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All Journal Telematika : Jurnal Informatika dan Teknologi Informasi Jurnas Nasional Teknologi dan Sistem Informasi EKOMBIS REVIEW: Jurnal Ilmiah Ekonomi dan Bisnis Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknik Komputer AMIK BSI KACANEGARA Jurnal Pengabdian pada Masyarakat Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JISKa (Jurnal Informatika Sunan Kalijaga) Syntax Idea Jurnal Sistem Komputer dan Informatika (JSON) Aiti: Jurnal Teknologi Informasi Indonesian Community Journal Journal of Social Science Asian Journal of Management, Entrepreneurship and Social Science
Rianto Rianto
Universitas Teknologi Yogyakarta
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Library & Information Science Public Health Social Sciences Other

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Sistem Rekomendasi Pada Tokopedia Menggunakan Algoritma K-Nearest Neighbor Rubangi Rubangi; Rianto Rianto
Jurnal Teknik Komputer AMIK BSI Vol 8, No 1 (2022): JTK Periode Januari 2022
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (253.952 KB) | DOI: 10.31294/jtk.v8i1.11823

Abstract

Tokopedia merupakan salah satu perusahaan perdagangan elektronik yang memiliki data pertumbuhan yang sangat pesat dengan seiring berjalannya waktu. Adanya data terus menerus bertambah besar sehingga dapat terjadinya masalah bagi user. User sering mengalami kendala dalam promosi produk yang sering dikunjungi pembeli. Selain itu pembeli sering mengalami kesulitan untuk menemukan kebutuhan produk terbaik yang sesuai kebutuhan pembeli. Dengan adanya masalah tersebut yang terjadi maka dapat diatasi dengan adanya sistem rekomendasi produk tertentu untuk ditawarkan kepada pembeli. Sistem rekomendasi penelitian ini mengimplementasikan dengan Algoritma K-Nearest Neighbor pada Rating Product Reviews Tokopedia. Algoritma K-Nearest Neighbor yang digunakan untuk menentukan top-n rekomendasi produk tertentu untuk ditawarkan kepada pembeli. Hasil dari penelitian yang dilakukan pada data 2040 rating produk dengan menggunakan algoritma K-Nearest Neighbors yaitu nilai Accuracy sebesar 73.53%, Precision sebesar 73.64%, Recall sebesar 99.62%.
Sistem Rekomendasi Jurusan pada Sekolah Menengah Kejuruan (SMK) dengan Algoritma K-Means Siska Howay; Rianto Rianto
Syntax Idea Vol 3 No 10 (2021): Syntax Idea
Publisher : Ridwan Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/syntax-idea.v3i10.1443

Abstract

Sistem Penentuan jurusan di SMK Negeri 02 Moswaren Kabupaten sorong selatan, merupakan hal yang sangat penting, karena di SMK belum ada sistem penetuan jurusan yang baik sehingga siswa seringkali salah dalam memilih jurusan berdasarkan kemampuan yang dimiliki. Oleh karena itu sistem ini dibuat untuk membantu pihak sekolah dalam menentukan jurusan yang sesuai berdasarkan data nilai rapot, minat, dan bakat. data di ambil dari beberapa angkatan mulai dari angkatan 2019 sampai dengan 2021. Atribut yang dipakai meliputi pemilihan jurusan SMK TKJ, TBSM, TPMG, ATPH, APAT nilai mata pelajaran Penddidikan Agama, PPKN, Bahasa Indonesia, Matematika, IPA, IPS, Penjas, Prakarya, Mulok, Kewira dengan menggunakan dataset 23 data siswa baru. hasil dari pola klasifikasi penentuan jurusan ini dapat digunakan pihak sekolah dalam menentukan kebijakan dalam penentuan jurusan calon siswa pada proses penerimaan peserta didik baru.
IMPLEMENTASI WEBSITE UNTUK MENINGKATKAN OMSET PENJUALAN BATIK BERKAH LESTARI Radjaban Radjaban; Septi Riana Dewi; Rianto Rianto
KACANEGARA Jurnal Pengabdian pada Masyarakat Vol 4, No 1 (2021): Januari
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/kacanegara.v4i1.832

Abstract

Marketing is one of the determinant factors on business success, even though there are still many negligent companies and still use conventional systems so that their sales turnover is low. The COVID-19 pandemic also creates problems on sales turnover. Micro, Small, and Medium Enterprises of Batik Berkah Lestari Imogiri are among those affected by the pandemic. This is related to the conventional marketing system that has been implemented up to this time. In addition, government policies related to pandemics also limit life activities. People are no longer free to visit shopping centers, so they need to make transaction media without leaving their homes. The development of internet technology has presented a medium called a website. Its flexibility, convenience, and simplicity make webiste to be widely used. Moreover,  the existence of website will be used for Batik Berkah Lestari in marketing its products during the pandemic. This study aims to implement the website as an online transaction medium for Batik Berkah Letasri. By utilizing the website as a medium for electronic transaction, the market reach will be even wider so that transaction opportunities at Batik Berkah Lestari will be even greater.
Efektifitas Penggunaan Association Rules Mining dalam Personalisasi Website Edi Priyanto; Arief Hermawan; Rianto Rianto; Donny Avianto
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 1 (2021): Januari 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (360.156 KB) | DOI: 10.14421/jiska.2021.61-07

