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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Agri-Informatika Indonesian Journal of Electrical Engineering and Informatics (IJEEI) JUITA : Jurnal Informatika AL ISHLAH Jurnal Pendidikan Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Teknoinfo ILKOM Jurnal Ilmiah Jurnal ULTIMATICS Petir IJISTECH (International Journal Of Information System & Technology) Jurnal Ilmiah Sinus Indonesian Journal of Business Intelligence (IJUBI) JITU : Journal Informatic Technology And Communication Automata Journal of Education Informatic Technology and Science Cakrawala Repositori Imwi Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences IJISTECH Journal Research of Social Science, Economics, and Management
Dhomas Hatta Fudholi
Jurusan Informatika, Universitas Islam Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering 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 Library & Information Science Mathematics Social Sciences Other

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PENGGUNAAN METODE STATIS DAN LIVE FORENSIK PADA UAV UNTUK MENDAPATKAN BUKTI DIGITAL Ibnu Fajar Arrochman; Dhomas Hatta Fudholi; Yudi Prayudi
ILKOM Jurnal Ilmiah Vol 11, No 2 (2019)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i2.444.152-158

Abstract

In recent years, the use of drones by civilians is increasing rapidly by the presentation of total sales continued to increase rapidly every year. With the increasing possibility of Unmanned Aerial Vehicle (UAV) abuse, crime in the use of UAVs to be larger. Through forensic analysis of data using static forensic and live forensic to obtain data that allows it to be used as digital evidence. To dig up information that could be used as digital evidence in the UAV and controllers, as well as to know the characteristics of digital evidence on a UAV. The results showed that digital evidence on a UAV, the smartphone is used as a controller UAV has a very important role in the investigation. The findings in aircraft has a percentage of 50% and a camera memory card with 16.6%. DJI Phantom 3 Advanced GPS coordinates always store data in flight LOG; the data is always stored even when the flight mode is used does not use GPS signals to stability. Due to DJI Phantom 3 Advanced always use GPS on flights, file, image or video captured by the camera has the best GPS location coordinates to the metadata therein.
Manajemen Pengelolaan Bukti Digital Untuk Meningkatkan Aksesibilitas Pada Masa Pandemi Covid-19 Moch Bagoes Pakarti; Dhomas Hatta Fudholi; Yudi Prayudi
Jurnal Ilmiah SINUS Vol 19, No 1 (2021): Vol. 19 No. 1, Januari 2021
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v19i1.502

Abstract

Covid-19 has a major impact on human life, including the process of managing digital evidence. Management of digital evidence requires special handling that can store and maintain the integrity of digital evidence. The current problem is there is no concept of storing digital evidence that can be accessed online in wider accessibility. Online digital evidence management is proposed as a solution to solve this problem. This concept is in the form of an online digital evidence management system that can be accessed anywhere and anytime using MD5 and SHA1 hash functions in order to maintain the properties of digital evidence so that it can be legally accepted. The problems with digital evidence management require a Management System for Digital Evidence that is suitable for application in Digital Forensics Laboratory. This research had successfully implemented the concept of online chain of custody. It is expected, with the concept of Online Digital Evidence Management, this digital evidence control and all activities related to it can be maintained and well documented. Moreover, it can reach a wider area accessed anywhere and any time and reduce the spread of Covid-19.
Pemodelan Topik pada Cuitan tentang Penyakit Tropis di Indonesia dengan Metode Latent Dirichlet Allocation Dziky ridhwanulah; Dhomas Hatta Fudholi
Jurnal Ilmiah SINUS Vol 20, No 1 (2022): Vol. 20 No. 1, Januari 2022
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v20i1.589

Abstract

Indonesia has a wide area and society. Therefore, a lot of information appear through social media, especially Twitter. This study aims to find out about conversation topics discussed by Indonesian people related to tropical diseases especially leprosy, malaria, and dengue fever. To find out the discussion topics, it can use the modeling topics analysis. One of the methods in topic modeling is Latent Dirichlet Allocation (LDA). Tweet data on tropical diseases in Indonesia was analyzed through this method. The study results showed that LDA was succeed in modeling the trend of Indonesian people's conversation topics related to tropical diseases. It obtained as many as 5 topics with a coherence value of 0.576453. Based on the results of the topic modeling, it can be concluded that the topics are such as the used funds to eradicate malaria and dengue fever, covid-19, blindness and leprosy, and its treatments and preventions.
KARAKTERISTIK METADATA PADA SHARING FILE DI MEDIA SOSIAL UNTUK MENDUKUNG ANALISIS BUKTI DIGITAL Dimas Pamilih Epin Andrian; Dhomas Hatta Fudholi; Yudi Prayudi
Jurnal Ilmiah SINUS Vol 19, No 1 (2021): Vol. 19 No. 1, Januari 2021
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v19i1.494

