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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Teknologi Informasi dan Ilmu Komputer Journal of ICT Research and Applications Seminar Nasional Informatika (SEMNASIF) Jurnal Teknologi dan Sistem Komputer Knowledge Engineering and Data Science JIKO (Jurnal Informatika dan Komputer) Jurnal TAM (Technology Acceptance Model) ILKOM Jurnal Ilmiah IJID (International Journal on Informatics for Development) JURIKOM (Jurnal Riset Komputer) ILKOMNIKA: Journal of Computer Science and Applied Informatics Jurnal E-Komtek JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Applied Data Sciences Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Pendidikan dan Teknologi Indonesia Jurnal Indonesia : Manajemen Informatika dan Komunikasi Journal of Informatics and Communication Technology (JICT) Journal of Engineering, Electrical and Informatics (JEEI) Konstelasi: Konvergensi Teknologi dan Sistem Informasi Malcom: Indonesian Journal of Machine Learning and Computer Science Journal of Scientific Research, Education, and Technology SmartComp Journal of Technology Informatics and Engineering Jurnal Indonesia : Manajemen Informatika dan Komunikasi The Indonesian Journal of Computer Science Journal of Informatics and Communication Technology (JICT) Jurnal TAM (Technology Acceptance Model) Jurnal Abdi Rakyat Journal of Engineering, Electrical and Informatics
Enny Itje Sela
Master Program Of Information Technology, Universitas Teknologi Yogyakarta, Jl. Siliwangi (Ringroad Utara), Jombor, Sleman, D.I. Yogyakarta 55285|Universitas Teknologi Yogyakarta
Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Klasifikasi Batik Pekalongan Berdasarkan Citra dengan Metode GLCM dan JST Backpropagation Fathul Am; Sela, Enny Itje
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 1 (2024): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i1.532

Abstract

Batik is an Indonesian cultural heritage that is internationally recognized by UNESCO. However, knowledge about the types of batik, especially traditional Pekalongan batik, is increasingly forgotten due to globalization. This research aims to create a Pekalongan traditional batik image classification system through Gray Level Co-Occurrence Matrix (GLCM) feature extraction and Artificial Neural Network (ANN) classification method. This system aims to make it easier for people to identify Pekalongan batik motifs without requiring special skills. The results showed that the GLCM and JST methods can be used to classify Pekalongan batik can predict correctly. The use of JST Backpropagation architecture with 3 hidden layers resulted in train data accuracy of 46.6% and test data accuracy of 55.5%. This system is expected to help preserve the cultural heritage of batik and increase public understanding of Pekalongan batik motifs.
Perancangan Aplikasi Quiz Sebagai Media Pembelajaran Sejarah Rachmawan, Idham Kholed; Sela, Enny Itje
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 1 (2024): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i1.575

Abstract

Mastery of historical concepts is important for students in increasing their understanding of country’s past dan history. However, conventional history learning metodhs still often experience difficulties in attracting and motivating students to learn. Therefore, we need an interactive and fun learning media to increase students’ learning history. One alternative interactive learning media is an interactive quiz application. This study aims to help teachers in the learning process so that students are more interested in learning history with learning media in the form of interactive quiz applications. The interactive quiz application developed in this final project is an android-based application that makes it easier for students to learn history in a fun way. This application provides quizzes rellated to history subject matter wich are presented interactively. In addition, this application also provides an evaluation feature to evaluate students’ ability to master historical concepts.
Pengembangan Sistem Point of Sale Berbasis Web dan Mobile di Kooi Coffee Prawirdani, Adil; Sela, Enny Itje
ILKOMNIKA Vol 6 No 3 (2024): Volume 6, Nomor 3, Desember 2024
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/ilkomnika.v6i3.689

