Garuda - Garba Rujukan Digital

p-Index From 2020 - 2025

7.416

P-Index

This Author published in this journals

All Journal International Journal of Evaluation and Research in Education (IJERE) ComEngApp : Computer Engineering and Applications Journal Indonesian Journal of Electronics and Instrumentation Systems IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmu Komputer dan Informasi Jurnal Ilmiah Informatika Komputer Jurnal Simetris Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Intiqad: Jurnal Agama dan Pendidikan Islam Telematika : Jurnal Informatika dan Teknologi Informasi Scientific Journal of Informatics CESS (Journal of Computer Engineering, System and Science) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Jurnal Fourier InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Proceeding of the Electrical Engineering Computer Science and Informatics JPSE (Journal of Physical Science and Engineering) Jurnal Teknologi dan Sistem Komputer Jurnal Informatika INTEGER: Journal of Information Technology Jurnal Matematika: MANTIK JURNAL MEDIA INFORMATIKA BUDIDARMA BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Informatika Universitas Pamulang JUMANJI (Jurnal Masyarakat Informatika Unjani) Jurnal Telematika Mathvision : Jurnal Matematika Building of Informatics, Technology and Science Transformasi : Jurnal Pendidikan Matematika dan Matematika Jurnal Mnemonic Majalah Ilmiah Matematika dan Statistika (MIMS) Dinamika Informatika: Jurnal Ilmiah Teknologi Informasi JUSTIN (Jurnal Sistem dan Teknologi Informasi) Serambi Engineering

Sari, Dian Candra Rini Novita

Universitas Islam Negeri Sunan Ampel Surabaya

Author-ID : 1971240

Religion Arts Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Transportation

Published : 65 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3 4 5

Klasifikasi Kelainan Pada Jantung Melalui Citra Iris Mata Menggunakan Fuzzy C-Means Sebagai Pengambil Fitur Iris Dan Klasifikasi Menggunakan Support Vector Machine novitasari, Dian candra rini; Rozi, Muhammad Fahrur; Veriani, Rafika
INTEGER: Journal of Information Technology Vol 4, No 1: May 2019
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Iridologi merupakan diagnosis sebuah iris mata yang merepresentasikan tanda-tanda seperti warna dan struktur dari iris sehingga didapatkan informasi tentang kesehatan seseorang. Penelitian ini tentang iridologi yang terkomputerisasi oleh sebuah sistem yang digunakan dalam mendeteksi keadaan jantung yang dirancang dengan langkah-langkah seperti pra-proseskonversi citra ari RGB menjadi Grayscale, penghapusan noise menggunakan median filter, pemangkasan, pengelompokan menggunakan Fuzzy C-Means (FCM), deteksi tepi menggunakan metode Canny dan diikuti fitur ekstraksi menggunakan Grey Level Co-occurrence Matrix (GLCM), serta klasifikasi menggunakan Support Vector Machine (SVM). Sampel iris pasien dalam keadaan normal dan tidak normal. Data iris pasien yang memiliki kelainan jantung sebanyak 20 citra. Hasil dari sistem deteksi kelainan Jantung melalui citra iris ini memiliki tingkat akurasi sebesar 75%.

Tide Prediction in Prigi Beach using Support Vector Regression (SVR) Method Utami, Tri Mar'ati Nur; Novitasari, Dian Candra Rini; Setiawan, Fajar; Ulinnuha, Nurissaidah; Farida, Yuniar; Sari, Ghaluh Indah Permata
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.28906

Purpose: Prigi Beach has the largest fishing port in East Java, but the topography of this beach is quite gentle, so it is prone to disasters such as tidal flooding. The tides of seawater strongly influence the occurrence of this natural event. Therefore, information on tidal level data is essential. This study aims to provide information about tidal predictions. Methods: In this case using the SVE method. Input data and time were examined using PACF autocorrelation plots to form input data patterns. The working principle of SVR is to find the best hyperplane in the form of a function that produces the slightest error. Result: The best SVR model built from the linear kernel, the MAPE value is 0.5510%, the epsilon is 0.0614, and the bias is 0.6015. The results of the tidal prediction on Prigi Beach in September 2020 showed that the highest tide occurred on September 19, 2020, at 10.00 PM, and the lowest tide occurred on September 3, 2020, at 04.00 AM. Value: After conducting experiments on three types of kernels on SVR, it is said that linear kernels can predict improvements better than polynomial and gaussian kernels.

