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All Journal JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi) Computatio : Journal of Computer Science and Information Systems INTECOMS: Journal of Information Technology and Computer Science MIND (Multimedia Artificial Intelligent Networking Database) Journal Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Jurnal Bakti Masyarakat Indonesia Infotech: Journal of Technology Information Jurnal Mandala Pengabdian Masyarakat International Journal Software Engineering and Computer Science (IJSECS) Joutica : Journal of Informatic Unisla Al-Khidmah Jurnal Pengabdian Masyarakat Prosiding Seri Seminar Nasional Internet of Things and Artificial Intelligence Journal Jurnal Serina Abdimas
Novario Jaya Perdana
Universitas Tarumanagara
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PENDETEKSIAN JUMLAH PENUMPANG YANG MASUK BERDASARKAN CCTV PADA PINTU BUS DENGAN METODE YOLO Vincent Marcellino; Viny Christanti Mawardi; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 10 No. 2 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v10i2.22539

Abstract

Salah satu cara untuk mengurangi kemacetan pada kota besar adalah dengan mengubah pola pikir masyarakat untuk lebih menggunakan kendaraan umum, kendaraan umum bus merupakan salah bentuk dari kendaraan umum. Namun kelebihan penumpang pada kendaraan umum merupakan permasalahan yang dapat ditemukan. Perancangan pendeteksian jumlah penumpang ini bertujuan untuk membantu melakukan perhitungan jumlah penumpang dari kendaraan umum menggunakan kamera, guna mendeteksi jumlah penumpang dalam kendaraan umum. Perancangan ini menggunakan algoritma YOLO (You Only Look Once), algoritma ini digunakan karena memiliki performa pendeteksian yang cepat pada skenario pendeteksian secara real-time. Perancangan ini menggunakan data berupa gambar yang telah dipecah dari video untuk kemudian digunakan sebagai data latih, data uji, dan data validasi. Setelah melakukan proses pengujian dengan 50 data video untuk pintu masuk dan pintu keluar, hasil yang didapatkan berupa 82% untuk tingkat akurasi perhitungan penumpang pada data video pintu masuk dan 72% untuk tingkat akurasi perhitungan penumpang pada data video pintu keluar.
APLIKASI PENCARIAN PROPERTI DI JAKARTA DENGAN METODE ANALYTIC NETWORK PROCESS DAN TOPSIS Yagyu Munenori M.E.; Viny Christanti Mawardi; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 10 No. 2 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v10i2.22542

Abstract

There have been several buying and selling applications that are intended to help bring together buyers, sellers, or agents in finding the house criteria needed. But there are still conditions where buyers find it difficult to find the house or property of their dreams. At the same time sellers are also difficult to find the right buyer. For that we need an application that can realize a search application with property recommendation features that can be used to find the best unit that suits their wishes. The methods used are the Analytic Network Process and TOPSIS methods. The ANP method is used because of the consideration of the interrelationships between elements at different levels. TOPSIS method is also used to be able to display more accurate results in terms of ranking. From the recommendation test, 90% of the 10 tests were obtained and the percentage result was 94.1% from 17 respondent tests. Based on these tests, it is known that the error occurred because the data was not found. The absence of property data in accordance with the Criteria can be caused by filling out invalid criteria and can also be caused by a lack of variation in property data.
KLASIFIKASI PENYAKIT KULIT MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK (CNN) DENGAN ARSITEKTUR VGG16 Supirman Supirman; Chairisni Lubis; Danu Yuliarto; Novario Jaya Perdana
Simtek : jurnal sistem informasi dan teknik komputer Vol. 8 No. 1 (2023): April 2023
Publisher : STMIK Catur Sakti Kendari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51876/simtek.v8i1.217

