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All Journal Telematika : Jurnal Informatika dan Teknologi Informasi Seminar Nasional Informatika (SEMNASIF) Jambura Journal of Mathematics Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) International Journal of Advances in Data and Information Systems Journal of Advanced in Information and Industrial Technology (JAIIT) Studies in Learning and Teaching Nusantara Science and Technology Proceedings Mitra Akademia: Jurnal Pengabdian Masyarakat TIERS Information Technology Journal International Journal of Data Science, Engineering, and Analytics (IJDASEA) International Journal Of Computer, Network Security and Information System (IJCONSIST) Journal of International Conference Proceedings Jurnal Aplikasi Sains Data
Prismahardi Aji Riyantoko
Department Of Data Science, Universitas Pembangunan Nasional “Veteran” Jawa Timur, Surabaya 60294, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Social Sciences Other

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Indonesian Sign Language (BISINDO) Classification Using Xception Transfer Learning Architecture Amelia, Meisya Vira; Saputra, Wahyu Syaifullah Jauharis; Hindrayani, Kartika Maulida; Riyantoko, Prismahardi Aji
International Journal of Advances in Data and Information Systems Vol. 6 No. 2 (2025): August 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i2.1392

Abstract

Human communication generally relied on speech. However, this was not applicable to the deaf people, who depended on sign language for daily interactions. Unfortunately, not everyone had the ability to understand sign language. In higher education environments, the lack of individuals proficient in sign language often created inequality in the learning process for deaf students. This limitation could be addressed by fostering a more inclusive environment, one of which was through the implementation of a sign language translation system. Therefore, this study aimed to develop a machine learning model capable of detecting and translating Indonesian Sign Language (BISINDO) alphabet gestures. The model was built using the Xception transfer learning method from Convolutional Neural Networks (CNN). The dataset consisted of 26 BISINDO alphabet gestures with a total of 650 images. The model was evaluated using K-Fold cross-validation and achieved an F1-score of 94% during testing.
Southeast Asia Happiness Report in 2020 Using Exploratory Data Analysis Riyantoko, Prismahardi Aji
IJCONSIST JOURNALS Vol 2 No 1 (2020): September
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (383.725 KB) | DOI: 10.33005/ijconsist.v2i1.31

Abstract

The happiness index to be one of part to presents that each country has indicator which affect each other. Many countries have a basic indicator to determine that happiness score, there are economy sector, social support, trust to the government, generosity, and measure life satisfactions. The indicator is presents in the dataset, it means need to explore, analysis, and visualization to give knowledge to the other people. Data science is one knowledge field to determine data. Exploratory data analysis (EDA) is part of data science process. In this works, we present happiness report in the Southeast Asia region using the dataset World Happiness Report 2020. The results, we describe and discuss the dataset using table with column and value or score, the other we using bar-plot, correlation bar-plot, bar-plot analysis, and map-plotting visualization. Output of EDA is only recommendation to next parts in the Data Science process, minimum has knowledge to reducing data, merge data, cleansing data, visualization data to be based of knowledge to build data modelling.
Exploratory Data Analysis and Machine Learning Algorithms to Classifying Stroke Disease Riyantoko, Prismahardi Aji; Fahrudin, Tresna Maulana; Hindrayani, Kartika Maulida; Idhom, Mohammad
IJCONSIST JOURNALS Vol 2 No 02 (2021): March
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (517.79 KB) | DOI: 10.33005/ijconsist.v2i02.49

Abstract

This paper presents data stroke disease that combine exploratory data analysis and machine learning algorithms. Using exploratory data analysis we can found the patterns, anomaly, give assumptions using statistical and graphical method. Otherwise, machine learning algorithm can classify the dataset using model, and we can compare many model. EDA have showed the result if the age of patient was attacked stroke disease between 25 into 62 years old. Machine learning algorithm have showed the highest are Logistic Regression and Stochastic Gradient Descent around 94,61%. Overall, the model of machine learning can provide the best performed and accuracy.
PEMANFATAAN APLIKASI CANVA SEBAGAI MEDIA PEMASARAN DI KAMPUNG KUE SURABAYA Riyantoko, Prismahardi Aji; Fahrudin, Tresna Maulana; Sa'diyah, Ilmatus; Varqa Ansori, Nine Alvariqati; Atnanda, Primus Akbar; Alamsyah, Ryan Badai
Mitra Akademia: Jurnal Pengabdian Masyarakat Vol 5 No 1 (2022): Mitra Akademia: Jurnal Pengabdian Masyarakat
Publisher : Pusat Penelitian dan Pengabdian kepada Masyarakat (P3M) Politeknik Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/mapnj.v5i1.4529

