Article Per Year (5 Year)
p-Index From 2021 - 2026
5.728
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Pendidikan CommIT (Communication & Information Technology) Journal of Food and Life Sciences Journal of Innovation and Applied Technology Journal of Environmental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer AGRIVITA, Journal of Agricultural Science Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) JINOP (Jurnal Inovasi Pembelajaran) Premiere Educandum Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Pendas : Jurnah Ilmiah Pendidikan Dasar Journal of Education Technology Jurnal Ilmiah Sekolah Dasar Istawa: Jurnal Pendidikan Islam UPEJ Unnes Physics Education Journal AMALIAH: JURNAL PENGABDIAN KEPADA MASYARAKAT Journal of Research and Educational Research Evaluation Pendagogia: Jurnal Pendidikan Dasar Cendikia Pendidikan Advances In Social Humanities Research JURNAL ILMIAH EKONOMI, MANAJEMEN, BISNIS DAN AKUNTANSI Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research
Candra Dewi
Fakultas Ilmu Komputer, Universitas Brawijaya
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

Published : 132 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 132 Documents
Search

 7   8   9   10   11 
Implementasi Algoritme Fuzzy C-Means dengan Particle Swarm Optimization (FCMPSO) untuk Pengelompokan Proses Berpikir Siswa dalam Proses Belajar Nur Sa'diyah; Ahmad Afif Supianto; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 6 (2020): Juni 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The current learning process can be carried out using a variety of learning media, one of which is called Monsakun, a learning media about simple arithmetic word problems. Learning activities undertaken by students at Monsakun will be stored in the datalog. The datalog is a representation of students' thought processes while studying with Monsakun. The thought process that students do when studying at Monsakun certainly varies from one student to another student. Therefore, clustering students who have a tendency to think similarly into the same group is needed in order to facilitate the teaching staff in handling and providing appropriate feedback on the learning constraints of their students. This study aims to utilize datalog from Monsakun learning media to get groups of students' thought processes in the learning process using the Fuzzy C-Means algorithm that is optimized with Particle Swarm Optimization (FCMPSO). Based on the results of the implementation that has been carried out using 12 data assignments at Monsakun, the best results are group formation dominated by 2 clusters. The optimum parameter values ​​have different results for each data assignment, and there is only the same optimum value for all data assignments on the learning factor parameters.
Penerapan Particle Swarm Optimization Pada Algoritme K-Means Untuk Pengelompokan Proses Berpikir Siswa Dalam Belajar Annisa Salamah Rahmadhani; Ahmad Afif Supianto; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 6 (2020): Juni 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The students' thought process during learning reflects their understanding and misunderstanding about the structure of the questions in an exercise. The application of understanding of the structure of questions has been packaged in a learning media called Monsakun. Monsakun provides support by offering the concept of understanding the structure of questions in solving simple arithmetic word problems (addition and subtraction). Although Monsakun has successfully provided support in learning, identification of group learning patterns among students has not been done. This pattern grouping needs to be done to make it easy for teachers to understand the characteristics of students' thinking, understand the difficulties faced, and provide feedback in accordance with the characteristics of thinking and difficulties experienced by these students. This study aims to group students' thought processes while studying at Monsakun using the K-Means algorithm that is optimized with the Particle Swarm Optimization algorithm in determining initial centroids. The data used is a Monsakun level 5 datalog consisting of 12 questions. Based on the implementation and testing that has been done, the results of grouping are dominated by 2 clusters where the quality of the cluster is determined using the Silhouette Coefficient method.