Abstract

Pada penelitian ini, fokus utama adalah mengklasifikasikan penyakit kulit menjadi 7 jenis yaitu dermatitis, campak, herpes, psoriasis, cacar air, kurap dan kutil. Metode yang digunakan adalah deep learning Convolutional Neural Network (CNN) yang merupakan bagian dari Artificial Intelligence (AI). Deep learning merupakan ilmu berbasis jaringan saraf tiruan yang mengajarkan komputer untuk melakukan tindakan yang dianggap alami oleh manusia. Data yang digunakan dalam perancangan ini adalah data citra 7 jenis penyakit kulit yaitu cacar air, campak, dermatitis, herpes, kurap, kutil dan psoriasis. Setelah seorang pakar memeriksa keseluruhan data, jumlah yang dapat digunakan dalam melatih kedua model arsitektur VGG16 dan MobileNet dengan 1.410 data citra. Data citra penyakit kulit berbasis mobile pada epoch 100 dengan tingkat Akurasi 82,14%, Precision 83%, Recall 82% dan F1-Score 82%, metode algoritma CNN memberikan hasil yang bagus dan dapat digunakan dalam pengujian data citra klasifikasi penyakit kulit berbasis mobile
Perancangan Portal Aktivitas Webinar Berbasis Web Derren Chrissanto; Bagus Mulyawan; Novario Jaya Perdana
INTECOMS: Journal of Information Technology and Computer Science Vol 6 No 1 (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.v6i1.6477

Abstract

Semenjak terjadinya COVID-19, banyak aktivitas yang harus dikerjakan di rumah untuk mencegah penyebaran virus, terutama dalam melakukan kerja, kuliah atau kegiatan sekolah. Setelah COVID-19 mereda, terdapat banyak masyarakat yang beradaptasi dalam melakukan kerja, kegiatan sekolah maupun kuliah secara daring agar masyarakat dapat melakukan aktivitas dimana saja tanpa harus mendatangi atau hadir dalam lokasi acara. Informasi terkait webinar selalu diberitahukan menggunakan media sosial maupun media lainnya pada internet, cara seperti ini sangat membuang waktu dalam mencari webinar yang diinginkan untuk mendaftar. Pengisian data pendaftaran webinar juga sangat membuang waktu. Maka tujuan dari pembuatan portal ini adalah untuk menjadi sarana antar institusi yang dapat mempromosikan atau membuat webinar yang dapat didaftarkan dan diikuti oleh peserta dengan mudah pada satu platform. Pada penelitian ini, dibangun sebuah portal yang mengumpulkan informasi mengenai webinar untuk mendukung masyarakat dengan menggunakan metode waterfall yang terdiri dari analisis, desain, implementasi, uji coba dan pemeliharaan program aplikasi. Berdasarkan hasil pengujian, 85.18% responden pria dan 80% responden wanita dapat menggunakan website aktivitas webinar dengan baik. Jika hasil pengujian dipecah berdasarkan users, maka 58.9% responden peserta dan 56.8% responden institusi dapat menggunakan website dengan mudah.
Klasifikasi Ujaran Kebencian Menggunakan Metode FeedForward Neural Network (IndoBERT) Steven Dharmawan; Viny Christanti Mawardi; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 1 (2023): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v11i1.24066

Abstract

Everyone in Indonesia has freedom of speech, both in real life and on social media. However, freedom of speech carried out without filtering can lead to hate speech. Hate speech is a form of discrimination directed against individuals or groups of individuals based on race, religion, gender, sexual orientation, or other identities. Hate speech can harm other parties which as a result can trigger conflict, violence, and can even cost a person's life. Therefore, it is important to be able to identify and manage this hate speech effectively. One way to manage hate speech on social media is to classify it. In this study, a web-based application was created that can classify a sentence to determine whether the sentence is hate speech or a normal sentence. The model created for classification uses the feedforward neural network method with IndoBERT. Based on the test results, the model created using the feedforward neural network method with IndoBERT provides the best accuracy of 89.52%.
IMPLEMENTASI METODE AGGLOMERATIVE HIERARCHICAL CLUSTERING UNTUK SISTEM REKOMENDASI FILM Vanesa Nellie; Viny Christanti Mawardi; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 1 (2023): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v11i1.24070

Abstract

People can now watch movies on their cellphones or other devices using applications, in addition to watching them on television or in theaters. The user's entered keywords are used as the basis for a system that suggests movies from among the many that have appeared over time. Later, similarity between these keywords and text data, such as movie titles and descriptions, will be assessed. This recommendation system will include preprocessing, and the TF-IDF method will be used to determine the weight value. After the weight values have been determined, the grouping calculations will be performed using agglomerative hierarchical clustering. Previously, the Manhattan Distance method will be used to calculate the distance. After that, the distance that is closest can be determined. The data will be clustered according to the shortest distance once the distance calculation is complete. Following that, the system will display the grouping as a dendrogram. The data used was updated as of the date of scraping, which is November 25, 2022, and contains a total of 2467 data. The Agglomerative Hierarchical Clustering method yielded the best silhouette coefficient value, 0.5025559374455285, forming 20 clusters.
ANALISA TOPIK TERHADAP KOMENTAR MENGENAI METAVERSE MENGGUNAKAN METODE CLUSTERING K-MEANS Andre Ertanto; Viny Christanti Mawardi; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 1 (2023): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v11i1.24073