Abstract

Metadata is information in a file which its contents are an explanation of the file. Metadata contains information about the contents of data for file management purposes. In various cases involving digital evidence, investigators can uncover a case through the metadata file. Problems that arise when file metadata has changed or deleted information, for example, the moment that a file is shared via social media. Basically, all of the shared files through social media will experience changes in metadata information. This study conducted detailed analysis of changes in metadata information and hex dump values to determine the changing characteristics of metadata files shared in social media. This research method applied a comparison table to see the details of changes in metadata values from all files and social media as research objects. The results of this study are expected to have contribution for forensic analysts to identify the shared metadata characteristics of files in social media. As a result, later, the source of shared files in social media will be known. Moreover, it is expected from these findings that forensic analysts can explore the social media used by the cybercrime perpetrators.
Analisis Faktor Penerimaan Layanan e-Government dengan Menggunakan Model UTAUT2 dan GAM di Kabupaten Gunungkidul Eko Setiawan; Wing Wahyu Winarno; Dhomas Hatta Fudholi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 1 (2021): Januari 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i1.2565

Abstract

Government through Presidential Regulation No. 95 of 2018 concerning SPBE supports and realizes clean, effective and transparent government governance so that it has quality and trusted public services. To improve society using e-government based services, it is necessary what factors influence a person to use e-government services. This study uses the UTAUT2 research model and the Government Adoption Model (GAM) to determine the factors that influence a person using e-government in Gunungkidul. This study used the PLS SEM measurement method and found that the factors that influence e-government acceptance are effort expectation, facilitating conditions, and computer self-efficacy.
Sistem Konten Pembelajaran di Indonesia : Systematic Literature Review Dhomas Hatta Fudholi; Insanur Hanifuddin; Sri Mulyati
Ultimatics : Jurnal Teknik Informatika Vol 13 No 1 (2021): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v13i1.1948

Abstract

Wikipedia is the largest web-based digital encyclopedia today that contains almost all knowledge in general. On Wikipedia many readers have difficulty finding accurate information about the topic they are looking for, as content on Wikipedia usually contains only an overview of the topic referenced from some existing references. This study aims to examine Wikipedia, other encyclopedias and other online media that contain specific topics with their target users. The study was conducted on literature related to Wikipedia, encyclopedias, education and children's interests, especially at the elementary school level. Literature search is done by including some of the main keywords in Google Scholar such as "Wikipedia", "encyclopedia", "elementary school curriculum", "educational content" and "learning media". Literature is also obtained through the official website of the Ministry of Education and Culture which contains elementary and junior high school education standards, educational assessment standards, and literacy and numeration learning modules at elementary level. The results of literature analysis include 4 classifications based on topics, namely evaluation of usage, content, online learning and media. Based on the results of the analysis found that there has not been much research on the digital encyclopedia for education.
Deep Learning for Aspect-Based Sentiment Analysis on Indonesian Hotels Reviews Siwi Cahyaningtyas; Dhomas Hatta Fudholi; Ahmad Fathan Hidayatullah
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vo. 6, No. 3, August 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i3.1300

