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All Journal Dinamik Techno.Com: Jurnal Teknologi Informasi JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Informatika Global Jurnal Teknologi Dan Sistem Informasi Bisnis JISA (Jurnal Informatika dan Sains) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) 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 Jurnal Lentera Pengabdian JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Proceeding International Pelita Bangsa VIDHEAS: Jurnal Nasional Abdimas Multidisiplin SAINTEK Dedikasi : Jurnal Pengabdian Lentera
Zy, Ahmad Turmudi
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Religion Agriculture, Biological Sciences & Forestry Humanities 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 Library & Information Science Social Sciences Other

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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%.
Analisis Sentimen Media Sosial Twitter Terhadap Calon Presiden RI Tahun 2024 Menggunakan Klasifikasi Algoritma Naïve Bayes Effendi, Muhammad Makmun; Zy, Ahmad Turmudi; Arwan, Asep
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5210

Abstract

The progress of social media is currently being felt by many Indonesian people, one of the social media that is often used is Twitter, which is a media for posting information. Currently the viral post is the election of Presidential Candidates (capres) of the Republic of Indonesia which will be held in 2024, in line with this, the General Election Commission (KPU) is holding a presidential candidate debate which will be held on various television media in Indonesia and from the results of this debate the Indonesian people usually give opinions or comments on the debate from the positive and negative sides of the presidential candidates who appeared at that time, namely Anis, Prabowo and Ganjar Pranowo. To find out the results of sentiment towards the presidential candidates, the researchers carried out an analysis using a classification of tweets containing public sentiment towards the 2024 presidential candidacy, namely Anis, Prabowo and Ganjar with the classification method used in this research is Naive Bayes Classification (NBC). Anies Baswedan dataset 61.35% of Twitter users have negative comments and 39.65% of Twitter users have positive comments, Ganjar Pranowo dataset 59.12% of Twitter users have negative comments and 41.88% of Twitter users have positive comments, Ganjar Prabowo Subianto dataset 49.25% Twitter users commented negatively and 51.75% of Twitter users commented positively. Comparing the results of the three presidential candidates, Anies Baswedan's accuracy value is smaller than the other two candidates because Anies Baswedan has more negative comments than the other two candidates. Anies Baswedan got an accuracy value of 67.23%, Prabowo Subianto 83.42% and Ganjar Pranowo 88.15%. The amount of data affects the results of sentiment analysis, the more data the better the accuracy value obtained.
Implementing Internet Of Things (IOT) Technology For Real-Time Detection And Monitoring Of LPG Gas Leaks Effendi, M Makmun; Zy, Ahmad Turmudi; Sanudin, Sanudin
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 03 (2024): Informatika dan Sains , Edition July - September 2024
Publisher : SEAN Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The Currently, LPG (Liquefied Petroleum Gas) is a vital resource for many households in Indonesia, as highlighted by the government's initiative to convert from kerosene to gas as a cooking fuel. The widespread adoption of LPG is attributed to its affordability and efficiency. However, the flammable nature of LPG poses significant risks, particularly in the event of leaks, which can lead to explosions and fires. This research aims to develop a system that monitors and detects gas leaks in real-time to prevent such hazardous incidents. The proposed system utilizes Internet of Things (IoT) technology, incorporating MQ-6 gas sensors and Raspberry Pi to detect LPG leaks. The MQ-6 sensors are capable of identifying the presence of gas, while the Raspberry Pi processes the data and sends notifications in the event of a leak. The methodology includes literature reviews, user interviews, and data analysis to design an effective monitoring system. The results indicate that the system can accurately detect gas leaks and provide real-time alerts via SMS or a mobile application. In conclusion, this study demonstrates that an IoT-based monitoring and detection system for LPG leaks can significantly enhance safety by enabling prompt responses to gas leaks. This system not only benefits users by facilitating quicker leak management but also contributes to broader safety measures in residential and commercial environments.
Sentiment Analysis of Dune: Part Two Movie Reviews Using the Naive Bayes Method Maheswari, Diyan Arum; Zy, Ahmad Turmudi; Afriantoro, Irfan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4604

