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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknik ITS IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science Semantik Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmiah Kursor Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal EECCIS Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Infotech Journal Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Inspiration KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) JOIV : International Journal on Informatics Visualization Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal ULTIMA InfoSys SISFO Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) PINISI Discretion Review Jurnal Rekayasa Industri (JRI) Teknika Journal La Multiapp JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) Melek IT: Information Technology Journal Jurnal Nasional Teknik Elektro dan Teknologi Informasi Sewagati Bulletin of Social Informatics Theory and Application Scientific Journal of Informatics
Yuhana, Umi Laili
Departemen Teknik Informatika, Fakultas Teknologi Elektro Dan Informatika Cerdas, Institut Teknologi Sepuluh Nopember Surabaya
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Analyzing interaction and player experience of game based learning using feature importance based clustering Alfan, Muhammad Bahauddin; Yuhana, Umi Laili; Herumurti, Darlis
Bulletin of Social Informatics Theory and Application Vol. 8 No. 2 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v8i2.772

Abstract

This study explores the dynamics of the gaming experience and its impact on learning efficiency through digital game-based learning (DGBL). Leveraging the Fingerstroke Level Model-GOMS (FLM-GOMS) for interaction analysis and the In-Game Experience Questionnaire (iGEQ) for player experience assessment, we examine the relationship between game-play mechanics and educational outcomes. Our research incorporates a comprehensive dataset, focusing on 40 features encompassing motivation and efficiency outcomes. Through clustering, we identify distinct player groups exhibiting signif-icant variations in efficiency outcomes and game experiences. We utilized the feature selection technique to identify the crucial features that differentiate groups of students who excel in implementing DGBL from those who do not. Through the Random Forest feature importance method, we have found that FLM-GOMS features and positive player in-game feedback play a pivotal role in determining the effectiveness of DGBL.
Pelatihan Pembuatan Media Pembelajaran Interaktif untuk Guru Pendidikan Anak Usia Dini Dengan Canva Sarwosri, Sarwosri; Rochimah, Siti; Yuhana, Umi Laili; Oranova, Daniel; Akbar, Rizky Januar; Nuralamsyah, Bintang
Sewagati Vol 9 No 1 (2025)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v9i1.2215

Abstract

Pada era modern kini, teknologi menjadi salah satu peran penting dalam kehidupan sehari-hari. Penguasaan teknologi menjadi kemampuan yang harus dimiliki berbagai lapisan masyarakat, tak terkecuali dalam bidang pendidikan. Semua tingkat pendidikan terdampak arus perkembangan teknologi, bahkan mencapai tingkat pendidikan anak usia dini. Melihat urgensi ini, penting bagi guru PAUD untuk memanfaatkan teknologi dalam kegiatan belajar mengajar. Salah satu pemanfaatan teknologi adalah dengan pembuatan media pembelajaran yang interaktif menggunakan Canva. Dengan memiliki kemampuan ini, diharapkan kualitas kegiatan belajar mengajar akan meningkat, mengingat metode belajar yang interaktif dan menarik menjadi salah satu kunci kesuksesan dari proses belajar anak pada usia dini. Laboratorium Rekayasa Perangkat Lunak mengadakan Pelatihan Pembuatan Media Pembelajaran Interaktif untuk Guru Pendidikan Anak Usia Dini. Jumlah peserta yang mengikuti pelatihan adalah 19 orang. Pelatihan dilakukan secara luring bertempat di Laboratorium Algoritma dan Pemrograman 2, Departemen Teknik Informatika ITS. Materi pelatihan yang diberikan meliputi pengenalan desain grafis dan canva, pembuatan kolase foto, pembuatan poster acara, dan pembuatan jadwal piket kelas. Pengabdian ini berhasil dilakukan dan dapat menjadi bentuk kontribusi ITS terhadap perkembangan pendidikan di Indonesia.
Pelatihan Pembuatan Media Pembelajaran Interaktif Berbasis Video untuk Guru Pendidikan Anak Usia Dini Nuralamsyah, Bintang; Sarwosri, Sarwosri; Rochimah, Siti; Yuhana, Umi Laili; Siahaan, Daniel Oranova; Akbar, Rizky Januar
Sewagati Vol 9 No 1 (2025)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v9i1.2593

