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All Journal Jurnal Masyarakat Informatika Semantik Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Jurnal Transformatika Scientific Journal of Informatics JAIS (Journal of Applied Intelligent System) ANDHARUPA Journal of Information System ITEj (Information Technology Engineering Journals) Edu Komputika Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Budimas : Jurnal Pengabdian Masyarakat Abdimasku : Jurnal Pengabdian Masyarakat Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Bumi: Jurnal Hasil Kegiatan Sosialisasi Pengabdian Kepada Masyarakat
Erika Devi Udayanti
Universitas Dian Nuswantoro, Semarang
Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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HYBRID WATERMARKING CITRA DIGITAL MENGGUNAKAN TEKNIK DWT-DCT DAN SVD Erwin Yudi Hidayat Yudi Hidayat; Erika Devi Udayanti
Semantik Vol 1, No 1 (2011): Prosiding Semantik 2011
Publisher : Semantik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (618.964 KB)

Abstract

Sebagai salah satu teknik perlindungan data multimedia, watermarking telah banyak dikembangkan. Teknik watermarking dapat dilakukan pada domain transformasi, dengan menggabungkan metode Discrete Wavelet Transform (DWT) dan Discrete Cosine Transform (DCT).Watermarking pada citra digital harus memperhatikan tiga kriteria: security, robustness, dan imperceptibility. Dua kriteria terakhir merupakan hal yang paling sering bertentangan pada watermarking domain transformasi. Singular Value Decomposition (SVD) sebagai salah satu metode yang paling populer dari aplikasi aljabar linear telah banyak dimanfaatkan dalam pengolahan sinyal termasuk watermarking. Penggabungan DWT-DCT dan SVD ditujukan untuk mengatasi konflik di antara robustness dan imperceptibility. Nilai Peak Signal to Noise Ratio (PSNR) dan Normalized Cross Correlation (NC) yang diperoleh dari percobaan menyatakan bahwa skema hybrid watermarking ini menghasilkan watermark yang tahanterhadap berbagai serangan, serta kualitas yang tinggi dari citra yang disisipi watermark. Hal ini menunjukkan bahwa konflik antara robustness dan imperceptibility yang muncul pada watermarking domain transformasi dapat diatasi.Kata kunci : Watermarking, DWT, DCT, SVD
Visualisasi dan Rekonstruksi 3D Citra Medis: Review Candra Irawan; Erika Devi Udayanti; Fajar Agung Nugroho
Semantik Vol 3, No 1 (2013): Semantik 2013
Publisher : Semantik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (458.278 KB)

Abstract

Kajian ini bertujuan untuk memberikan literature review dalam visualisasi citra medis 3D  (tiga dimensi ruang)  dan teknik rekonstruksi citra. Masing-  masing teknik rekonstruksi dan penerapannya akan dipaparkan. Surface rendering dan volume rendering adalah teknik rekonstruksi  citra 3D  yang paling banyak digunakan. Algoritma marching cube  sebuah algoritma isosurfacing merekonstruksi model 3D dari kumpulan citra 2D  (dua dimensi ruang)  yang mempunyai singgungan. Marching Squares menghasilkan contour guna memilih thresholds dalam rekonstruksi 3D.  Pada bagian ahir, kajian ini juga akan memaparkan bahasan mengenai beberapa software aplikasi yang digunakan dalam pengolahan visualisasi citra medis seperti MIPAV, VTK, dan IDL.
DESAIN FRAMEWORK MULTIMEDIA QUEUEING SYSTEM BERBASIS ANDROID ANTRIAN PASIEN PUSKESMAS Erika Devi Udayanti; Fajar Agung Nugroho
Techno.Com Vol 14, No 3 (2015): Agustus 2015 (Hal. 165-241)
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (246.806 KB) | DOI: 10.33633/tc.v14i3.946