PREDIKSI KASUS AKTIF KUMULATIF COVID-19 DI INDONESIA MENGGUNAKAN MODEL REGRESI LINIER BERGANDA Elen Riswana Safila Putri; Fahriza Novianti; Yasirah Rezqita Aisyah Yasmin; Dian Candra Rini Novitasari
TRANSFORMASI Vol 5 No 2 (2021): TRANSFORMASI : Jurnal Pendidikan Matematika dan Matematika
Publisher : Pendidikan Matematika FMIPA Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/tr.v5i2.1231

Regresi linier berganda digunakan untuk mengidentifikasi hubungan antara variabel respons dengan minimal dua variabel prediktor. Variabel respons merupakan variabel yang dipengaruhi, sedangkan variabel prediktor merupakan variabel yang mempengaruhi. Tujuan penelitian ini adalah melakukan prediksi kasus aktif kumulatif dengan variabel prediktor kasus positif kumulatif, kesembuhan kumulatif, dan korban meninggal kumulatif pada kasus COVID-19 di Indonesia sejak 1 Mei 2021 hingga 26 Agustus 2021 menggunakan metode regresi linier berganda. Hasil penelitian ini menghasilkan prediksi dengan MAPE sebesar 2,11%. Prediksi yang dilakukan memiliki akurasi yang sangat baik karena memiliki nilai galat yang sangat kecil. Berdasarkan hasil tersebut disimpulkan bahwa akan terjadi penurunan kasus aktif kumulatif COVID-19 pada 1-5 September 2021 dengan penurunan terbanyak pada 5 September sebesar 17079 orang.

ANALISIS PENDEKATAN STATISTIK DAN FUZZY MAMDANI DALAM PREDIKSI PRODUKTIVITAS PADI Ferryan, Dhandy Ahmad; Zulfa, Elok Indana; Novitasari, Dian Candra Rini
Majalah Ilmiah Matematika dan Statistika Vol 22 No 1 (2022): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v22i1.30304

Indonesia has fertile soil, so it is suitable for agricultural land. However, Indonesia still needs to import rice from abroad because rice productivity in Indonesia is often inconsistent. Therefore, rice productivity in Indonesia needs to be estimated for the future. This study aimed to determine the amount of rice productivity from production factors and harvested area that occurred in Indonesia from September 2021 to June 2022. The data used were rice production and rice harvested from January 2019 to August 2021 sourced from the Central Statistics Agency, Indonesia. Data processing in this study uses the Polynomial Regression method to determine predictions of future rice production and harvest area and the Mamdani Fuzzy Logic method. Data processing in this study uses a prediction method, namely the Polynomial Regression method, to determine future production and harvested area predictions and the Mamdani method of Fuzzy Logic for decision making. The results obtained from the Mamdani polynomial and fuzzy regression methods, predictions of rice productivity in September 2021 to June 2022 have increased in the range of 23.33 to 27.91.Keywords: Fuzzy Mamdani, polynomial regression, prediction, rice productivityMSC2020: 62A86

Detection of potential errors in measurement results of madrasa admission instruments in Indonesia Ahmad Yusuf; Kusaeri Kusaeri; Ahmad Hidayatullah; Dian Candra Rini Novitasari; Ahmad Hanif Asyhar
International Journal of Evaluation and Research in Education (IJERE) Vol 10, No 4: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v10i4.21412

Madrasa (Islamic boarding school) in Indonesia have a strategic role in character building. At present madrasa education is still considered second class education. Besides, to improve the quality of madrasas can be started by improving the quality of the student national admission to all madrasas in Indonesia. This study aimed to trace the potential errors in the measurement results of Students National Admission of Madrasah Aliyah Negeri (SNPDB MAN-IC) 2020. Tracing was carried out on two aspects: i) Equality between test sets used based on evidence of test responses; and ii) Further tests on equality between question sets based on evidence of relationship between variables, taking into account the origin of the participating schools (MTs/JHS) and the origin of the participating regions (West, Central and East of Indonesia). This study involved 13,115 participants in 23 MAN-ICs throughout Indonesia in 2020. The materials tested comprised learning potential and academic ability (Mathematics, Natural Sciences, Social Studies, English, Arabic, and Islamic Religious Education). The study used achievement test with mathematics as a sample of test subjects. Based on the test response evidence, it was found that seven of the 15 questions were thought to have an indication of inequality between item sets. The results of tracing the evidence between variables indicated that it was the participants' origin of institutions that influenced the inequality between item sets. On the other hand, regional origin did not affect the inequality between item sets because the majority of participants came from the western region of Indonesia.

Lung cancer classification based on CT scan image by applying FCM segmentation and neural network technique Ahmad Zoebad Foeady; Siti Ria Riqmawatin; Dian Candra Rini Novitasari
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.18874

The number of people with lung cancer has reached approximately 2.09 million people worldwide. Out of 9.06 million cases of death, 1.76 million people die due to lung cancer. Lung cancer can be automatically identified using a computer-aided diagnosis system (CAD) such as image processing. The steps taken for early detection are pre-processing feature extraction, and classification. Pre-processing is carried out in several stages, namely grayscale images, noise removal, and contrast limited adaptive histogram equalization. This image feature extracted using GLCM and classified using 2 method of neural network which is feed forward neural network (FFNN) dan feed backward neural network (FBNN). This research aims to obtain the best neural network model to classify lung cancer a. Based on training time and accuracy, the best method of FFNN is kernel extreme learning machine (KELM), with a training time of 12 seconds and an accuracy of 93.45%, while the best method of FBNN is Backpropagation with a training time of 18 minutes 04 seconds and an accuracy of 97.5%.