Implementasi untuk Prediksi Jumlah Kedatangan Wisatawan Domestik Pulau Bali menggunakan Algoritme Performance Improved Holt winters Nabila Arief; Mochammad Tanzil Furqon; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 7 (2020): Juli 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The arrival of tourists into a tourist destination (DTW) has brought prosperity and to local people. Therefore, it is a sector that governments rely on in Indonesia to generate foreign exchange reserves. According to a study conducted by the World Travel and Tourism Council (WTTC) in 2004, the tourism sector can increase local income because of its Quick Yielding Industry. But the number of visitors entering an area is uncertain, for it was predicted the arrival of the tourists. In the study his method was Performance Improved Holt winters so it could be obtained information regarding predictions of the number of domestic tourists arriving to Bali. Performance Improved Holt winters was used for tourist predictions to Bali because of Improved methods used to predict seasonal data patterns. Performance Improved Holt winters rely on scaling trends and seasonal improvements based on the smoothing level equations, the smoothing trend and the smoothing seasonal equations, using data of the number of domestic tourists to Bali during January 2004-December 2018 received from bali.bps.go.id (official website of the BPS). Based on the tests done on this research, the value parameter α (alpha) = 0,03; β (beta) = 0,003; γ (gamma) = 0,04 and value of the smallest error using MAPE is 8% with the number of training data = 168 and testing data = 12.
Klasifikasi Risiko Human Papillomavirus menggunakan Metode Naive Bayes dan Seleksi Fitur Relief Indah Wahyuning Ati; Sigit Adinugroho; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 9 (2020): September 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Human Papillomavirus is a virus that causes various types of diseases such as warts, infertility, miscarriage, vaginosis, and others. However, HPV status in tumors is a factor that helps in surviving and developing to survive in getting better response to radiotherapy and tumor control compared to tumors without HPV. Factors used to understand the problem or not. HPV does not only depend on status, age, age, tumor differences, sex and treatment strategies. But, also age, less exposure to tobacco and alcohol, as well as factors related to tumors. Classification and feature selection will be carried out to study features with significant weights used for the classification of HPV use in tumors. Algorithm flow in this research is by selecting features using the relief method, then classification using the naive bayes method is to predict the probability of class classification used in nominal and numeric type datasets. In this study, the appropriate features were obtained, namely, N_Category, T_Category, Tumor_side, Smoking_status_at_diagnosis, Tumor_substite, AJCC_Stage, and Age_at_diagnosis features. The best accuracy value is 90.97% by testing the number of features using 5 times, for each fold 25 test data and 98 training data are used. Meanwhile, the accuracy of testing the balanced data is 85% using 20 balanced data with 4 test data and 16 training data.
Klasifikasi Dokumen Pengaduan Sambat Online menggunakan Metode Multinomial Naive Bayes dan N-Gram Feri Angga Saputra; Indriati Indriati; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 9 (2020): September 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In an effort to utilize technology in public services, the Malang Office of Communication and Information has launched the SAMBAT Online web application (Integrated Questions Society Application System) to accommodate criticism, suggestions, and complaints given by the public. To improve time efficiency and make it easier for admins to classify incoming complaints the text classification method is needed. The Naive Bayes Multinomial method is widely used because this algorithm is very simple and efficient. But the Naive Bayes Multinomial algorithm has the disadvantage of having dependence on the amount of data. To improve these deficiencies researchers used a support method as feature extraction, N-gram. The test results using the Multinomial Naive Bayes method and N-gram show that the unigram n-gram can provide the highest accuracy rate of 88.23% with an average overall accuracy of 80.88% with an f-measure value of 0,8013.
Pengembangan Aplikasi Pencarian Pembantu Rumah Tangga berbasis Android Ilham Harazki; Agi Putra Kharisma; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 11 (2020): November 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The search for housekeepers on life is now a common thing for some people. It is not closed the possibility that housekeepers are also looking for employers who want to hire them. High time intensity also makes employers difficult to find suitable workers because of the absence of time. Therefore, research is developed based on the problems that have been raised. In the development of search housemaid, model prototyping is used to get the necessary needs in application development. This developed application will be excavated needs to be used to create useful applications for prospective employers and prospective housekeepers. In the use of this method there is a mockup created as a picture of the application to be used, the mockup will be evaluated by the user and will be reviewed either the addition of the need or reduction of needs until the discovery of the completed application in the evaluation and will be implemented using Android. Android is an operating system that is widely used among people nowadays, development of this application using Android Studio application with database using Google Firebase Realtime database. Testing of the application there are three Tests namely Blackbox testing, usability testing, and compatibility testing, which results from the three tests are useful to make the application run as function, accepted in all actors and can run on many types of Android operating systems.