Abstract

Kooi Coffee, sebuah kedai kopi di Karimun, Kepulauan Riau, masih menggunakan sistem pencatatan transaksi secara konvensional. Dalam sistem ini, pencatatan pesanan hingga pembuatan setruk dilakukan menggunakan kertas dan direkapitulasi ke dalam buku transaksi di akhir hari. Sistem konvensional tersebut berpotensi menimbulkan berbagai permasalahan, seperti kesulitan dalam pelacakan penjualan, risiko kesalahan pencatatan, ketidakakuratan laporan keuangan, serta belum dapat mengakomodasi permintaan metode pembayaran digital oleh pelanggan. Penelitian ini bertujuan mengembangkan sistem Point of Sale (POS) berbasis web dan mobile untuk mengoptimalkan proses transaksi dan manajemen operasional Kooi Coffee. Sistem POS dikembangkan melalui pendekatan client-server dengan arsitektur REST API, di mana bagian backend dibangun menggunakan bahasa pemrograman Go (Golang), PostgreSQL sebagai basis data relasional, aplikasi web manajerial menggunakan React, dan aplikasi mobile kasir dikembangkan menggunakan Flutter. Pengujian sistem menggunakan metode black box testing menunjukkan keberhasilan 100% pada total 31 skenario yang diuji. Sistem POS yang dikembangkan telah mampu mengintegrasikan proses transaksi, manajemen menu, pengelolaan akun pengguna, pelaporan, serta pembayaran digital melalui payment gateway. Selain itu, aplikasi mobile juga dapat terhubung dengan printer thermal untuk mencetak setruk transaksi. Secara keseluruhan, sistem POS yang dihasilkan dapat memberikan kemudahan dalam operasional Kooi Coffee dan mengoptimalkan proses bisnisnya.
Development and Implementation of Mobile Application for Warehouse Inventory Reporting System Julian Ega Prabowo; Sela, Enny Itje
Journal of Informatics and Communication Technology (JICT) Vol. 6 No. 2 (2024)
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The company is engaged in the sale of emping mlinjo crackers and currently still uses manual recording methods to manage its operational activities. The main problem faced is the process of making monthly reports to record the movement of goods in and out of goods and monitor the stock of finished goods and raw materials. Along with the rapid growth of the company, this manual method has become inefficient in handling the high volume of goods and many daily transactions. This often leads to errors and discrepancies in reports, resulting in less efficient distribution of goods. This research aims to digitize the warehouse management system of warehouse management by developing a reporting application for the emping warehouse. goods. This application is designed to monitor the movement of goods and generate reports digitally. It is expected that this application will improve operational efficiency by facilitating data recording and management by the SO (Sales Order) Team, Sales Order Team, Production Team, Distribution Team, and provide convenience for the owner as a super admin in managing warehouse activities. The research method used is interviews and observations to identify the problems faced by the company. Based on the findings, the design, development, and implementation of the application and system testing were carried out. Descriptive analysis was used to evaluate the impact of the application on warehouse management and company operations. The results showed that the application was effective in recapitulating incoming and outgoing goods, making it easier to generate reports, and calculating profit or loss from sales transactions. The app enables real-time monitoring, simplifies data input by employees, and increases transaction audit transparency. The digital reporting system simplifies warehouse management, improves operational efficiency, and reduces recording errors and stock management mistakes.
Debtor Eligibility Prediction Using Deep Learning with Chatbot-Based Testing Noviania, Reski; Sela, Enny Itje; Latumakulita, Luther Alexander; Sentinuwo, Steven R.
Knowledge Engineering and Data Science Vol 7, No 2 (2024)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v7i22024p128-138

Abstract

Predicting debtor eligibility is essential for effective risk management and minimizing bad credit risks. However, financial institutions face challenges such as imbalanced data, inefficient feature selection, and limited user accessibility. This study combines Recursive Feature Elimination (RFE) and Deep Learning (DL) to improve prediction accuracy and integrates a chatbot interface for user-friendly testing. RFE effectively identifies critical features, while the DL model achieves a validation accuracy of 97.62%, surpassing previous studies with less comprehensive methodologies. The chatbot's novel design not only ensures accessibility but also enhances user engagement through flexible input options, such as approximate values, enabling non-experts to interact seamlessly with the system. For financial institutions, this chatbot-based testing approach offers practical benefits by streamlining debtor evaluation processes, reducing dependency on manual assessments, and providing consistent, scalable, and efficient solutions for credit risk management. It allows institutions to handle inquiries outside business hours, ensuring a continuous service flow. Furthermore, the system’s flexibility supports better customer interaction, increasing trust and transparency. By combining advanced machine learning with accessible interfaces, this study offers a scalable solution to improve the precision and practicality of debtor eligibility assessments, making it a valuable tool for modern financial institutions.
Utilization of Augmented Reality as a Media Introduction to Pests in Rice Plants Using the Marker Base Method Fatah Nur Saifullah; Enny Itje Sela
Journal of Scientific Research, Education, and Technology (JSRET) Vol. 3 No. 4 (2024): Vol. 3 No. 4 2024
Publisher : Kirana Publisher (KNPub)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58526/jsret.v3i4.533