Abstract

The evolution of information technology in Industrial 4.0 and Society 5.0 makes people have to divert buying and selling activities using digital media. A cake cluster (kampung kue) in Surabaya needs a media or application based on information technology for making catalogs that can be published through social media. We offer a solution to make it easier for the sellers by using the Canva Application as a medium for cataloging and marketing the cake through many social media to attract buyers and customers. In carrying out the promotion, it is necessary to prepare the best promote the Indonesian Language, hence we also give the participant to improve the promotion skills. The other result of our training and mentoring approach during community service is a training module publication. This module provides participants with how to use the Canva Application and promotional language. Therefore, marketing and selecting strategies are the main keys in the business of the digital era. Utilizing information technology and social media has proven to have a very positive impact on increasing sales effects. Keywords: Catalog, Canva, Kampung Kue, Promotion Language Abstrak Perkembangan teknologi informasi di era Industri 4.0 dan Society 5.0 menjadikan masyarakat harus mengalihkan kegiatan jual beli melalui media digital. Salah satu komunitas di Kota Surabaya yaitu Kampung Kue membutuhkan media pembuatan katalog yang bisa dipublikasikan melalui media sosial. Solusi yang bisa kami tawarkan untuk memudahkan Ibu-Ibu penjual kue adalah dengan memanfaatkan aplikasi canva sebagai media pembuatan katalog dan memasarkan hasil katalognya melalui banyak media sosial untuk menarik pembeli dan pelanggan. Dalam melakuakan promosi dibutuhkan penyusunan Bahasa Indonesia yang baik, benar dan tepat, agar kualitas promosinya lebih baik, sehingga kami juga melatih keterampilan Ibu-Ibu di Kampung Kue dengan memberikan keterampilan promosi. Kegiatan ini menghasilkan ketertarikan Ibu-Ibu untuk memanfaatkan aplikasi canva sebesar 80% dari total jumlah peserta yang hadir selama dua hari. Salah satu hasil yang diberikan dari pelatihan dan pendampingan ini adalah modul pelatihan. Modul ini memberikan tata cara penggunaan aplikasi canva dan Bahasa promosi kepada pengusaha kue. Oleh karena itu, memasarkan dan pemilihan strategi serta media sosial menjadi kunci utama dalam usaha di era digital ini. Dengan memanfaatkan teknologi informasi dan media sosial terbukti sangat berdampak positif dalam meningkatkan hasil penjualan. Kata kunci: Katalog, Canva, Kampung Kue, Bahasa Promosi  
Penyusunan media pembelajaran digital menggunakan bahasa pemrograman R-Shiny 4.3.3 pada jenjang sekolah menengah atas Trimono, Trimono; Ikaningtyas, Maharani; Widayawati, Eny; Riyantoko, Prismahardi Aji; Widison, Daffin Tanjiro; Khosyi, Hanun Aufa Nur
Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) Vol. 6 No. 3 (2025)
Publisher : Universitas Islam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33474/jp2m.v6i3.22899

Abstract

Penerapan Kurikulum Merdeka pada jenjang SMA berorientasi pada pemanfaatan teknologi dalam proses pembelajaran. Namun, fakta yang terjadi menunjukan bahwa penerapan belum berjalan optimal karena keterbatasan perangkat dan kurangnya penguasaan teknologi oleh guru dan murid. Hal tersebut berdampak pada proses transfer materi yang terhambat, hasil belajar yang belum sesuai target sekolah, serta siswa yang mengalami kesulitan dalam mempelajari materi yang diberikan. Untuk mengatasinya, akan disusun aplikasi pembelajaran digital berbasis Graphical User Interface (GUI).  Aplikasi disusun menggunakan bahasa pemrograman R-Shiny 4.3.3 dan terdiri dari dua struktur utama yaitu ui.io dan server.io. Ui.io berisi perintah mengatur tampilan aplikasi dan dijalankan melalui perintah dashboardHeader, dashboardSidebar dan tabsetPanel. Server.io berisi perintah komputasi untuk memperoleh hasil akhir. Perintah yang digunakan meliputi output$contents, renderDataTable, renderPrint, dan renderPlot. Kegiatan ini bertujuan untuk memberikan keahlian kepada guru untuk menciptakan aplikasi pembelajaran digital yang dapat diterapkan pada proses pembelajaran. Melalui uji mean sampel berpasangan, pada tingkat kepercayaan α = 5% diperoleh hasil bahwa terdapat peningkatan yang signifikan dalam hal kemampuan guru dalam menyusun media pembelajaran. Rata-rata kemampuan guru sebelum mengikuti pelatihan adalah 1,21 dan setelah pelatihan adalah 8,34. Luaran utama yang diperoleh adalah aplikasi pembelajaran untuk mata kuliah Matematika, Fisika, Kimia, dan Ekonomi.
Daily Forecasting for Antam's Certified Gold Bullion Prices in 2018-2020 using Polynomial Regression and Double Exponential Smoothing Fahrudin, Tresna Maulana; Riyantoko, Prismahardi Aji; Hindrayani, Kartika Maulida; Diyasa, I Gede Susrama Mas
Journal of International Conference Proceedings Vol 3, No 4 (2020): Proceedings of the 8th International Conference of Project Management (ICPM) Mal
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v3i4.1009

