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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnas Nasional Teknologi dan Sistem Informasi Proceeding of the Electrical Engineering Computer Science and Informatics PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Ilmiah Media Sisfo JURIKOM (Jurnal Riset Komputer) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Informatika dan Rekayasa Komputer Jurnal Manajemen Teknologi dan Sistem Informasi Jurnal Manajemen Sistem Informasi
Sharipuddin, Sharipuddin
Universitas Dinamika Bangsa
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Intrusion detection with deep learning on internet of things heterogeneous network Sharipuddin Sharipuddin; Benni Purnama; Kurniabudi Kurniabudi; Eko Arip Winanto; Deris Stiawan; Darmawijoyo Hanapi; Mohd. Yazid Idris; Rahmat Budiarto
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i3.pp735-742

Abstract

The difficulty of the intrusion detection system in heterogeneous networks is significantly affected by devices, protocols, and services, thus the network becomes complex and difficult to identify. Deep learning is one algorithm that can classify data with high accuracy. In this research, we proposed deep learning to intrusion detection system identification methods in heterogeneous networks to increase detection accuracy. In this paper, we provide an overview of the proposed algorithm, with an initial experiment of denial of services (DoS) attacks and results. The results of the evaluation showed that deep learning can improve detection accuracy in the heterogeneous internet of things (IoT).
Network anomaly detection research: a survey Kurniabudi Kurniabudi; Benni Purnama; Sharipuddin Sharipuddin; Darmawijoyo Darmawijoyo; Deris Stiawan; Samsuryadi Samsuryadi; Ahmad Heryanto; Rahmat Budiarto
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 7, No 1: March 2019
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (416.184 KB) | DOI: 10.52549/ijeei.v7i1.773

Abstract

Data analysis to identifying attacks/anomalies is a crucial task in anomaly detection and network anomaly detection itself is an important issue in network security. Researchers have developed methods and algorithms for the improvement of the anomaly detection system. At the same time, survey papers on anomaly detection researches are available. Nevertheless, this paper attempts to analyze futher and to provide alternative taxonomy on anomaly detection researches focusing on methods, types of anomalies, data repositories, outlier identity and the most used data type. In addition, this paper summarizes information on application network categories of the existing studies.
Enhanced Deep Learning Intrusion Detection in IoT Heterogeneous Network with Feature Extraction Sharipuddin Sharipuddin; Eko Arip Winanto; Benni Purnama; Kurniabudi Kurniabudi; Deris Stiawan; Darmawijoyo Hanapi; Mohd Yazid bin Idris; Bedine Kerim; Rahmat Budiarto
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 3: September 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/.v9i3.3134

Abstract

Heterogeneous network is one of the challenges that must be overcome in Internet of Thing Intrusion Detection System (IoT IDS). The difficulty of the IDS significantly is caused by various devices, protocols, and services, that make the network becomes complex and difficult to monitor. Deep learning is one algorithm for classifying data with high accuracy. This research work incorporated Deep Learning into IDS for IoT heterogeneous networks. There are two concerns on IDS with deep learning in heterogeneous IoT networks, i.e.: limited resources and excessive training time. Thus, this paper uses Principle Component Analysis (PCA) as features extraction method to deal with data dimensions so that resource usage and training time will be significantly reduced. The results of the evaluation show that PCA was successful reducing resource usage with less training time of the proposed IDS with deep learning in heterogeneous networks environment. Experiment results show the proposed IDS achieve overall accuracy above 99%.
Time Efficiency on Computational Performance of PCA, FA and TSVD on Ransomware Detection Benni Purnama; Deris Stiawan; Darmawijoyo Hanapi; Mohd. Yazid Idris; Sharipuddin Sharipuddin; Nurul Afifah; Rahmat Budiarto
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 1: March 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i1.3481

Abstract

Ransomware is able to attack and take over access of the targeted user'scomputer. Then the hackers demand a ransom to restore the user's accessrights. Ransomware detection process especially in big data has problems interm of computational processing time or detection speed. Thus, it requires adimensionality reduction method for computational process efficiency. Thisresearch work investigates the efficiency of three dimensionality reductionmethods, i.e.: Principal Component Analysis (PCA), Factor Analysis (FA) andTruncated Singular Value Decomposition (TSVD). Experimental results onCICAndMal2017 dataset show that PCA is the fastest and most significantmethod in the computational process with average detection time of 34.33s.Furthermore, result of accuracy, precision and recall also show that the PCAis superior compared to FA and TSVD.
User Behavior in Using Mobile Commerce (Scale Development: Perspective of Trust and Risk) Setiawan Assegaff; Jasmir Jasmir; Dodo Zaenal Abidin; Sharipuddin Sharipuddin
Jurnal Nasional Teknologi dan Sistem Informasi Vol 3, No 3 (2017): Desember 2017
Publisher : Jurusan Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v3i3.2017.320-325

