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All Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Teknologi Dan Sistem Informasi Bisnis Journal of Computer System and Informatics (JoSYC) Journal of Computer Networks, Architecture and High Performance Computing J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Info Sains : Informatika dan Sains JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Proceeding International Pelita Bangsa VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Pelita Pengabdian SAINTEK
Zy, Ahmad Turmudi
Unknown Affiliation
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Social Sciences

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Journal : Journal of Computer Networks, Architecture and High Performance Computing

 1 
The Use of K-Means Algorithm Clustering in Grouping Life Expectancy (Case Study: Provinces in Indonesia) Nugraha, Dimas Reza; Zy, Ahmad Turmudi; Sunge, Aswan Supriyadi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4171

Abstract

Life expectancy is defined as information that illustrates the age of the death of a population. Life expectancy is a general picture of the state of a region. If the infant mortality rate is high, then the life expectancy in the area is low. And vice versa, if the infant mortality rate is low, the life expectancy in the region is high. Life expectancy is also a benchmark for government actions in improving the welfare of society and the human development index. For this reason, it is necessary to group life expectancy data to make it easier to determine the provinces with high, middle, and low life expectancy. The results of cluster testing using the silhouette score method showed that two subjects had a low silhouette score level, which caused the cluster value to be less than optimal, namely East Java  & Gorontalo. The clustering results found that the cluster was divided into 3, namely cluster 1, with a high level of life expectancy consisting of 10 provinces, namely East Java, Riau, North Sulawesi, Bali, North Kalimantan, DKI Jakarta, West Java, Central Java, East Kalimantan and Special Region of Yogyakarta. Cluster 2 has a level of middle-life expectancy consisting of 18 provinces, namely Gorontalo, North Maluku, Central Sulawesi, South Kalimantan, North Sumatra, Bengkulu, West Sumatra, Central Kalimantan, Aceh, South Sumatra, Banten, Kep. Riau, South Sulawesi, Kep. Bangka Belitung, Lampung, West Kalimantan, Southeast Sulawesi and Jambi. Cluster 3, with a low level of life expectancy, consists of 6 provinces, namely West Sulawesi, Papua, Maluku, West Papua, West Nusa Tenggara, and East Nusa Tenggara.
Analysis of Manual and Automated Methods Effectiveness in Website Penetration Testing for Identifying SQL Injection Vulnerabilities Anaoval, Abdul Aziz; Zy, Ahmad Turmudi; S, Suherman
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4249

Abstract

This research aims to identify vulnerabilities to SQL Injection attacks on websites through penetration testing using quantitative and descriptive methods. In the current digital era, data and information security has become a crucial aspect. One of the frequent threats is SQL Injection attacks, where attackers insert malicious SQL commands into queries executed by web applications. This study utilizes tools such as Burp Suite to identify and exploit vulnerabilities in a login form created by the researchers. The research process begins with the Pre-Engagement Interactions phase, which includes information gathering and setting the testing scope. Subsequently, Vulnerability Testing is conducted to evaluate existing weaknesses. The exploitation of vulnerabilities is performed using the 'OR'1'='1 technique, which successfully demonstrates that the website is vulnerable to SQL Injection attacks. The results of this study indicate that the login form on the website is susceptible to SQL Injection due to insufficient input validation and the use of dynamic SQL queries without prepared statements. Implementing stricter input validation techniques and using prepared statements has proven effective in enhancing website security. This research makes a significant contribution to the field of information system security, particularly in the prevention of SQL Injection attacks. The results of this study can serve as a practical guide for web developers in improving the security of their applications and provide a deeper understanding of the threats and mitigation techniques for SQL Injection.
The Analysis of Product Sales in the Application of Data Mining with Naive Bayes Classification Zahri, M. Hannata; Sunge, Aswan S.; Zy, Ahmad Turmudi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4255

Abstract

H&F Shoe Store is a privately owned Micro, Small, and Medium Enterprises retail store that sells merchandise. The owner serves customers directly and also acts as a cashier. In this store, the business owner is less aware of what types or categories of products are most in demand by customers, making sales operations less than optimal. Because of this, special expertise is needed to handle the problems in the retail store, namely data mining or Data Mining with the aim of digging up information related to sales problems, in this case the author will use the Classification method with the Naive Bayes algorithm. In this study, the author uses secondary data obtained from sales notebooks and re-collected into Microsoft Excel according to research needs. The data that has been collected on the software is 121 data which have 10 attributes, namely “Nama Produk”, “Size Produk”, “Kategori Produk”, “Jenis Produk”, “Gender Produk”, “Merek Produk”, “Stok Awal”, “Stok Terjual”, “Stok Sisa”, and “Penjualan”. The Naive Bayes Classifier method has successfully produced good results in classifying sales on a type or category of marketed products, the results obtained are in the form of product sales analysis and Naive Bayes model evaluation values. The results of the model evaluation values on the Confusion Matrix obtained are accuracy of 86.11%, recall of 84.62% and precision of 84.62%.
Co-Authors . Ermanto Abdul Azis Abdul Ghofir Alfian Ma’arif Ananda, Angga Thifal Anaoval, Abdul Aziz Arwan, Asep Astuti, Asri Liya Djoko Nugroho Effendi, M Makmun Effendi, Muhammad Makmun Fadlurrohman, Muhammad Shiddiq Gunawan, G Handono, Bagus Tri Hartono, Rudi Jeckson Sidabutar Khotimah, Nur Maharani, Siti Mutia Muktiali, Saiful Nugraha, Dimas Reza Nugroho, Agung Nurmaulida*, Irma Perdana, Anggi Permatasari, Antini Pradini, Purnama Sakhrial Pranoto, Kirana Astari Ramadhan, Yogi Reza s, suherman Sanudin Sanudin Sasongko, Ananto Tri Shintania, Mira Simanjuntak, Antonius Simarangkir, Manase Sahat H Sunge, Aswan S Sunge, Aswan S. Sunge, Aswan Supriyadi Surojudin, Nurhadi Suryadi, Dikky Wahyu Caesarendra Wijaya, Kurnia Difa Zahri, M. Hannata