Abstract

The development of the internet doesn't stop there, but continues to develop and evolve, even in a game, humans can interact with each other, make transactions with each other and maybe it becomes an opportunity to earn income, one that combines all of these things is known as the Metaverse. Metaverse is a layer that connects two worlds, namely: the real world and the virtual world. Metaverse offers a 3-dimensional experience that can be shared between users and interact within this technology where every activity of its users can be carried out with the help of Augmented and Virtual Reality technology services. In the metaverse, people want to see what topics are contained in the discussion. So a website was created to determine the topic of metaverse comments from social media. The method used on this website is Clustering K-means. Use this method to divide comments into groups that have something in common. The group of comments will be determined by the topic of the highest frequency of words. Evaluation uses the Elbow Method to determine the optimal k value in Clustering K-means.
WEBSITE REKOMENDASI DAN KLASIFIKASI LAGU MENGGUNAKAN METODE WEIGHTED K-NEAREST NEIGHBOR Caroline Wili Harto; Viny Christanti Mawardi; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 1 (2023): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v11i1.24074

Abstract

As the years went by, music has become one of the most evolving aspects of human history. There is a load of musical development around the globe, especially in music genres. Due to these differences and developments, a design was created to be able to make song recommendations according to the genre types and classifications of music or song. The data that is processed as training data is in the form of song metadata with various music features sourced from Spotify. Song recommendations are performed using the Euclidean Distance calculation between musical features or songs, while song classification is carried out using the Weighted K-Nearest Neighbor (WKNN) method calculation through audio wave type file analysis which then takes the musical features and calculates them based on the existing song or music data. The end result of this process is the genre class label. There is also a classification evaluation calculation using a confusion matrix. With the design of this system, it is hoped that the user will be able to search for song recommendations that have similarities to the song chosen by the user and classify genres according to the user's input song.
PERANCANGAN APLIKASI PENJUALAN PAKET WISATA BERBASIS WEB PADA PT FAJAR BUANA TOUR Natalicia Margatan; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 1 (2023): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v11i1.24104

Abstract

In the era of information technology development, which is becoming increasingly sophisticated each year, The emergence of advanced technology in the current generation has made B2C e-commerce transactions in Indonesia have experienced positive growth over the years, triggering the online tourism sector to gain major benefits and become one of the main drivers of B2C e-commerce in Indonesia. With the development of today's technology, competition between manufacturers to win the competition is getting tougher significantly. It is the above that builds a sense that in this problem there are opportunities that can be built to solve the problem. The emergence of online travel agents (OTA) in Indonesia makes it more difficult for conventional travellers or other small travellers to compete in marketing their products both domestically and internationally. This is what triggers the emergence of a solution that creates a product for this problem, where the solution is the author wants to make a website-based PT Fajar Buana Tour travel agent, using the prototype method and implementing The 7C Framework guidelines in its manufacture.
PEMBUATAN SISTEM FREQUENTLY ASKED QUESTIONS PADA WEBSITE RUPARUPA Tamara Violeta; Desi Arisandi; Novario Jaya Perdana
Joutica Vol 8 No 2 (2023): Journal of Informatic Unisla
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/informatika.v8i2.1022