Abstract

Perkembangan teknologi yang pesat membuat setiap individu tak terkecuali tenaga pendidik untuk berkembang mengikutinya. Dalam perkembangan teknologi, tenaga pendidik diuji keterampilannya dalam membuat media pembelajaran yang mampu menarik perhatian dan berkulitas bagi para peserta didik. Disisi lain, pentingnya media pembelajaran sebagai media penyampaian ilmu menjadi salah satu fokus yang perlu mendapatkan perhatian khusus demi memfasilitasi perkembangan anak terutama pada masa emas perkembangan anak usia dini. Terbentuklah pelatihan guna meningkatkan ketrampilan tenaga pendidik dalam membuat media pembelajaran berbasis video yang interaktif dengan Laboratorium Rekayasa Perangkat Lunak sebagai panitia acara. Terdapat 19 peserta yang mengikuti pelatihan terkait dengan detail peserta merupakan Paguyuban Guru PAUD Gunung Anyar Tambak. Pelatihan berjalan secara luring di Laboratorium Pemrograman 2, Departemen Informatika ITS. Materi pelatihan meliputi dasar penyuntingan video, elemen-elemen dalam penyuntingan video, sampai membagikan video. Pengabdian masyarakat berbentuk pelatihan ini berhasil dilakukan dengan tingkat kepuasan 2,965 dari 3. Pelatihan ini merupakan bentuk kontribusi ITS terhadap peningkatan dan perkembangan pendidikan di Indonesia.
Improve Software Defect Prediction using Particle Swarm Optimization and Synthetic Minority Over-sampling Technique Amirullah, Afif; Umi Laili Yuhana; Muhammad Alfian
Scientific Journal of Informatics Vol. 11 No. 4: November 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i4.16808

Abstract

Purpose: Early detection of software defects is essential to prevent problems with software maintenance. Although much machine learning research has been used to predict software defects, most have not paid attention to the problems of data imbalance and feature correlation. This research focuses on overcoming the problems of imbalance dataset. It provides new insights into the impact of these two feature extraction techniques in improving the accuracy of software defect prediction. Methods: This research compares three algorithms: Random Forest, Logistic Regression, and XGBoost, with the application of PSO for feature selection and SMOTE to overcome the problem of imbalanced data. Comparison of algorithm performance is measured using F1-Score, Precision, Recall, and Accuracy metrics to evaluate the effectiveness of each approach. Result: This research demonstrates the potential of SMOTE and PSO techniques in enhancing the performance of software defect detection models, particularly in ensemble algorithms like Random Forest (RF) and XGBoost (XGB). The application of SMOTE and PSO resulted in a significant increase in RF accuracy to 87.63%, XGB to 85.40%, but a decrease in Logistic Regression (LR) accuracy to 72.98%. The F1-Score, Precision, and Recall metrics showed substantial improvements in RF and XGB, but not in LR due to the decrease in accuracy, highlighting the impact of the research findings. Novelty: Based on the comparison results, it is proven that the SMOTE and PSO algorithms can improve the Random Forest and XGB models for predicting software defect.
Multimodel Prediction Score Based on Academic Procrastination Behavior in E-Learning Sartana, Bruri Trya; Nugroho, Supeno Mardi Susiki; Yuhana, Umi Laili; Purnomo, Mauridhi Hery
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 1 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i1.85880

Abstract

This research investigates the impact of academic procrastination on student performance in online learning environments and explores a multimodel approach for grade prediction. Academic procrastination is a well-documented issue that negatively affects learning outcomes, often leading to lower academic performance and increased dropout rates in self-paced learning platforms. This study analyzes behavioral data from 377 students, extracted from Moodle activity logs, which record real-time student interactions with learning materials. To address the gap in understanding procrastination patterns through activity logs, key procrastination-related features were derived from timestamps of task access, submission, and engagement duration. Using K-Means clustering with the Elbow method, students were categorized into three procrastination clusters: low procrastination with high academic performance, high procrastination with low performance, and moderate procrastination with average performance. Seven machine learning models were evaluated for predicting student grades, with Random Forest (RF) achieving the highest accuracy (R² = 0.812, MAE = 6.248, RMSE = 8.456). These findings highlight the potential of using activity logs to analyze procrastination patterns and predict student performance, allowing educators to develop early intervention strategies that support at-risk students and improve learning outcomes.
Analyzing User Experience and Satisfaction in the B-Block Game-Based Assessment Husniah, Lailatul; Kholimi, Ali Sofyan; Yuhana, Umi Laili; Yuniarno, Eko Mulyanto; Purnomo, Mauridhi Hery
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 1 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i1.92784