Abstract

Saat ini antrian di puskesmas masih dilakukan dengan metode konvensional, yaitu dengan menumpuk kartu registrasi. Metode seperti ini memungkinkan kartu menjadi terselip. Selain itu, penumpukan kartu yang tidak benar dapat mengakibatkan urutan menjadi tidak sesuai dengan urutan yang seharusnya. Pasien yang datang lebih ahir dimungkinkan untuk dapat dilayani lebih awal dari pasien yang sudah lama menunggu. Penelitian ini mengusulkan multimedia queueing system berbasis android untuk layanan antrian pasien puskesmas. Sistem ini mencatat antrian di dalam database server, sehingga tidak ada kartu yang terselip ataupun salah tumpuk. Lebih lanjut lagi, penelitian ini akan mengangkat kecanggihan mesin android sebagai input device. Sedangkan untuk output devicenya, menggunakan portable bluetooth printer dan layar LCD. Setiap pasien yang datang dapat mencetak tiket antrian dengan menyentuh tombol pada layar mesin android. Mesin android tersebut kemudian akan mencetak tiket melaui printer portable yang disediakan dan mengirim nomor antrian ke database server. Selain itu, mesin android ini juga memotret wajah pasien yang masuk, dan file foto akan dikirim beserta nomor antrian ke server. Pada saat giliran pasien tiba, layar LCD akan menampilkan nomor antrian pasien beserta fotonya. Metode ini diharapkan mampu menyelesaikan problem kartu registrasi terselip, dan juga membantu pasien yang buta huruf/angka. Kata Kunci: puskesmas, sistem antrian, android
IMPLEMENTASI FIREBASE CLOUD MESSAGING PADA EMERGENCY CALL BERBASIS ANDROID Etika Kartikadarma; Widi Widayat Yutriatmansyah; Erika Devi Udayanti; Nisa'ul Hafidhoh
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 10, No 2 (2019): JURNAL SIMETRIS VOLUME 10 NO 2 TAHUN 2019
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v10i2.3196

Abstract

Tindak asusila atau kriminalitas merupakan satu dari banyak faktor serius yang dapat mengancam keselematan atau bahkan nyawa seseorang. Tindak kejahatan atau kriminalitas yang dilakukan baik oleh individu maupun kelompok (komplotan) dapat terjadi dimana saja dan kapan saja. Kebutuhan akan rasa aman menjadi suatu kebutuhan yang sangat penting. Kesadaran masyarakat akan kewaspadaan terhadap tindak kejahatan yang bisa terjadi pun meningkat. Perkembangan perangkat teknologi informasi dan komunikasi meningkat dengan pesat. Penelitian ini mengusulkan solusi berbasis teknologi yang dapat diimplementasikan untuk mengatasi situasi darurat korban kejahatan dengan aplikasi Emergency Call berbasis Android. Penerapan Firebasse Cloud Messaging digunakan untuk menjalankan Push Notification pada Android. Dengan pengembangan aplikasi Emergency Call ini diharapkan dapat mengurangi resiko akibat kejahatan yang lebih serius.
Keyphrase Extraction on Covid-19 Tweets Based on Doc2Vec and YAKE Fahri Firdausillah; Erika Devi Udayanti
Journal of Applied Intelligent System Vol 6, No 1 (2021): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v6i1.4454

Abstract

Keyword and keyphrase extraction are one of the initial foundations for performing several text processing operations such as summarization and document clustering. YAKE is one of the techniques used for unsupervised and independent keyphrase extraction, it does not require a corpus for linguistic tools such as NER and POS-tag. However, the use of YAKE in microblogging documents such as Twitter often results in a keyphrase that is less representative because of the lack of words used for ranking. This paper offers a solution to this problem by looking for similar tweets in the keyphrase extraction process using Doc2Vec so that the number of words used in the YAKE ranking process can be greater. Covid-19 tweets related are used as dataset as the topic is currently widely discussed on social media to prove that the proposed approach could improve keyphrase extraction performance
Analisis Sentimen Masyarakat Terhadap Layanan Shopeefood Melalui Media Sosial Twitter Dengan Algoritma Naïve Bayes Classifier Farah Syadza Mufidah; Sri Winarno; Farrikh Alzami; Erika Devi Udayanti; Ramadhan Rakhmat Sani
JOINS (Journal of Information System) Vol 7, No 1 (2022): Edisi Mei 2022
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1882.622 KB) | DOI: 10.33633/joins.v7i1.5883

Abstract

Twitter adalah salah satu media sosial dan fasilitas microblogging yang menjadi tempat bagi penggunanya berbagi pengalamannya secara bebas, realtime, dan bersifat publik. Hal ini dapat menjadikan twitter sebagai sumber informasi yang dapat berupa opini, ataupun komentar yang bersifat positif maupun negatif. Dari opini masyarakat tersebut dapat diimplementasikan sebagai tolak ukur, karena memiliki nilai bagi suatu perusahaan agar dapat menjadi bahan evaluasi untuk menentukan langkah dalam meningkatkan layanannya. Oleh karena itu untuk mengolah opini tersebut dibutuhkan teknik analisis sentimen untuk dapat mengidentifikasi opini baik positif maupun negatif. Pada penelitian ini akan menganalisis tweet berbahasa Indonesia dengan topik layanan yang ada pada E-commerce shopee yaitu layanan ShopeeFood yang sedang populer dikalangan masyarakat saat ini. Metode yang akan digunakan untuk analisa sentimen pada penelitian ini yaitu Naïve Bayes Classifier untuk proses mengklasifikasi. Berdasarkan hasil pengujian klasifikasi tweet pada penelitian ini dibuktikan keakuratan yang didapatkan melalui confusion matrix dengan nilai accuracy sebesar 90,62%, precision sebesar 88,23%, dan recall sebesar 93,75%. Kata kunci: Analisis Sentimen, Teks Mining, Naïve Bayes Classifier, Twitter, ShopeeFood
Sistem Deteksi Surel SPAM Dengan DNSBL Dan Support Vector Machine Pada Penyedia Layanan Mail Marketing Fahri Firdausillah; Muhammad Hafidz; Erika Devi Udayanti; Etika Kartikadarma
Journal of Information System Research (JOSH) Vol 3 No 4 (2022): Juli 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (581.527 KB) | DOI: 10.47065/josh.v3i4.1795

