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All Journal Jurnal Pendidikan dan Pengajaran TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Terapan Abdimas QUANTUM: Jurnal Inovasi Pendidikan Sains PROtek : Jurnal Ilmiah Teknik Elektro Jurnal SOLMA Jiko (Jurnal Informatika dan komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Jurnal Tekinkom (Teknik Informasi dan Komputer) Buletin KKN Pendidikan Medfarm: Jurnal Farmasi dan Kesehatan MURHUM : JURNAL PENDIDIKAN ANAK USIA DINI Buletin Literasi Budaya Sekolah Jurnal Teknologi Pendidikan : Jurnal Penelitian dan Pengembangan Pembelajaran IJORER : International Journal of Recent Educational Research Semah : Jurnal Pengelolaan Sumberdaya Peraira Jurnal Penyuuhan dan Pemberdayaan Masyarakat (JPPM) Proceeding ISETH (International Summit on Science, Technology, and Humanity) Jurnal Ilmu Akuntansi Mulawarman (JIAM) Mestro Warta LPM Bina Bangsa International Journal of Business and Management Jurnal PETISI (Pendidikan Teknologi Informasi) Proceeding of Informatics Collaborations and Dessimenation Meeting (Infocoding)
Irma Yuliana
Universitas Muhammadiyah Surakarta
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Other

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Uji Usabilitas Media Interaktif Berbasis Augmented Reality untuk Pembelajaran Konsep Pemrograman Sukirman, Sukirman; Yuliana, Irma; Ihsanuddin, Irsyad; Abi, Bayu Setia
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.5717

Abstract

Pemrograman merupakan salah satu keahlian yang sangat dibutuhkan di era teknologi digital saat ini. Akan tetapi, media pembelajaran yang digunakan kebanyakan kurang interaktif dan inovatif. Penelitian ini bertujuan untuk mengembangkan media interaktif berbasis augmented reality (AR) yang dirancang untuk memfasilitasi pembelajaran konsep pemrograman dan menguji usabilitasnya. Pengujian usabilitas dilakukan menggunakan System Usability Scale (SUS) untuk mengukur efektivitas, efisiensi, dan kepuasan pengguna. Media ini menekankan pembelajaran konsep algoritma melalui representasi visual flowchart yang interaktif. Partisipan yang terlibat dalam penelitian ini sebanyak 38 siswa SMK dengan usia 15-16 tahun. Mereka diminta untuk menggunakan media interaktif AR yang sudah dikembangkan untuk belajar konsep pemrograman dan kemudian mengisi kuesioner SUS. Hasil menunjukkan bahwa nilai rata-rata SUS adalah 71.32, yang berada di atas ambang batas 70, menunjukkan tingkat usabilitas yang baik. Dengan demikian, dapat disimpulkan bahwa media interaktif berbasis AR ini dapat digunakan (usable) untuk belajar konsep pemrograman.
Play-Based Unplugged untuk Mendukung Pembelajaran STEAM pada Anak Usia Dini Qonitah Faizatul Fitriyah; Choiriyah Widyasari; Irma Yuliana; Tri Asmawulan
Murhum : Jurnal Pendidikan Anak Usia Dini Vol. 7 No. 1 (2026): Juli
Publisher : Perkumpulan Pengelola Jurnal (PPJ) PAUD Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37985/murhum.v7i1.2075

Abstract

Penelitian ini membahas kebutuhan yang semakin meningkat untuk mengintegrasikan pemikiran komputasional (CT) ke dalam pendidikan anak usia dini dengan cara yang sesuai dengan perkembangan. Penelitian ini bertujuan untuk mengkonseptualisasikan dan menyempurnakan kerangka kerja pedagogis yang mengintegrasikan pembelajaran berbasis bermain dan pemikiran komputasional tanpa perangkat digital untuk mendukung pembelajaran STEAM di usia dini. Pendekatan penelitian berbasis desain kualitatif digunakan melalui siklus iteratif desain, implementasi, observasi, dan penyempurnaan di kelas anak usia dini. Data dikumpulkan melalui observasi kelas yang direkam video, catatan lapangan, jurnal reflektif guru, artefak anak-anak, dan diskusi kelompok fokus. Temuan menunjukkan bahwa konstruksi CT seperti decomposition, pattern recognition, abstraction, algorithmic thinking muncul secara alami dalam skenario bermain terstruktur ketika didukung oleh perancah guru yang disengaja. Analisis interaksi menunjukkan bahwa perkembangan CT dimediasi secara sosial melalui dialog, pemecahan masalah kolaboratif, dan keterlibatan material daripada bergantung pada alat digital. Studi ini menghasilkan kerangka kerja pedagogis yang disempurnakan yang terdiri dari desain bermain terstruktur, perancah strategis, dan mediasi material nyata untuk memperkuat kompetensi STEAM di usia dini.
analisis kebutuhan modal kerja pada cv yola intan mandiri di bontang Yuliana, Irma; Iskandar, Iskandar; Sari, Dhina Mustika
Jurnal Ilmu Akuntansi Mulawarman (JIAM) Vol. 3 No. 4 (2018): November
Publisher : Fakultas Ekonomi dan Bisnis Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29264/jiam.v3i4.3389