Abstract

Game-based assessment (GBA) has developed as an innovative education method, including learning basic arithmetic operations. This study aims to analyze user experience and satisfaction using B-Block, an assessment-based game for basic arithmetic operations. The study involved 94 junior high school students with an age distribution of 12-13 years old and varying levels of gaming experience. The research used descriptive statistical analysis, validity and reliability test, Pearson correlation test, and multiple linear regression to identify factors influencing user satisfaction and continuance usage intention. The analysis showed that B-Block has good usability and educational benefits, with user satisfaction being the most dominant aspect. Validity and reliability tests confirmed that most variables were valid and reliable (Cronbach's Alpha > 0.7), except Errors, which had lower reliability (α = 0.632). Pearson correlation shows that Perceived Usefulness has a strong relationship with satisfaction (r = 0.784), while user satisfaction contributes significantly to continuance intention (r = 0.694). Multiple linear regression revealed that perceived usability and perceived usefulness were the main factors influencing user satisfaction, while confirmation and satisfaction had the most effect on continuance intention. The findings confirm that the gameplay's usability and perceived usefulness are key in increasing user satisfaction while matching the experience with initial expectations, and user satisfaction contributes to continued use.
Analisis Metode Estimasi Biaya pada Perangkat Lunak Beserta Faktor-Faktor yang Mempengaruhi : A Systematic Literature Review Ariyanto, Amelia Devi Putri; ‘Azizah, Lutfiyatul; Yuhana, Umi Laili
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 4: Agustus 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021864611

Abstract

Estimasi biaya sampai sekarang masih menjadi salah satu permasalahan utama dalam perencanaan proyek perangkat lunak. Estimasi biaya ini memiliki peran yang penting karena berpengaruh pada berjalannya proyek dan menjadi penentu keberhasilan suatu proyek perangkat lunak. Kegagalan estimasi biaya dalam perencanaan proyek perangkat lunak dapat menyebabkan proyek tidak berjalan dengan baik dan menimbulkan kerugian bagi perusahaan. Oleh karena itu, banyak peneliti sampai saat ini masih mencari dan melakukan penelitian untuk mendapatkan estimasi terbaik. Berbagai metode diusulkan untuk mendapatkan ketepatan akurasi dengan memperhatikan faktor-faktor estimasi biaya. Tujuan penelitian ini adalah membuat Systematic Literature Review (SLR) yang berisi rangkuman dan analisis perkembangan penelitian terbaru tentang estimasi biaya pada perangkat lunak, khususnya pada metode yang digunakan serta faktor-faktor yang mempengaruhi. Penelitian ini berhasil mengkaji 21 penelitian lain dalam lima tahun terakhir (2015-2020) dan didapatkan 24 metode usulan yang terbagi menjadi tiga jenis metode yang sering digunakan dalam melakukan estimasi biaya perangkat lunak yaitu nonparametrik, parametrik dan semiparametrik. Selain itu, penelitian ini juga berhasil menemukan metode dan kombinasi metode terbaik berdasarkan ketepatan akurasi beserta lima faktor utama yang mempengaruhi estimasi biaya sehingga dapat digunakan para peneliti atau praktisi lain untuk mengembangkan estimasi biaya pada proyek perangkat lunak. AbstractCost estimation has an important role because it affects the project’s progress and determines the success of a software project. Failure to estimate costs in software project planning can cause the project to not run well and cause losses to the company. Therefore, many researchers are still looking for and researching to get the best estimation by considering the cost estimation factors. The purpose of this study is to create a Systematic Literature Review (SLR) which contains a summary and analysis of the latest research developments on cost estimation in software, especially in the methods used and the factors that affect cost estimation. This study successfully reviewed 21 other studies in the last five years (2015-2020) and obtained 24 planning methods which are divided into three types of methods that are often used in conducting software cost research, namely nonparametric, parametric and semiparametric. Besides, this study also succeeded in finding the best method and combination of methods based on best accuracy, namely COCOMO II and the combination of Genetic Algorithm and Artificial Bee Colony, along with the five main factors that influence cost estimation so that it can be used by researchers or other practitioners to develop cost estimates for software projects.
Prediksi Man-Hours Menggunakan Analisis Regression dan Cyclomatic Complexity Hersyaputra, Mohamad Syazimmi; Jaya, Muhammad Triyanda Taruna; Yuhana, Umi Laili; Alfian, Muhammad
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 11, No 1 (2025): Volume 11 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v11i1.89462

