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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 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

Author-ID : 247406

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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KLASIFIKASI LAGU BERDASARKAN LIRIK BAHASA INDONESIA MENGGUNAKAN METODE SUPPORT VECTOR MACHINE Hendri Yukianto; viny Christanti M; Tony Tony
Jurnal Ilmu Komputer dan Sistem Informasi Vol 2, No 2 (2014): 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.v2i2.3209

A song has lyrics that sets it apart from other songs, because the lyrics are a set of words that make up a song. Song lyrics exhibit specific properties different from plain text documents – many lyrics are for example have different frequencies when compared to other text documents. Classification based on the Indonesian song lyrics still very rarely done. This study uses a Support Vector Machine (SVM) to classify Indonesian song based on lyric with genres Pop, Rock, Punk and Rap. In this study using SVM-light implementation that generates file model and file prediction from the results of the classification. Further, lyrics may use differ greatly in the length and complexity of the language used, which can be measured by some statistical features such as word or verse length, and the amount of repeating text. In this paper, we present results for musical lyric classification on a test collection in order to demonstrate our analysis. The highest accuracy obtained in this study using 50 training data amounted to 67.5%. Key words classification, Indonesian song, musical lyric, Support Vector Machine

SISTEM REKOMENDASI PAKET MINUMAN BERDASARKAN PESANAN PELANGGAN DENGAN METODE FREQUENT PATTERN GROWTH Steven Steven; Viny Christanti Mawardi; Tri Sutrisno
Jurnal Ilmu Komputer dan Sistem Informasi Vol 8, No 1 (2020): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

It is proposed that a beverage package is determined based on customer orders by looking for different frequent itemset patterns in the transaction data that has occurred. These data can be analyzed to be more useful. The method used is the association method. With the predicted beverage package the company can increase sales. With so many transaction data stored, the difficulty in managing data requires a method called the association method. Frequent Pattern Growth Algorithm is an alternative algorithm that is quite effective for finding the set of data that most often appears (frequent itemset) in a large data set. The test results from the Frequent Pattern Growth method can determine a number of packages that meet the minimum value of support and confidence with a combination of two itemset

IMPLEMENTASI OPINION MINING UNTUK PROVIDER INTERNET MENGGUNAKAN METODE NAIVE BAYES. Devin Abipraya; Viny Christanti Mawardi; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol 9, No 2 (2021): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

The development of information technology is growing from year to year. To support the smooth flow of information, there are many internet service providers circulating in Indonesia to support their needs. Some of the largest internet service providers in Indonesia such as Indihome, First media, and Biznet Home definitely have their own advantages and disadvantages.At this time, internet provider providers only accept customer complaints or suggestions through the customer service (CS) call center. Meanwhile, many young Indonesians currently use one of the popular Social Media services, namely Twitter as a user-friendly microblogging service so that users can easily use it, especially in delivering messages in the form of tweets. Therefore, a sentiment analysis program was designed for several internet providers in Indonesia. Opinions or Opinions will be analyzed to determine public sentiment. These sentiments will be classified into 3 sentiments, namely negative, positive, and neutral sentiments. The sentiment classification process can be done manually, but if there is too much data, it requires a system equipped with a classification method, so that the determination of classification can be done quickly. The design of this program applies the Naive Bayes Classifier method. Because this method is supervised learning, it requires training datasets with labels. Labeling will be done automatically using the K-means method. K-Means will sort tweets into groups which are divided into 3 labels. The results of the K-means clustering accuracy are 73.4%. The results of this application are divided into 2 parts, namely a pie chart which is divided into slices that describe the results of the percentage of tweet classifications and a table of classification results containing the number, content of the tweet, and the results of the classification. The best level of accuracy in testing uses 220 training data, and 54 training data. The results of the accuracy of 83.3%.