Abstract

Mail marketing is an effective communication medium for users and internet providers. Many companies use email as a mean of communication with customers to ensure customers are not left behind with the latest information, and at once provide personalized offers to specific customers. However, not all emails that are sent reach mail inbox as expected. There are several factors as the cause including content that does not comply with the writing rules and tends to have SPAM signatures, invalid e-mail addresses, the sender domains are registered in the blacklist and so forth. Mail marketing service providers such as MTarget and Mailchimp must ensure that emails sent by their customers have no potential to become spam, because it can affect all of their mail marketing services will be blacklisted, thus promotional goals will not be achieved. In that case, a system is needed to check the e-mail that will be sent by the customer, to ensure that the e-mail will not detected as a spam by email service applications such as Gmail. This research produces an email validator system that can prevent sending emails that have the potential to become SPAM, so as to reduce the risk of a mail marketing service provider being blacklisted which results in delays in promotion via email and a decrease in marketing turnover. The proposed method used in this research is the Domain Name System-Based Blackhole List (DNSBL) to check the IP and the sending domain and the Support Vector Machine (SVM) to check the content of the email to be sent. The system developed has been functioning as expected and has an accuracy rate of 97.54% in detecting SPAM emails.
Testing the Budhara Digital Book Application (Borobudur Dalam Cerita) Sri Mulatsih; Raden Arief Nugroho; Valentina Widya Suryaningtyas; Aloysius Soerjowardhana; Ali Muqoddas; Erika Devi Udayanti
Journal of Applied Intelligent System Vol 7, No 3 (2022): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v7i3.7286

Abstract

Borobudur Temple is one of the icons of Indonesian tourism in the world. Unfortunately, tourists, domestic and foreign, do not have knowledge of the importance of the existence of Borobudur Temple as a cultural heritage. Evidence of the lack of knowledge of domestic tourists about the conservation of Borobudur Temple is reflected in the vandalism of thousands of people who left stains on the Borobudur stone. This has the potential to damage the rock layers of the temple. Foreign tourists themselves are also seen as lacking comprehensive knowledge about Borobudur Temple. They know a lot about the history of Borobudur, but do not understand the history of the villages surrounding the supporters of Borobudur Temple. The history of the villages around Borobudur is an important element in supporting Borobudur as a cultural heritage. In addition, efforts are needed to maintain tourist interest in visiting Borobudur Temple and the surrounding villages during the limited number of visitors. For this reason, a way is needed to educate the general public about the history and conservation efforts of the Borobudur Temple and the surrounding villages which have historical and geographical links. Based on these problems, the researchers developed a digital book called Buddhara (Borobudur Dalam Cerita) and has been testing using questionnaire.
COVID-19 Suspects Monitoring System Based on Symptom recognition using Deep Neural Network Erika Devi Udayanti; Etika Kartikadharma; Fahri Firdausillah; Nur Ikhsan
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 2 No 1 (2023): March 2023
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v2i1.2073