Klasifikasi Sinyal EEG Menggunakan Metode Fuzzy C-Means Clustering (FCM) Dan Adaptive Neighborhood Modified Backpropagation (ANMBP) Dian Candra Rini
Jurnal Matematika MANTIK Vol. 1 No. 1 (2015): Matematika dan Terapan
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (277.307 KB)

Instrumen EEG (electroencephalography) merupakan suatu instrumen yang digunakan sebagai perekam aktivitas otak dengan memperlihatkan gelombang otak. Prinsip kerja EEG adalah dengan mendeteksi perubahan muatan secara tiba-tiba dari sel neuron yang ditandai dengan adanya interictal spike-and-wave pada hasil EEG (electroencephalogram). Terdapat suatu data set sinyal EEG, direkam pada sukarelawan normal dan epilepsi. Pada penelitian ini dengan menggunakan data tersebut akan dilakukan suatu sistem klasifikasi sinyal EEG dengan berdasar pada kondisi normal dan epilepsi. Klasifikasi sinyal EEG menggunakan Metode Adaptive Neighborhood Base Modified Backpropagation (ANMBP). Hasil ekstraksi fitur dari sinyal EEG dengan menggunakan metode Fuzzy C-Means (FCM) Clustering, dimana proses awalnya melalui dekomposisi wavelet menggunakan Discrete Wavelet Transform (DWT) dengan level 2 didapatkan 3 koefisien wavelet kemudian pada masing masing koefisien tersebut di clustering menggunakan FCM dengan 2 cluster sehingga menghasilkan 6 fitur yang akan menjadi vektor fitur. Dari vektor fitur tersebut digunakan sebagai inputan untuk dilakukan proses klasifikasi dengan menggunakan metode ANMBP. Hasil sistem sementara didapatkan recognition rate sebesar 74.37%.

PENGKLASTERAN LAHAN SAWAH DI INDONESIA SEBAGAI EVALUASI KETERSEDIAAN PRODUKSI PANGAN MENGGUNAKAN FUZZY C-MEANS Nur Afifah; Dian Candra Rini Novitasari; Ahmad Lubab
Jurnal Matematika MANTIK Vol. 2 No. 1 (2016): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (180.695 KB)

The number of rice field in Indonesia is decreasing due to development of residential areas and buildings. Consequently, it reduces foodstuff availability and government should import it from other. Increasing food production and minimizing imported food can be started by clustering fields as an evaluation. This clustering is approached by Fuzzy C-Means. Training and Testing data are implemented on Matlab and yield three categories, wide, medium and narrow field. Moreover, the most potential field is East Java, Central Java, and West Java

Classification of EEG Signals using Fast Fourier Transform (FFT) and Adaptive Neuro Fuzzy Inference System (ANFIS) Suwanto Suwanto; M. Hasan Bisri; Dian Candra Rini Novitasari; Ahmad Hanif Asyhar
Jurnal Matematika MANTIK Vol. 5 No. 1 (2019): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Epilepsy is a disease that attacks the brain and results in seizures due to neurological disorders. The electrical activity of the brain recorded by the EEG signal test, because EEG test can be used to diagnose brain and mental diseases such as epilepsy. This study aims to identify whether a person has epilepsy or not along with the result of accurate, sensitivity, and precision rate using Fast Fourier Transform (FFT) and Adaptive Neuro-Fuzzy Inference System (ANFIS) method. The FFT is used to transform EEG signals from time-based into frequency-based and continued with feature extraction to take characteristics from each filtering signal using the median, mean, and standard deviations of each EEG signal. The results of the feature extraction used for input on the category process based on characteristics data (classification) using ANFIS. EEG signal data is obtained from epilepsy center online database of Bonn University, German. The results of the EEG signal classification system using ANFIS with two classes (Normal-Epilepsy) states accuracy, sensitivity, and precision of 100%. The classification systems with three class division (Normal-Not Seizure Epilepsy-Epilepsy) resulted in an accuracy of 89.33% sensitivity of 89.37% and precision of 89.33%.

