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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

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Pendekatan Deep Learning Untuk Prediksi Durasi Perjalanan Nur Ghaniaviyanto Ramadhan; Yohani Setiya Rafika Nur; Faisal Dharma Adhinata
Teknika Vol. 11 No. 2 (2022): Juli 2022
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v11i2.460

Abstract

Setiap orang dalam kehidupan memiliki kecenderungan untuk berpindah dari satu tempat ke tempat lainnya. Perpindahan tersebut dapat dilakukan dengan menggunakan berbagai macam cara seperti menggunakan transportasi pribadi atau umum (bus, taksi, pesawat, dan kereta api), Pada perkembangan teknologi saat ini mode transportasi sudah semakin canggih. Akan tetapi masih ada mode transportasi yang belum modern misalnya seperti taksi, dimana salah satunya tidak dapat memprediksi lama waktu perjalanan. Meskipun sudah ada taksi yang berbasis online seperti Uber, akan tetapi masih banyak taksi yang belum berbasis online sehingga tidak bisa dilakukan estimasi waktu dan jarak. Permasalahan di atas dapat diselesaikan dengan cara melakukan pendekatan berbasis pembelajaran mesin. Salah satu keuntungan yang didapatkan jika kita dapat mengetahui lama waktu estimasi perjalanan yaitu dapat mengatur waktu perjalanan sesuai dengan rutinitas yang sedang dikerjakan ataupun juga dapat menghemat biaya yang dikeluarkan dengan mengetahui jarak yang akan dijalankan. Pada penelitian ini bertujuan untuk memprediksi durasi perjalanan pada dataset New York taxi trip duration menggunakan pendekatan deep learning yaitu Long Short Term Memory Reccurent Neural Network (LSTM-RNN). Eksperimen dilakukan dengan melakukan tuning parameter terkait seperti epoch, nilai dropout, dan neurons. Pengukuran hasil menggunakan nilai Root Mean Square Error (RMSE) dan nilai loss. Hasil yang didapatkan menggunakan model LSTM-RNN sebesar 0,0012 untuk nilai loss dan RMSE 0,4.
Aplikasi Klasifikasi SMS Berbasis Web Menggunakan Algoritma Logistic Regression Fitran Dwi Pramakrisna; Faisal Dharma Adhinata; Nia Annisa Ferani Tanjung
Teknika Vol. 11 No. 2 (2022): Juli 2022
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v11i2.466

Abstract

Jenis SMS spam adalah jenis pesan teks yang tidak diinginkan atau tidak diminta yang dikirim ke ponsel pengguna, seringkali untuk tujuan komersial. Untuk mengatasi masalah spam, diperlukan teknik untuk memilah kata atau kalimat termasuk spam atau bukan spam. Pada penelitian ini diusulkan menggunakan machine learning untuk mengklasifikasikan pesan mana yang spam dan mana yang tidak spam. Data yang digunakan pada penelitian ini terdiri dari 1140 pesan, dimana sudah diberi label 0 untuk pesan yang tidak spam dan 1 untuk pesan yang spam. Algoritma yang digunakan untuk kasus ini adalah Logistic Regression. Hasil penelitian menunjukkan model memiliki tingkat akurasi untuk mengklasifikasi pesan, sebesar 97%. Aplikasi yang dikembangkan untuk menerapkan hasil pemodelan machine learning menggunakan bentuk sebuah website sederhana dengan bantuan Flask framework dari Python. Hasil akhir dari aplikasi ini adalah model machine learning yang dapat dibuka melalui website.
Pengenalan Jenis Kelamin Manusia Berbasis Suara Menggunakan MFCC dan GMM Faisal Dharma Adhinata; Diovianto Putra Rakhmadani; Alon Jala Tirta Segara
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 1 No 1 (2021): February
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (686.041 KB) | DOI: 10.20895/dinda.v1i1.198

