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All Journal JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Computer Networks, Architecture and High Performance Computing Brilliance: Research of Artificial Intelligence SIGMA: Information Technology Journal Ranah Research : Journal of Multidisciplinary Research and Development VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Pelita Pengabdian Review: Journal of Multidisciplinary in Social Sciences
ARIF SUSILO
S1 Pendidikan Teknik Mesin FT Unesa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Transportation Other

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Determining Superior Classes Based on Academic Grades at SMK Karya Pembaharuan with the K-Means Clustering Method Siregar, Lydia Diffani; Susilo, Arif; Widiyatmoko, Arif Tri
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.v6i4.4866

Abstract

Dalam lingkungan pendidikan, pengelompokan k-means dapat membantu sekolah menemukan kelas terbaik berdasarkan nilai akademik siswa. Dengan mengelompokkan siswa berdasarkan nilai akademik, sekolah dapat lebih mudah mengidentifikasi kelompok siswa yang memiliki nilai akademik tinggi, sedang, dan rendah. Kemudian penelitian yang digunakan adalah Semua objek dalam satu cluster memiliki karakteristik yang sama , tetapi setiap cluster memiliki karakteristik yang berbeda. Novi dan Ade Mubarok menulis jurnal pada tahun 2021 yang berjudul “Penerapan Algoritma K-Means Untuk Menentukan Kelas Unggulan Pada Smp Pelita Bandung” yang menyimpulkan bahwa SMP Pelita Bandung membutuhkan 3 cluster. Setelah peneliti melakukan eksperimen, mereka dapat menghasilkan 3 cluster, yaitu cluster 0 merupakan cluster dengan nilai rata-rata terendah yang akan masuk ke dalam kelas C sebanyak 42 siswa, pada cluster 1 dengan nilai rata-rata sedang akan masuk ke dalam kelas B sebanyak 37 siswa, sedangkan pada cluster 3 dengan nilai rata-rata siswa, sedangkan pada cluster 3 dengan nilai rata-rata tertinggi akan masuk ke dalam kelas A sebanyak 40 siswa. Hasil penelitian ini menunjukkan bahwa terdapat 6 siswa dalam kategori tinggi, 24 siswa dalam kategori sedang, dan 14 siswa dalam kategori rendah. Evaluasi terhadap hasil pengelompokan menunjukkan hasil yang cukup baik, dengan nilai Davies Bouldin Index (DBI) sebesar 1,180 yang mendekati angka 0.
ANALISIS EFEKTIVITAS SISTEM DETEKSI INTRUSI TERHADAP SERANGAN DDOS: INVESTIGASI BERBASIS SIMULASI Isarianto, Isarianto; Turmudi Zy, Ahmad; Maulana, Donny; Susilo, Arif
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 4 (2025): JATI Vol. 9 No. 4
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i4.14359

Abstract

Serangan Distributed Denial of Service (DDoS) merupakan ancaman serius bagi keamanan jaringan modern karena mampu melumpuhkan layanan digital secara masif. Penelitian ini menyoroti pentingnya sistem deteksi intrusi (Intrusion Detection System/IDS) yang tangguh dalam menghadapi serangan tersebut, terutama dengan pendekatan pembelajaran mesin. Permasalahan utama yang diangkat adalah bagaimana meningkatkan akurasi deteksi serangan dalam kondisi distribusi data yang tidak seimbang. Penelitian ini bertujuan untuk mengevaluasi efektivitas IDS berbasis algoritma XGBoost dalam mengidentifikasi lalu lintas jaringan berbahaya, khususnya serangan DDoS, dengan memanfaatkan dataset CICIDS2017. Metode yang digunakan meliputi pra-pemrosesan data, penyeimbangan kelas menggunakan undersampling, normalisasi fitur, pelatihan model dengan XGBoost, serta optimasi hyperparameter melalui grid search. Evaluasi kinerja dilakukan menggunakan metrik precision, recall, F1-score, confusion matrix, dan ROC-AUC. Hasil menunjukkan bahwa model mencapai nilai di atas 99% untuk seluruh metrik evaluasi, menandakan performa deteksi yang sangat baik. Penelitian ini menyimpulkan bahwa kombinasi balancing data dan optimasi XGBoost mampu menghasilkan IDS yang andal dalam skenario simulasi serangan DDoS, serta menyoroti pentingnya pengujian lanjutan pada data nyata untuk mengukur kemampuan generalisasi sistem.
Web-Based Tuition Payment Application System at SDIT Fidarussalam South Cikarang Susilo, Arif; Purnama, Lukman
Review: Journal of Multidisciplinary in Social Sciences Vol. 2 No. 08 (2025): August 2025
Publisher : Lentera Ilmu Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59422/rjmss.v2i08.1044

Abstract

This study aims to design and implement a web-based tuition payment system at SDIT Fidarussalam, Cikarang Selatan. The research was motivated by the manual payment recording process that often caused errors, duplication, and potential data loss. To address these issues, the study applied the waterfall development model, which includes stages of requirement analysis, system design, coding, testing, and maintenance. Data collection was conducted through observation, interviews, and literature study. The system was developed using PHP and MySQL, while UML diagrams were employed as design tools. The results show that the system enables efficient, accurate, and structured data management. Key features include student data entry, payment processing, receipt generation, and reporting. Black-box testing confirmed that all functional requirements were successfully met, and the system operated as expected. The implementation of the web-based tuition payment system significantly improves administrative efficiency and accuracy compared to the previous manual method. It reduces human error, prevents data duplication, and minimizes the risk of data loss. Moreover, it streamlines payment processes and facilitates better record management. In conclusion, this research demonstrates that adopting a web-based application can enhance school administration by integrating technology into financial management. The system provides a reliable solution for managing tuition payments while ensuring data security and supporting decision-making through comprehensive reporting features.
Pelatihan Pengembangan Aplikasi Mobile untuk Peningkatan Literasi Digital di STMIK Al Muslim Bekasi Susilo, Arif; Hutauruk, Basar Maringan; Saputra, Alhadi
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 3 No. 1 (2025): Juni 2025
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v3i1.120

