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PENGAMANAN BERKAS DOKUMEN MENGGUNAKAN FUNGSI ALGORITMA STEGANOGRAFI LSB Indra Gunawan; Sumarno Sumarno; Eka Irawan; Heru Satria Tambunan
ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA Vol 2, No 1 (2018): April 2018
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (298.573 KB) | DOI: 10.30829/algoritma.v2i1.1617

Abstract

In the World of Information Technology computer science, data security something that is very important so that data can not be misused by some parties who have not / not have rights. In the delivery of documents documents is needed a security so that the document file can be accepted by those who have the right to receive it. It is therefore very necessary to process a document encryption / encryption file. Among the science of cryptography that can secure the document file such as LSB Steganography Algorithm (Least Significant Bit). This analysis aims to improve the security of document files by encoding a document file, then providing a password into the document file.Keywords : Encryption, Data Security, LSB Steganography, Files, Documents
PERANCANGAN REPOSITORY DIGITAL STIKOM TUNAS BANGSA MENGGUNAKAN CODEIGNITER Willy Hairis Resmantama Silaen; Saifullah Saifullah; Eka Irawan
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 3, No 1 (2019): Smart Device, Mobile Computing, and Big Data Analysis
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v3i1.1682

Abstract

This study aims to design a Codeigniter-Based New Repository. This software serves to simplify the process of designing the repository. This research also aims to facilitate students and the general public to access examples of student thesis at Stikom Tunas Bangsa Pematangsiantar. This research method is Research and Development. The development model used is Waterfall which consists of analysis, design, implementation, and testing. Based on the results of this study, it can be concluded that the results of software development are in the form of Codeigniter-Based Digital Repository.Keywords: Repository, Code igniter.
SISTEM PENDUKUNG KEPUTUSAN REKOMENDASI PEMILIHAN SMARTPHONE TERBAIK MENGGUNAKAN METODE TOPSIS Anggi Eryzha; Solikhun Solikhun; Eka Irawan
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 3, No 1 (2019): Smart Device, Mobile Computing, and Big Data Analysis
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v3i1.1668

Abstract

Smartphones are a primary need for all upper class and lower class people. As these needs are many smartphone vendors that offer different prices, features, systems and technologies at competitive prices. Many people want specifications that are capable but limited in financial terms. This causes smartphone users not to be able to make the right choice according to their needs because the frequent selection of smartphones is based on prestige and consumer consumptive behavior. The TOPSIS method is a multicriteria method used to identify solutions from alternative sets based on simultaneous minimization of the ideal point distance and maximizing the distance from the lowest point. The expected results can be input to potential smartphone buyers in accordance with their finances and qualified specifications.Keywords: Decision Support System, Topsis Method, Smartphone.
PEMETAAN HASIL PRODUKSI BUAH-BUAHAN DENGAN TEKNIK DATA MINING K-MEDOIDS Ira Audita; Irfan Sudahri Damanik; EKA IRAWAN
Jurnal Teknik Mesin, Industri, Elektro dan Informatika Vol. 1 No. 3 (2022): September : JURNAL TEKNIK MESIN, INDUSTRI, ELEKTRO DAN INFORMATIKA
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1102.947 KB) | DOI: 10.55606/jtmei.v1i3.535

Abstract

Buah-buahan merupakan salah satu komoditas hortikultura yang memegang peranan penting bagi pembangunan pertanian di Indonesia. Secara garis besar, produksi buah-buahan di Provinsi Sumatera Utara selama periode 2018-2020 mengalami penurunan. Penurunan jumlah produksi buah-buahan dapat mengakibatkan harga buah menjadi mahal, dan stok buah-buahan menjadi langkah. Penelitian ini bertujuan untuk mengetahui hasil dari pengelompokkan tanaman buah-buahan menggunakan metode K-Medoids yang merupakan bagian dari Data Mining. Metode K-Medoids ini merupakan metode clustering yang dapat memecahkan dataset menjadi beberapa kelompok. Pada penelitian ini data yang digunakan bersumber dari Badan Pusat Statistik pada tahun 2017-2021. Hasil dari penelitian ini diperoleh sebanyak 21 komoditas yang tergolong cluster rendah dan 2 komoditas yang tergolong dalam cluster tinggi. Penelitian ini diharapkan dapat Membantu Pihak Dinas Pertanian Provinsi Sumatera Utara dalam mengupayakan meningkatkan hasil produksi tanaman buah-buahan yang ada di Provinsi Sumatera Utara.
ANALISIS TINGKAT KEPUASAN PENGGUNA GOOGLE CLASSROOM DALAM PEMBELAJARAN ONLINE MENGGUNAKAN ALGORITMA NAÏVE BAYES Fildzah Nadya Arieni; Eka Irawan; Dedi Suhendro
Jurnal ilmiah Sistem Informasi dan Ilmu Komputer Vol. 2 No. 3 (2022): November : Jurnal ilmiah Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juisik.v2i3.327

Abstract

SMK Negeri 3 Pematangsiantar is one of the schools affected by the COVID-19 pandemic, which at that time the whole world was facing an outbreak of this infectious disease. The Covid-19 pandemic that was hitting the whole world at that time, required all students and students to carry out the online learning process in order to prevent the spread of the Covid-19 virus. This study aims to classify the level of satisfaction of Google classroom users using nave Bayes data mining techniques. Sources of data obtained from questionnaires given to students randomly as many as 100 students. The criteria used as Google Classroom user satisfaction include: system quality, service, information, usage, user satisfaction. The model generated by researchers and Rapid Miner Software with training data as much as 75 data. There are 25 test data that are processed in Rapid Miner 5.3. get test results with an accuracy of 96.00%, namely 15 satisfied users and 10 dissatisfied users.