Prediksi Cuaca Kota Denpasar menggunakan Algoritma ELM dengan Optimasi Quantum Delta Particle Swarm Optimization Adam Sulthoni Akbar; Candra Dewi; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 3 (2021): Maret 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Weather is an important factor for beach visitors on the island of Bali, especially in the city of Denpasar. Clear weather, is the perfect weather to visit the beach. To make tourist not come to beach when weather it's rainy, a weather prediction is needed, so tourists can determine the right time to visit the beach in the city of Denpasar. Weather is a natural phenomenon that occurs in a relatively short period of time. Weather data is collected via satellite, and can be used to predict the weather in the future. In this research, the weather data used were temperature, wind speed, humidity and air pressure. To make these predictions, an artificial neural network using the Extreme Machine Learning method is used, with the optimization of the Quantum Delta Particle Swarm Optimization. With 5 hidden neuron, the result of accuracy from ELM is 39%, otherwise, with QDPSO optimization with 10 particles, 42 iterations, and g value 0,96, have result 100% accuracy.
Perancangan Aplikasi Penyedia Jasa Ilustrator berbasis Android menggunakan Metode Human Centered Design (HCD) Nooriza Fariha Rumagutawan; Agi Putra Kharisma; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 4 (2021): April 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

An illustrator is an artist who specializes in improving writing or explaining concepts by providing a visual representation that matches the content of the text or related ideas (Charles & Herbert, 1985). In 2018 the Indonesian Information and Communication Technology Creative Industry Society (MIKTI) stated that the most popular startup was e-commerce with 352 startups. This opens up job opportunities for illustrators and attracts illustrators who want to pursue this work, unfortunately being a freelance illustrator in Indonesia is still difficult, because there is no special platform in Indonesia that connects illustrators and customers. Currently, freelance illustrators in Indonesia use illustrator marketplace services from abroad, their weakness is they do not provide withdrawals via bank or e-wallet, this causes a long process. In addition, selling illustrator services on social media is not the best solution, fraud often occurs from both parties. In order for the creative industry ecosystem to become stronger, a connector is needed which is none other than Information and Communication Technology (Anastasia & Handriani, 2018). The method used in this research is the Human Centered Design (HCD) method because this method focuses on solving problems creatively by focusing on consumer behavior and needs rather than their demographics. The test used in this research is usability testing using the System Usability Scale (SUS) questionnaire, This test produces an average value of 76.5, which means that the value is above the minimum average value of 68. The average value is between the ranges of good and excellent, including in grade B and acceptable to users (ACCEPTABLE).
Implementasi Bagging Naive Bayes untuk Klasifikasi Stenosis Left Anterior Descending (LAD), Left Circumflex Artery (LCX) dan Right Coronary Artery (RCA) dalam Diagnosis Coronary Artery Disease (CAD) Amalia Luhung; Muhammad Tanzil Furqon; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 4 (2021): April 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Coronary Artery Disease (CAD) is a disease that occurs due to the accumulation of atherosclerotic plaque that causes blockage (stenotic) in the tunica intima lining of coronary arteries. The coronary arteries are Left Anterior Descending (LAD), Left Circumflex Artery (LCX), and Right Coronary Artery (RCA). Stenosis in coronary arteries can cause heart attacks and even death. Diagnosis needs to be done quickly to reduce the impact of CAD so, a system was built to help find out LAD, LCX, and RCA stenosis through classification. Classification is done to classify patients' coronary arteries into normal or stenotic classes using the Bagging Naive Bayes method. This method allows the classification to be carried out by several predictor models made based on bootstrap by sampling with replacement to get aggregate results. The steps taken to implement this method are preprocessing, bootstraping, Naive Bayes classification, voting. The highest accuracy in the LAD classification obtained was 0.7573 when the classification was done using 200 data, 25 bootstrap samples (T), and the classification was carried out with all features. Its result ​​of precision, sensitivity and specificity are 0.8065, 0.7938, and 0.7012. In LCX classification the highest accuracy achieved is 0.7282 when the classification is done using 200 data, T = 1, and the classification is done with the features selected. Precision, sensitivity, and specificity result are 0.9042, 0.7262, and 0.7368. Whereas in the RCA classification the highest accuracy achieved is 0.7282 when the classification was carried out using 150 data, T = 1, and the classification was carried out with the results of the selection of precision, sensitivity and specificity values ​​0.9242, 0.7262, and 0.7368. The intended feature selection method is Pearson's chi-squared and One-way ANOVA.
