Article Per Year (5 Year)
p-Index From 2021 - 2026
9.296
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) CommIT (Communication & Information Technology) Jurnal Transformatika JUITA : Jurnal Informatika Journal of Information Systems Engineering and Business Intelligence Indonesian Journal on Computing (Indo-JC) Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Knowledge Engineering and Data Science Jurnal CoreIT JURNAL MEDIA INFORMATIKA BUDIDARMA JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Pertahanan : Media Informasi tentang Kajian dan Strategi Pertahanan yang Mengedepankan Identity, Nasionalism dan Integrity DoubleClick : Journal of Computer and Information Technology Journal of Information Technology and Computer Engineering JURIKOM (Jurnal Riset Komputer) Logista: Jurnal Ilmiah Pengabdian Kepada Masyarakat KOMPUTIKA - Jurnal Sistem Komputer Jurnal Riset Informatika Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Building of Informatics, Technology and Science Jurnal Teknologi Informasi dan Multimedia RADIAL: JuRnal PerADaban SaIns RekAyasan dan TeknoLogi Jurnal Teknik Elektro dan Komputasi (ELKOM) Jurnal E-Komtek Indonesian Journal of Electrical Engineering and Computer Science Journal of Computer System and Informatics (JoSYC) Madani : Indonesian Journal of Civil Society Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Jurnal Teknik Informatika (JUTIF) Journal of Informatics and Vocational Education Teknika ICTEE (Engineering Journals of Information, control, telecommunication and electrical) Insyst : Journal of Intelligent System and Computation Journal of Dinda : Data Science, Information Technology, and Data Analytics IJCOSIN : Indonesian Journal of Community Service and Innovation Journal of Embedded Systems, Security and Intelligent Systems El-Mujtama: Jurnal Pengabdian Masyarakat JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) RADIAL: Jurnal Peradaban Sains, Rekayasa dan Teknologi Jurnal Komtika (Komputasi dan Informatika) Jurnal Kajian Ilmu dan Teknologi (JKIT)
Faisal Dharma Adhinata
Institut Teknologi Telkom Purwokerto
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Social Sciences Other

Published : 70 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 70 Documents
Search

 1   2   3   4   5 
Perancangan Mobile Ad-Hoc Network Mengunakan Optimasi Routing AOMDV Aditya Wijayanto; Alon Jala Tirta Segara; Faisal Dharma Adhinata
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3352

Abstract

Natural disasters are unpredictable events of the time and place that occur. In fact, natural disasters in Indonesia often make the destruction of an area that can cause the destruction of facilities in the region. Disaster events make regional communication usually cut off, so it requires backup communication tools in the event of a disaster. Backup communications can be built using infrastructure without a network. In this research we will design a network system where we will try to use the system to select some good ad hoc mobile protocols for sending data. The movement of each node means that each node is the data sent. The proposed service may also provide such services. . However, since there is no access to banks in disaster areas, the use of electronic currency for online transactions has become limited. Therefore, the secure payment system will be centered on our offline transactions after conducting simulations and looking at the existing comparison values then we get a conclusion about the results of the parameter trial in the end to end delay test parameters in this simulation we also get the best value that on node 50 is 3.2 seconds and on node 30 get a value of 15.03 seconds this happens because there is a 50
Review: Metode-Metode Ekstraksi Ciri dan Klasifikasi Identifikasi Pembicara Faisal Dharma Adhinata; Nur Ghaniaviyanto Ramadhan
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 1 (2022): Januari 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i1.3469

Abstract

Identifying a person's identity still often uses an ID card (KTP, SIM, passport, etc.). This method has a weakness because the ID Card is easily damaged and lost. Biometric recognition systems provide a solution by using human body parts as identity recognition. Sounds are readily available biometric information. Voice pattern recognition is used for the speaker identification process to obtain the identity of someone speaking. This paper reviews several feature extraction and classification methods that are often used in speaker identification. The selection of feature extraction methods and classification functions in computation and the level of accuracy of the speaker identification system. Based on the survey dataset applied with the feature extraction method, the Mel Frequency Cepstral Coefficients (MFCC) method has high accuracy even with noise input. Then in classification, the Gaussian Mixture Model (GMM) method is most often used because it can work in noise. Recently, a hybrid classifier has been developed, which increases the accuracy value.
AGILE SOFTWARE DEVELOPMENT ON DESIGN AND LAYOUT OF BOOKING ROOM WEBSITE (CASE STUDY: WITEL TELKOM YOGYAKARTA) Reva Rahardian; Ananda Aulia Rizky; Narantyo Maulana Adhi Nugraha; Faisal Dharma Adhinata; Annisaa Utami
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 1 (2022): JUTIF Volume 3, Number 1, February 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.1.132

