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All Journal Jurnal ULTIMATICS Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Abdimasku : Jurnal Pengabdian Masyarakat
Is Mardianto
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Social Sciences

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PERBANDINGAN WAKTU EKSEKUSI PERAMALAN HARGA KOMODITAS PANGAN MENGGUNAKAN SPARKR DAN R STUDIO Dedy Sugiarto; Dimmas Mulya; Abdul Rochman; Is Mardianto
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 16 No. 1 (2022): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v16i1.3911

Abstract

The arrival of the big data era with characteristics such as large volumes of data makes the calculation of execution time a concern when carrying out data analytics processes, such as forecasting food commodity prices. This study aims to examine the effect of the big data framework through the use of sparkR. The test is carried out by varying several deep learning forecasting models, namely the multi-layer perceptron model and by using the price of one food commodity from 2018 to 2020. The results show that sparkR is significantly shorter its execution time when compared to R studio. The results of testing the influence of the MLP model also show that a model with two hidden layers with a maximum node of 13 nodes in hidden layers 1 and 2 produces the longest execution time compared to only using 1 hidden layer with 5 nodes or using two hidden layers with a number of nodes of 5 and 3.
Pemanfaatan Scratch Sebagai Media Pembelajaran Pemrograman Berbasis Animasi Di Sekolah Dasar Binti Solihah; Sucipto Adi Suwiryo; Gatot Budi Santoso; Is Mardianto; Uray Assifa Mufti Azzahra
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 5, No 2 (2022): Mei 2022
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/ja.v5i2.469

Abstract

Sumber Daya Manusia yang dibutuhkan pada Era Industri 4.0 minimal harus memiliki 5 kompetensi utama diantaranya critical thinking dan problem solving. Kemampuan tersebut harus dilatih sedini mungkin. Salah satu cara melatih skill tersebut adalah dengan mengajarkan pemrograman kepada anak usia dini. Guru sekolah dasar sebagai pelaksana kegiatan usia dini harus dibekali dengan keterampilan tersebut. Diantara metode yang dapat dilakukan untuk mengenalkan materi tersebut kepada para guru sekolah sadar adalah melalui kegiatan workshop dan pelatihan. Tim Pengabdian Kepada Masyarakat Program Studi Teknik Informatika dan Sistem Informasi mengadakan kegiatan pelatihan Pemrograman Scratch bagi guru-guru SD. Kegiatan ini dilaksanakan secara daring dan diikuti oleh sejumlah guru dan siswa Sekolah Dasar di Wilayah Kembangan Jakarta Barat. Berdasarkan kuisioner yang dikumpulkan pada sesi terakhir pelatihan, pelatihan ini bermanfaat untuk meningkatkan literasi teknologi informasi
Implementasi Keamanan pada Transaksi Data Menggunakan Sertifikat Digital X.509 Is Mardianto; Kuswandi Kuswandi
Ultimatics : Jurnal Teknik Informatika Vol 8 No 1 (2016): Ultimatics: Jurnal Ilmu Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1828.12 KB) | DOI: 10.31937/ti.v8i1.496

Abstract

Security issues have become a major issue on the Internet. One of the security methods that are widely used today is to implement a digital certificate. Digital certificates have evolved over time, one of which is the X.509 digital certificate. Digital certificates have been widely used as authentication applications, web network authentication and other authentication systems that require digital certificates. This research is carried out by implementing an X.509 digital certificate technology as a mobile web service with its client. Secure Hash Algorithm (SHA), Diffie-Hellman, and Advanced Encryption Standard (AES) are used to secure the data exchange transaction between the web service and mobile phone. SHA algorithm will be used for user authentication, Diffie-Hellman algorithm will be used for public key exchange and AES algorithms will be used for symmetric cryptography data. The results of the application of digital certificates, the SHA algorithm, Diffie-Hellman, and AES in mobile phone applications, provide security application running on web service. Index Terms—Digital Certificate, X.509, SHA, Diffie Hellman, AES
Pengenalan Wajah Bebas Ekspresi Menggunakan Metode Nearest Feature Line dengan Representasi Ciri dalam Ruang Eigen Is Mardianto
Ultimatics : Jurnal Teknik Informatika Vol 12 No 1 (2020): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (508.757 KB) | DOI: 10.31937/ti.v12i1.1562

Abstract

Facial recognition with different expressions is one part of the pattern recognition problem which is quite complex when compared to pattern recognition on a normal profile. The expression-free face recognition method using the Nearest Feature Line (NFL) technique works by finding the closest projection distance between feature vectors, assuming that the closer the projection distance of a feature vector (face) to another feature vector (face), the more similar the properties will be physical feature vector (face) which are close together. The NFL distance calculation is performed on the eigen dimensional space with the aim that the calculated feature vector (face) dimension has a much smaller dimension in order to increase the level of recognition accuracy and speed up computational time. The test results obtained indicate the NFL method provides a fairly good level of recognition accuracy in the average value of 76.7% with the advantage of low computational time needed when compared with other intelligent methods such as artificial neural network systems.
Co-Authors Abdul Rochman Binti Solihah Dedy Sugiarto Dimmas Mulya Gatot Budi Santoso Mala Nurilmala Sucipto Adi Suwiryo Uray Assifa Mufti Azzahra