Pengembangan Aplikasi Rekomendasi Makanan Bagi Pasien Hiperkolesterolemia Berbasis Web Ayuri Alfarianti; Agi Putra Kharisma; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 6 (2021): Juni 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penyakit Hiperkolesterolemia merupakan penyakit yang dapat memicu terjadinya penyakit lain seperti penyakit kardiokasvular, jantung koroner dan stroke. Salah satu solusi yang dapat dilakukan bagi pasien hiperkolesterolemia adalah dengan mengonsumsi makanan diet yang berpedoman pada aneka ragam makanan gizi seimbang. Konsultasi dengan ahli gizi dapat membantu pasien dalam mengatur kebutuhan gizi seimbang yang harus dipenuhi oleh pasien. Namun terdapat masalah utama yaitu sulit menentukan makanan yang harus dikonsumsi perharinya. Pasien tidak diberi detail variasi makanan yang harus dikonsumsi, melainkan diserahkan kepada masing-masing pasien. Berdasarkan permasalahan tersebut diperlukan sebuah aplikasi rekomendasi makanan bagi pasien hiperkolesterolemia. Pada penelitian yang dilakukan, diperoleh 21 kebutuhan fungsional dan 1 kebutuhan non-fungsional berdasarkan hasil analisis kebutuhan. Masing-masing kebutuhan fungsional dan non-fungsional dimodelkan dengan menggunakan usecase diagram dan usecase scenario. Selanjutnya dilakukan perancangan aplikasi yang dijadikan acuan untuk tahapan implementasi. Aplikasi yang dikembangkan merupakan aplikasi berbasis web. Aplikasi diimplementasikan menggunakan beberapa bahasa pemrograman dengan bantaun framework Codeigniter. Selain itu juga diterapkan algoritme genetika sebagai metode untuk menentukan rekomendasi makanan yang sesuai. Pada tahapan pengujian dilakukan pengujian unit, pengujian integrasi, pengujian validasi dan pengujian compatibility. Pengujian ini menghasilkan 100% valid pada 37 kasus uji dan tidak ditemukan issue pada saat pengujian compatibility dengan menggunakan Sortsite.
Co-Authors Abdul Fatih Achmad Yusuf Adam Sulthoni Akbar Adinugroho, Sigit Aditya Chandra Nurhakim Aditya Septadaya Adiyasa, Bhisma Afrialdy, Firman Aghata Agung Dwi Kusuma Wibowo Agi Putra Kharisma Agus Wahyu Widodo Ahmad Afif Supianto Ahmad Afif Supianto Ahmada Bastomi Wijaya Akmal Subakti Wicaksana Alan Primandana Almasyhur, Muhammad Bin Djafar Amalia Luhung Amita Tri Prasasti, Pinkan Anang Tri Wiratno Andhika Satria Pria Anugerah Anggita Mahardika Ani Budi Astuti Ani Rusilowati Anim Rofi'ah Annisa Puspitawuri Annisa Salamah Rahmadhani Arbawa, Yoke Kusuma Aria Bayu Elfajar Arief Andy Soebroto Arjunani, Rusmalistia Intan Ayuri Alfarianti Azhari, Muhammad Rizqi Azizul Hanifah Hadi Barik Kresna Amijaya Bayu Rahayudi Brillian Aristyo Rahadian Budi Astuti Budi Darma Setiawan Chelsa Farah Virkhansa Daneswara Jauhari Daneswara Jauhari, Daneswara Dany Primanita Kartikasari Dennes Nur Dwi Iriantoro Deo Hernando Desy Wulandari Dewanti, Amalya