Abstract

Online booking is one way to find and order easily using media connected using the internet network so that it can be accessed anywhere and anytime easily so that it can increase time effectiveness. One of the applications is Telkom Room which functions to help Telkom employees to book meeting rooms online to make them easier to use and don't need to come to the office and contact them to use them. The Booking Room website also uses the agile development method because the software development process requires a relatively short period and does not require enormous resources. Therefore, changes can be handled more quickly according to client needs and provide feedback to the development team in the manufacturing process. The existence of this Booking Room website can help facilitate the user in the room booking process so that the user does not have to come directly to the office and so that it is fast and easy to carry out the meeting process that will be held.
WEB-BASED APPLICATION WITH SDLC WATERFALL METHOD ON POPULATION ADMINISTRATION AND REGISTRATION INFORMATION SYSTEM (CASE STUDY: KARANGKLESEM VILLAGE, PURWOKERTO) Teguh Rijanandi; Tri Dimas Cipto Satrio Wibowo; Ikadhanny Yudyan Pratama; Faisal Dharma Adhinata; Annisaa Utami
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 1 (2022): JUTIF Volume 3, Number 1, February 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.1.145

Abstract

Based on research conducted in one of the Neighborhood Associations (RT) in Karangklesem Village, South Purwokerto found that a population administration and recording system did not use computer technology. Our authors created a web-based village information system design using CodeIgniter based on this research. The software development method used is the Software Development Life Cycle (SDLC) Waterfall method. With the software that we have developed, it is hoped to help facilitate all administrative matters and village records that are currently still manual. The design we made uses the PHP programming language version 7.4 CodeIgniter framework with a MySQL database. We hope that this system design can reduce human errors in recording administration.
PENERAPAN HAIR RECOGNITION MENGGUNAKAN METODE HAAR CASCADE CLASSIFIER DAN CNN DEEP LEARNING Teguh Rijanandi; Andra Aulia Rizaldy; Adam Nur Kridabayu; Emmanuel Genesius Evan Devara; Faisal Dharma Adhinata
JURNAL ILMU KOMPUTER Vol 8 No 1 (2022): Edisi April
Publisher : LPPM Universitas Al Asyariah Mandar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35329/jiik.v8i1.214

Abstract

Zaman modernisasi seperti saat ini, proses identifikasi berkembang sangat pesat dan banyak diterapkan di berbagai aplikasi. Teknologi pengenalan rambut menggunakan Artificial Intelligence untuk mengenali rambut seseorang. Penelitian ini menggunakan pengenalan rambut real-time berbasis OpenCV dan algoritma histogram pola biner lokal dan metode Haar Cascade classifier untuk mengklasifikasikan jenis-jenis rambut yang ada. Sistem disini dapat mendeteksi, selain itu mengenali serta serta membandingkan rambut yang ditangkap kamera yang ada didalam database rambut yang sudah tersimpan. Citra rambut yang digunakan adalah citra RGB dengan ukuran 480 x 680 piksel dan berekstensi .jpg atau .png yang dapat diubah kedalam citra grayscale agar dapat melakukan pengkasifikasian jenis rambut. Dengan memodelkan sistem seperti ini diharapkan dapat membantu masyarakat dalam mengklasifikasikan jenis-jenis rambut.
Mendeteksi Kematangan Pada Buah Mangga Garifta Merah Dengan Transformasi Ruang Warna HSI Ahmad Muslih Syafi’i; Muhammad Fajar Ahadi; Muhammad Iqbal Rasyid; Faisal Dharma Adhinata; Apri Junaidi
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3217

Abstract

Garifta Mango is obtained from the combination of the best quality local mangoes. Garifta mango is said to have a sweeter taste variant than the quality of other types of mango. However, when choosing Red Garifta mangoes with a good level of ripeness, we are often confused. Sometimes Red Garifta mango entrepreneurs still use manual methods to distinguish the ripeness of Red Garifta mangoes. Therefore, this study carried out a systematic design using the HSI color space transformation method. We used 15 Red Garifta mangoes as test data and 30 Red Garifta mangoes as training data in the testing phase. After doing the test, we get the accuracy, precision, and recall of 15 test data, respectively 80%, 80%, and 87%. From this percentage value, it can be concluded that the method we use can be used to detect the ripeness of the Red Garifta mango fruit.
Comparison of Supervised Learning Methods for COVID-19 Classification on Chest X-Ray Image Faisal Dharma Adhinata; Nur Ghaniaviyanto Ramadhan; Arif Amrulloh; Arief Rais Bahtiar
CommIT (Communication and Information Technology) Journal Vol. 16 No. 2 (2022): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v16i2.7970