Abstract

Gold investment is currently a trend in society, especially the millennial generation. Gold investment for the younger generation is an advantage for the future. Gold bullion is often used as a promising investment, on other hand, the digital gold is available which it is stored online on the gold trading platform. However, any investment certainly has risks, and the price of gold bullion fluctuates from day to day. People who invest in gold hopes to benefit from the initial purchase price even if they must wait up to five years. The problem is how they can notice the best time to sell and buy gold. Therefore, this research proposes a forecasting approach based on time series data and the selling of gold bullion prices per gram in Indonesia. The experiment reported that Holt’s double exponential smoothing provided better forecasting performance than polynomial regression. Holt’s double exponential smoothing reached the minimum of Mean Absolute Percentage Error (MAPE) 0.056% in the training set, 0.047% in one-step testing, and 0.898% in multi-step testing.
Implementation of Web Scraping on Google Search Engine for Text Collection Into Structured 2D List Fahrudin, Tresna Maulana; Riyantoko, Prismahardi Aji; Hindrayani, Kartika Maulida
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.v20i2.9575

Abstract

Purpose: This research proposes the implementation of web scraping on Google Search Engine to collect text into a structured 2D list.Design/methodology/approach: Implementing two important stages in the process of collecting data through web scraping, namely the HTML parsing process to extract links (URL) on Google Search Engine pages, and HTML parsing process to extract the body text from website pages on each link that has been collected.Findings/result: The inputted query is adjusted to the latest issues and news in Indonesia, for example the President's important figures, the month of Ramadan and Idul Fitri, riots tragedy (stadium) and natural disasters, rising prices of basic commodities, oil and gold, as well as other news. The least number of links obtained was 56 links and the most was 151 links, while the processing time to obtain links for each of the fastest queries was 1 minute 6.3 seconds and the longest was 2 minutes 49.1 seconds. The results of scraping links from these queries were obtained from Wikipedia, Detik, Kompas, the Election Supervisory Body (Bawaslu), CNN Indonesia, the General Election Commission (KPU), Pikiran Rakyat, and others.Originality/value/state of the art: Based on previous research, this study provides an alternative to produce optimal collection of links and text from web scraping results in the form of a 2D list structure. Lists in the Python programming language can store character sequences in the form of strings and can be accessed using index keys, and manipulate text efficiently.
Application of Convolutional Neural Network (CNN) for Web-Based Translation of Indonesian Text into Sign Language Prameswari, Diajeng; Larasati; Muhammad Naswan Izzudin Akmal; Prismahardi Aji Riyantoko; Dwi Arman Prasetya
Jurnal Aplikasi Sains Data Vol. 1 No. 2 (2025): Journal of Data Science Applications.
Publisher : Program Studi Sains Data UPN "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/jasid.v1i2.12

Abstract

Communication for the deaf and hard of hearing is often hindered by the limited number of sign language interpreters. This research aims to develop a web-based text-to-text sign language translation system using Convolutional Neural Networks (CNN) to bridge this communication gap. The system is built with the ASL Alphabet dataset containing 87,000 images from 29 classes (A-Z, SPACE, DELETE, NOTHING). The CNN model was designed with three convolutional layers and trained for 15 epochs using 80% of the data, while 20% of the data was used for testing. The user interface was developed using Streamlit for ease of use. Training results showed a training accuracy of 98.96% and a validation accuracy of 98.61% at the 15th epoch. Model evaluation yielded an overall accuracy of 98%, with high precision, recall, and F1-score values for most classes. This research demonstrates the significant potential of CNN in developing automatic sign language translators, which is expected to improve information accessibility and inclusivity for the deaf community.
Application of K-Means Clustering for Regency/City Clustering in East Java Based on 2024 Human Development Index Indicators Emilia, Kholidatus; Rahayu, Ayu Sri; Yuliani, Devina Putri; Prasetya, Dwi Arman; Riyantoko, Prismahardi Aji
Jurnal Aplikasi Sains Data Vol. 1 No. 2 (2025): Journal of Data Science Applications.
Publisher : Program Studi Sains Data UPN "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/jasid.v1i2.21