Trisuci Diajeng Tania Ananda Paramitha Dian Eka Ratnawati Dloifur Rohman Alghifari Dwi Fitriani Dwi Novi Setiawan Dwi, Endah Dyang Falila Pramesti Edo Ergi Prayogo Edy Santoso Edy Santoso Erik Aditia Ismaya Eriq Muh. Adams Jonemaro Falih Gozi Febrinanto Faris Febrianto Febri Ramadhani Fenori, Muhammad Dajuma Feri Angga Saputra Fianti Fianti, Fianti Fitri Anggarsari Fitriana, Rosita Nur Fitriani , Dwi Fitriani, Delvi Guntur Syafiqi Adidarmawan Himawan, Alfian Iftinan, Salsa Nabila Ikhwanul Kiram, Muh Zaqi Ilham Harazki Imam Cholisoddin Imam Cholissodin Imam Cholissodin Indah Lestari, Indah Indah Wahyuning Ati Indah, Yuliana Indra Eka Mandriana Indriati Indriati Indriati Indriati Indriati, Indriati - Iqbal Santoso Putra Iskarimah Hidayatin JANAH, NURUL Jumadi Jumadi Khairiyyah Nur Aisyah Kharisma, Agi Krisyanto, Edy Kurnianingtyas, Diva Kurniawan, I Gede Jayadi Kusumawardani, Septyana Dwi Lailil Muflikah Lailil Muflikhah Maharani Tri Hastuti Mardji Mardji Marinda Ika Dewi Sakariana Marinda, Vira Marwa Mudrikatussalamah Maulan, Erika Maulana Putra Pambudi Maulida, Farida Mochammad Tanzil Furqon Mohammad Nuh Mohammad Setya Adi Fauzi Muh Arif Rahman Muhammad Ihsan Diputra Muhammad Misbachul Asrori Muhammad Noor Taufiq Muhammad Prabu Sutomo Muhammad Riduan Indra Hariwijaya Muhammad Tanzil Furqon Muhja Mufidah Afaf Amirah Muhyidin Ubaiddillah Mukh. Mart Hans Luber Nabila Arief Nadia Artha Dewi Naily Zakiyatil Ilahiyah Naniek Kusumawati Nazzun Hanif Ahsani Nirzha Maulidya Ashar Nooriza Fariha Rumagutawan Noval Dini Maulana Novanto Yudistira Nur Hidayat Nur Sa'diyah Nurhidayati Desiani Nurul Faridah, Nurul Nurul Hidayat Nuryatman, Pamelia Nuzula, Nila Firdauzi Pande Made Rai Raditya Phutpitasari, Rosa Devi Pupung Adi Prasetyo Putra Pandu Adikara Putri Aprilia Putu Gede Pakusadewa Rachmalia Dewi Rahma Juwita Sany Randy Cahya Wihandika Ratih Kartika Dewi Rayhan Tsani Putra Reiza Adi Cahya Reza Wahyu Wardani Rifan, Mohamad Rina Christanti, Rina Rizal Setya Perdana Rizal, Moch. Khabibur Robih Dini Rohmah, Yushinta Lailatul Rohmanurmeta, Fauzatul Ma’rufah Rokky Septian Suhartanto Romlah Tantiati Rosyita, Elyana Santoso, Allegra Santoso, Andri Saputra, Rendi Ramadani Saputro, Rinaldi Eko Saputro Sekar Dwi Ardianti Selle, Nurfatima Selvi Marcellia Setya Perdana, Rizal Sigit Pangestu Siti Nurjanah Siti Nurlaela Sundari, Suci Sunyoto Eko Nugroho, Sunyoto Eko Susenohaji, Susenohaji Sutrisno . Syarif, Adnan Tirana Noor Fatyanosa, Tirana Noor Ulfah Mutmainnah Veni, Silvia Wahyu, Dwi Wayan Firdaus Mahmudy Werdha Wilubertha Himawati, Werdha Wilubertha Wiandono Saputro Wilis Biro Syamhuri Wiratama Paramasatya Yasin, Patbessani Septani Firman Yessica Inggir Febiola Yosua Christopher Sitanggang Yudha Eka Permana Yudistira, Indrajati Yuita Arum Sari Yulia Trianandi Yulian Ekananta Yusi Tyroni Mursityo Zulhan, Galang