Article Per Year (5 Year)
p-Index From 2019 - 2024
0.659
P-Index
This Author published in this journals
All Journal JIPTEK : Jurnal Ilmiah Pendidikan Teknik dan Kejuruan Journal of Telematics and Informatics Sistemasi: Jurnal Sistem Informasi Indonesian Journal of Informatics Education DEDIKASI: Community Service Reports Journal of Informatics and Vocational Education
Aris Budianto
Universitas Sebelas Maret
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Social Sciences Other

Published : 8 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 8 Documents
Search

 1 
SISTEM REKOMENDASI BURSA KERJA KHUSUS (BKK) SMK DENGAN METODE SIMPLE ADDITIVE WEIGHTING Isabela Maharani; Aris Budianto; Rosihan Ari Yuana
Sistemasi: Jurnal Sistem Informasi Vol 7, No 3 (2018): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1194.024 KB) | DOI: 10.32520/stmsi.v7i3.383

Abstract

Bursa Kerja Khusus (BKK) di Sekolah Menengah Kejuruan berguna untuk menyebarkan informasi lowongan pekerjaan bagi siswa/alumni SMK. Sistem ini bermanfaat menyebarkan informasi. Namun dengan banyaknya lowongan maka siswa diharuskan memilih perusahaan-perusahaan yang sesuai dengan minat dan keahliannnya. Untuk mengatasi masalah tersebut, pada penelitian ini akan dilakuan penggembangan sistem rekomendasi bagi Bursa Kerja Khusus (BKK). Selain membantu penyebaran informasi, sistem dilengkapi dengan fitur rekomendasi. Siswa/alumni calon pencari kerja akan mendapatkan rekomendasi mengenai perusahaan yang sesuai dengan minat dan keahliannya. Sedangkan bagi perusaan akan diberikan rekomendasi calon pendaftar yang memiliki keahlian yang dibutuhkan oleh perusahaan. Sistem rekomendasi menggunakan metode pengambilan keputusan Simple Additive Weighting. Metode Simple Additive Weighting memberikan bobot terhadap setiap atribut yang kemudian dilanjutkan dengan adanya proses perangkingan semua atribut. Penelitian dan pengembangan ini menggunakan metode penelitian Research and Development (R&D) oleh Borg and Gall. Pada penilaian oleh ahli sistem menunjukkan hasil 88.9%. Penilaian dari dua ahli substansi menunjukkan hasil 87.8%. penilaian dari siswa/ alumni SMK menunjukkan hasil 88.3%. Sedangkan penilaian dari perusahaan menunjukkan hasil 92.1%. Keseluruhan penilain tersebut berada pada rentang 81% - 100%, sehingga sistem dikategorikan sangat layak untuk digunakan.
PERANCANGAN INTELLIGENT TUTORING SYSTEM UNTUK PEMBELAJARAN JARINGAN KOMPUTER Aris Budianto; Rosihan Ari Yuana
Sistemasi: Jurnal Sistem Informasi Vol 8, No 1 (2019): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1587.567 KB) | DOI: 10.32520/stmsi.v8i1.411

Abstract

Proses pembelajaran mata kuliah Jaringan Komputer di prodi Pendidikan Teknik Informatika (PTIK), Fakultas Keguruan dan Ilmu Pendidikan (FKIP), Universitas Sebelas Maret (UNS) terjadi sebuah gap antara Mahasiswa dari SMA dan SMK. Sebagian mahasiswa dengan latar belakang SMA belum memiliki konsep-konsep dasar Jaringan Komputer, sedangkan mahasiswa dari SMK sudah pada tahap sudah jauh lebih advance. Untuk menjembatani hal tersebut maka salah satu solusi yang bisa diimplementasikan adalah sebuah e-learning yang menyediakan sistem pembelajaran mandiri. E-learning yang dikembangkan akan menyediakan materi yang lengkap, latihan dan dan video tutorial. Pada penelitian ini, berbeda dengan E-Learning konvensional yang bersifat sama (flat) untuk setiap pengguna, E-Learning yang akan dikembangkan dilengkapi dengan Machine Learning metode Naïve bayes. Machine Learning akan membantu proses pembelajaran dengan pendekatan one-to-one, dimana sistem akan memiliki kemampuan mendeteksi kemampuan mahasiswa yang menggunakan E-Learning. Sistem menyesuaikan materi dan latihan sesuai dengan kemampuan pengguna dalam proses belajar mandiri. Dengan tutorial yang bertahap dan pendekatan yang berbeda dalam proses belajar setiap siswa diharapkan mampu meningkatkan pemahaman siswa mengenai mata kuliah Jaringan Komputer di PTIK, FKIP, UNS.
Automatic License Plate Recognition: State of the Art and The Opportunities for Implementation in Indonesia (Literature Review) Aris Budianto
Journal of Telematics and Informatics Vol 6, No 4: December 2018
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v6i4.