Abstract

The Coronavirus (COVID-19) pandemic is still ongoing in almost all countries in the world. The spread of the virus is very fast because the transmission process is through air contaminated with viruses from COVID-19 patients’ droplets. Several previous studies have suggested that the use of chest X-Ray images can detect the presence of this virus. Detection of COVID-19 using chest X-Ray images can use deep learning techniques, but it has the disadvantage that the training process takes too long. Therefore, the research uses machine learning techniques hoping that the accuracy results are not too different from deep learning and result in fast training time. The research evaluates three supervised learning methods, namely Support Vector Machine (SVM), K-Nearest Neighbor (K-NN), and Random Forest, to detect COVID-19. The experimental results show that the accuracy of the SVM method using a polynomial kernel can reach 90% accuracy, and the training time is only 462 ms. Through these results, machine learning techniques can compensate for the results of the deep learning technique in terms of accuracy, and the training process is faster than the deep learning technique. The research provides insight into the early detection of COVID-19 patients through chest X-Ray images so that further medical treatment can be carried out immediately.
Deteksi Berita Palsu Menggunakan Metode Random Forest dan Logistic Regression Nur Ghaniaviyanto Ramadhan; Faisal Dharma Adhinata; Alon Jala Tirta Segara; Diovianto Putra Rakhmadani
JURIKOM (Jurnal Riset Komputer) Vol 9, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i2.3979

Abstract

Fake news is information that is presented incorrectly or falsely. Of course, if the spread of fake news continues, it can result in wrong knowledge of the information obtained. One of the efforts to prevent the spread of fake news is by detecting whether the news is genuine or fake in order to provide an explanation to the readers of the related news. This study aims to detect fake news using a supervised learning random forest model. The news dataset used contains 6256 rows of titles that have a fake or real class. The dataset first goes through a cleaning, tokenization, and stemming process to break sentences into words. The results obtained using the random forest model of 84%, this result is higher than using the logistic regression model of 77%.
Sentiment analysis on vaccine COVID-19 using word count and Gaussian Naïve Bayes Nur Ghaniaviyanto Ramadhan; Faisal Dharma Adhinata
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1765-1772

Abstract

Since the Coronavirus disease 2019 (COVID-19) pandemic hit the world, it had a significant negative impact on individuals, governments, and the global economy. One way to reduce the negative impact of COVID-19 is to vaccinate. Briefly, vaccination aims to enable the formed immune system to remember the characteristics of the targeted viral pathogen and be able to initiate an immune response that is rapid and strong enough to defeat future live viral pathogens. However, there are still many people in the world who are anti-vaccine. This certainly greatly hampers the process of accelerating the formation of the body's immune system widely in the community. Anti-vaccine people can be found on various social media platforms. Twitter was chosen as the data source because twitter is a common source of text for sentiment analysis. This study aims to analyze public sentiment on the COVID-19 vaccine through twitter in the form of tweets and retweets. This study uses the Gaussian Naïve Bayes method to see the results of the classification of sentiment analysis. The results obtained based on experiments prove that the Gaussian Naïve Bayes method can produce an average accuracy of 97.48% for each vaccine dataset used.
DIAGNOSIS SYSTEM IN CHICKEN DISEASE USING FORWARD CHAINING METHOD Annisaa Utami; Faisal Dharma Adhinata; Yaqutina Marjani Santosa
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 3 (2022): JUTIF Volume 3, Number 3, June 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.3.179