Abstract

As the usage of the internet grows, more and more information is obtained, thus presenting challenges, especially for users and website owners. Website users often have difficulty finding products or services that are relevant to their needs caused by abundant amounts of products and services delivered on a website. Website owners often find it difficult to convey information about the right products and services to certain target users. Based on the problem given above, we can conclude that a recommendation system approach that can improve personalization on their website is needed. The recommendation system approach must be able to provide navigation on the website to make it more adaptive towards the interests and information needed by the user. This study uses Association Rules formed from Microsoft web access log data by finding visitor patterns based on frequently visited web site pages. From the results of the research conducted, the performance of the method used has a precision value of 0.896, 0.058 recall, and F-measure 0.104. Whereas the measurement of the accuracy value resulted in a performance recommendation of exactly 3%, an acceptable rate of 87%, and 10% incorrect. This research shows that the Association Rules method can increase the effectiveness of website personalization to provide relevant information recommendations for visitors. For further research, it can concentrate on improving existing methods thus website personalization becomes more adaptive.
Decentralized Finance (DeFi), Strengths Become Weaknesses: a Literature Survey Aziz Perdana; Erik Iman HU; Rianto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 2 (2023): April 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i2.4806

Abstract

The use of blockchain technology in Decentralized Finance (DeFi) has gained popularity, with 23 public companies and one country holding bitcoin. DeFi aims to create an open and decentralized financial ecosystem that is accessible to everyone, eliminates intermediaries like financial institutions, and is verifiable, immutable, globally accepted, fast, low-cost, anonymous, and non-custodial. Despite its benefits, the rapid growth of DeFi has led to increased security risks. This study assesses the validity of DeFi's superiority claims in light of security incidents and events in 2022 and Twitter trends. This study used a Systematic Literature Review from various research articles and news from 2022. This research found that DeFi's superiority claims seem to be inconsistent with what is being advertised. It also found that if DeFi is not properly prepared and audited, its strength (Anonymous, open-source, decentralized, non-custodial, eliminates third parties and regulation) may become its weakness. Despite this, users still exhibit high levels of trust and optimism, as seen in the most popular terms shared by user tweets during significant losses, with 301,654 unique tweets between April 30 and May 31, 2022 and 344,519 unique tweets between October 3 and December 3, 2022, that are crypto, nft, and blockchain.
Kombinasi Algoritma Kriptografi Vigenere Cipher dan SHA256 untuk Keamanan Basis Data Rian Oktafiani; Erik Iman Heri Ujianto; Rianto Rianto
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 3 (2023): Maret 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i3.5583

Abstract

An organization must consider and manage the security of data storage in databases or databases, and special procedures are needed to protect data from various security risks. The problem in this study is that the population data contained in the Girisuko village administrative service information system has not been encrypted or secured. This can pose a risk that the data stored in the database can be intercepted and misused. In this study, the cryptographic technique used was a combination of the Vigenere Cipher and SHA 256 algorithms to secure or encrypt databases, especially population data in the Girisuko village administrative service information system. The text in the database is encrypted using the Vigenere Cipher, and SHA-256 is used to generate a hash value or a random value that is different from the text in the database. Messages will be encrypted using the Vigenere Cipher and then hashed with SHA-256 simultaneously. As a result, it will be difficult for an attacker to decrypt the text stored in the database because they have to break the Vigenere Cipher encryption, and also have to solve the hash value generated using SHA-256. This combination aims to increase security and maintain the confidentiality of messages from attackers. The application of the Vigenere Cipher and SHA to the village administration service information system application with a real-time database works well, as evidenced by the fast running-time of 0.39 seconds the data encryption process uses the Vigenere Cipher with 894,968 keys/second and an analyzed key length of 7 characters then text on population database successfully secured. By conducting this research, it is hoped that it can contribute to improving database system security.
Convolutional Neural Network for Identifying Tree Species Using Stem Images Nadia Pramesti; Rianto Rianto
Telematika Vol 20, No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.8774

Abstract

Purpose: Identification of tree species based on stem images using programming assistance to design an automation tool to be able to distinguish tree species directly based on stem images from the new data entered.Design/methodology/approach: Identifying tree species is usually done using leaf images, in previous studies related to identifying tree species based on leaf images this resulted in quite high accuracy but was felt to be not optimal. In this study, we used a convolutional neural network to compare the accuracy of bar images.Findings/result: from 1000 tree trunk image data, identification was carried out using the help of python with the CNN method it can be concluded that the test results used the best acuration at epoch 25 with a value reaching 96.80%Originality/value/state of the art: Research with theme identification of tree species based on stem images using the CNN method has never been done by previous researchers. 
Perbandingan Algoritma Support Vector Machine (SVM) dan Decision Tree untuk Sistem Rekomendasi Tempat Wisata Rian Oktafiani; Rianto Rianto
Jurnal Nasional Teknologi dan Sistem Informasi Vol 9, No 2 (2023): Agustus 2023
Publisher : Jurusan Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v9i2.2023.113-121