Abstract

Tourism is one of the fastest-growing industries. Many travelers book hotels and share their experiences using travel e-commerce sites. To improve the quality of products and services, we can take advantage by analyzing their reviews. We can see the good and the bad thing reviews in every aspect of the hotel. However, research to analyze sentiment in every aspect using Indonesian hotel reviews is still relatively new. In this work, we propose to create an Aspect-based Sentiment Analysis (ABSA) using Indonesian hotel reviews to solve the problem. This research consists of four steps: collecting data, preprocessing, aspect classification, and sentiment classification. Our classification process compares with eight deep learning methods (RNN, LSTM, GRU, BiLSTM, Attention BiLSTM, CNN, CNN-LSTM, and CNN-BiLSTM). In aspect classification, we have six classes of aspects which are harga (price), hotel, kamar (room), lokasi (location), pelayanan (service), and restoran (restaurant). In sentiment analysis, we compared two scenarios to classify sentiments as positive or negative. The first one is to classify sentiment in all aspects, and the second one is to classify sentiment in every aspect. The results showed that LSTM achieved the best model for aspect classification with an accuracy value of 0.926. For sentiment classification, our experiments showed that classify sentiment in every aspect achieved a better result than classify sentiment in all aspects. The result showed that the CNN model gets an average accuracy score of 0.904.
A Study on Visual Understanding Image Captioning using Different Word Embeddings and CNN-Based Feature Extractions Dhomas Hatta Fudholi; Annisa Zahra; Royan Abida N. Nayoan
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 1, February 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i1.1394

Abstract

Image captioning is a task that can provide a description of an image in natural language. Image captioning can be used for a variety of applications, such as image indexing and virtual assistants. In this research, we compared the performance of three different word embeddings, namely, GloVe, Word2Vec, FastText and six CNN-based feature extraction architectures such as, Inception V3, InceptionResNet V2, ResNet152 V2, EfficientNet B3 V1, EfficientNet B7 V1, and NASNetLarge which then will be combined with LSTM as the decoder to perform image captioning. We used ten different household objects (bed, cell phone, chair, couch, oven, potted plant, refrigerator, sink, table, and tv) that were obtained from MSCOCO dataset to develop the model. Then, we created five new captions in Bahasa Indonesia for the selected images. The captions might contain details about the name, the location, the color, the size, and the characteristics of an object and its surrounding area. In our 18 experimental models, we used different combination of the word embedding and CNN-based feature extraction architecture, along with LSTM to train the model. As the result, models that used the combination of Word2Vec + NASNetLarge performed better in generating Indonesian captions than the other models based on BLEU-4 metric.
Kajian Algoritma Optimasi Penjadwalan Mata Kuliah Tri Handayani; Dhomas Hatta Fudholi; Septia Rani
PETIR Vol 13 No 2 (2020): PETIR (Jurnal Pengkajian Dan Penerapan Teknik Informatika)
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33322/petir.v13i2.1027

Abstract

Penjadwalan mata kuliah merupakan hal penting yang dilakukan pada awal semester akademik. Proses penyusunan jadwal kuliah secara manual seringkali mengalami kesulitan karena terdapat beberapa konstrain sehingga membutuhkan waktu yang lama. Penelitian ini bertujuan mengkaji algoritma-algoritma yang sesuai dengan masalah penjadwalan mata kuliah. Pencarian dan analisis dilakukan terhadap literatur yang berkaitan dengan optimasi penjadwalan. Proses pencarian literatur dilakukan pada Google Scholar dan Science Direct dengan memasukkan kata kunci utama “course timetable”, “university timetable problem”, “school scheduling”, dan “algoritma penjadwalan”. Hasil analisis literatur meliputi sebaran domain, analisis algoritma serta gap dari penelitian sebelumnya. Pada penelitian sebelumnya terdapat kekurangan seperti algoritma yang tidak dapat menghasilkan solusi optimal. Hasil sebaran domain yang diperoleh ialah universitas dan sekolah dengan persentase 88% dan 12% dari keseluruhan makalah. Adanya temuan 14 sebaran algoritma dapat diklasifikasikan menjadi 3 metode, yaitu heuristic, metaheuristic, dan hyper-heuristic. Berdasarkan hasil analisis, dapat diberikan beberapa rekomendasi. Untuk optimasi yang cepat, Simulated Annealing (SA) dapat menjadi solusi karena mampu menghasilkan solusi dengan waktu 0.481-10.102s. Untuk solusi waktu dan nilai fitness terbaik, Genetic Algorithm (GA) dapat menjadi solusi karena mampu menghasilkan solusi dengan waktu 0.964-73.461s dan nilai fitness 1.
Kajian Pengaruh Dataset dan Bias Dataset terhadap Performa Akurasi Deteksi Objek Ridho Iman Tiyar; Dhomas Hatta Fudholi
PETIR Vol 14 No 2 (2021): PETIR (Jurnal Pengkajian Dan Penerapan Teknik Informatika)
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33322/petir.v14i2.1350