Abstract

The research method used in this study is the working capital turnover method. Working capital requirements is determined by comparing income in 2017 (using CV Yola Intan Mandiri’s income estimate) with working capital turnover in 2016.                Results of the study show that in 2017 the working capital that is required is 294.206.150 rupiah while the available working capital is 262.868.304 rupiah. These data indicate that CV Yola Intan Mandiri’s working capital has deficiency amounting to 31.337.846 rupiah. Therefore, the available working capital is not enough to cover the working capital requirements in order to support fluency of CV Yola Intan Mandiri operational activities in 2017. Keywords: Working Capital, Working Capital Need, Working Capital Turnover Method      
DEVELOPMENT OF MULTIMEDIA INTERACTIVE SCIENCE LEARNING BASED ON CROSS PLATFORM ON HUMAN REPRODUCTIVE SYSTEM MATERIALS IN THE NINTH GRADE OF JUNIOR HIGH SCHOOL Guntur Nurcahyanto; Irma Yuliana; Nazzilah Maluha Risalam; Evita Anggraini; Farihatul Faizah Laela
QUANTUM: Jurnal Inovasi Pendidikan Sains Vol 15, No 1 (2024): April 2024
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/quantum.v15i1.15749

Abstract

This study aimed to develop a multimedia interactive science learning product that is cross-platform-based (handphone and Laptop) with Articulate Storyline 3 Software. The research method used was Research and Development (R&D) with a waterfall process model from Pressman. The data analysis applied to this study consists of quantitative and qualitative data. The research results: 1). Media expert testing obtained an average value of 3.56, with a very decent category; 2). Material expert testing obtained an average value of 3.77, with a very decent category; 3) Limited Scale Test, using usability assessment on students and teachers, obtained an average system usability scale (SUS) value of 75.625, with an excellent category, so it can be concluded that interactive science learning multimedia on human reproductive system material developed is acceptable (proper) used in the process of teaching and learning activities in the ninth grade of junior high school.
An Augmented Reality-Based Boardgame for Anti-Corruption Education: Design, Development, and Evaluation Using the MDLC Model Naurah Qolbia Salamah; Irma Yuliana; Eko Prasetyo
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 8 No. 1 (2026): Juni 2026
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v8i1.16983

Abstract

The objective of this study is to develop an Augmented Reality (AR)-based educational board game called SiKilat, which stands for “Ready to Fight Corruption and Nepotism,” to help students better understand anti-corruption principles. The Multimedia Development Life Cycle (MDLC) was employed, consisting of five stages: initialization, blueprint design, asset preparation, product development, and testing and validation. The focus of the study is university students. Interviews, expert reviews, and pre- and post-tests were used as data collection methods. The results indicate that the developed medium is effective and has the potential to enhance student engagement in learning. The Wilcoxon test yielded a significance value of 0.00018 (< 0.05), and the average score increased from 4.9 to 9.3. Consequently, the SiKilat AR board game helps students understand anti-corruption principles and can serve as an alternative interactive learning medium
Acoustic Pattern Classification in Female Voice Using K-Nearest Neighbor with MFCC Feature Extraction Aris Rakhmadi; Joko Handoyo; Irma Yuliana; Dimara Kusuma Hakim
Mestro: Jurnal Teknik Mesin dan Elektro Vol 8 No 01 (2026): Edisi Juni (In Progres)
Publisher : Fakultas Teknik Universitas 17 Agustus 1945 Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47685/mestro.v8i01.794

Abstract

This study investigates the classification of acoustic patterns in female voice signals using the K-Nearest Neighbors (KNN) algorithm and Mel-Frequency Cepstral Coefficients (MFCCs). Acoustic features derived from speech signals contain important spectral information that can be utilized to distinguish variations in voice characteristics. However, variability in speech signals and overlapping feature distributions present challenges for accurate classification. To address this issue, this study employs a structured approach comprising data preparation, MFCC feature extraction, and KNN classification. Each speech sample is represented as a 58-dimensional MFCC feature vector, and the dataset is split into testing and training subsets using a 20:80 ratio. The KNN model is trained using Euclidean distance and evaluated on precision, accuracy, recall, and F1-score. The results show that the proposed approach reaches an accuracy of 87.75%, indicating that MFCC features effectively capture acoustic characteristics in female voice signals. The confusion matrix analysis reveals that categories with distinct acoustic patterns, such as surprise and calm, achieve higher classification performance, whereas overlapping categories, such as happy and disgust, lead to increased misclassification. These findings demonstrate that KNN can serve as a reliable baseline method for acoustic pattern classification. However, further improvements can be achieved through enhanced feature representation and more advanced classification models.
Pengembangan Website Otomotif Tamsky Sebagai Media Informasi Untuk Meningkatkan Preferensi Pelanggan Rahmat Misbiyantoro Purnomo; Irma Yuliana
JURNAL PETISI (Pendidikan Teknologi Informasi) Vol. 7 No. 1 (2026): JURNAL PETISI (Pendidikan Teknologi Informasi)
Publisher : Universitas Pendidikan Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36232/jurnalpetisi.v7i1.4158