REKOMENDASI CALON KARYAWAN TETAP DI PERUSAHAAN J&T EXPRESS DENGAN METODE SIMPLE ADDTIVE WEIGHTING Prabu Alif Anggadiputra; Viny Christanti Mawardi; Tri Sutrisno
Jurnal Ilmu Komputer dan Sistem Informasi Vol 10, No 1 (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.v10i1.17794

The definition of an expedition is the delivery of goods or a company that transports goods. Expeditions for shipping goods are now often found in Indonesia because of the large number of people who make transactions via online. There is a J&T Express expedition service which is one of the shipping services that is able to serve deliveries within cities, between cities and between provinces. J&T Express has problems in determining permanent warehouse employees. The determination of warehouse employees for permanent employees at J&T Express is still done individually by the Supervisor of each J&T Express branch. The Simple Additive Weighting method is one method to make it easier for Supervisors to choose permanent warehouse employees with rankings. The way it works is that the user selects the 7 criteria provided, namely performance, attendance, manners, appearance, ability, knowledge, and responsibility.

CLUSTERING LIRIK LAGU ROHANI MENGGUNAKAN METODE K-MEANS Kevin Prasetio; Viny Christanti Mawardi
Jurnal Ilmu Komputer dan Sistem Informasi Vol 5, No 1 (2017): 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.v5i1.776

In a spiritual worship, choosing the relevant song with theme is very important to reflection for the congregation in the service. In the fact, the people often having a difficult to choose some relevant songs because, they must see, search and read the song one by one. The problem is a motivation that it needs a searching system for the people. In the system, using a Vector Space Model after that the system does a clustering from the relevant songs using K-Means method. In the searching system, It is to search by unigram and bigram with the maximum keywords are six keywords. The system using NKB (Nyanyian Kidung Baru) as data which nuance of hymne. The Result of precision evaluation from the relevant documents using MAP (Mean Average Precision), was getting the searching with unigram is the good result than bigram with the percentages is 70.41%. While, the clustering evaluation, using purity with the some trials for k values, was getting k = 4 and unigram given the good result with the percentages is 76.88%.

Clustering pada Mikrobloging Twitter menggunakan K-Means Meiriani Tjandra; Viny Christanti; Jeanny Pragantha
Jurnal Ilmu Komputer dan Sistem Informasi Vol 1, No 2 (2013): 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.v1i2.3141

Twitter merupakan salah satu layanan mikrobloging yang sangat populer yang memungkinkan penggunanya berbagi dan membahas tentang segala hal termasuk berita, gosip, informasi pekerjaan dan berbagai macam promosi produk. Tweets merupakan pesan teks berisi informasi yang disampaikan di Twitter.Dalam penelitian ini clustering digunakan untuk mengelompokkan tweet ke dalam cluster berdasarkan nilai centroid yang ditentukan secara acak. Nilai ini menjadi salah satu bahan percobaan untuk memperoleh hasil clustering yang optimal. Hasil akurasi clustering terbaik dengan metode K-Meansyaitu sebesar 90% dengan menggunakan kumpulan tweets sebanyak 100 tweets. Key wordsTwitter, Clustering, K-Means.

Pembuatan Website Online Store Dilengkapi dengan Chatbot Fredickson Dinata; Viny Christanti Mawardi; Janson Hendryli
Jurnal Ilmu Komputer dan Sistem Informasi Vol 9, No 1 (2021): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

The advance of technology and the increased number of internet usage, have caused many companies to build their online store as a way to market their product. But getting the attention of people isn’t an easy thing to achieve, so livechat and chatbot are implemented into the system to increase the quality of services. This chatbot was developed using the Vector Space Model which will calculate the similarity of each question and the input, before using the vector space model each question will be weighted with term weighting. The chatbot was tested directly and the result is calculated to get the precision of 0.813, recall of 0.751, and f-measurement of 0.766. From the results, we can say the performance of the chatbot is quite decent for it has increased the quality of the services which the online store provided.

