Eno Hakimah Kusuma Dewi
Universitas Singaperbangsa Karawang

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Black Box Testing pada Aplikasi Pencatatan Peminjaman Buku Menggunakan Boundary Value Analysis Eno Hakimah Kusuma Dewi; Ilyas Shiddiq Pratama; Audy Sukma Putera; Carudin Carudin
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 6, No 3 (2022)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (250.946 KB) | DOI: 10.30998/string.v6i3.11958

Abstract

The book borrowing recording application can record activities related to borrowing books in the library, such as recording a track record of borrowing a book. However, applications that have been made in such a way need to go through a test flow to find out how far the performance and quality of the application itself is. Therefore, it is necessary to have a test to find out how the quality is. So, the purpose of this research is to carry out a testing on the book lending recording application to identify whether the application is in accordance with user needs or not. The test, which is one of the stages of the Software Development Life Cycle (SDLC) methodology carried out on this book lending recording application, applies Black Box Testing with the Boundary Value Analysis method which focuses on aspects of input validation, observing input content, and input results. The test results show that in the book borrowing recording system, discrepancies were found in the input process in the loan registration feature and book borrowing form so that it needed to be corrected before being used by the user.
IMPLEMENTASI COSINE SIMILARITY DALAM ANALISIS INVESTIGASI CYBERBULLYING PADA TWITTER DENGAN FRAMEWORK NIST Eno Hakimah Kusuma Dewi; Aries Suharso; Chaerur Rozikin
Cyber Security dan Forensik Digital Vol. 5 No. 1 (2022): Edisi Mei 2022
Publisher : Fakultas Sains dan Teknologi UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/csecurity.2022.5.1.3397

Abstract

Pengguna Twitter di Indonesia pada tahun 2021 tercatat mencapai 63,6% dari jumlah populasi dan menempati urutan ke-5 sosial media yang sering diakses oleh masyarakat Indonesia. Semakin tingginya tingkat pengguna Twitter memberi peluang bagi penggunanya untuk melakukan cybercrime seperti cyberbullying. Korban cyberbullying rentan terkena depresi dibandingkan dengan korban tindakan kekerasan verbal lainnya. Melihat dampak yang ditimbulkan maka diperlukan langkah-langkah untuk mengatasi cyberbullying dengan investigasi forensik untuk membuktikan dan menemukan bukti digital yang membantu menyelesaikan kasus cyberbullying yang  marak terjadi di media sosial seperti pada Twitter, sehingga dapat diajukan sebagai bukti kuat, konkrit, serta dapat diproses di pengadilan. Tujuan dari penelitian ini untuk menemukan bukti digital dan mengidentifikasi tindakan cyberbullying pada fitur pesan grup Twitter dengan alur kerja NIST (National Institute of Standards and Technology). Penelitian ini berhasil mendapatkan bukti digital berupa teks percakapan pada smartphone korban yang diekstrak dengan tools MOBILEdit Forensic Express dan dianalisis dengan text processing, pembobotan term/kata, dan menerapkan formula cosine similarity untuk mengidentifikasi cyberbullying. Hasil penelitian menujukkan alur kerja NIST berhasil mengangkat barang bukti hingga pelaporan barang bukti. Metode cosine similarity berhasil mengidentifikasi kalimat yang terindikasi bullying dengan nilai yang berbeda, pelaku dengan nilai tertinggi mencapai 0,377, sedangkan pelaku dengan nilai terendah menyentuh angka 0,02 berdasarkan dengan percakapan terhadap query (kata kunci) bullying. Kata kunci: digital forensik, cyberbullying, cosine similarity, nist, twitter ------ Twitter users in Indonesia in 2021 are recorded at 63.6% of the total population and ranks 5th on social media that are often accessed by Indonesian people. The higher level of Twitter users provides opportunities for users to commit cybercrime such as cyberbullying. Victims of cyberbullying are more prone to depression than other victims of verbal abuse. Seeing the impact, it is necessary to take steps to overcome cyberbullying with forensic investigations to prove and find digital evidence that helps resolve cyberbullying cases that are rife on social media such as Twitter, so that it can be submitted as strong, concrete evidence, and can be processed in court. The purpose of this study was to find digital evidence and identify acts of cyberbullying on the Twitter direct message group with the NIST (National Institute of Standards and Technology) methodology. This study succeeded in obtaining digital evidence in the form of text conversations on the victim's smartphone which was extracted with the MOBILEdit Forensic Express tool and analyzed by text processing, weighting terms/words, and applying the cosine similarity formula to identify cyberbullying. The results of the study show that the NIST has succeeded in raising evidence to reporting evidence. The cosine similarity method succeeded in identifying sentences that indicated bullying with different values, the perpetrator with the highest score reached 0.377, while the perpetrator with the lowest score touched 0.02 based on conversations about the bullying query (keyword). Keywords: digital forensic, cyberbullying, cosine similarity, nist, twitter