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All Journal KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Techno Nusa Mandiri : Journal of Computing and Information Technology
Mohamad Ardi
Unknown Affiliation
Computer Science & IT

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APLIKASI KRIPTOGRAFI PESAN SHORT MESSAGE SERVICE PADA SMARTPHONE BERBASIS ANDROID DENGAN METODE PLAYFAIR CIPHER Heliza Rahmania Hatta; Mohamad Ardi; Septya Maharani
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 4, No 1 (2017)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v4i1.66

Abstract

The current technological developments, allows humans to communicate and exchange information remotely. Along with the demands for security against the confidentiality of the information exchanged is increasing. Therefore, it is developing branch of science that studies on ways of securing data or better known as cryptography. Playfair cipher method is one method for text encoding cryptography. This study aims to develop an application of cryptography SMS (Short messsage Service) on the android based smartphone with Playfair cipher method, which can send SMS messages cryptography and receive text messages encrypted and then decrypted. These applications do cryptography in text form letters. The key used in the form of letters. The results of this study are in the form of android-based application that can make sending SMS messages that have been encrypted using the Playfair cipher method, so that the confidentiality of the message can be gated.Keywords: Cryptography, SMS, Smartphone, Android, Playfair Cipher.Perkembangan teknologi sekarang ini, memungkinkan manusia dapat berkomunikasi dan dapat bertukar informasi secara jarak jauh. Seiring dengan itu tuntutan akan keamanan terhadap kerahasiaan informasi yang saling dipertukarkan tersebut semakin meningkat. Oleh karena itu, dikembangkanlah cabang ilmu yang mempelajari tentang cara-cara pengamanan data atau lebih dikenal dengan Kriptografi. Metode playfair cipher merupakan salah satu metode kriptografi untuk penyandian teks. Penelitian ini bertujuan untuk membangun suatu aplikasi kriptografi pesan SMS (Short Messsage Service) pada smartphone berbasis android dengan metode playfair cipher, yang dapat mengirim kriptografi pesan SMS dan menerima pesan teks terenkripsi yang kemudian didekripsi. Aplikasi ini melakukan kriptografi pada teks berupa huruf. Kunci yang digunakan berupa huruf. Hasil dari penelitian ini adalah berupa aplikasi berbasis android yang dapat melakukan pengiriman pesan SMS yang telah terenkripsi menggunakan metode playfair cipher, sehingga kerahasiaan dari pesan tersebut dapat terjaga keamanannya.Kata kunci: Kriptografi, SMS, Smartphone, Android, Playfair Cipher.
FEATURE SELECTION COMPARATIVE PERFORMANCE FOR UNSUPERVISED LEARNING ON CATEGORICAL DATASET Fitriyanto, Rachmad; Mohamad Ardi
Jurnal Techno Nusa Mandiri Vol. 22 No. 1 (2025): Techno Nusa Mandiri : Journal of Computing and Information Technology Period o
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v22i1.6512

Abstract

In the era of big data, Knowledge Discovery in Databases (KDD) is vital for extracting insights from extensive datasets. This study investigates feature selection for clustering categorical data in an unsupervised learning context. Given that an insufficient number of features can impede the extraction of meaningful patterns, we evaluate two techniques—Chi-Square and Mutual Information—to refine a dataset derived from questionnaires on college library visitor characteristics. The original dataset, containing 24 items, was preprocessed and partitioned into five subsets: one via Chi-Square and four via Mutual Information using different dependency thresholds (a low-mid-high scheme and dynamic quartile thresholds: Q1toMax, Q2toMax, and Q3toMax). K-Means clustering was applied across nine variations of K (ranging from 2 to 10), with clustering performance assessed using the silhouette score and Davies-Bouldin Index (DBI). Results reveal that while the Mutual Information approach with a Q3toMax threshold achieves an optimal silhouette score at K=7, it retains only 4 features—insufficient for comprehensive analysis based on domain requirements. Conversely, the Chi-Square method retains 18 features and yields the best DBI at K=9, better capturing the intrinsic characteristics of the data. These findings underscore the importance of aligning feature selection techniques with both clustering quality and domain knowledge, and highlight the need for further research on optimal dependency threshold determination in Mutual Information.
Co-Authors Fitriyanto, Rachmad Heliza Rahmania Hatta Septya Maharani