Abstract

This study applies the K-Means clustering algorithm to group 38 regencies and cities in East Java Province based on five Human Development Index (HDI) indicators for the year 2024. These indicators include Life Expectancy (UHH), Expected Years of Schooling (HLS), Mean Years of Schooling (RLS), and Real Expenditure Per Capita (PPK). The aim of this research is to uncover hidden patterns and disparities in regional development, which can be used as a basis for more targeted and data-driven policy interventions.The optimal number of clusters was determined using three evaluation metrics: the Elbow Method, Silhouette Score, and Davies-Bouldin Index. These evaluations collectively identified three distinct clusters. Cluster 0 represents regions with high levels of development across all indicators. Cluster 1 consists of regions with moderate development levels and potential for improvement, while Cluster 2 contains regions with significantly lower values, particularly in education and income metrics.In addition to clustering, a correlation analysis was conducted to examine the relationship between HDI and its supporting indicators. The results show that Mean Years of Schooling (RLS) and Real Expenditure Per Capita (PPK) have the strongest positive correlation with HDI across all clusters. This highlights the key role of education and economic well-being in improving human development. The findings emphasize the importance of clustering analysis in shaping equitable and region-specific development strategies.
Application of XGBoost for Risk Level Classification of Fires in Surabaya City in 2024 and Interactive Spatial Visualization Based on Streamlit Sarah, Sarah Aprilia Hasibuan; Divia, Divia Prisillia Prisca; Dila, Annita Fadhilah Aprilia; Arman, Dwi Arman Prasetya; Prisma, Prismahardi Aji Riyantoko
Jurnal Aplikasi Sains Data Vol. 1 No. 2 (2025): Journal of Data Science Applications.
Publisher : Program Studi Sains Data UPN "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/jasid.v1i2.24

Abstract

 Fire in urban areas such as Surabaya City is a non-natural disaster that can have a significant impact on public safety, economic stability, and the environment. This study aims to develop a fire risk level classification model using Extreme Gradient Boosting (XGBoost) algorithm based on selected predictor variables, namely response time, fire subtype, and number of victims affected. The dataset consists of 859 fire events throughout 2024, enriched with spatial and demographic attributes. The research methodology involved data preprocessing (including label coding and normalization), class imbalance handling with Synthetic Minority Over-sampling Technique (SMOTE), model training with XGBoost, and evaluation using metrics such as accuracy, precision, recall, and f1-score. The classification model achieved excellent performance, with an overall accuracy of 1.00% and perfect precision, recall, and f1-score of 1.00 across all risk categories (low, medium, and high). Confusion matrix and ROC curve analysis confirmed the high predictive ability of this model. In addition, the results were visualized using a Streamlit-based interactive dashboard to enhance the usability of the model for decision-making. These findings highlight the potential of XGBoost as a powerful tool for fire risk classification and emphasize its relevance in supporting early warning systems and evidence-based disaster mitigation policies in urban environments.
Co-Authors Ahmad Khairul Faizin Alamsyah, Ryan Badai Ali Shodikin Alifansa, Dimas Mirza Amalia, Indira S. Amelia, Meisya Vira Amri Muhaimin Anggraini Puspita Sari Arista Pratama Arman, Dwi Arman Prasetya Atnanda, Primus Akbar Burhan Syarif Acarya Dila, Annita Fadhilah Aprilia Divia, Divia Prisillia Prisca Diyasa, I Gede Susrama Mas Dwi Arman Prasetya Dwi Arman Prasetya Dwi Arman Prasetya Emilia, Kholidatus Fahrudin, Tresna Maulana Fairuz Mumtaz Idhizar Farraz Hendri Prabowo I Gede Susrama Mas Diyasa I Gusti Putu Asto Buditjahjanto I Maruddani , Di Asih idhom, Mohammad Ikaningtyas, Maharani Ilmayasinta, Nur Kartika Maulida Hindrayani Kartika Maulida Hindrayani Khosyi, Hanun Aufa Nur Larasati Made Hanindia Prami Swari Mohammad Idhom Mohammad Idhom Muhammad Naswan Izzudin Akmal Munoto Novandi Kevin Pratama Nur Imro’atus Solikha Prameswari, Diajeng Pratama, Novandi Kevin Rahayu, Ayu Sri Rochmatin, Ulifatur Sa'diyah, Ilmatus Safitri, Eristya Maya Sarah, Sarah Aprilia Hasibuan Soemarsono, Annisa Rahmita Solikha, Nur Imro’atus Susrama Masdiyasa, I Gede Tahta Dari Timur Tresna Maulana Fahruddin Tresna Maulana Fahrudin Tresna Maulana Fahrudin Tresna Maulana Fahrudin Tresna Maulana Fahrudin Trimono Trimono, Trimono Varqa Ansori, Nine Alvariqati Wahyu Kyestiati Sumarno Wahyu Syaifullah Jauharis Saputra Widayawati, Eny Widison, Daffin Tanjiro Yuliani, Devina Putri