Abstract

Industri pariwisata Indonesia berkembang dari tahun ke tahun. Daerah Istimewa Yogyakarta merupakan salah satu provinsi yang memiliki banyak destinasi wisata. Pertumbuhan internet dan teknologi informasi juga menjadi faktor dalam industri pariwisata Indonesia. Dengan adanya informasi mengenai pariwisata di internet, dapat memudahkan wisatawan untuk mencari informasi. Namun, karena jumlah informasi yang sangat banyak akan membuat wisatawan kebingungan untuk menentukan tujuan wisata. Selain itu, wisata lokal memiliki potensi yang cukup tinggi untuk membantu perekonomian daerah, namun saat ini belum dieksplorasi secara maksimal. Sistem rekomendasi dan kemampuan klasifikasi tempat wisata diperlukan untuk memberikan akurasi rekomendasi yang baik. Untuk menentukan jumlah fitur yang paling menguntungkan untuk klasifikasi lokasi wisata, Teknik Principal Component Analysis (PCA) digunakan dalam penelitian ini untuk membandingkan metodologi Support Vector Machine (SVM) dan Decision Tree (DT). Hasilnya menunjukkan bahwa, dengan nilai akurasi 98.97% penerapan PCA dengan nilai n=5 dan berada pada perbandingan Split Data 75% : 25%, pendekatan SVM memiliki performa lebih baik daripada metode Decision Tree. Metode Decision Tree juga memiliki performa yang baik, dengan menggunakan PCA dengan nilai n=5, Decision Tree memiliki akurasi 96.55% yang berada pada perbandingan Split Data 85% : 15%.
Convolutional Neural Network untuk mengklasifikasi tingkat keparahan jerawat Rianto Rianto; Demas Risdho Listianto
AITI Vol 20 No 2 (2023)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v20i2.167-176

Abstract

Klasifikasi merupakan salah satu metode yang digunakan dalam ilmu medis khususnya untuk deteksi dini ataupun klasifikasi jenis penyakit. Dalam ilmu kesehatan kulit, klasifikasi dapat digunakan untuk memprediksi jenis dan tingkat keparahan jerawat sehingga dapat ditentukan cara pengobatannya. Penelitian ini bertujuan untuk mengembangkan model klasifikasi jenis dan tingkat keparahan jerawat menggunakan Deep Learning dengan Convolutional Neural Network (CNN). Label yang digunakan dalam data latih terdiri dari level 0, 1, dan 2 yang merepresentasikan tingkat keparahan jerawat. Model pengklasifikasi dikembangkan menggunakan data sekunder yang diperoleh dari www.kaggle.com dengan masing-masing label berjumlah 500 citra. Optimizer yang digunakan dalam penelitian ini adalah ADAM dengan membandingkan jumlah epoch mulai dari 50, 80, sampai dengan 100. Hasil akurasi dalam data latih yang diperoleh adalah 0.6363, 0.8783, dan 0.9234.
Decision Support System For Manager Placement In The Plantation Industry Using Topsis Method Teguh Widodo; Nur Wening; Rianto Rianto
Journal Of Social Science (JoSS) Vol 3 No 7 (2024): JOSS : Journal of Social Science
Publisher : Al-Makki Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57185/joss.v3i7.344

Abstract

Accuracy in placing employees determines the performance of a company. Likewise done by PT XYZ in determining the placement of managers in the plantation industry by using a decision support system. This is done in order to minimize the level of subjectivity of the manager placement determination system at PT XYZ. This research aims to provide alternative preference values to prospective employees who will occupy manager positions in the plantation industry. The method used in the placement of managers with a decision support system is the technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method. The criteria used in this method are 7 criteria taken based on the criteria for BUMN talent management according to the Regulation of the Minister of BUMN Number PER-3 / MBU / 03/2023, these criteria are Professional Work Period, Variety of Work Experience, Managerial Competence, Technical Competence, Educational Strata, Performance Assessment Results, Level of Punishment that has been received. The results of this study are from the results of the calculation analysis through the TOPSIS method on 7 alternatives, then there is name number 5 managed to get the best score of 0.80 and was determined as a preference to be placed in class A garden.
Co-Authors Arief Hermawan Aziz Perdana Demas Risdho Listianto Dewi, Septi Riana Donny Avianto Edi Priyanto Enny Itje Sela Erik Iman Heri Ujianto Erik Iman HU Evada Rustina Hening Nakuloadi Nadia Pramesti Nur Wening Retno Prihatini Rian Oktafiani Rian Oktafiani Rubangi Rubangi Siska Howay Teguh Widodo Teguh Widodo