Abstract

Research on films is fascinating because of the profound changes that the development of information and communication technology has brought about in our interactions with and consumption of media content. This study performs sentiment analysis on "Dune: Part Two" movie reviews using the Naïve Bayes method. Review data was collected from IMDb and then processed through several stages such as preprocessing, feature selection with TF-IDF, data splitting, and data mining and evaluation. Naïve Bayes was chosen for its simplicity and ability to handle large datasets effectively. The test results showed a high accuracy rate of 95%, indicating that this model can identify positive, negative, and neutral sentiments well. The use of TF-IDF in feature selection allowed the model to focus on important words, enhancing its sentiment classification ability. This research can provide insights into audience perceptions of the film "Dune: Part Two," which is beneficial for the film industry.
Comparative Analysis of Earthquake Prediction with SVM, Naïve Bayes, and K-Means Models: Comparative Analysis of Earthquake Prediction with SVM, Naïve Bayes, and K-Means Models Muttaqin, Ahmad Fadhiil; Sunge, Aswan Supriyadi; Zy, Ahmad Turmudi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 1 (2025): Article Research January 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i1.5085

Abstract

Earthquakes are natural disasters with significant impacts on people and the environment, so effective methods for prediction are needed to improve preparedness and risk mitigation. This study analyzes the performance of three algorithms Support Vector Machine (SVM), Naïve Bayes, and K-Means in predicting earthquakes in Indonesia using a dataset containing 4,645 historical data from BMKG processed through preprocessing, data separation, analysis, and performance evaluation with RapidMiner tools. The results show that SVM has the best performance with 99.87% accuracy, 99.83% precision, and 95.61% recall, making it highly relevant for earthquake prediction. Naïve Bayes achieved 90.31% accuracy and 95.08% recall, but the low precision (57.24%) shows the limitations of this model. K-Means successfully clusters earthquakes into two categories: small (3,661 data) and large (55 data) earthquakes, with a Davies-Bouldin Index value of 0.579, reflecting good clustering quality. Based on these results, SVM is recommended as a superior earthquake prediction model, while Naïve Bayes and K-Means are more suitable for additional analysis. This approach confirms the potential of machine learning algorithms in supporting future earthquake risk mitigation.
Penentuan Jadwal Overtime Dengan Klasifikasi Data Karyawan Menggunakan Algoritma C4.5 Romli, Ikhsan; Zy, Ahmad Turmudi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i2.260

Abstract

Technological development and scientific advancement are very important and influential parts of all fields. With the development and advancement of technology, being experts in a field is a must because it is required to know more and learn about the technology that is currently developing. Information technology and informatics are needed to support performance. Large and small companies also need fast and accurate information to make easier decisions making. Therefore, data mining classification techniques are needed to solve these problems. The classification used in data mining is a Decision tree because it is a technique that is widely used and produces output with existing rules so that it can present employee data to determine the overtime schedule. This study uses the C4.5 algorithm to determine the overtime schedule. The test results of the overtime schedule with the C4.5 algorithm with the Confusion matrix have good accuracy, precision, and recall values, namely 91% accuracy, 86.05% precision, and 92.5% recall.
Implementasi Keamanan Data dalam Sistem Informasi Manajemen Masjid Menggunakan Kriptografi Caesar Cipher Putri, Tiara; Rahma, Syifa Aurellia; Novitasari, Aas; S.Djawas, Fathia Wardah; Zy, Ahmad Turmudi
Dinamik Vol 30 No 1 (2025)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v30i1.10061

Abstract

Penenelitian ini bertujuan untuk meningkatkan keamanan data pada Sistem Informasi Manajemen Masjid (SIM Masjid) dengan menggunakan algoritma Caesar Cipher. Algoritma ini mengenskripsi data login, seperti username dan password, dengan metode pergeseran karakter. Hasil pengujian menunjukan bahwa algoritma ini mampu menjaga kerahasiaan data tingkat dasar, meskipun rentan terhadap serangan brute force. Oleh karena itu, metode ini cocok untuk sistem dengan kebutuhan keamana rendah dan dapat dikombinasikan dengan algoritma lain untuk meningkatkan perlindungan. Pendekatan ini memberi solusi sederhana dan efisien untuk sistem informasi di lingkungan dengan keterbatasan sumber daya.
Evaluasi dan Penyempurnaan Sistem Informasi Benih Anggur Berbasis Web dengan Pendekatan Agile Zy, Ahmad Turmudi; Sari, Nita Winda; Effendi, M Makmun; Nugroho, Agung; Siregar, Amril Mutoi
Dedikasi: Jurnal Pengabdian Lentera Vol. 2 No. 06 (2025): Juni 2025
Publisher : Lentera Ilmu Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59422/djpl.v2i06.929

