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All Journal International Journal of Electrical and Computer Engineering Techno.Com: Jurnal Teknologi Informasi Bulletin of Electrical Engineering and Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTECOMS: Journal of Information Technology and Computer Science Jurnal Mantik Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Pendidikan Indonesia (Japendi)
Dhani Ariatmanto
Universitas Amikom Yogyakarta
Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice

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Image watermarking based on integer wavelet transform-singular value decomposition with variance pixels Ferda Ernawan; Dhani Ariatmanto
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (882.464 KB) | DOI: 10.11591/ijece.v9i3.pp2185-2195

Abstract

With the era of rapid technology in multimedia, the copyright protection is very important to preserve an ownership of multimedia data. This paper proposes an image watermarking scheme based on Integer Wavelet Transform (IWT) and Singular Value Decomposition (SVD). The binary watermark is scrambled by Arnold transform before embedding watermark. Embedding locations are determined by using variance pixels. Selected blocks with the lowest variance pixels are transformed by IWT, thus the LL sub-band of 8×8 IWT is computed by using SVD. The orthogonal U matrix component of U3,1 and U4,1 are modified using certain rules by considering the watermark bits and an optimal threshold. This research reveals an optimal threshold value based on the trade-off between robustness and imperceptibility of watermarked image. In order to measure the watermarking performance, the proposed scheme is tested under various attacks. The experimental results indicate that our scheme achieves higher robustness than other scheme under different types of attack.
Understanding the role of individual learner in adaptive and personalized e-learning system Alva Hendi Muhammad; Dhani Ariatmanto
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.3192

Abstract

Dynamic learning environment has emerged as a powerful platform in a modern e-learning system. The learning situation that constantly changing has forced the learning platform to adapt and personalize its learning resources for students. Evidence suggested that adaptation and personalization of e-learning systems (APLS) can be achieved by utilizing learner modeling, domain modeling, and instructional modeling. In the literature of APLS, questions have been raised about the role of individual characteristics that are relevant for adaptation. With several options, a new problem has been raised where the attributes of students in APLS often overlap and are not related between studies. Therefore, this study proposed a list of learner model attributes in dynamic learning to support adaptation and personalization. The study was conducted by exploring concepts from the literature selected based on the best criteria. Then, we described the results of important concepts in student modeling and provided definitions and examples of data values that researchers have used. Besides, we also discussed the implementation of the selected learner model in providing adaptation in dynamic learning.
Data Mining Untuk Klasifikasi Produk Menggunakan Algoritma K-Nearest Neighbor Pada Toko Online Ma’ruf Aziz Muzani; M. Iqbal Abdullah Sukri2; Syifa Nur Fauziah; Agus Fatkhurohman; Dhani Ariatmanto
Prosiding SISFOTEK Vol 5 No 1 (2021): SISFOTEK V 2021
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (404.365 KB)

Abstract

The rapid growth of e-commerce in Indonesia has been largely facilitated by the presence of e-marketplaces. The e-marketplace trend in Indonesia continues to develop along with the development of technology and the internet. During its development, e-marketplaces offer more and more products. As a result, buyers need more effort to find the product they want. In order to facilitate the search for these products, a product classification is carried out. This study classifies products in the Shopee emarketplace using the K-Nearest Neighbor algorithm. The product data used comes from web scraping in the categories of cellphones and accessories, Muslim fashion, and home appliances. The stages of the classification system begin with the preprocessing stage, then the term weighting stage uses the TF-IDF method, then cosine similarity to calculate the similarity distance between documents, and then sorting the results of the cosine similarity to retrieve data for the number of k values. Based on testing on 9 product data with three different k values. Obtained an average that shows the lowest accuracy, precision, and recall results when the value of k = 3. The accuracy result is 88.89%, precision is 83.33%, and a recall of 100% is obtained when using the value of k = 5 or k = 7.
Utilization of Information Technology for Tourism Development of Lake Kelimutu, Ende Regency, East Nusa Tenggara With a Virtual Tour Based on Mobile Web Emanuel Minggu; Bambang Soedijono; Dhani Ariatmanto
Jurnal Mantik Vol. 6 No. 3 (2022): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The development of technology that is increasingly rapid day by day, gives rise to many new innovations from technology. One of the technological development innovations is virtual tours which are starting to be widely used, for example in some applications to introduce a location. However, the use of virtual tour applications as a medium for promoting tourism in Indonesia is still very small. Virtual tour Kelimutu lake tourism in Ende regency, East Nusa Tenggara, was created to be able to visually display information from the natural attractions of lake kelimutu The development methodology used in this study is the Multimedia Development Life Cycle (MDLC) methodology which is a multimedia software design method that emphasizes the 6 stages of multimedia development with this virtual tour users can see the state of 3600 natural lake attractions kelimutu made with immersive photography techniques. By presenting information in the form of a 3600 panoramic image, it makes it easier for users to visually display information from the tourist attraction
Analisis Penerapan Audio Ducking Dalam Paska Produksi Multimedia dengan Metode Basic dan Multiband Sidechain Compression Maulana Brama Shandy; Ema Utami; Dhani Ariatmanto
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 12, No 1: April 2023
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v12i1.1177

