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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.
PELATIHAN PERAKITAN KOMPUTER UNTUK MENINGKATKAN PEMAHAMAN PERANGKAT KERAS SISWA KELAS VII SMPN 2 CIMAHI Ernawati, Tati; Yusuf, Muhammad Ahyadi; Permana, Adhitia Rian; Syani, Mamay; Sudrajat , Ari; Upayarto, Budi
PUAN INDONESIA Vol. 7 No. 2 (2026): Jurnal Puan Indonesia Vol 7 No 2 januari 2026
Publisher : ASOSIASI IDEBAHASA KEPRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37296/jpi.v7i2.458

Abstract

Understanding computer hardware is an important skill for the younger generation in facing the technology-based world of work. This PkM activity aims to improve the knowledge and skills of seventh-grade students of SMP Negeri 2 Cimahi in assembling computer components. Based on initial observations, seventh-grade students have not learned about computer assembly, so the team initiated this training program. The implementation method used a practical training and demonstration approach that included material on the function and role of computer hardware such as the motherboard, central processing unit, memory, hard drive, graphics card, power supply unit, system bus, and co-processor, as well as hands-on computer assembly. Evaluation was conducted through question-and-answer sessions and interactive discussions. This training provides a strong foundation for participants in understanding computer hardware and is expected to improve student competence in the field of information and communication technology.