Abstract

The aim of ours research is to explore the relation between the elements of trust and risk and their impact on consumer behavior in the intention of use of mobile commerce services based on sales. The final goal of this research is to understand consumer behavior in the use of mobile commerce application services in Indonesia by considering the elements of trust and risk in consumer behavior. Finding from previous research have revealed that trust and risk is one of the critical aspects in the use of e-commerce services. This article focus is to discuss the development stages of research instruments development to be used in next survey agenda. By applying Technology Acceptance Model (TAM) as a theoretical basis of a conceptual model and the research instrument was developed. Models and instruments then validated through a pilot study involving 75 students as respondents. Survey data were analyzed via Smart-PLS software version 2 to ensure reliability level and validity of the instrument. This study resulted in a validated instrument that will be used to collect data from actual surveys
Features Extraction on IoT Intrusion Detection System Using Principal Components Analysis (PCA) Sharipuddin Sharipuddin; Benni Purnama; Kurniabudi Kurniabudi; Eko Arip Winanto; Deris Stiawan; Darmawijoyo Hanapi; Mohd. Yazid Idris; Rahmat Budiarto
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 1: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2098

Abstract

There are several ways to increase detection accuracy result on the intrusion detection systems (IDS), one way is feature extraction. The existing original features are filtered and then converted into features with lower dimension. This paper uses the Principal Components Analysis (PCA) for features extraction on intrusion detection system with the aim to improve the accuracy and precision of the detection. The impact of features extraction to attack detection was examined. Experiments on a network traffic dataset created from an Internet of Thing (IoT) testbed network topology were conducted and the results show that the accuracy of the detection reaches 100 percent.
PERANCANGAN SISTEM INFORMASI REKAM MEDIK PADA PUSKESMAS KONI JAMBI Benniardi Benniardi; Sharipuddin Sharipuddin; Ibnu Sani Wijaya
Jurnal Processor Vol 9 No 2 (2014): Processor
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (734.416 KB)

Abstract

Puskesmas Koni Jambi merupakan salah satu puskemas yang berlokasi di daerah Jambi dimana pengolahan informasi dari rekam medik masih menggunakan cara manual. Sehingga terjadi permasalahan yaitu sulitnya untuk melakukan pencarian dan penyimpanan data rekam medik pasien dan pengolahan data stok obat yang sering terjadi perbedaan antara data fisik dengan data yang dicatat di kertas .Oleh karena itu, penelitian ini bertujuan memberikan solusi untuk permasalahan yang terjadi dengan menawarkan sistem informasi rekam medik menggunakan bahasa pemograman PHP dan database MySQL dimana penulis melakukan pengembangan sistem dengan metode waterfall dan menggunakan pendekatan model sistem unified model language menggunakan usecase diagram, activity diagram, class diagram dan flowchart diagram. Sistem baru menghasilkan output yang dapat mengelola dan menampilkan data petugas, data dokter, data jadwal dokter, data obat, data pasien, data rekam medik dan dapat mencetak laporan – laporan yang dibutuhkan oleh pengguna sistem
PEMANFAATAN COMPARISON PRICING MODEL (MODEL PERBANDINGAN HARGA) PADA E-COMMERCE Sharipuddin Sharipuddin
Jurnal Processor Vol 9 No 3 (2014): Processor
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (192.2 KB)

Abstract

E-Commerce menjadi salah satu pilihan dalam melakukan kegiatan bisnis.E-Commerce mempermudah user dalam melakukan kegiatan jual-beli, sehingga semua perusahaan yang bergerak dibidang jual-beli menggunakan layanan ini. Comparison Pricing Model ( model perbandingan harga ) mempermudah user / konsumen dalam melakukan pembelanjaan produk karena tersedianya layanan dunia teknologi internet yaitu melalui Web
PERANCANGAN APLIKASI E-LEARNING PADA MTS NEGERI 1 MERANGIN SHARIPUDDIN SHARIPUDDIN; EFFIYANDI EFFIYANDI; DWI FEBRYANTO
Jurnal Processor Vol 14 No 1 (2019): Processor
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1642.737 KB) | DOI: 10.33998/processor.2019.14.1.576