Abstract

Indonesia is an agrarian country where rice is a major commodity and a primary food source for the Indonesian population. To encourage the interest and knowledge of the younger generation as farmers, innovation is needed as a basic learning medium about agriculture, specifically rice. This research aims to develop a mobile application based on Marker-Based Augmented Reality (AR) to enhance the effectiveness of pest identification in rice plants. The application is designed to provide visual and interactive information to farmers about the types of pests that frequently attack rice plants, along with their characteristics. Data on rice pests are collected through literature reviews and interviews with several rice farmers. The application utilizes markers that can be recognized by the mobile device's camera to display 3D models and information about the pests. Testing results show that the application works well as expected, and the 3D object information regarding rice pests, along with their characteristics, can be displayed. Additionally, this application is expected to contribute to reducing crop losses due to pest attacks by improving farmers' quick and accurate responses, and it can serve as an effective and innovative tool in the field of agriculture, particularly in pest identification in rice plants.
Utilization of Flutter Framework in Developing an Android-Based Cooking Recipe Application Algadrie, Saniah Evatri; Sela, Enny Itje
Journal of Scientific Research, Education, and Technology (JSRET) Vol. 3 No. 4 (2024): Vol. 3 No. 4 2024
Publisher : Kirana Publisher (KNPub)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58526/jsret.v3i4.593

Abstract

Cooking has become a common activity in everyday life. Cooking activities require recipes that are used as a guide in processing food ingredients into a dish. The collection of recipes in print media has not been able to meet the needs of users with a dynamic lifestyle. Therefore, researchers developed an android mobile-based cooking recipe application which is a solution to make it easier for users to find and practice recipes efficiently. This research uses a design process using the System Development Life Cycle (SDLC) approach. And in making this application, researchers used the Flutter framework with the Dart programming language which is designed for fast, efficient, and high-performance application development. Later this application will relate to the API (Application Programming Interface) of TheMealDB which provides recipe data. The result of this research is an application that is able to display innovative cooking recipes so that users can easily find and implement cooking recipes and support the improvement of cooking skills and creativity.
Osteoporosis Detection Using a Combination of Recursive Feature Elimination and Naive Bayes Classifier with Rule-Based Chatbot Testing Sela, Enny Itje; Rianto, Rianto; Anggara, Afwan; Utami, Wahyu Sri
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.409

Abstract

Osteoporosis is a condition characterized by reduced bone mass and density, increasing the risk of fractures. Early detection relies on patient awareness and proactive health management. Despite advances in technology, patient independence and awareness remain critical for early diagnosis. A rule-based chatbot tool can assist by helping patients screen their bone health. The chatbot provides automated recommendations, offering an alternative to traditional hospital visits. This study presents a rule-based chatbot designed to detect osteoporosis, using Recursive Feature Elimination (RFE) combined with the Naïve Bayes Classifier (NBC). Machine learning is integrated to enhance the chatbot's ability to identify early signs of osteoporosis. The model’s performance is compared to other feature selection methods, such as Principal Component Analysis (PCA), and machine learning algorithms like Deep Learning, Support Vector Machine (SVM), and Logistic Regression. The dataset used includes public data sets for training and validation, as well as data from the Yogyakarta Health Office for predictions. Research phases include normalization, data encoding, feature selection, training, validation, and prediction. The chatbot implements text preprocessing techniques, such as tokenization, stop word removal, and feature extraction, alongside normalization and encoding of numeric data. The prediction stage determines if the patient has a positive or negative osteoporosis status. Validation results show the RFE-NBC model is particularly effective for osteoporosis detection, offering a balanced performance in identifying both positive and negative cases. Additionally, this model served as the foundation for creating a rule-based chatbot designed to detect osteoporosis. Based on the set of testing metrics using chatbot, the model demonstrates strong overall performance, with a good balance between identifying positive and negative instances.
Penerapan Augmented Reality Pada Aplikasi Pembelajaran Senjata Tradisional Indonesia Berbasis Android. Adidarma, Muhamad Bahru; Sela, Enny Itje
KONSTELASI: Konvergensi Teknologi dan Sistem Informasi Vol. 4 No. 2 (2024): Desember 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/konstelasi.v4i2.10269

