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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Teknik dan Ilmu Komputer JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi) Jurnal Informatika dan Teknik Elektro Terapan Computatio : Journal of Computer Science and Information Systems Jurnal Sinergitas PkM & CSR MITRA: Jurnal Pemberdayaan Masyarakat MIND (Multimedia Artificial Intelligent Networking Database) Journal Jurnal Muara Ilmu Sosial, Humaniora, dan Seni Jurnal Muara Sains, Teknologi, Kedokteran dan Ilmu Kesehatan Jurnal Infortech Jurnal Bakti Masyarakat Indonesia Journal of Computer and Information Systems Ampera Prosiding Konferensi Nasional PKM-CSR Indonesian Journal of Multidisciplinary Science Prosiding Seri Seminar Nasional Madani : Jurnal Pengabdian Kepada Masyarakat Communication and Information Journal International Journal of Application on Economics and Business Inovasi Teknologi Masyarakat International Journal of Advances in Artificial Intelligence and Machine Learning Jurnal Serina Abdimas
Viny Christanti M
Program Studi Teknik Informatika Fakultas Teknologi Informasi Universitas Tarumanagara Jakarta - Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts 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 Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Nursing Public Health Social Sciences Other

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Aplikasi Bimbingan Belajar Bahasa Inggris Tingkat Sekolah Dasar (SD) Dengan Fitur Live Chat Dan Automatic Essay Scoring Destu Adiyanto; Viny Christanti Mawardi; Manatap Dolok Lauro
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.v10i2.22533

Abstract

In the current pandemic, parents want to do additional learning for their children. Therefore, a research was conducted with the title of Application of English Tutoring for Elementary School Level (SD) with Live Chat and Automatic Essay Scoring features and is expected to help the learning carried out by teachers and students. The hope of this application can be useful and can make it easier for teachers to find places to do learning. The system created today is a scoring system in the form of an essay where when students solve problems in the current system it will produce points per question worked on and the total points will produce the correct number of points. Experiments were carried out with several students with several similar questions to find out whether the designed system worked as expected or not. By conducting three trials on students with the same 10 questions and with K-Gram 3, 4 and 5. 4 which was carried out, the results were 70% and for the accuracy results from the K-Gram 5 experiments carried out, the results were 65%.
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.
Sistem Rekomendasi Kamera Mirrorless Dengan Metode Simple Multi Attribute Rating Technique (SMART) Marvellino; Viny Christanti Mawardi; Manatap Dolok Lauro
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.v10i2.22550

Abstract

Photography are an activity that can be done through a lot of other media, some uses DSLR (Digital Single Lens Reflex) camera, Mirrorless and even from their smartphones. Choosing a mirrorless camera by those who doesn’t have the knowledge of the specifications of a camera might be a problem by itself. The problem itself rose because there’re a lot of criterias that need to be considered in getting the right one and due to lack of information. That is why recommendation system based on website are developed which can help users choosing the right product using SMART (Simple Multi Attribute Rating Technique) method. SMART method are a method for taking decisions that are multi attribute used for supporting decisions which have other alternatives. In developing this website it uses 5 brands of camera that is Canon, Fujifilm, Nikon, Panasonic and Sony. The validity test based from UAT (User Acceptance Rate) of 35 respondents gives a result of 85.71% accuracy that agrees that the recommendation system is appropriate to what user wants and proves that the system gaves the recommendation based on what user wants and beneficial to be used.
Implementing Hybrid Filtering on Korean Drama Recommendation Through K Nearest Neighbor Algorithm Mutiara Ramadhani Sugiri; Viny Christanti Mawardi; Janson Hendryli
Indonesian Journal of Multidisciplinary Science Vol. 1 No. 4 (2022): Indonesian Journal of Multidisciplinary Science
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1596.895 KB) | DOI: 10.55324/ijoms.v1i4.72

Abstract

Over time, many cultures from South Korea entered Indonesia, such as music, food, and drama series. From year to year, the number of Korean dramas released increased as well as fans of the Korean drama. Therefore, the researcher aimed to create a system that might help K-drama lovers to sort recommendations regarding favorite dramas. The researcher designed the system, starting from collecting data to calculating adjusted cosine similarity. Based on the results of the user acceptance testing and the answers of the respondents, it can be concluded that the Korean drama recommendation system website's function is effective and provide suggestions based on user ratings.
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.
Implementasi Metode Collaborative Filtering Based Untuk Sistem Rekomendasi Buku Fiksi Pharadya Ajeng Swari Sukmawati; Lely Hiryanto; Viny Christanti Mawardi
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 2 (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.v11i2.25999