Abstract

The outbreak of the Corona virus or COVID-19 was still a global concern even though it has been declared an endemic in several countries in the world, including Indonesia. However, with the emergence of new variants of this virus, preventive efforts continue to be made to prevent its spread. To prevent the spread of this virus, early detection was important, especially in knowing prospective clients who are positive and reactive to this virus, thus enabling early isolation measures for prospective patients who are taking action. This identification can be carried out in public areas that are the center of community activities. In this study, an intelligent system will be developed that can detect people suspected of COVID-19 through fever and breathing problem symptoms that can provide solutions to prevent the spread of this virus. Identify these symptoms through thermography-based image processing sourced from thermal camera sensors and then look for the possibility of suspected and reactive COVID19. Furthermore, the AI model was used by the early detection system of people suspected of being positive and reactive for COVID-19 using the Deep Neural Network method. This study aims to identify symptoms of fever and respiratory infection through image processing sourced from thermal camera sensors and further diagnose prospective patients who are suspected of being positive and reactive for COVID19 using the CNN method as an intelligent system for early detection of suspected positive and reactive COVID19 patientsIn the process of testing the classification training model, the performance results in the CNN classification process have an accuracy value of more than 88%. Furthermore, a comparison was made between the CNN classification and other classifications, such as SVM, Naive Bayes and Multi-Layer Perceptron (MLP). The results obtained from this comparison have an average percentage of accuracy above 80%. MLP has the lowest accuracy among its classification methods of 83.56%. CNN has the highest accuracy value compared to other methods of 88.68%. Therefore, CNN can be chosen to be the right one for use in the COVID-19 suspect detection system through the recognition of symptoms and respiratory disorders. Based on these performance measurements, the process of detecting COVID19 suspects indicated by health symptoms can be applied to real data.
Implementation of the K-Nearst Neighbor (k-NN) Algorithm in Classification of Angora and Country Cats Andriana, Wiwin; Wisnumurti, Reza; Lestari, Yuni; Indriyono, Bonifacius Vicky; Wibowo, Dibyo Adi; Udayanti, Erika Devi
Journal of Applied Intelligent System Vol. 8 No. 1 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i1.7129

Abstract

There are so many types of mixed cats from various cat breeds, so many people find it difficult to identify and classify them. Therefore, we need a method that can classify the type of cat breeds. In this study the authors used the K-Nearest Neighbor (k-NN) algorithm to make it easier to recognize and classify cat breeds based on certain characteristics. The author took samples of 2 types of cat races, namely the Anggora race and the Kampung race. The implementation stage is to determine the euclidean distance and sort it and then determine the value of K to find the nearest neighbor. In testing, the authors used 50 training data and 50 test data with 6 attributes used, namely body shape, nose width, nose height, food type, hair type and hair length. The results of the classification of cat breeds using the k-NN method obtained an accuracy rate of 94% and an error rate of 6%.
Co-Authors Affandy Affandy Afida, Dita Ahmad MAULANA Aisyatul Karima ALI MUQODDAS Ali Muqoddas Aloysius Soerjowardhana Alzami, Farrikh Andriana, Wiwin Anggadiva, Rifky Anwarri, Kenza Amalia Putri Arika Norma Wahyu Dorroty Aritonang, Ivana Junita Bonifacius Vicky Indriyono Bonifacius Vicky Indriyono, Bonifacius Vicky Candra Irawan Chornelius Aneba Moza Ikratama Christiawan Yosua Hertinando Christy Atika Sari Comara, Maulana Muhammadin Dian Restu Adji Dibyo Adi Wibowo Djuniadi Djuniadi Doheir, Mohamed Dwi Puji Prabowo, Dwi Puji Erba Lutfina Erwin Yudi Hidayat Yudi Hidayat Ery Mintorini Etika Kartikadarma Etika Kartikadharma Fahri Firdausillah Fajar Agung Nugroho Fajar Agung Nugroho Fajar Agung Nugroho Fajrian Nur Adnan Farah Syadza Mufidah Febrianto, Kevin Florentina Esti Nilawati Gery Gadman Rachmad Hafidhoh, Nisa'ul Hafidhoh, Nisa?ul Hafidhoh, Nisa’ul Hafidhoh, Nisa’ul Hafidhoh, Nisa’ul Ikhsan, Nur Iqlima Zahari Karmila Karmila Kartikadharma, Etika Lutfina, Erba Megantara, Rama Aria Mellati, Pita Muhammad Agus Muljanto Muhammad Hafidz Muna, Mohamad Sirojul Natalinda Pamungkas Natalinda Pamungkas Nisa'ul Hafidhoh Nur Ikhsan Nur Iksan Pratiwi, Yunita Ayu Putra, Yogi Pratama Raden Arief Nugroho Ramadhan Rakhmat Sani Sanina Quamila Putri Sanjaya, Yusuf Yudha Soerjowardhana, Aloysius Sri Mulatsih Sri Winarno Sri Winarno Syafira Putri Yuanita Valentina Widya Suryaningtyas, Valentina Widya Widayat Yutriatmansyah, Widi Widi Widayat Yutriatmansyah Wildan Mahmud Wisnumurti, Reza Yuni Lestari Yutriatmansyah, Widi Widayat Yutriatmansyah, Widi Widayat Zahari, Iqlima  Ignasius Yoga Puji Hascaryo