Abstract

Biometric information that exists in humans is unique from one human to another. One of the biometric data that is easily obtained is the human voice. The human voice is identic data that can differentiate between individuals. When we hear human voices directly, it is easy for our ears to tell the person who is speaking is male or female. But sometimes male voices can resemble girls and vice versa. Therefore, we propose a human voice detection system through Artificial Intelligence (AI) in machine learning. In this study, we used the Mel Frequency Cepstrum Coefficients (MFCC) method to extract human voice features and Gaussian Mixture Models (GMM) for the classification of female or male voice data. The experiment results showed that the system built was able to detect human gender through biometric voice data with an accuracy of 81.18%.
Perancangan UI/UX Webinar Booking Terhadap Kepuasan Pengguna Menggunakan Metode Design Thinking Rachma Wukir Purwitasari; Purnama Dileon Yamora Nainggolan; Novi Rahmawati; Faisal Dharma Adhinata; Nur Ghaniaviyanto Ramadhan
JURIKOM (Jurnal Riset Komputer) Vol 8, No 6 (2021): Desember 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v8i6.3700

Abstract

In order to meet user needs, designing an exemplary user interface requires in-depth knowledge of design principles and guidelines and an understanding of the multi-component design space. Multi-components are the image parts that can be used, their layout options, and visual effects options. This research was conducted to meet user needs. With the Design Thinking method, we can find out the user's needs and adjust to the user's interests. With the Webinar Booking application, it is hoped to be a solution for today's life
A Hybrid DenseNet201-SVM for Robust Weed and Potato Plant Classification Muhammad Dzulfikar Fauzi; Faisal Dharma Adhinata; Nur Ghaniaviyanto Ramadhan; Nia Annisa Ferani Tanjung
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 2 (2022): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i2.23886

Abstract

Potato plant growth needs to be protected from weeds that grow around it. Currently, the manual spraying of pesticides by farmers is not only precise on weeds but also on cultivated plants. Therefore, we need an intelligent system that can appropriately classify potato plants and weeds. The research contribution combines feature extraction and appropriate classification methods to obtain optimal accuracy. In addition, the small amount of data also contributes to this research. In this research, it is proposed to use a combination of feature extraction using deep learning techniques and classification using machine learning. We use the feature extraction method with the DenseNet201 model because this study's data is not too much. Complex vectors from DenseNet201 were reduced using Principal Component Analysis (PCA). Then we classified it with the Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) classification methods. The experimental results show that the PCA method can reduce the complexity of high-dimensional features into 2 and 3 dimensions. The average of the best classification results using SVM was obtained with a 3-dimensional PCA configuration, but on the contrary, using KNN obtained the best results in a 2-dimensional PCA configuration. The results showed 100% accuracy on the DenseNet201-SVM hybrid. The SVM kernel configuration used is a linear kernel. The results of this study can be an insight into an accurate classification method for separating weeds and potatoes so that agricultural technology can apply this method for classification.
Sistem Penilaian Inovasi Karyawan Digital Amoeba Menggunakan Desain Arsitektur Microservice Pada Aplikasi Mobile Fitran Dwi Pramakrisna; Faisal Dharma Adhinata; Nia Annisa Ferani Tanjung
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 3 (2022): Juli 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i3.4187

Abstract

Digital Amoeba employees want an application system that can be integrated directly into the Ideabox application to be assessed the innoavtions directly. Therefore, innovations do not need to be assessed using third parties such as Google Sheets SurveyMonkey. Therefore, an application system called Scoring was created. This application system is designed using a microservice architecture design, where each service has its own database. The services used in the Scoring application system are User Service, Ideas Service, Event Service, and Scoring Service. The application system is built using the PHP programming language and the CodeIgniter version 4 framework. This system is implemented both on web and mobile platform
Implementasi Website Rahayu River Tubing sebagai Media Promosi dan Reservasi bagi Wisatawan Faisal Dharma Adhinata Adhinata; Diovianto Putra Rakhmadani; Alon Jala Tirta Segara; Nur Ghaniaviyanto Ramadhan
Madani : Indonesian Journal of Civil Society Vol. 4 No. 2 (2022): Madani, Agustus 2022
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/madani.v4i2.1439