Abstract

Proses pembelajaran yang berlangsung di MTS Negeri 1 Merangin masih bersifat konvensional, guru dan murid masih bertatap muka secara langsung untuk melakukan proses belajar-mengajar, sehingga apabila guru berhalangan hadir maka informasi tentang materi pelajaran yang disampaikan kurang maksimal dan keterbatasan waktu yang disediakan menyebabkan lambatnya proses pembelajaran dan kurangnya pemahaman materi pelajaran pada siswa. E-learning adalah proses pembelajaran efektif yang diciptakan dengan cara menggabungkan konten yang disampaikan secara digital dengan jasa dan sarana pendukung pembelajaran. Aplikasi dibangun menggunakan Macromedia Adobe Dreamweaver CS5 dan database MySQL. Hasil dari penelitian ini adalah sebuah aplikasi e-learning yang dapat memberikan kemudahan pada siswa untuk mengakses materi pelajaran meski tidak ada pertemuan di kelas dan sebagai solusi alternatif bagi guru untuk tetap dapat memberikan materi meski tidak bisa hadir saat jam pelajaran.
ANALISIS DAN PERANCANGAN APLIKASI PENJUALAN PADA GALLERY BATIK JAMBI DESMIATI Andeh Lukito; Sharipuddin Sharipuddin; Ali Sadikin
Jurnal Processor Vol 10 No 2 (2015): Processor
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (485.19 KB)

Abstract

Saat ini sistem pengolahan data penjualan pada Gallery Batik Jambi Desmiati belum dikelola secara terkomputerisasi Seperti, Data barang, kategori barang, data satuan barang, data transaksi penjualan. masih dibuat atau di kelola secara manual dalam bentuk laporan yang masih menggunakan metode pencatatan yang di masukan ke dalam buku besar, sedangkan transaksi antara pembeli dan penjual dilakukan dengan mencatat nama barang serta harga beli yang dimaksukan ke dalam nota pembayaran. Sehingga, dalam masalah ini dibutuhkan suatu solusi untuk memecahkan masalah tersebut yaitu dengan membangun Perancangan Aplikasi Penjualan yang dapat mengelola data penjualan tersebut secara terkomputerisasi yang nantinya akan tersimpan dalam suatu database. Untuk merancang sistem ini diperlukan beberapa metode penelitian, diantaranya metode pengumpulan data menggunakan penelitian lapangan serta metode pengembangan sistem menggunakan waterfall. Analisis Dan Perancangan Aplikasi Penjualan Pada Gallery Batik Jambi Desmiati dibangun secara keseluruhan menggunakan bahasa pemoprograman Vb, DBMS Mysql. Dengan Dirancangnya Sistem Aplikasi Penjualan Pada Gallery Batik Jambi Desmiati ini dapat mempermudah pihak pemilik gallerry untuk mengelola data penjualan
Co-Authors Ahmad Heryanto Ahmad Yani Ali Sadikin Andeh Lukito Bedine Kerim Benniardi Benniardi Caroline Zahri Darmawijoyo, Darmawijoyo Deris Stiawan Dodi Sandra Dodi Sandra Dodo Zaenal Abidin Dwi EFFIYANDI EFFIYANDI EFFIYANDI Eko Arip Winanto Feranika, Ayu Gunardi Gunardi Hendri Hendri Ibnu Sani Wijaya Idris, Mohd. Yazid Jasmir Jasmir Jasmir Jasmir Khairuldi Khairuldi Kurniabudi, Kurniabudi Lukito, Andeh Mahyuni Mahyuni MARIA BINTANG Marrylinteri Istoningtyas Martono Martono Martono Martono Martono Mohd Yazid bin Idris Mohd. Yazid Idris Mohd. Yazid Idris Mohd. Yazid Idris Purnama, Benni Rahmat Budiarto Rifki Williandi Rita Rita SABARIAH . Samsuryadi Samsuryadi SATRIYAS ILYAS Setiawan Assegaf Sherin Devanty Situmorang Syahrial Syahrial Wiken Winata William Yessi Hartiwi Yoant Prasiska Yundari, Yundari Zulwaqar Zain Mohtar