Abstract

Estimasi effort pengembangan perangkat lunak secara akurat merupakan kunci keberhasilan proyek untuk memastikan alokasi sumber daya yang efisien dan penyelesaian tepat waktu. Ketepatan dalam menghitung estimasi effort ini sangat krusial dalam proses pengembangan sistem perangkat lunak untuk mencapai keberhasilan dan mengurangi risiko, seperti risiko reputasi dari suatu organisasi. Metode konvensional seperti expert judgement sering kali kurang konsisten dan rawan kesalahan subjektif. Untuk mengatasi keterbatasan tersebut, penelitian ini mengusulkan pendekatan prediksi man-hours berbasis static code analysis, dengan fokus pada cyclomatic complexity sebagai fitur utama dalam pemodelan machine learning yang dapat diintegrasikan dalam proses rekayasa perangkat lunak untuk mendukung pengambilan keputusan yang lebih tepat dalam perencanaan proyek. Penelitian ini menggunakan data proyek perangkat lunak pada institusi perbankan. Tahapan preprocessing meliputi encode dengan teknik one hot encoding, data cleaning, dan data partitioning. Penelitian ini memanfaatkan cyclomatic complexity dari program perangkat lunak untuk memprediksi upaya dalam variabel man-hours menggunakan model Linear Regression, Lasso Regression, dan Ridge Regression. Evaluasi model dilakukan menggunakan metrik mean absolute percentage error (MAPE), mean absolute error (MAE), mean squared error (MSE), dan R-Squared guna menilai performa prediktif. Berdasarkan pengujian, model Lasso Regression menghasilkan peforma prediktif yang unggul dengan evaluasi menggunakan metrik MAPE 22.2731%, MAE 66.9679, MSE 8538.6359, dan R-Squared 0.98521. Temuan ini menunjukan bahwa pendekatan machine learning yang memanfaatkan analisis cyclomatic complexity mampu meningkatkan akurasi estimasi upaya dibandingkan metode konvensional.
Measuring the Quality of the Development Process Academic System with E-GQM Method Sarwosri, -; Nisa, Maidina Choirun; Rochimah, Siti; Akbar, Rizky Januar; Yuhana, Umi Laili
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.424

Abstract

In a software development project, aspects of software quality are fundamental; all stakeholders expect high-quality software. To ensure the quality of software products, it is necessary to ensure the software quality process. A software process is essential to be assessed from their quality. In the software development process, the developer needs guidance in carrying out every aspect of it. The goals to achieve and the procedure to measure for each aspect's goals performance must be determined. One method that can be used is the Extended Goal Question Metric method. This method determines what aspects must be achieved for each development process. A few goals to measure are defined for each aspect. For each goal, one or more goals determine one or more relevant questions. For each question, an appropriate metric is  determined. The next step is mapping between G to Q and Q to M. The measurement was conducted by calculating the goal value obtained from the metric calculation. From this metric, each goal's value could be obtained, whether it is achieved or not. The tests were carried out on the software process to develop the academic Directorate of Technology and Information System Development of Institut Teknologi Sepuluh Nopember Surabaya, Indonesia. Each goal's value exceeded 0.51 (for a scale of 0-1), which achieved the Software development process's quality. The total average score was 0.889.
SISTEM PEMBANGKIT ANOTASI PADA ARTIKEL BERGAMBAR DENGAN PENDEKATAN KONTEKSTUAL Diana Purwitasari; Dian Saputra; Esti Yuniar; Umi Laili Yuhana; Daniel Siahaan
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 9, No 1, Januari 2011
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (553.833 KB) | DOI: 10.12962/j24068535.v9i1.a64