Abstract

Indonesia adalah negara yang kaya akan keberagaman suku bangsa, menjadi rumah bagi beragam budaya, bahasa, dan tradisi. Salah satu warisan budaya yang berharga adalah senjata tradisional. Namun, dalam era modern ini, keberadaan serta pemahaman akan senjata tradisional sering terabaikan, terutama di kalangan generasi muda yang lebih tertarik pada teknologi modern. Penelitian ini bertujuan untuk merancang aplikasi edukasi berbasis Augmented Reality (AR) pada platform Android sebagai sarana interaktif untuk memperkenalkan senjata tradisional Indonesia. Data mengenai senjata tradisional dikumpulkan melalui kajian literatur yang mencakup senjata dari setiap provinsi di Indonesia. Aplikasi ini memanfaatkan teknologi AR dengan marker untuk menghasilkan objek 3D, audio, serta informasi terkait senjata tersebut. Fitur kuis juga disertakan sebagai evaluasi dari proses pembelajaran. Pengujian aplikasi dilakukan secara internal untuk memastikan fungsionalitas teknologi AR, dan hasilnya menunjukkan bahwa aplikasi dapat beroperasi dengan baik serta berpotensi menjadi alat edukasi yang menarik di masa depan, terutama bagi generasi muda.
Sistem Pendukung Keputusan Calon Penerima Beasiswa Yayasan Politeknik Kesehatan Bhakti Setya Indonesia Menggunakan Metode SAW Dan TOPSIS Senoaji, Muhammad Senoaji Wibowo; Enny Itje Sela; Apriyaldi Lukman; Ferryma Arba Apriansyah; Olwin Kirab Novaldy
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2183

Abstract

The scholarship selection system at the Bhakti Setya Indonesia Health Polytechnic Foundation is still conducted manually, making it less transparent and time-consuming. This process requires an objective and measurable method to ensure fairness in determining scholarship recipients. This study aims to develop a decision support system for scholarship selection using the Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The SAW method calculates scores based on the aggregation of weighted normalized values, while the TOPSIS method evaluates candidates based on their proximity to ideal solutions. The criteria used in this study include parental income, number of dependents, GPA, organizational involvement, and achievements. The results indicate that the developed system is capable of ranking candidates with high accuracy. Candidates with the best performance consistently ranked at the top in the results of both methods.
Co-Authors Adidarma, Muhamad Bahru Agus Ardiyanto Agus Ardiyanto Agus Harjoko Agus Harjoko AKBAR MAULANA Akbar, Riolandi Algadrie, Saniah Evatri Alhafiz, Amirrul Dafa Anggara, Afwan Anindita Septiarini, Anindita Apriyaldi Lukman Ari Hendrawan Arif Amrulloh Asep Zainal Alfarizi Briyan Efflin Syahputra Edi Priyanto Fatah Nur Saifullah Fathul Am Fathul Am Ferryma Arba Apriansyah Ganda Sinarna Hendrawan, Ari Idham Kholed Rachmawan Julian Ega Prabowo Luther Alexander Latumakulita Luther Latumakulita M Ihsan Munakhir Mudjosemedi Nathaniela Aptanta Parama Noourul Islam Noviania, Reski Nugroho, Faishal Tirto Nur Wening, Nur Olwin Kirab Novaldy Prawirdani, Adil Rachmawan, Idham Kholed Retantyo Wardoyo Rianto Rianto Risky Devandra Hartana Saucha Diwandari Senoaji, Muhammad Senoaji Wibowo Sri Hartati Steven Ray Sentinuwo Syahrul Gunawan Ramdhani Syamsu Windarti Totok Suprawoto Triwibowo, Muhammad Ilham Tundo, Tundo Utami, Wahyu Sri