Abstract

This study addresses the issue of inaudible speech in multimedia content due to the lack of post-production techniques, particularly in the ducking process, which remains a persistent problem in the audio engineering industry. This study presents two methods of sidechain compression: basic sidechain compression and multiband compression, aimed at improving the quality of speech in multimedia content. Using a comparative analysis of the two compression methods, this paper recommends the most suitable method for each musical genre that will be used in multimedia content. This research offers valuable insights for media industry professionals and audio processing researchers, as it provides a better understanding of the role of sidechain compression in enhancing the quality of multimedia content. The results of the study demonstrate the effectiveness of the compression methods in improving the quality of dialog in multimedia content. Keywords: Audio Processing; Sidechain Compression; Speech intelligibility; Audio Ducking; Multimedia  AbstrakStudi ini membahas masalah ketidakjelasan dialog pada konten multimedia karena kurangnya teknik pasca-produksi, terutama pada proses ducking, yang masih menjadi masalah yang persisten dalam industri rekayasa audio. Studi ini mempresentasikan dua metode sidechain compression: basic sidechain compression dan multiband compression, yang bertujuan untuk meningkatkan kualitas pidato dalam konten multimedia. Dengan melakukan analisis perbandingan dari kedua metode kompresi, tulisan ini merekomendasikan metode yang paling cocok untuk setiap genre musik yang akan digunakan dalam konten multimedia. Penelitian ini memberikan wawasan berharga bagi profesional industri media dan peneliti pemrosesan audio, karena memberikan pemahaman yang lebih baik tentang peran sidechain compression dalam meningkatkan kualitas konten multimedia. Hasil penelitian menunjukkan efektivitas metode kompresi dalam meningkatkan kualitas dialog/narasi dalam konten multimedia.
Classification of Acute Lymphoblastic Leukemia based on White Blood Cell Images using InceptionV3 Model Rizki Firdaus Mulya; Ema Utami; Dhani Ariatmanto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 4 (2023): August 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i4.5182

Abstract

Acute lymphoblastic leukemia (ALL) is the most common form of leukemia that occurs in children. Detection of ALL through white blood cell image analysis can help with the prognosis and appropriate treatment. In this study, the author proposes an approach to classifying ALL based on white blood cell images using a convolutional neural network (CNN) model called InceptionV3. The dataset used in this research consists of white blood cell images collected from patients with ALL and healthy individuals. These images were obtained from The Cancer Imaging Archive (TCIA), which is a service that stores large-scale cancer medical images available to the public. During the evaluation phase, the author used training data evaluation metrics such as accuracy and loss to measure the model's performance. The research results show that the InceptionV3 model is capable of classifying white blood cell images with a high level of accuracy. This model achieves an average ALL recognition accuracy of 0.9896 with a loss of 0.031. The use of CNN models such as InceptionV3 in medical image analysis has the potential to improve the efficiency and precision of image-based disease diagnosis.
Identifikasi Penyakit Tanaman Jagung Berdasarkan Citra Daun Menggunakan Convolutional Neural Network Bima Widianto; Ema Utami; Dhani Ariatmanto
Techno.Com Vol 22, No 3 (2023): Agustus 2023
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/tc.v22i3.8425

