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All Journal Jurnal Teknologi Jurnal Informatika dan Teknik Elektro Terapan Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JUMANJI (Jurnal Masyarakat Informatika Unjani) Jurnal Informasi dan Komputer Journal of Information System, Applied, Management, Accounting and Research JATI (Jurnal Mahasiswa Teknik Informatika) Competitive Jurnal Puan Indonesia Jurnal INFOTEL Competitive
Tati Ernawati
Politeknik TEDC Bandung
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Public Health Transportation Other

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PENERAPAN ALGORITMA FREQUENT PATTERN GROWTH PADA POLA PEMBELIAN KONSUMEN (STUDI KASUS G.I.B STORE KOTA CIMAHI ) Resa Hardiyanti; Tati Ernawati
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3S1 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3S1.6773

Abstract

Transaction pattern analysis constitutes one of the key factors in business decision-making, particularly in retail business decisions. This study aims to identify consumer purchasing patterns at G.I.B store in Cimahi City by implementing the Frequent Pattern Growth (FP-Growth) algorithm as a data mining method to discover associative patterns among products that are frequently purchased together. This research utilized data from 2023 encompassing both online and offline sales transactions, and the research process included data collection, data cleansing, data transformation, and the application of the FP-Growth algorithm using Google Colaboratory, as well as analysis of the resulting association patterns. The findings demonstrate that strong relationships exist between certain specific products, such as between Junior Premium 8 and Kids Premium M, with a confidence level of 77.91%. These patterns can assist in determining and formulating business strategies for promotions, product bundling, and more efficient inventory management. The implementation of the FP-Growth algorithm has proven effective in helping business owners understand customer shopping behaviors and support more targeted decision-making.
Case Study in Network Security System Using Random Port Knocking Method on The Principles of Availability, Confidentiality and Integrity Ernawati, Tati; Idham Kholid; Dahlan; Rohmayani, Dini
JOIN (Jurnal Online Informatika) Vol 9 No 1 (2024)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v9i1.1254

Abstract

Preventing unidentified individuals from misusing their access to information is a major concern when it comes to data security. Network administrators are charged with working harder to be able to secure the computer network they manage. The utilization of right method is a challenge for network administrators to protect computer network from intruders. The RPK method is one of solution to overcome this problem. This research aims to implement RPK method on the principles of availability, confidentiality, and integrity which have not been explored by previous studies. The network system configuration stage involved installing Debian 9, NMAP, Hydra, RPK, cloud server, remote admin, and attacker. The network security system's performance was tested, revealing a 99.97% availability rate and 100% confidentiality. The system's integrity was assessed, with an average response time of 0.22 seconds and 100% blocking accuracy. The test results indicate that the system's network security performance, using the RPK method, capable of protecting server attacks and effectively upholding security stability.
PENGGUNAAN ALGORITMA NAÏVE BAYES DAN SUPPORT VECTOR MACHINE UNTUK ANALISIS SENTIMEN KONFLIK PALESTINA DAN ISRAEL PADA PLATFORM X Andriawan, Muhammad Guruh; Ernawati, Tati
Jurnal Informatika dan Teknik Elektro Terapan Vol. 12 No. 3 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3.4943

Abstract

Abstrak. Penelitian ini mengkaji penggunaan algoritma Naïve Bayes dan Support Vector Machine (SVM) untuk analisis sentimen konflik Palestina-Israel pada platform X. Alasan pemilihan topik ini adalah karena peran signifikan media sosial dalam mencerminkan opini publik terhadap konflik global. Dengan menganalisis tweet dari pengguna Indonesia, penelitian ini bertujuan untuk mengklasifikasikan sentimen menjadi kategori positif, negatif, dan netral. Pengumpulan data dilakukan menggunakan API X, mengumpulkan 599 tweet antara 7 Mei hingga 31 Desember 2023. Tahap pra-pemrosesan meliputi pembersihan, tokenisasi, penghapusan stopword, dan stemming. Hasil penelitian menunjukkan bahwa algoritma Naïve Bayes mencapai akurasi sebesar 82,22%, mengungguli algoritma SVM yang memiliki akurasi sebesar 74,44%. Temuan ini menyoroti bahwa sebagian besar sentimen publik adalah netral, dengan kehadiran sentimen positif dan negatif yang signifikan. Hasil ini menekankan efektivitas Naïve Bayes dalam klasifikasi sentimen untuk analisis media sosial, menyediakan alat yang berharga untuk memahami opini publik tentang isu-isu politik sensitif.
Co-Authors Andriawan, Muhammad Guruh Arif Hidayat Azizah, Nur Aviani Dahlan Effendi, Puput Amelia Endah Rachmawati Endrawan, Jemi Febi Febiansyah Fikri Faiz Fadhlur Rachmat Idham Kholid Ihsan Kamil, Ali Iqbal Heriyadi Iskandar, Rachmat Jemi Endrawan Kosasih, Heldi Akbar Muhammad Apipudin Safaat Nia Ekawati, Nia Pratiwi, Cece Raafidiani, Reni Resa Hardiyanti Rohmayani, Dini Sugianto, Castaka Agus Susdin, Susdin Syams, Fawwaz Muhammad Tresnawati, Shandy