawa Gita Purnamasari R Hani Khaulasari Hanimatim Mu'jizah Ifadah, Corii Ilmiatul Mardiyah Indra Ariyanto Wijaya Irkhana Indaka Zulfa Jauharotul Inayah Kusaeri Kusaeri Luluk Mahfiroh Lutfi Hakim Lutfi Hakim Luthfi Hakim M. Hasan Bisri Mayandah Farmita Moh. Hafiyusholeh Moh. Hafiyusholeh Moh. Hafiyusholeh Moh. Hafiyusholeh Mohammad Lail Kurniawan Mohammad Rizal Abidin Monika Refiana Nurfadila MUHAMMAD FAHRUR ROZI Muhammad Fahrur Rozi Muhammad Syaifulloh Fattah Muhammad Thohir Musfiroh Musfiroh Nanang Widodo Nanang Widodo Nanang Widodo Nisa Trianifa Noviati Maharani Sunariadi Noviati Maharani Sunariadi Nur Afifah Nur Hidayah Nurissaidah Ulinnuha Nurissaidah Ulinnuha Nurissaidah Ulinnuha Putri Wulandari Putroue Keumala Intan Putroue Keumala Intan Putroue Keumala Intan Putroue Keumala Intan Rafika Veriani Ratnasari, Cristanti Dwi RIFA ATUL HASANAH Rifa Atul Hasanah Rozi, Muhammad Fahrur Sari, Ghaluh Indah Permata Setiawan, Fajar Siti Nur Fadilah Siti Nur Fadilah Siti Ria Riqmawatin Suwanto Suwanto Suwanto Suwanto Tasya Auliya Ulul Azmi Thohir, Muhammad Ulinnuha, Nurissaidah Umi Masruroh Kusman Unix Izyah Arfianti USWATUN KHASANAH Utami, Tri Mar'ati Nur Veriani, Rafika Vina Fitriyana Wanda N.P. Sunaryo Wika Dianita Utami Wika Dianita Utami Wika Dianita Utami Wika Dianita Utami Wika Dianita Utami Wika Dianita Utami Dianita Utami Yasirah Rezqita Aisyah Yasmin Yuni Hariningsih Yuniar Farida Yuniar Farida, Yuniar Yuyun Monita Yuyun Monita Zulfa, Elok Indana