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FIRMAN TEMPOLA
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Jiko (Jurnal Informatika dan komputer)
Published by Universitas Khairun
ISSN : 26148897     EISSN : 26561948     DOI : -
Core Subject : Science,
Computer Science & IT
Jiko (Jurnal Informatika dan Komputer) Ternate adalah jurnal ilmiah diterbitkan oleh Program Studi Teknik Informatika Universitas Khairun sebagai wadah untuk publikasi atau menyebarluaskan hasil - hasil penelitian dan kajian analisis yang berkaitan dengan bidang Informatika, Ilmu Komputer, Teknologi Informasi, Sistem Informasi dan Sistem Komputer. Jurnal Informatika dan Komputer (JIKO) Ternate terbit 2 (dua) kali dalam setahun pada bulan April dan Oktober
Arjuna Subject : -
Articles 22 Documents
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Search results for , issue "Vol 7, No 3 (2024)" : 22 Documents clear
QUESTION BANK SECURITY USING RIVEST SHAMIR ADLEMAN ALGORITHM AND ADVANCED ENCRYPTION STANDARD Monica, Taris; Hadiana, Asep Id; Melina, Melina
JIKO (Jurnal Informatika dan Komputer) Vol 7, No 3 (2024)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i3.8654

Abstract

Data security is essential. Educational question banks at vocational high schools (SMK) contain confidential information that could be misused if not properly secured. This research aims to ensure students question bank data and develop a responsive web platform for Pusdikhubad Cimahi Vocational School by implementing the integration of the Advanced Encryption Standard (AES) and Rivest Shamir Adleman (RSA) cryptographic algorithms through the encryption and decryption process. AES is a symmetric key cryptography algorithm, while RSA is an encryption algorithm based on using public keys to encrypt the keys required by AES-256. The integration of these two algorithms aims to ensure data confidentiality, prevent manipulation, and facilitate access to exam materials by authorized parties. This research shows that the process of encrypting and decrypting question data using a combination of RSA and AES was successfully carried out on the question bank system. Avalanche Effect testing shows that the RSA and AES 256-bit encryption has an Avalanche Effect level of 49.99%. Apart from that, the system feasibility test using black box testing results shows that the SIFILE system has a percentage level of 100%. It is hoped that the results of this research can serve as a data security system at Pusdikhubad Cimahi Vocational School and other educational institutions to secure the question bank from unauthorized access
CUSTOMER CHURN PREDICTION USING THE RANDOM FOREST ALGORITHM Setiawan, Yosep; Hadiana, Asep Id; Umbara, Fajri Rakhmat
JIKO (Jurnal Informatika dan Komputer) Vol 7, No 3 (2024)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i3.8711

Abstract

Customer churn prediction plays a vital role in modern business, accurately influencing strategic and operational decisions that influence customer loyalty to a service. Customer churn focuses on customer retention being more profitable than attracting new customers because long-term customers provide lower profits and costs while losing customers increases the costs and need to attract new customers. However, customer churn still occurs frequently and cannot be predicted. If customer churn is left unchecked, it will endanger the company or banking industry because it can cause loss of income, damage reputation, and decrease market share. Random Forest, a data mining technique, was used in this research because of its ability to predict and handle many variables. This research aims to predict customer churn using the Random Forest method with datasets from Europe, especially France, Spain, and Germany, hoping to benefit the banking industry by identifying customers at high risk of abandoning services. This research is expected to benefit business people from customer churn predictions. Especially in the banking industry, it can help identify customers at high risk of abandoning service. Thus, companies can take appropriate steps to retain these customers, increase customer retention, strengthen customer loyalty and optimize their business performance. The results of this research are an accurate system for predicting customer churn in the future. The research obtained accuracy results of 87% in predicting customer churn using accuracy testing in the form of a confusion matrix.

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