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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

Author-ID : 925602

Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Public Health Social Sciences Other

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IMPLEMENTASI DATA MINING DENGAN METODE APRIORI UNTUK REKOMENDASI SUKU CADANG PONSEL DAN PREDIKSI PENJUALAN PRODUK SETIAP PELANGGAN Hanven Pradana; Viny Christanti Mawardi; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol 8, No 1 (2020): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Application of cell phone parts recommendations and product sales predictions for each customer for Brader Parts is an application that is made aiming to provide predictions of each customer's buying habits as well as recommendations in selecting what items are most salable to sell and most sought after. This application was designed using the ASP.Net programming language. Method of Calculating application using Apriori. The design of the application uses the System Development Life Cycle. The test results are performed using the User Acceptance Test method and user satisfaction testing. With this application, it is expected that the process of consideration and selection of goods at the Brader Parts company can be helped.

PERANCANGAN SISTEM PENGELOMPOKAN DAN REKOMENDASI SAHAM LQ45 DENGAN K-MEDOIDS, EXPONENTIAL MOVING AVERAGE DAN WEIGHTED PRODUCT Alvin Chandra; Bagus Mulyawan; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol 9, No 1 (2021): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Stock is an instrumentation that has the fundamentalsof a company. Owning a share means owning theshares of the company. Shares can be traded on theIndonesian Stock Exchange by the entire public. TheLQ45 stock grouping and recommendation applicationis a desktop-based application that aims to assist inmaking investment decisions in the Indonesian CapitalMarket. The application is designed using the Pythonprogramming language. The application applies the KMedoidsClustering method to group stocks andExponential Moving Average along with WeightedProducts to make recommendations or sort shares.Users can enter the desired share criteria and theapplication will recommend according to the inputcriteria from the user. Testing on this application iscarried out by the BlackBox testing method,questionnaire, K-Medoids Algorithm Testing and theoutput results of the program. From the results of theblack box testing, the application results can runaccording to plan. In testing the K-Medoids Algorithm,the results obtained that the number of clustersdetermined are in accordance with the number of 2clusters using the elbow method. And in testing theoutput results of the program, the results obtained arethe recommendation accuracy of 80.8%.

PERANCANGAN APLIKASI PREDIKSI MASA STUDI MAHASISWA DENGAN METODE NAÏVE BAYES DAN C4.5 Charles Yuliansen; Bagus Mulyawan; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol 7, No 2 (2019): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

In college studies each study period uses a semester system where each semester of study period will obtain a Grade Point Average (GPA) in which the GPA shows the value obtained during the study period in that semester. With the right calculation the GPA can be used as a long time determinant of a student's study period. This prediction application is made using the classification method. The data used is obtained legally from the faculty and is used to carry out the training process and test applications that have been made. For the development method use the test structure method with several tools and workmanship techniques such as flowcharts, context diagrams, and relationships between tables. The programming language used in making applications is PHP, Python, the database used is MySQL. The training and testing methods used in making the application are Naïve Bayes and C4.5. The results of system testing show that using 237 student data obtained that the C4.5 method is always superior compared to the Naïve Bayes method. Addition of sex variables did not change the accuracy significantly.

PERANCANGAN SISTEM INFORMASI PEMINJAMAN DAN PENGEMBALIAN MOBIL PADA RENT CAR 168 Hizkia Natanael; Zyad Rusdi; 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