Abstract

The Automatic License Plate Recognition (ALPR) has been becoming a new trend in transportation systems automation. The extraction of vehicle’s license plate information from image or sequence of images can be done without human intervention. Despite such technology has been widely adopted in developed countries, developing countries remain a far-cry from implementing the sophisticated image and video recognition for some reasons. This paper assesses the possibilities of implementing Automatic License Plate Recognition within Indonesia’s circumstances. Previous knowledge suggested in the literature, and state of the art of the automatic recognition technology is amassed for consideration in future research and practice.
PERBANDINGAN K-NEAREST NEIGHBOR (KNN) DAN SUPPORT VECTOR MACHINE (SVM) DALAM PENGENALAN KARAKTER PLAT KENDARAAN BERMOTOR Aris Budianto; Rosihan Ariyuana; Dwi Maryono
Jurnal Ilmiah Pendidikan Teknik dan Kejuruan Vol 11, No 1 (2018): JIPTEK : Jurnal Ilmiah Pendidikan Teknik dan Kejuruan
Publisher : Fakultas Keguruan dan Ilmu Pendidikan Universitas Sebelas Maret Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jiptek.v11i1.18018

Abstract

Penelitian mengenai pengenalan karakter plat nomor kendaraan atau Automatic License Plate Detection (ALPR) sudah banyak dilakukan. Berbagai metode machine learning digunakan pada proses pengenalan karakter plat nomor kendaraan. Pada penelitian ini akan membandingkan metode K-Nearest Neighbor (KNN) dan Support Vector Machine (SVM) dalam pengenalan karakter plat nomor kendaraan. Pengujian sistem pada 20 pengujian didapatkan hasil sebagai berikut: Akurasi pengujian pengenalan plat kendaraan dengan metode Support Vector Machine dengan akurasi 95%. Sedangkan menggunakan metode KNN mendapatkan akurasi pengujian 80%.
Sekar Indonesia: Interactive Android-Based Learning Media for History Learning Muhammad Hassan Massaty; Yudianto Sujana; Aris Budianto
IJIE (Indonesian Journal of Informatics Education) Vol 1, No 2 (2017): (IJIE) Indonesian Journal of Informatics Education
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v1i2.12392

Abstract

Historical learning in Indonesia is very minimal innovation. Due to the lack of innovation from year to year emerged various problems in historical learning activities such as monotonous, boring and uninteresting. The variety of learning media will be able to increase interest of learners in the learning process. The result of this research is an interesting and non-boring Android-based history learning media that is called Sekar Indonesia and worthy of being used as a learning media. This research method is research and development (R & D). This study was conducted using a research model developed by Borg & Gall. The research model consists of five steps: research and data collection, planning, product drafting, preliminary field testing and main product revision. Applications Sekar Indonesia tested by material experts, media experts and users. Expert testing results obtained percentage of 86.1% from material experts, 92.85% from media experts, and 97.7% form users. From the test results obtained the conclusion that the application Sekar Indonesia that has been developed can be used as a learning media.
Technology Acceptance Model for Examining the Feasibility of a Computer-based Test System (an Indonesian Context) Septian Nugroho; Cucuk Budiyanto; Aris Budianto
IJIE (Indonesian Journal of Informatics Education) Vol 2, No 2 (2018): (IJIE) Indonesian Journal of Informatics Education
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (520.666 KB) | DOI: 10.20961/ijie.v2i2.12598