PENGEMBANGAN SISTEM AGREGATOR BERITA BAHASA INDONESIA MENGGUNAKAN CONTENT EXTRACTION DAN HIERARCHICAL AGGLOMERATIVE CLUSTERING Stenly Tirta Wijaya; Viny Christanti Mawardi; Janson Hendryli
Jurnal Ilmu Komputer dan Sistem Informasi Vol 4, No 2 (2016): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

The main focus of this study is to develop system to aggregate Indonesian online newspaper and cluster it according to its topic automatically. The system use content extraction to get the main content of articles and Hierarchical Agglomerative Clustering to group articles by its topic with Dice Similarity Coefficient for similarity measure. To determine the cutting point, we cut dendrogram where the gap between two successive combination similarities is largest. Additionally, we add threshold to limit cutting area to improve cluster result. We use Standard Boolean Model for searching feature and Silhouette to evaluate cluster results. Test results using 998 articles shows that limiting cutting area with 0.1 and 0.5 can produce highest average silhouette value 0.264.

Pembuatan Game “Snake & Ladder Dungeon” dengan Fitur Virtual Reality James Eklie; Rendi Kristyadi; Viny Christanti Mawardi
Jurnal Ilmu Komputer dan Sistem Informasi Vol 5, No 2 (2017): 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.v5i2.1121

The "Snake & Ladder Dungeon" game is a 3-dimensional game that uses the Virtual Reality feature, where players are positioned as the main character who must free themselves from the dungeon where players have to climb to each floor and have to reach the last floor of the 20th floor. Players must climb up each floor, try to survive, take power ups to add player status and also finish off the enemies until the last boss to finish the game.The gameplay of this game is the player must climb the ladder to reach to the 20th floor, by shuffling the dice to get the key that works open the door to go up to the next floor, must take power ups to raise the player's status and must defeat the last boss to finish the game. This game is for Android Smartphone with VR BOX and Bluetooth Controller.

SISTEM ANALISIS KINERJA SALES BERDASARKAN TRANSAKSI PENJUALAN DENGAN REGRESI LINEAR DAN ALGORITMA APRIORI Tania Rizgitta; viny Christanti Mawardi; Janson Hendryli
Jurnal Ilmu Komputer dan Sistem Informasi Vol 7, No 2 (2019): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Sebuah perusahaan mempunyai sales untuk menawarkan produk atau jasa yang dijual. Sales ini dianggap sebagai representative dari perusahaan dimana sales inilah yang memasarkan dan menjual produk perusahaan kepada customer. Pentingnya nilai-nilai yang dipegang oleh seorang sales sebagai sumber pendapatan bagi perusahaan. Maka dari itu, menganalisis penjualan tiap sales, dan mengetahui sales yang memiliki kinerja paling baik merupakan hal yang penting bagi perusahaan dalam meningkatkan penjualannya. Maka dari itu, untuk mempermudah menilai kinerja sales dibuatlah sebuah sistem dimana perusahaan dapat melihat kinerja sales nya dengan parameter-parameter yang sesuai dengan masing-masing perusahaan. Pengujian metode Regresi Linear untuk memprediksi penjualan sales berikutnya menggunakan koefisien determinasi yang bernilai antara 54.5% sampai 84.5%. Sedangkan pengujian metode Algoritma Apriori, didapatkan 3 kriteria yang dipilih yaitu memenuhi target penjualan, memenuhi jumlah target total transaksi per tahun per tahun, dan memenuhi jumlah transaksi penjualan maksimum per tahun dan 3 nama dan id sales yang menjadi rekomendasi yaitu: id sales 98908 (Ekowati), 98912 (Nini Anggraini), dan 98916 (Ronny Rustan).

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 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 Didit Suprihanto, Didit Dinata, Fredickson Dyah Larasati, Annita Edward Darmaja Edy Susanto Endah Purnamasari Endah Setyaningsih Erikson T Erikson T Erwin Erwin Ery Dewayani 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 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 Manatap Dolok Lauro, Manatap Dolok 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 Niki Valentine Niki Valentine, Niki 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 Sharlene Solikhah, Nafia Stenly Tirta Wijaya stephanie stephanie Steven Steven Dharmawan Steven Muliadi Steven Muliadi, Steven Steven Steven 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

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