Aplikasi yang dibuat adalah aplikasi untuk melakukan pemesanan rental mobil pada 168Premiumcar atau juga RentCar 168. Rental 168Premiumcar sendiri adalah perusahaan yang bergerak di dalam bidang transportasi, yaitu melayani rental mobil. Aplikasi yang dibuat ini adalah aplikasi 168Premiumcar yang berfungsi sebagai media untuk memudahkan pelanggan dalam melakukan pesanan sewa mobil. Aplikasi ini dibuat menggunakan bahasa pemrograman Java Android, PHP serta menggunakan MySQL dan phpMyAdmin sebagai database nya. Pemilihan aplikasi mobile android sendiri juga dipilih karena mudah untuk pengoperasiannya dan dapat diakses dari mana saja. Aplikasi ini mempermudah pelanggan dalam melakukan pesanan sewa mobil,karena pelanggan dapat melakukan pesanan dan melihat pesanan secara virtual. Dan juga aplikasi ini sangat memudahkan pemilik dari rental untuk memberikan informasi mengenai harga sewa mobil dan lain-lain. Dan selama masa pandemi covid-19 ini dengan menggunakan aplikasi mobile ini, maka pelanggan bisa mengurangi waktu untuk berpergian keluar rumah dan bisa membantu mencegah penyebaran virus covid-19.

PERANCANGAN E-LEARNING SMA DAMAI PADA PLATFORM ANDROID DAN WEBSITE Edwin Suryaputra; Bagus Mulyawan; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol 7, No 1 (2019): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

During this time DAMAI High School still applied a conventional system in the teaching and learning process conducted by teachers with students. Therefore, the solution needed is to make an Android-based e-learning application and website. E-Learning is a system or concept of education that utilizes information technology in the teaching and learning process. This e-learning application is made using descriptive research methods with a type of case study research in schools, where data collection techniques are used between observation and interviews. For the development method using a structured method with several tools and workmanship techniques such as flowcharts, context diagrams, and relationships between tables. The programming language used in designing e-learning is PHP and the database used is MySQL. The method used to integrate Android with a website is by using a RESTful API that is distributed using JSON. With the DAMAI high school e-learning Android and website application solution, it is hoped that it can help teachers and students in conducting teaching and learning activities flexibly.

IMPLEMENTATION OF MINIMUM STOCK DETERMINATION USING PREDICTION AND ECONOMIC ORDER QUANTITY (EOQ) METHOD Kelvin Fernando Pinem; Bagus Mulyawan; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol 9, No 1 (2021): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

In an effort to get competitive prices, one must be able to organize the planning of the availability of the goods it owns so that it can maintain a balance between demand and the existing stock of goods (supply). This application aims to create a precise forecasting system that is useful for determining the inventory of goods in stock that must be done in accordance with the old sales data that have occurred. The method used in this research is forecasting to predict or predict the inventory of goods, then calculating the Economic Order Quantity (EOQ) to return the number of items ordered which will ultimately reduce the cost of inventory. The forecasting method used is Single Exponential Smoothing (SES), Double Exponential Smoothing (DES). The results of data testing on the Forecast method using Forecasting used are Single Exponential Smoothing (SES) and Double Exponential Smoothing (DES). The smallest MAD results were obtained from each of the Forecast methods. After forecasting, the best forecasting method will be chosen which has the value of Mean Absolute Deviation (MAD), mean quality squared (Mean Square Error), the proportion of mean absolute error (Mean Absolute Percentage Error). This Economic Order Quantity (EOQ) method helps to determine the optimal purchase frequency. How to determine and the optimal frequency of purchases.

PENGGUNAAN METODE SUPPORT VECTOR MACHINE UNTUK KLASIFIKASI SENTIMEN E-WALLET Bryan Filemon; Viny Christanti Mawardi; Novario Jaya Perdana
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.v10i1.17824

In Google Play Store there are lots of application ready to be explored and downloaded. Google Play Store is a place where many developers can sell applications that they have made. Apart from being a place for searching and downloading applications, Google Play Store can also be used to conduct a research. E-Wallet is one of a technological development that can be used to do many transactions. Doing transaction with e-wallet can be done anywhere you want. E-wallet in Indonesia is growing very rapidly especially in the present time where covid-19 is growing rapidly. This is one of the reasons why many people now using e-wallet for doing transcations. Many interesting promotions that were given is also one of the reason why people start using e-wallet. This research had the objective to visualize people’s emotion on e-wallet based on user opinion in Google Play Store. The research stage starts from scrapping data from Google Play Store, preprocessing data, classification with Support Vector Machine, evaluation with confusion matrix. Data were scrapped from google play store using google_play_scrapper API. This research uses OVO review of 500 data, DANA review of 500 data, LinkAja review of 500 data. The classification results will then be evaluated using a confusion matrix. The highest accuracy results will be used as a model for the classification stage. The classification results will be displayed in the form of tables and pie charts that describe the percentage results of sentiment classification.