Abstract

Community service aims to implement website-based information technology as a media for promoting Rahayu River Tubing tourism and its reservation. The attractions offered are Tubing, Pangasinan Waterfall, Pengkol Hill, and Pedestal View. Before this website, promotions were only carried out on social media, and reservations were still manual by contacting the manager directly. This community service method is by identifying problems, developing the Rahayu River Tubing website at the address http://rahayurivertubing.com, and evaluating activities. This activity was attended by 15 participants from the manager and tour guide held at the Rahayu River Tubing basecamp. At the end of the activity, feedback is given to evaluate this community service activity. There are five statements on the questionnaire with an average result of 99%. These results indicate that community service partners are delighted with the socialization and training on the use of the Rahayu River Tubing tourism website.
Analisis Penerapan Metode Ensembled Learning Decision Tree Pada Klasifikasi Virus Hepatitis C Rifqi Alfinnur Charisma; Sofiyudin Pamungkas; Rifqi Akmal Saputra; Nur Ghaniaviyanto Ramadhan; Faisal Dharma Adhinata
Journal of Computer System and Informatics (JoSYC) Vol 3 No 4 (2022): August 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i4.2064

Abstract

Hepatitis C virus is a deadly virus that attacks the liver. This virus can cause chronic infections, even 80% of sufferers have experienced an illness. To minimize the risk of exposure to disease caused by the hepatitis C virus, consultation with a doctor or using an intelligent detection system can be conducted. Of course, if used a smart strategy, our need data that already contains parameters related to hepatitis C. This study uses a public dataset that the public can access. So, the purpose of this study is to classify patients with hepatitis C virus using a tree-based algorithm. The results obtained by applying the proposed algorithm are 93% accuracy, 92% precision, and 91% recall. This study also performs comparisons with other methods, namely naive bayes. The results show that the tree-based way is superior.
Prediksi Gaji Berdasarkan Pengalaman Bekerja Menggunakan Metode Regresi Linear Irsyad Zulfikar; Muhammad Arif Saputra; Nike Prasetyo; Teguh Rijanandi; Faisal Dharma Adhinata
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 2 No 2 (2022): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v2i2.548

Abstract

Industri tidak bisa dipisahkan dari adanya sumber daya manusia (SDM). Walaupun industri memiliki teknologi yang maju dan juga modern, namun berhasilnya suatu perusahaan tak lepas dari jasa para sumber daya manusia yang unggul. Dengan begitu perlu bagi perusahaan untuk memperhatikan para pekerjanya. Salah satu usaha untuk meningkatkan mutu SDM yaitu dengan pemberian gaji berdasarkan pengalaman kerja. Ketika seseorang yang sudah lama bekerja di suatu perusahaan maka gajinya akan semakin naik. Penelitian ini ditujukan guna menganalisis prediksi gaji karyawan berdasarkan lama tahun bekerja. Dalam penelitian ini faktor pengujianya menggunakan variable (X) sebagai faktor pemicu terhadap variable (Y) konsekuensi. Metode yang digunakan dalam riset ini yaitu menggunakan metode Regresi linier. Kemudian kami menggunakan survey kuesioner kepada 30 responden sebagai metode pengambilan data.
Perancangan Basis Data Menggunakan Normalisasi Tabel Pada Perusahaan Dagang Barokah Abadi Sayyid Yakan Khomsi Pane; Nur Ghaniaviyanto Ramadhan; Faisal Dharma Adhinata
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 2 No 2 (2022): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v2i2.563

Abstract

Many human activities are related to information systems. Not only in developed countries, in Indonesia, information systems have been widely applied everywhere, such as in offices, supermarkets, airports, and even at home when users interact with the internet. Increased company operations in business activities can not be separated from information technology. The use of information technology is one of the effective steps in data processing, as well as business transactions using increasingly sophisticated computer equipment. A good database design plays a very important role in the performance and smooth running of an agency. So, in this research, a database design will be carried out with table normalization using MySQL at the Barokah Abadi trading company. This research also designs using entity relationship diagram (ERD).
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