Abstract

A book is the result of someone's work in the form of a collection of papers containing articles intended for publication. One of the benefits of books is that they can open people's horizons and can educate reason, thoughts and faith. Indonesia is ranked 60 out of 61 countries with reading interest problems causing low public interest in reading. One of the factors that can be taken into consideration for interest in reading in Indonesia is the difficulty in finding books to read because the many kinds of books in circulation make it difficult for readers to decide which books to read, besides that readers only want to read books with the best reputation. The purpose of creating a book recommendation system is to make it easier to find fiction-type books to read. The data used in this design are book data and rating data from Kaggle. This design uses one of the recommendation system methods, namely collaborative filtering. Collaborative filtering is a recommendation method that calculates similarity between items by users to make choices. The system will recommend 5 books according to the book title that the user will input.
Co-Authors Agus Budi Dharmawan Albert Jeremy Aleksander Nihcolson Andre Ertanto Andre Raymond Andreas Andreas Andreas Andreas Andreas Khosasi Anggreiny, Phoebe Cecilia Angkasa, Adhelia Anindita Septiarini, Anindita Antonius Sakti Wiradinata ARDAN, MOHAMAD Ardianto Ardianto Arwi, Adelia Vannissa Augusfian, Fendy Bagus Mulyawan bagus Mulyawan Benedicta, Cheria Berlin Ong Karo Karo Billy Fernando Brandon Alexander Jayadi Bryan Filemon Buana, Salsabila Ayunda Martsa Calvin Calvin Carlene Lim Carlene Lim Caroline Wili Harto Chintia, Tiffany Dali S Naga Dali S. Naga Dali S. Naga Dali S. Naga Dali S. Naga, MMSI Dali S.Naga Dali Santun Naga Daniel Daniel Daniel Daniel Darius A Haris Darius Andana Haris Darryl Kresnadi Nugroho Davin Pratama Dedi Trisnawarman Denis Kusbowo Desi Arisandi Desi Arisandi Desi Arisandi Dessy Yanti Destu Adiyanto Devi Ayu Permatasari Devin Abipraya Dewi Triani Dhani Andika Maharsi Didit Suprihanto, Didit Dinata, Fredickson Dyah Larasati, Annita Edward Darmaja Edy Susanto Endah Purnamasari Endah Setyaningsih Erikson T Erikson T Erwin Erwin Ery Dewayani Eryca Dhamma Shanty Fat, Joni Fendy Augusfian Ferry Ruben Yudistira Ferry Ruben Yudistira Yudistira, Ferry Ruben Yudistira Freddy Kurniawan Fredickson Dinata Fundroo Orlando Geraldine, Karmelia Gerry Geraldicky Gian Praista Gunadi, Alvin Nicolas Haikal M, Andrew Hamdani Hamdani Handoko Susanto Handoko Susanto, Handoko Handry Wardoyo Hanven Pradana Hartanto, Jonathan Chris Helen, Helen Hendri Yukianto Hendri Yukianto, Hendri Hendryli, Janson Henry Hartono Herman, Sylvia Hetty Karunia Tunjungsari Husada, Yusianne Kasih Irvan Lewenusa Irvan Lewenusa, Irvan Ivanka, Risa James Eklie Janson Hendryli Janson Hendryli Janson Hendryli Janson Hendryli Janson Hendryli Januar Mansur Jayadi, Brandon Alexander Jeanny Pragantha Jeanny Pragantha Jeffri Alimin Jesica Jesica Jesica Kurniadi, Jesica Jesslyn Jesslyn Jimmy Jimmy Joko Joko Jonathan Adrian Wibowo Joshua Octavianus Joshua Octavianus, Joshua Julius Evan Harya Chandra Kalyani, Khema Dwi Karo Karo, Berlin Ong Kenneth Hakim Kevin kevin Kevin Kurniawan H. Kevin Prasetio Kevin The Kuncoro Yoko Lavenia Lely Hiryanto Lie, Nadia Natha Livienia Livienia Maharsi, Dhani Andika Manatap Dolok Lauro, Manatap Dolok Marco Marco Maria Asinta Marpaung Maria Asinta Marpaung, Maria Asinta Marsel Dwiputra Marsel Dwiputra, Marsel Martsha Buana, Salsabilla Ayundha Marvellino Mei Ie Meiliansyah, Carens Berliyanti Meiriani Tjandra Meiriani Tjandra Meiske Yunitree Suparman Michael, Valentino Muhammad Farras Mutiara Ramadhani Sugiri Mutiara, Maitri Widya Nadia Natha Lie Naga, Dali S. Natasya, Stephanie Nathaniel, Nikolaus Niki Valentine Niki Valentine, Niki Nikolaus Nathaniel Novario Jaya Perdana Nurmadewi, Dita Okengwu, Ugochi A Orlando, Fundroo Pangandaheng, Grasella Aldonia Pharadya Ajeng Swari Sukmawati Phung, Mulan Prabu Alif Anggadiputra Prof. Dr. Ir. Dali S. Naga, MMSI Pusaka, Semerdanta Putra Lukita Putri, Aneesa Joenice rani puspitasari Rendi Kristyadi Ricky Cangniago Ricky Martin Rini, Cika Puspita Riwanda, Josephine Kayla Riyanto, Radika Yudha Rizqi Amelia, Aulya Robertus Budihalim Robertus Budihalim, Robertus Rudy Rudy Salsabila, Nur Maya Saskia Lavinsky Septiasari, Abellia Shanty, Eryca Dhamma Sharlene Solikhah, Nafia Stenly Tirta Wijaya stephanie stephanie Steven Steven Dharmawan Steven Muliadi Steven Muliadi, Steven Steven Steven Sugisandhea, Georgia Supriyanton, Adolf Asih Susilo, Andri Sylvia Wulandari, Sylvia TAKESHI, CECILIANA Tania Rizgitta Tony Tony Tony Tony TRI SUTRISNO TRI SUTRISNO Utama, Didi Widya Vanesa Nellie Vincent Marcellino Wati, Masna Widi Santoso Wijaya, Dion Dwi Willyanto, Vinnie Wilson Gozal, Wilson Yagyu Munenori M.E. Yasser, Achmad Yohan Prasetyo Sugianto Yohanes Calvinus Yolanda, Aubrey Yosua Pandapotan Sianipar Yukianti, Chiara Rizka Yulianto Yulianto Yulianto Yulianto Zyad Rusdi Zyad Rusdi