IMPLEMENTASI ALGORITMA GOOGLE LATENT SEMANTIC DISTANCE UNTUK EKSTRAKSI RANGKAIAN KATA KUNCI ARTIKEL JURNAL ILMIAH Novario Jaya Perdana
Computatio : Journal of Computer Science and Information Systems Vol 2, No 2 (2018): COMPUTATIO : JOURNAL OF COMPUTER SCIENCE AND INFORMATION SYSTEMS
Publisher : Faculty of Information Technology, Universitas Tarumanagara

The accuracy of search result using search engine depends on the keywords that are used. Lack of the information provided on the keywords can lead to reduced accuracy of the search result. This means searching information on the internet is a hard work. In this research, a software has been built to create document keywords sequences. The software uses Google Latent Semantic Distance which can extract relevant information from the document. The information is expressed in the form of specific words sequences which could be used as keyword recommendations in search engines. The result shows that the implementation of the method for creating document keyword recommendation achieved high accuracy and could finds the most relevant information in the top search results.

REVIEW SENTIMEN ANALISIS APLIKASI SOSIAL MEDIA DI GOOGLE PLAYSTORE MENGGUNAKAN METODE LOGISTIC REGRESSION Edward Darmaja; Viny Christanti Mawardi; Novario Jaya Perdana
PROSIDING SERINA Vol. 1 No. 1 (2021): PROSIDING SERINA III 2021
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Tarumanagara

Everyone has their own nature and way of thinking, which makes their style of conveying what they are thinking is different from one to another. Not only that, what they are conveying can have a different meanings according to the person who listens to it and which perspective they take it into. From this, the reviews given have different meanings for each person which other people can easily understand the meaning behind it. Although humans can distinguish whether the review given by other people has a positive or negative meaning, machine cannot understand this without being given instructions first, in order for machine to find out the meaning in the text, Therefore, this research was conducted. The purpose of designing this system is to make it easier to analyze a collection of reviews on a social media application from google playstore without the need to see all the review given by other users. This system is also designed to fulfill the purpose of evaluating using the TF-IDF method and the Logistic Regression method on the program to be created. The intended evaluation is from the level of accuracy obtained from the use of the model formed using the method chosen and how many predictions have the correct value based on the result of Confusion Matrix from the program that has been designed . From the results obtained, it can be concluded whether the social media application has a good reputation from its users or not.

PENERAPAN METODE SUPPORT VECTOR MACHINE UNTUK ANALISIS SENTIMEN PADA ULASAN PELANGGAN HOTEL DI TRIPADVISOR Willyanto Wijaya; Dyah Erny Herwindiati; 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.v10i2.22538

Indonesia is an archipelagic country that has very beautiful nature, in addition to the natural beauty of cultural diversity is also one of the factors Indonesia has a tourist attraction. One of the effects of Indonesia's natural beauty and cultural diversity can be seen from the increase in hotel occupancy rates. This hotel analysis system design uses training data and test data from the tripadvisor website. Tripadvisor is a website that focuses on tourism. on tripadvisor there are a lot of services offered ranging from transportation, lodging, travel experiences, and restaurants. One of the useful features of tripadvisor is the review column, this review column can be used to do research. visitor reviews from the tripadvisor comments column can be used as a value. to visualize and see people's emotions how the services provided by the hotel to visitors. The research phase starts from scrapping data from the triapadvisor review column, preprocessing data, word weighting, SVM, and evaluation with a confusion matrix. The data taken from the review column is done by web scraping technique. This study uses data from 3000 reviews from 15 hotels. The results of the classification will then be evaluated with a confusion matrix. The highest accuracy result will be used as a model for classification. the classification results will be displayed in the form of detailed tables and diagrams that describe the percentage of sentiment classification results.

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

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