Analysis of Livestock Meat Production in Indonesia Using Fuzzy C-Means Clustering Chalawatul Ais; Abdulloh Hamid; Dian Candra Rini Novitasari
Jurnal Ilmu Komputer dan Informasi Vol. 15 No. 1 (2022): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Informatio
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21609/jiki.v15i1.993

The production of livestock in Indonesia is one type of food that the public can consume. Indonesia is still importing meat for food for its people. This study aims to classify provinces in Indonesia with high livestock meat production and low livestock meat production so that the government can maximize areas with high livestock meat production and can seek to increase livestock meat production in areas with low production. Clustering is needed to identify groups of livestock meat-producing provinces with high and low production. The data is grouped into 2 clusters using FCM with a silhouette index value of 0.95664, the first cluster with the highest meat production total in three provinces (West Java, Central Java, and East Java) and the second cluster with the lowest meat production total 31 provinces. West Java, Central Java, and East Java mostly work as livestock breeders due to the availability of sufficient land.

Co-Authors Abdulloh Hamid Abdulloh Hamid Achmad Teguh Wibowo Adam Fahmi Khariri Adyanti, Deasy Ahmad Hanif Asyhar Ahmad Hidayatullah Ahmad Zoebad Foeady Ahmad Zoebad Foeady Aisyah, Nora Alvin Nuralif Ramadanti Amin, Faris Mushlihul Arifin, Ahmad Zaenal Aris Fanani Ariyanto Wijaya, Indra Ariyanto, Dimas Azmi, Tasya Auliya Ulul Chalawatul Ais Damayanti, Adelia Deasy Adyanti Dianita Utami, Wika Dilla Dwi Kartika Diva Ayu Safitri Nur Maghfiroh Elen Riswana Safila Putri Fahriza Novianti FAJAR SETIAWAN Fajar Setiawan Fajar Setiawan Fajar Setiawan Fajar Setiawan Fanani, Aris Farida, Yuniar Faris Mushlihul Amin Farmita, Mayandah Ferryan, Dhandy Ahmad Firmansjah, Muhammad Fitria, Nur Annisa Foeady, Ahmad Zoebad Galuh Andriani Ganeshar B.D. Prasanda Gita Purnamasari R Hani Khaulasari Hanimatim Mu'jizah Haq, Dina Zatusiva Ifadah, Corii Indriyani, Jiphie Gilia Irkhana Indaka Zulfa Jauharotul Inayah Kurniawan, Mohammad Lail Kusaeri Kusaeri Lubab, Ahmad Luluk Mahfiroh Lutfi Hakim Lutfi Hakim Lutfi Hakim Luthfi Hakim Luthfi Hakim M. Hasan Bisri Mardiyah, Ilmiatul Masruroh Kusman, Umi Maulana, Achmad Resnu Maulana, Jeneiro Moh. Hafiyusholeh Mohammad Rizal Abidin Mohd Fauzi, Shukor Sanim Monika Refiana Nurfadila MUHAMMAD FAHRUR ROZI Muhammad Fahrur Rozi Muhammad Syaifulloh Fattah Muhammad Thohir Musfiroh Musfiroh, Musfiroh Nanang Widodo Nanang Widodo Nanang Widodo Nanang Widodo Nisa Trianifa Noviati Maharani Sunariadi Noviati Maharani Sunariadi Nur Afifah Nur Hidayah Nurissaidah Ulinnuha Pramesti, Diah Devi Puspitasari, Wahyu Tri Putri Wulandari Putri, Evi Septya Putroue Keumala Intan Rafika Veriani Ramadanti, Alvin Nuralif Ratnasari, Cristanti Dwi RIFA ATUL HASANAH Rifa Atul Hasanah Rozi, Muhammad Fahrur Rozzy, Fahrul Safira, Icha Dwi Sani, Puteri Permata Sari, Firda Yunita Sari, Ghaluh Indah Permata Sari, Yana Vita Setiawan, Fajar Setyawati, Maunah Siti Nur Aisah Siti Nur Fadilah Siti Nur Fadilah Siti Ria Riqmawatin Sukarni, Adinda Ika Sulistiya Nengse Sulistiyawati, Dewi Suwanto Suwanto Suwanto Suwanto Swindiarto, Victory T. Pambudi Tasya Auliya Ulul Azmi Unix Izyah Arfianti USWATUN KHASANAH Utami, Tri Mar'ati Nur Utami, Wika Dianita Utami Dianita Veriani, Rafika Vina Fitriyana Wanda N.P. Sunaryo Wijaya, Indra Ariyanto Wika Dianita Utami Wika Dianita Utami Wika Dianita Utami Wika Dianita Utami Wisnawa, Gede Gangga Yasirah Rezqita Aisyah Yasmin Yuliati, Dian Yuliawanti, Felia Dria Yuni Hariningsih Yuniar Farida, Yuniar Yusuf, Ahmad Yuyun Monita Yuyun Monita Zahroh, Khofifah Auliyatuz Zulfa, Elok Indana

Title

Found 65 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 65 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 65 Documents
Search