Abstract

This training aimed to improve the digital literacy of STMIK Al Muslim Bekasi students by mastering the fundamentals of mobile application development. In today's digital era, the ability to develop Android-based applications is a crucial skill that can support graduates' competency and competitiveness in the workforce. The training, conducted in-person and hands-on, covered topics on interface design (UI/UX), basic programming using Android Studio, and publishing applications to digital platforms. Participants were students majoring in Informatics Engineering and Information Systems with an interest in software development. The results of this training demonstrated an increased understanding of mobile application development concepts and basic technical skills in creating and running simple applications. The training also fostered participants' interest in developing digital solutions relevant to community needs. Thus, this activity positively contributes to supporting digital literacy programs within higher education institutions. Keywords: Digital literacy, mobile applications, Android Studio, training, students.
Pendampingan Pengembangan Aplikasi Mobile untuk Pemberdayaan UMKM di STMIK Al Muslim Bekasi Susilo, Arif; Hutauruk, Basar Maringan; Saputra, Alhadi
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 2 No. 2 (2024): Desember 2024
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v2i2.133

Abstract

This community service activity aims to provide assistance in developing a mobile application as a means of empowering Micro, Small, and Medium Enterprises (MSMEs) at STMIK Al Muslim Bekasi. MSMEs play a strategic role in local economic growth but still face various challenges such as limited market access, low digital literacy, and suboptimal utilization of information technology. Through this program, the implementation team assisted MSME partners in designing, implementing, and operating a mobile application that functions as a medium for promotion, transactions, and customer communication. The implementation methods included needs analysis, technology utilization training, mobile-based system development, and application performance evaluation. The results of the mentoring showed an increase in partners’ understanding of digital technology, improved online product promotion capabilities, and greater confidence among MSME actors in managing technology-based businesses. Thus, this activity not only provides practical solutions through mobile application development but also contributes to strengthening MSME competitiveness and enhancing the digital economic ecosystem in Bekasi. Keywords: MSMEs, mobile application, empowerment, STMIK Al Muslim Bekasi, digital literacy.
Linear Regression Algorithm Analysis for Predicting Electrical Panel Painting Quality Susilo, Arif; Widodo , Edy; Rilvani, Elkin; Suryana, Syahro
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4096

Abstract

Industry is increasingly developing rapidly and has an impact on the emergence of competition between companies, both private and state, both companies engaged in manufacturing and service companies. Linear Regression is used to find out how the dependent/criterion variable can be predicted through independent variables or predictor variables, individually. Based on the results of the tests that have been carried out, the variables or attributes used in this research (minute and thinkness results) have a significant effect on this research. It is proven that using the linear regression algorithm is able to provide good results with a Root Mean Squared Error value of 0.273 +/- 0.000. This is because there is a correlation or functional relationship (cause - effect) between one variable (dependent or criterion) and another variable (independent or predictor). This testing process is carried out to identify stock needs using a linear regression algorithm
Application of the C 4.5 Algorithm to Classify Customer Characteristics at PT. Bayer Indonesia Siswandi, Arif; Anwar, M. Syaibani; Susilo, Arif; Hasibuan, Sultan
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4174

Abstract

PT. Bayer Indonesia is a company engaged in drug production. In running its business, companies need to know customer characteristics in determining what actions to take next. This research aims to apply the C 4.5 algorithm in classifying customer characteristics at PT. Bayer Indonesia. The C 4.5 algorithm is a decision tree algorithm that is often used in data mining for classification purposes. This research was conducted to make it easier to find out customer characteristics. Starting with collecting data, then selecting the attributes that will be used. Then the data is separated using split data, the initial comparison used is 60% train data and 40% test data. Then training data is carried out using the C4.5 algorithm. Next, the classification results were evaluated using the confusion matrix method. The data used was 200 data with 9 attributes, obtained an accuracy of 86.25%, precision of 86.25% and recall of 54.55%. Then change the data split parameters to 70% : 30%, 80% : 20% and 90% : 10%. The best accuracy is 100%. The research results show that the C 4.5 algorithm has good performance in classifying the characteristics of PT customers. Bayer Indonesia. The resulting model can be used by companies for more effective marketing strategies and personalized customer service.
Co-Authors Abdul Rohim, Abdul Abdul Wahab Amali, Amali Andriani Anwar, M. Syaibani Aprila Hardi, Resty Arwan Sulaeman, Asep Butsianto, Sufajar Eko Putra, Fibi Elkin Rilvani Hasibuan, Sultan Hutauruk, Basar Maringan Isarianto Isarianto, Isarianto Iwan Mulyana Maulana, Donny Mustafanah, Alif Naya, Candra Nugroho, Agung Purnama, Lukman Saputra, Alhadi Sarifah Faujiah, Rani Setyawan, Wisnu Siregar, Lydia Diffani Siswandi, Arif Suryana, Syahro Turmudi Zy, Ahmad Wangsadanureja, Miftah Widiyatmoko, Arif Tri Widodo , Edy Wiyanto -