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All Journal SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Riset Informatika dan Teknologi Informasi (JRITI)
Yunizar Pratama Yusuf, Ajif
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Computer Science & IT Control & Systems Engineering Engineering

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KLASIFIKASI TEKS ULASAN APLIKASI NETFLIX PADA GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA NAÏVE BAYES DAN SVM Khoirunnisaa, Nabiilah; Nabila Nastiti Kesuma, Kaylista; Setiawan, Septhiyanthi; Yunizar Pratama Yusuf, Ajif
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 7 No 1 (2024): Jurnal SKANIKA Januari 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v7i1.3138

Abstract

Netflix is a subscription streaming platform that presents various shows, such as TV series, documentaries, and films, connected to a device connected to the internet. One of the most popular sites for streaming videos is Netflix, throughout the world and is now starting to apply data analysis and machine learning technology to improve its user services. Through the Google Play Store, users can submit various reviews about the Netflix application. It is possible to extract significant hidden information from this vast quantity of review data that is helpful for assessing an application's quality. Therefore this research aims to classify text reviews of the Netflix application by comparing the two algorithms applied, that is, Support Vector Machine (SVM) and Naive Bayes. With the aim of finding out which algorithm performs better in terms of accuracy. The dataset was obtained through the Google Play Store and applied to the scraping method, totaling 1000 reviews, and processed utilizing the Python programming language. Then the Netflix application review data that was obtained was divided into 70% train data and 30% test data. 82% of the accuracy results were obtained using the Naive Bayes approach., while the support vector machine (SVM) yielded 85% accuracy. It therefore demonstrates that support vector machines (SVM) are no more successful than the outcomes of applying the Naive Bayes method. (SVM).
RANCANGAN CHATBOT REKOMENDASI COFFEE SHOP JABODETABEK DENGAN MENGGUNAKAN DIALOGFLOW NATURAL LANGUAGE PROCESSING Syahrani, Gina; Sevira, Silviana; Yunizar Pratama Yusuf, Ajif
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 7 No 1 (2024): Jurnal SKANIKA Januari 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v7i1.3139

Abstract

Public interest in coffee culture is increasing, especially in the JABODETABEK area. Some ways to get information about finding recommendations for coffee shops that are tiring through social media platforms, asking peers, advertisements and others still feel less effective and efficient. Utilization of chatbot technology and Natural Language Processing as an effective solution in providing coffee shop recommendations to users. This research aims to design and implement a chatbot that has the ability to deliver coffee shop recommendations based on user preferences. This chatbot is applied with Dialogflow which is able to connect to the Telegram platform. Dialogflow is used to process user input in the form of natural language and provide additional information such as location, opening hours, prices, menus, and social media to communicate to the coffee shop. Chatbot is a practical way for Telegram users to communicate information quickly. The expected result of this coffee shop recommendation chatbot system using Dialogflow NLP is to be able to provide useful and relevant recommendations to users, with the potential to promote coffee culture in the Jabodetabek area.
Analisis Sentimen Menggunakan Algoritma Naïve Bayes Pada Aplikasi m-BCA berdasarkan Ulasan Pengguna di Google Play Store rahmawati, irma; Rika Fitriani, Tiara; Yunizar Pratama Yusuf, Ajif
Jurnal Riset Informatika dan Teknologi Informasi Vol 1 No 2 (2024): Desember 2023 - Maret 2024
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v1i2.116

Abstract

m-BCA (Mobile Banking) adalah layanan perbankan dari PT.Bank Central Asia,Tbk yang memungkinkan akses langsung melalui telepon seluler. Meskipun populer, pengguna sering mengalami pengalaman negatif, seperti error dalam mengakses aplikasi dan keluhan terkait transaksi. Meskipun terdapat opini negatif, opini positif di Play Store juga ditemukan. Penelitian ini menggunakan metode Naïve Bayes untuk menganalisis sentimen pengguna BCA Mobile berdasarkan ulasan di Google Play Store. Hasil analisis diharapkan dapat membantu BCA meningkatkan kualitas layanan mereka. Penelitian terkait menggunakan berbagai metode, dan penelitian ini memilih Naïve Bayes karena kecepatan dan efisiensinya. Tahap penelitian mencakup pengumpulan data dari Google Play Store, preprocessing data, dan penerapan algoritma Naïve Bayes, Random Forest, serta Logistic Regression. Penelitian ini menyimpulkan bahwa sebagian besar ulasan memiliki orientasi negatif dan model Naïve Bayes menonjol dengan tingkat akurasi yang paling tinggi, mencapai presisi 84%, recall 82%, F1-score 81%, dan tingkat akurasi sebesar 82%.
Implementasi Open Source Enterprise Resource Planing (ERP) ODOO Pada PMB Universitas Bhayangkara Jakarta Raya iskandar, rudi; Syahroni, Muhammad; Yunizar Pratama Yusuf, Ajif
Jurnal Riset Informatika dan Teknologi Informasi Vol 2 No 2 (2025): Desember 2024 - Maret 2025
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v2i2.153

Abstract

Currently, Information and Communication Technology is developing rapidly, including in the field of education. In general, technology is used to process data, which includes processing, obtaining, compiling, storing, and manipulating data in various ways and procedures to produce high-quality information. Universities must continue to improve their services to meet the needs of the academic community in order to continue to exist. The rapid development of technology and information in the field of education also triggers fierce competition, especially when accepting new students every academic year. Universitas Bhayangkara Jakarta Raya (Ubhara Jaya), one of the private universities in Bekasi City, routinely carries out the new student admission process (PMB) at the beginning of each academic year. This process is managed by a marketing team that must handle many applicants, remind prospective students about the entrance exam time, and manage the re-registration and payment process. All of this requires an adequate system to meet the needs of universities and applicants. Management also needs reports that can be used to determine promotional strategies based on the results of new student admissions. With the implementation of Odoo, it is expected to increase efficiency in data processing, analysis, reporting, and evaluation of new student admissions. 
Co-Authors Khoirunnisaa, Nabiilah Muhammad Syahroni Nabila Nastiti Kesuma, Kaylista Raden Mohamad Herdian Bhakti Rika Fitriani, Tiara Rudi Iskandar, Rudi Setiawan, Septhiyanthi Sevira, Silviana Syahrani, Gina