Abstract

Chickens are animals that are mostly kept by the community both on a large and small scale traditionally. Because the population is large, the disease is also more complex, from mild disease to diseases that can be transmitted to humans so that it can cause death such as bird flu. Diseases in chickens such as Newcastle Disease (ND), Infectious Bronchitis (IB), Gumboro Disease and Flu. Problems about chicken disease faced requires a system to help in diagnosing diseases in chickens. Expert system is a system in which a variety of knowledge comes from an expert so that users can consult. Forward Chaining method is a method of searching or forward-looking where tracking begins with information that da and combine rules to produce an expected conclusion or goal. The study used 9 disease data, 34 symptom data and 20 cases of chicken disease. The results of the accuracy test get a value of 90%. The purpose of this study is: diagnosing chicken disease as a first step to applying artificial intelligence in the medical world, designing and applying systems. Based on the data, it can be concluded that the protythepe expert system by implementing the Forward Chaining Method can help farmers and chicken owners in diagnosing chicken diseases.
Co-Authors Abdul Majid Abdurrahman Ibnul Rasidi Adam Nur Kridabayu Adil El-Faruqi Aditya Wijayanto Aditya, Gilang Afzal Ziqri Agustyn, Zulfa Basmallah Ahmad Muslih Syafi’i Ajeng Fitria Rahmawati Akhmad Jayadi Aldhan Tri Maulana Alfan Adi Chandra Alissyah Putri Alon Jala Tirta Segara Alya Aulia Hanafi Ananda Aulia Rizky Ananda Aulia Rizky Andra Aulia Rizaldy Anshari Rusmeniar R.A Apri Junaidi, Apri Arief Rais Bahtiar Arif Amrulloh Ariq Cahya Wardhana Bagus Bayu Sasongko Bita Parga Zen Christoph Quix Christyan, Timothy Condro Kartiko Dani Azka Faz Darmawan, Bagus Tri Yulianto Dayal Gustopo Setiadjit Dian Nugraha Diovianto Putra Rakhmadani Emmanuel Genesius Evan Devara Fadlan Raka Satura Fajar Malik Falah Arfani Fauzi, Muhammad Dzulfikar Fawwaz Muhammad Zulfikar Febry Ardiansyah Firdonsyah, Arizona Fitran Dwi Pramakrisna Fitran Dwi Pramakrisna Gilang Aditia GITA FADILA FITRIANA Gracia Rizka Pasfica Hendrowati, Retno Herman Yuliansyah Herman Yuliansyah, Herman Hidayat, Wahrul Hussien, Nur Syahela Ibnul Rasidi, Abdurrahman Ikadhanny Yudyan Pratama Irsyad Zulfikar Jahfal Rizqi Putra Pradhana Kridabayu, Adam Nur Lisan, Fauzan Fashihul M Alfian Maulana Al Azhar Merlinda Wibowo Metha Khafifah Isty Rikhanah Mohammad Rifqi Zein Muhammad Arif Saputra Muhammad Fajar Ahadi Muhammad Ikhsan Muhammad Iqbal Rasyid Muhammad Pajar Kharisma Putra Nainggolan, Purnama Dileon Yamora Narantyo Maulana Adhi Nugraha Naseh Hibban Nasution, Annio Indah Lestari Nia Annisa Ferani Tanjung Nike Prasetyo Nisrina Eka Salsabila Novi Rahmawati Novi Rahmawati Nugraha, Aditya Rizkiawan Nugraha, Narantyo Maulana Adhi Nur Ghaniaviyanto Ramadhan Nur Syahela Hussien Nursatio Nugroho Pasaribu, Yolanda Al Hidayah Purnama Dileon Yamora Nainggolan Putra, Muhammad Daffa Arviano Putro, Iwan Nofi Yono Quix, Christoph Rachma Wukir Purwitasari Raden Sumiharto Rahardian, Reva Rahmanda Trinova Putra Ramadhan, Faiz Zaki Renna Nur Injiyani Reva Rahardian Riadi, Daffa Rayhan Rifki Adhitama, Rifki Rifqi Akmal Saputra Rifqi Alfinnur Charisma Rival Fahmi Hidayat Rizki Rafiif Amaanullah Rohman Beny Riyanto Saputra, Rifqi Akmal Saputro, Satria Nur Satria Adi Nugraha Satrio Wibowo Sayyid Yakan Khomsi Pane Shalma, Hastin Ajeng Sofiyudin Pamungkas Suheryadi, Adi Teguh Rijanandi Teguh Rijanandi Teguh Rijanandi Tri Dimas Cipto Satrio Wibowo Try Susanto Ummi Athiyah Utama, Safitri Yuliana Utami, Annisaa Vincent Nathaniel Wahyono Wahyono Wibowo, Merlinda Widi Widayat Wijayanto, Danur Winanto, Tawang Sahro Yaqutina Marjani Santosa Yohani Setiya Rafika Nur Yolanda Al Hidayah Pasaribu Yuni nur fari'ah Zanuar Rahmat Saputra Ziqri, Afzal