Abstract

Komoditas jagung di Indonesia menjadi tanaman pangan terbesar kedua setelah padi sebagai sumber karbohidrat. Namun dikarenakan keterbatasan kemampuan petani dan faktor lingkungan menyebabkan upaya penanganan tanaman jagung akibat adanya serangan organisme pengganggu tanaman menjadi terhambat. Penelitian ini mengusulkan upaya deteksi secara dini terhadap jenis penyakit pada daun tanaman jagung menggunakan metode Convolutional Neural Network (CNN) yang dikenal sebagai algoritma pembelajaran mesin berkinerja tinggi dalam mengklasifikasikan jenis penyakit tanaman ke dalam beberapa kelas seperti Blight, Common Rust, Grey Leaf Spot, dan Healthy. Selain itu, transformasi warna citra dari RGB, HSV dan Grayscale, proses segmentasi dengan Region of Interest (ROI) serta dilengkapi dengan penerapan ektraksi fitur tekstur dengan menggunakan GLCM telah mampu menghasilkan tingkat akurasi sebesar 94% dan nilai loss rate yang relatif kecil yaitu 0.1742. Hasil penelitian ini menunjukkan bahwa penggunaan metode CNN terbukti secara efisien & efektif dalam melakukan identifikasi jenis penyakit tanaman.
Sentiment Analysis of BNI Mobile Application Using The K-Nearest Neighbor Algorithm (KNN) With Particle Swarm Optimization (PSO) Feature Selection Dewi Yustika Lakoro; Ema Utami; Dhani Ariatmanto
INTECOMS: Journal of Information Technology and Computer Science Vol 6 No 2 (2023): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v6i2.7912

Abstract

Analysis sentiment is field studies analyze opinions, sentiments, evaluations, attitudes and emotions to entity like products, services, organizations, individuals, issues, events, films and topics. Sentiment analysis first succeed used previously in various fields, such as movie ratings, service ratings, product ratings, etc. and recently This get popularity in the field economy especially on e- commerce applications. Moment This industry banking do various innovation finance that is shift their focus from banking traditional to banking based technology for fulfil need customers as well as For increase Power competitive. Mobile banking is one of them from innovation that. Response in use of this mobile banking application enter every the day with amount response as much hundreds so that response the difficult For sorted become responses included positive or including negative response. Study This using private data which is comment BNI Mobile banking application in the application laystore. Existing data Then will be done preprocessing with do a number of stages, ie started from tokenization, stemming, stopword removal and Term Frequency Inverse Document Frequency (TF-IDF) was carried out. Initial process carried out in classification is accept input comment data then the preprocessing process is carried out, then included in the classification model, method classification used is K-Nearest Neighbor with particle swarm optimization Optimization and finally is the results issued is accuracy from method used. After That researcher do optimization use one algorithm optimization namely PSO with combine with KNN or called KNN-PSO gain accuracy of 92.33% or only has an error of 7.67%. If seen from the amount of data is successful do classification as many as 277 data, in meaning only has 23 errors or missing data succeed classified with good.
Deteksi Penyakit Gigi dan Mulut Menggunakan Algoritma Inception-V3 Detection of Dental and Oral Diseases Using Inception-V3 Dloifur Rohman Al Ghifari; Ema Utami; Dhani Ariatmanto
Jurnal Pendidikan Indonesia Vol. 6 No. 4 (2025): Jurnal Pendidikan Indonesia
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/japendi.v6i4.7649

Abstract

Kesehatan gigi dan mulut sangat penting bagi kesejahteraan umum, namun banyak orang mengabaikan pengobatan karena kurangnya kesadaran atau tantangan diagnostik. Metode diagnostik tradisional sering kali kurang akurat dan efisien. Penelitian ini bertujuan mengembangkan sistem otomatis untuk mengklasifikasikan penyakit gigi dan mulut menggunakan algoritma deep learning Inception-V3 guna meningkatkan akurasi diagnostik. Penelitian menggunakan dataset 8.776 citra oral yang diseimbangkan dengan SMOTE dan diproses dengan teknik augmentasi. Inception-V3 dilatih dan dibandingkan dengan CNN, VGG-16, ResNet50, serta model machine learning tradisional. Model Inception-V3 mencapai akurasi 94%, mengungguli model lain (CNN: 81%, VGG-16: 88.7%, ResNet50: 76.25%) dan menunjukkan stabilitas tanpa overfitting. Studi ini menegaskan potensi Inception-V3 dalam analisis gambar medis, menawarkan alat diagnostik yang andal untuk deteksi dini penyakit gigi dan mulut, sehingga dapat meningkatkan hasil layanan kesehatan.
Co-Authors Adrianto Mahendra Wijaya Agus Fatkhurohman Alva Hendi Muhammad annisa gatri zakinah Ari Eka Prasetiyanto Bambang Soedijono Bima Widianto Dewi Yustika Lakoro Dloifur Rohman Al Ghifari Ema Utami Fatihatul Khairani Ferda Ernawan M. Iqbal Abdullah Sukri2 Maulana Brama Shandy Ma’ruf Aziz Muzani Minggu, Emanuel Rizki Firdaus Mulya Syifa Nur Fauziah