Abstract

Deteksi objek merupakan kemampuan sistem yang dapat mengenali objek tertentu yang berada dalam suatu gambar atau video. Dalam proses deteksi objek, sistem bisa memberikan hasil yang tidak sesuai atau tidak dapat mendeteksi suatu objek yang disebabkan oleh dataset yang tidak optimal. Penelitian ini bertujuan mengkaji proses pembuatan dataset dan bias yang muncul. Pencarian dan analisis dilakukan terhadap literatur yang berkaitan dengan dataset deteksi objek. Proses pencarian literatur dilakukan pada Google Scholar, Science Direct, dan DSpace Repository dengan memasukkan kata kunci utama “data centric”, “object detection dataset”, dan “dataset bias”. Hasil analisis literatur meliputi dataset dan bias dataset. Pada penelitian sebelumnya terdapat kekurangan seperti belum adanya peningkatan performa sistem deteksi objek melalui pengoptimalan dataset. Dari kajian literatur, pembuatan dataset yang baik dapat dilakukan dengan cara menyesuaikan kondisi pengambilan gambar saat pengumpulan data dan pengujian di lapangan. Selain itu, untuk dapat menambah kemampuan generalisasi sistem dengan cara menambahkan variasi gambar dalam dataset melalui teknik augmentasi. Selanjutnya, dalam proses pembuatan dataset pasti akan selalu ada bias dalam data sehingga mempengaruhi kemampuan deteksi objek. Oleh karena itu, dalam proses pembuatan sistem deteksi objek, data memiliki pengaruh yang cukup besar terhadap performa akurasi deteksi objek.
Co-Authors Abdullah Aziz Sembada Abdullah Aziz Sembada ABDURRAHIM Abyan Fadilla Noor Aditya Perwira Joan Dwitama Affan Taufiqur Afrianto, Nurdi Ahmad Fathan Hidayatullah, Ahmad Fathan Ahmad Luthfi Ahmad Rafie Pratama Altesa Yunistira Andi Wafda Andri Heru Saputra Annisa Zahra Ari Farhan Nurihsan Ari Sujarwo Arief Rahman Arrie Kurniawardhan Arrie Kurniawardhani Arrie Kurniawardhani Chandra Kusuma Dewa Dendy Surya Darmawan Deny Rahmalianto Dimas Adi Wibowo Dimas Danu Budi Pratikto Dimas Pamilih Epin Andrian Dimas Panji Eka Jalaputra Dirgahayu, Raden Teduh Dziky ridhwanulah Eko Prasetio Widhi Eko Setiawan Erin Eka Citra Fahmi Adi Nugraha Ferdian Nursulistio Fery Luvita Sari Gilang Persada Bhagawadita Gunanto Gunanto Harry Akbar Al Hakim Ibnu Fajar Arrochman Insanur Hanifuddin Iqbal Syauqi Mubarak Izzan Yattaqi Nugraha Izzati Muhimmah Jaka Nugraha LAILA KUSUMA WARDANI Lizda Iswari M. Ulil Albab Surya Negara Malik Abdul Aziz Mawar Hardiyanti Meilita . Moch Bagoes Pakarti Moch Yusuf Asyhari Muhammad Abyanda Tamaza Muhammad Habib Izdhihar Muhammad Rizhan Ridha Muhammad Sulthon Alif Novian Mahardika Putra Prastyo Eko Susanto Purwoko, Agus Raden Teduh Dirgahayu Rahadian Kurniawan Rakhmat Syarifudin Rendy Ressa Sutrisno Ridho Iman Tiyar Ridho Rahmadi Risca Naquitasia Royan Abida N. Nayoan Sabar Aritonang Rajagukguk Safira Yuniar Putri Buana Salma Aufa Azaliarahma Salsabila Zahirah Pranida Septia Rani Septia Rani Sigit Nugroho Siti Mutmainah Siwi Cahyaningtyas Sri Mulyati Teduh Dirgahayu Tri Handayani Umar Abdul Aziz Al-Faruq Wahyu Fajrin Mustafa Wahyuzi, Zikri windi astriningsih Yasmin Aulia Ramadhini Yoga Sahria Yudi prayudi Yurio Windiatmoko