Abstract

Indonesia is a country with rapid technological developments in all sectors including education. This can be proved by the government's success in applying computer-based test in 2014 junior high school. Many conveniences obtained when the exam using computer such as the assessment automatically, get feedback quickly and the question can be stored in the bank question. In this research, computer-based test system will be developed based on the convenience as above and will be added some other features to suit of the school using waterfall development model. Additional features include classroom major, question grouping in the question bank, user management and ease of registration during new year academic calendar. After developing system has been done, the CBT system is tested to one class at a vocational high school in Indonesia using an system feasibility instrument adapted from technology acceptance model (TAM) to know the level of feasibility the CBT system in perceived usefulness and perceived easy of use. The test results show that CBT system is very suitable for use in the class and can be applied to all schools in Indonesia.
Penerapan Teknologi Image Processing untuk Optimalisasi Petik Merah pada Kebun Kopi Rakyat Aris Budianto; Cucuk Budiyanto; Qois Amin Fauzan; Indah Widiastuti; Dwi Maryono
DEDIKASI: Community Service Reports Vol 2, No 1 (2020): DEDIKASI: Community Service Report
Publisher : FKIP Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/dedikasi.v2i1.35845

Abstract

AbstractCoffee has been cultivated as the secondary produce for decades in Girimarto, Wonogiri, however, the selective picking practice remain alient for local farmers. Selective picking is considered impractical due to time consumption and laborous work that farmers should carry out. The community service project designs and implements image recognition technology to help acquire           coffee-cheery ripeness condition. Adopting a geolocation, the appropriate routing strategies, would enable farmers to selectively pick the red cherries in a systematic sequence. The image processing technology was applied by adopting Raspberry Pi microcomputer, Raspberry Pi Camera Board, version 2, and OpenCV programming language. The transition to selective picking and the subsequent post-harvest technology would likely produce high-quality green bean coffee. It is expected that the income of smallholder coffee farmers will gradually be increasing.ABSTRAKPraktek petik buah merah dalam budidaya kopi belum menjadi prosedur baku pada perkebunan kopi rakyat di wilayah Girimarto, Wonogiri. Petani menganggap praktek petik merah pada panen buah kopi merepotkan dan memakan waktu karena dalam satu kunjungan ke kebun mereka hanya memetik buah kopi yang benar-benar matang. Pengabdian ini mendesain dan menerapkan perangkat pemantau kematangan buah kopi untuk membantu petani memperoleh informasi lokasi buah matang dan estimasi jumlahnya sehingga petani bisa merencanakan jalur pemetikan kopi berdasarkan lokasi batang pohon kopi tingkat kematangannya. Teknologi image processing diterapkan dengan mengadopsi penggunaan komputer mikro Raspberry Pi, modul kamera Raspberry Pi Camera Board, versi 2, dan bahasa pemrograman OpenCV. Perubahan pola panen buah kopi dari petik sembarang (petik racutan_ menjadi panen petik merah diikuti dengan perbaikan proses fermentasi buah kopi diharapkan menghasilkan kualitas green bean menjadi lebih baik dan harga jual yang lebih tinggi.
Development of a Facial Recognition-based Attendance System using Binary Patterns Histograms Method and Telegram Bot Notification Qois Amin Fauzan; Aris Budianto; Cucuk Wawan Budiyanto
Journal of Informatics and Vocational Education Vol 5, No 2 (2022): Journal of Informatics and Vocational Education - July
Publisher : Pendidikan Teknik Informatika dan Komputer, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v5i2.65789

Abstract

In carrying out attendance activities, most schools still use the manual attendance method, which utilizes the attendance book as a medium. However, the presence of the manual still causes some problems that arise when using this method. With the aim of this study, a "Facial Recognition-Based Attendance System" was created. This study used the Local Binary Pattern Histogram (LBPH) method to detect and recognize faces. The system is made to recognize the student's face and name, which the attendance system will then carry out along with the student's identity in the form of Name and Absence Number in real time to find out that the student is present in the class. The names that have been diabase can be saved through the XLS format. The result of this study is a facial recognition-based attendance system using the LBPH (Local Binary Pattern Histogram) method. The system is web-based, so users can easily access it through the internet. This research method uses research and development methods. This research stage consists of research and information collection, planning, and product draft development. The results of this study showed the feasibility level of facial recognition-based attendance systems. The eligibility rate obtained showed a score of 78.98%. From these results, this system is worthy of being used as an attendance system.
Co-Authors Cucuk Budiyanto Cucuk Budiyanto Cucuk Wawan Budiyanto Dwi Maryono Indah Widiastuti Isabela Maharani Muhammad Hassan Massaty Qois Amin Fauzan Rosihan Ari Yuana Rosihan Ari Yuana Rosihan Ariyuana Septian Nugroho Yudianto Sujana