Abstract

Teknologi membawa pengaruh besar terhadap hidup masyarakat tanpa dapat diprediksi setiap generasinya. Pengaruh yang didatangkan dari teknologi mengarahkan masyarakat untuk memulai bisnis dengan membuat toko online, sebagai bagian dari e-commerce. PT Omni Digitama Internusa (Ruparupa) merupakan salah satu e-commerce yang menjual berbagai peralatan rumah tangga, furnitur, dan gaya hidup dibawah naungan Kawan Lama Group. Sebagai e-commerce, dibutuhkan wadah informasi dengan penyediaan FAQ (Frequently Asked Questions) untuk efisiensi waktu dan peningkatan traffic website, serta lebih membangun kepercayaan dan profesionalisme. FAQ yang efektif dapat dilihat dari penyajian informasi yang ringkas, detil, dan mudah diakses. FAQ Ruparupa saat ini masih menggunakan kata statis, dimana belum dapat menampilkan pertanyaan berulang dan akses yang terhitung masih cukup sulit. Muncul ide sebagai solusi untuk mengatasi permasalahan tersebut, yaitu pembuatan sistem FAQ terbaru dengan adanya pengkategorian FAQ dengan pendukung fitur-fitur tambahan. Tujuannya membantu konsumen dengan memusatkan perhatian mereka pada kasus yang lebih spesifik, sehingga meningkatkan efisiensi waktu, baik dari sisi konsumen, maupun tim Ruparupa. Sistem dibuat menggunakan metode SDLC (System Development Life Cycle) dengan model Scrum. Bahasa pemrograman yang digunakan yaitu ReactJS dengan database MongoDB. FAQ ini akan meningkatkan kualitas UI/UX Ruparupa dan memberikan kemudahan untuk mengelola FAQ dengan adanya user-friendly dashboard.
Co-Authors Agus Budi Dharmawan Agus Budi Dharmawan Alvin Chandra Andre Ertanto Andre, Andre Andy Wijaya Nusantara Angeline, Mariani Anindya, Florentina Pramita Anthony Arisandi, Desi bagus Mulyawan Bagus Mulyawan Bernike Burnama Bryan Filemon Budiyantara, Agus Bunardi Budiman Burnama, Bernike Calvinus, Yohanes Caroline Wili Harto Chairisni Lubis Chairisni Lubis Chairisni Lubis Charles Yuliansen Chavia Rossyerin Prabowo Sutjiadi Daffa Hilmi Aji Daniel Ary Nugroho Danu Yuliarto Darwin Raharja Dedi Trisnawarman Derren Chrissanto Desi Arisandi Desi Arisandi Devin Abipraya Dhananjaya, Asoka Dyah Erny Herwindiati Dyah Erny Herwindiati Edgar Lawrence Edward Darmaja Edwin Suryaputra Endah Setyaningsih Faithtria, Monica Glory Felicia, Clara Ferdinand, Kelvin Fransisca Iriani Roesmala Dewi Frederick, Thomas Gian Ramanda Gilang Samudro Giselle Naomi Sutanto Gozali, Carisha Puspa Gumay, Fhilia Anasty Han, Hansen Hanven Pradana Herwindiati, Dyah Erni Hetty Karunia Tunjungsari Hidayat, Farasya Syifa Hizkia Natanael Ivan Ivan Sutedjo Jane Syahwalina Kaprica Sandra Jap Tji Beng Jason Jeanny Pragantha Jeffri Alimin Jonathan Jovian, Ernestito Kacen Kalengkongan, Aurelia Naftali Kelvin Fernando Pinem Kelvin Wijaya Kevin kevin Kevin Marcello Jonathan Lim, Yulia Lioviani Gavrilla Louis, Josh Mariani Angeline Mei Ie Milson, Audie Muhammad Adi Nugraha Mulyawan, Bagus Natalicia Margatan Nathan, Michael Nathaniel Andrew Nicko Kurniawan Nizham Kamil Hia Owen Maytrio Phratama Pertiwi , Saula Rahmadianti K. Phang, Jastien Phratama, Owen Maytrio Prisiani, Yuri Putri, Tiara Maharani Azkia Ramanda, Gian Ribka Suwardy Richard, Richard Riyanto, Radika Yudha Salsabila, Unik Hanifah Sandra, Jane Syahwalina Kaprica Santoso, Salim Sarah Azka Nazwah Saula Rahmadianti Krisma Pertiwi Sebastian, Dennis Sherena Yemima Purba Sri Tiatri Steven Cang Steven Dharmawan Sudono Widjaja Sukardi, Aldy Supirman Supirman Sutanto, Giselle Naomi Suwarjono, Gilang Samudro TAKESHI, CECILIANA Tamara Violeta Teny Handhayani Tony Tony Trisnawarman, Dedi Valencia Valencia, Valencia Vanesa Nellie Victor Femona Laoli Vincent Marcellino Viny Christanti M Viny Christanti Marwadi Wasino Wasino Wasino Wasino, Wasino William Antonius William Wijaksana Willyanto Wijaya Windah Maria Sonia Nadiah Hutagalung Yagyu Munenori M.E. Yongky Saputra Zyad Rusdi Zyad Rusdi