Abstract

Development of E-learning sites and their materials make it is necessary to help users finding the desired materials. Context-based search engine will help users for the finding task. However that kind of searching can only be done for learning materials that have been semantically signed or annotated. Annotation is given for the article’s content or the article’s image within. There are many constraints for manually providing annotations to the learning articles such that automatic metadata or annotation generating method is needed. This paper discusses about annotation generating system with two subsystems: annotation recommender for learning material using contextual analysis and image metadata generator. The methods for contextual analysis are Latent Semantic Analysis (LSA) and WordNet-lexical dictionary usage. Our experimental results showed that subsystems can be used to generate annotation for articles and images in the articles though we have not done combination of two subsystems.
Co-Authors Achmad Affandi Agung Prasetya Ahmad Budi Kurniawan Ahmad Nur Hidayat Akbar Noto Ponco Bimantoro Akbar, Rizky Januar Alfan, Muhammad Bahauddin Ali Sofyan Kholimi Amelia Devi Putri Ariyanto Amirullah, Afif Andhik Ampuh Yunanto Andi Besse Firdausiah Anisah Herdiyanti Apriyanto, I Nengah Putra Ariatama, Ilham Putra Arief Rahman Ary Mazharuddin Shiddiqi As'ad Arismadhani Ayu Purwarianti Azzmi. H., M. Naufal ‘Azizah, Lutfiyatul Badrudin, Arif Bambang Setiawan Buliali, Joko Lianto Chastine Fatichah Daniel Oranova Daniel Oranova Siahaan Daniel Siahaan Darlis Herumurti Denni Aldi Ramadhani Denni Aldi Ramadhani Denni Aldi Ramadhani Denni Aldi Ramadhani Diana Purwitasari Diana Purwitasari Donny Fitrado Dwi Sunaryono Dwi Sunaryono Eka Alifia Kusnanti Eko M. Yuniarno Eko Mulyanto Yuniarno Esti Yuniar Fadilla Sukma Alfiani Faizah Alkaff Fanji Hastomo Febri Fernanda Gultom, Rudy Agus Gemilang Habibi, Ahmad Faqih Hadziq Fabroyir Hanim Maria Astuti Hazna At Thooriqoh Hersyaputra, Mohamad Syazimmi Hervit Ananta Vidada Hidayat, Taufik I Gusti Lanang Agung Oka Cahyadi Pradipta Ilham, Karina Fitriwulandari Imam Kuswardayan Imamah Imamah Irnayanti Dwi Kusuma Jaya, Muhammad Triyanda Taruna Kadek Anggrian Mahendra Putra Kurniawan, Adi Lailatul Hidayah Lailatul Husniah Lauretha Devi Fajar Vantie Lesmideyarti, Dwi Mamluatul Hani’ah Mauridhi Hery Purnomo Muhamad Fauzi Muhammad Alfian Muhammad Alfian, Muhammad Muhammad Faisal Fanani Muhammad Najib Muhammad Zain Fawwaz Nuruddin Siswantoro Nawang Sulistyani Nisa, Maidina Choirun Nugroho, Supeno Mardi S. Nuralamsyah, Bintang Oranova, Daniel Puspitaningrum, Ari Cahaya Putu Yuwono Kusmawan Ratnasari, Fitria Dwi Resky Ayu Dewi Talasari Rizal Setya Perdana Rizky Januar Akbar Rizqa Raaiqa Bintana Rully Agus Hendrawan Rully Soelaiman Sally Indah Khansa Sally Indah Khansa Santi Tiodora Sianturi Santoso, Bagus Jati Saptarini, Istiningdyah Sari Sahadi, Fitria Vera Sartana, Bruri Trya Sarwosri Sarwosri Sarwosri Sarwosri, - Setiawan, Wahyu Fajar Siska Arifiani Siswahyudianto Siti Rochimah Sjahrunnisa, Anita Sumantri, Siswo Hadi Supeno Mardi S. Nugroho Supeno Mardi Susiki Nugroho, Supeno Mardi Suyadi Suyadi Tiara Nur Annisa Toshihiro Kita Wighneswara, Alifiannisa Alyahasna Yasinta Romadhona Yogi Kurniaawan Yogi Kurniaawan, Yogi Yuniarno, Eko M.