Abstract

Kegiatan pengabdian ini bertujuan untuk mengevaluasi dan menyempurnakan sistem informasi benih anggur berbasis web yang telah diterapkan pada Komunitas Anggur Cikarang. Sistem ini dikembangkan dengan pendekatan Agile yang memungkinkan pengembangan iteratif dan partisipatif. Permasalahan utama yang diidentifikasi meliputi kurangnya pusat informasi terintegrasi, minimnya pemanfaatan teknologi informasi, dan jangkauan pemasaran yang terbatas. Solusi yang ditawarkan meliputi desain ulang sistem, pengembangan fitur baru berdasarkan umpan balik pengguna, serta pelatihan dan pendampingan komunitas dalam penggunaan sistem. Hasil kegiatan diharapkan dapat meningkatkan efisiensi manajemen bibit, memperluas distribusi pasar, serta mendorong pemberdayaan ekonomi masyarakat berbasis teknologi.
Implementasi Media Promosi dan Informasi Pada SMP Insan Kamil Cikarang Berbasis Website Zy, Ahmad Turmudi; Muhammad, Najamuddin Dwi Miharja; Edora, Edora; Rakhmat, Adrianna Syariefur; Fahamsyah, Mohammad Hatta
Lentera Pengabdian Vol. 1 No. 01 (2023): Januari 2023
Publisher : Lentera Ilmu Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59422/lp.v1i01.14

Abstract

ABSTRAK Di Indonesia, terdapat beberapa jenjang sekolah yang terdiri dari SD (Sekolah Dasar), SMP (Sekolah Menengah Pertama), SMA (Sekolah Menengah Atas), dan SMK (Sekolah Menengah Kejuruan). Salah satu sekolah SMP di Indonesia adalah SMP Insan Kamil Cikarang. Website merupakan salah satu media yang sangat efektif untuk digunakan sebagai media promosi dan penyebaran informasi bagi sekolah, Salah satu cara yang sering digunakan oleh sekolah dalam mempromosikan diri adalah dengan menyebarkan pamflet. Namun, pamflet sebenarnya merupakan salah satu media promosi yang sudah kuno dan kurang efektif. Pembuatan Website sebagai media Promosi dan Informasi di SMP IT Insan Kamil Cikarang Kabupaten Bekasi ternyata berdampak positif bagis sekolah dalam penyebaran Informasi dan promosi. Kata kunci: PKM, Website, Promosi
Co-Authors Abdul Azis Abdul Ghofir Abdul Halim Anshor Adrianna Syariefur Rakhmat Afriantoro, Irfan Ainur Rofieq Alfian Ma’arif Ananda, Angga Thifal Anaoval, Abdul Aziz Andika, Sophian Anwar, M Syaibani Arwan, Asep Astuti, Asri Liya Aswan Supriyadi Sunge Ayassy, Bayu Maulana Djoko Nugroho Edora, Edora Effendi, M Makmun Effendi, Muhammad Makmun Fadlurrohman, Muhammad Shiddiq Fahamsyah, Mohammad Hatta Gatot Tri Pranoto Gunawan, G Handono, Bagus Tri Hartono, Rudi Hidayatullah, Cahyo Ikhsan Romli Isarianto, Isarianto Isro, Aditya Bani Jeckson Sidabutar Khotimah, Nur Maharani, Siti Mutia Maheswari, Diyan Arum Muhamad Ekhsan Muhammad, Najamuddin Dwi Miharja Muttaqin, Ahmad Fadhiil Nadya Safitri, Nadya Novitasari, Aas Noviyanti, Rosa Nugraha, Dimas Reza Nurmaulida*, Irma Pamungkas, Bagas Perdana, Anggi Permatasari, Antini Pranoto, Kirana Astari PUTRI, TIARA Rahma, Syifa Aurellia Ramadhan, Yogi Reza Rozikin, Zaenur s, suherman S.Djawas, Fathia Wardah Saiful Muktiali Sanudin Sanudin Sari, Nita Winda Sasongko, Ananto Tri Sen , Tjong Wan Shintania, Mira Simanjuntak, Antonius Simarangkir, Manase Sahat H Sinaga, Frans Putra Siregar, Amril Mutoi Sunge, Aswan S Sunge, Aswan S. Sunita Dasman Surojudin , Nurhadi Surojudin, Nurhadi Suryadi, Dikky Wahyu Caesarendra Wangsadanureja, Miftah Wijaya, Kurnia Difa Yoga Pratama Zahri, M. Hannata