Abstract

Penelitian ini bertujuan mengembangkan website Tamsky Automotive sebagai media informasi interaktif untuk meningkatkan preferensi pelanggan terhadap merek Hyundai Solo Baru. Pendekatan penelitian menggunakan metode Research and Development (R&D) dengan model Waterfall yang meliputi tahap analisis kebutuhan, desain, implementasi, pengujian, dan pemeliharaan. Website dikembangkan menggunakan framework Laravel dengan fitur utama katalog kendaraan, simulasi kredit, personalisasi produk, test drive, dan layanan purna jual. Uji kelayakan dilakukan melalui Black-Box Testing serta validasi ahli media dan uji pengguna berdasarkan standar ISO/IEC 25010. Hasil pengujian menunjukkan: (1) fungsionalitas sistem mencapai 100% (Sangat Layak); (2) validasi ahli media memperoleh skor 93,4% (kategori “Sangat Layak”) dengan nilai Aiken’s V sebesar 0,89 (Sangat Tinggi); dan (3) uji pengguna dengan validitas dan reliabilitas terhadap 25 butir pernyataan menunjukkan seluruh indikator “Valid” karena nilai r hitung > r tabel (0,266) atau Sig. (2-tailed) ≤ 0,05. Hasil reliabilitas menunjukkan enam indikator berkategori “Sangat Reliabel” (Cronbach’s Alpha > 0,90) dan satu indikator “Reliabel” (Cronbach’s Alpha > 0,60). Berdasarkan perhitungan skor ISO/IEC 25010, seluruh variabel penilaian berada pada kategori “Sangat Setuju”, yang mengindikasikan kualitas sistem sangat baik dan layak digunakan sebagai media informasi digital untuk meningkatkan keterlibatan dan preferensi pelanggan terhadap Hyundai Solo Baru.
Acoustic Pattern Classification in Female Voice Using K-Nearest Neighbor with MFCC Feature Extraction Aris Rakhmadi; Joko Handoyo; Irma Yuliana; Dimara Kusuma Hakim
Mestro: Jurnal Teknik Mesin dan Elektro Vol. 8 No. 01 (2026): Edisi Juni 2026
Publisher : Fakultas Teknik Universitas 17 Agustus 1945 Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47685/mestro.v8i01.794

Abstract

This study investigates the classification of acoustic patterns in female voice signals using the K-Nearest Neighbors (KNN) algorithm and Mel-Frequency Cepstral Coefficients (MFCCs). Acoustic features derived from speech signals contain important spectral information that can be utilized to distinguish variations in voice characteristics. However, variability in speech signals and overlapping feature distributions present challenges for accurate classification. To address this issue, this study employs a structured approach comprising data preparation, MFCC feature extraction, and KNN classification. Each speech sample is represented as a 58-dimensional MFCC feature vector, and the dataset is split into testing and training subsets using a 20:80 ratio. The KNN model is trained using Euclidean distance and evaluated on precision, accuracy, recall, and F1-score. The results show that the proposed approach reaches an accuracy of 87.75%, indicating that MFCC features effectively capture acoustic characteristics in female voice signals. The confusion matrix analysis reveals that categories with distinct acoustic patterns, such as surprise and calm, achieve higher classification performance, whereas overlapping categories, such as happy and disgust, lead to increased misclassification. These findings demonstrate that KNN can serve as a reliable baseline method for acoustic pattern classification. However, further improvements can be achieved through enhanced feature representation and more advanced classification models.
Speech Emotion Recognition in Male Speech Using 58-Dimensional MFCC Features and Random Forest Classification Aris Rakhmadi; Dewi Soyusiawaty; Irma Yuliana; Dimara Kusuma Hakim
Proceeding of Informatics Collaborations and Dessimenation Meeting Vol. 2 No. 1 (2026)
Publisher : Universitas Muhammadiyah Surakarta

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

Abstract

Speech emotion recognition (SER) has developed into a significant research topic in affective computing and human–computer interaction because emotional cues embedded in speech signals can enhance communication between humans and intelligent systems. However, accurately identifying emotional states from speech remains challenging due to dissimilarities in acoustic patterns, speaker features, and recording situations. This study investigates the effectiveness of Mel-Frequency Cepstral Coefficient (MFCC) acoustic features for emotion recognition in male speech using a Random Forest classification model. The dataset used in this research consists of 35,910 male speech samples, each represented by a 58-dimensional MFCC feature vector extracted from emotional speech recordings. The speech samples are categorized into eight emotional classes: angry, fear, calm, disgust, neutral, happy, sad, and surprise. To develop and evaluate the model’s performance, the MFCC data were divided into 80% for training and 20% for testing. The Random Forest model was trained to learn emotional patterns embedded in MFCC features. The experimental findings reveal that the proposed approach achieved an overall classification accuracy of 84.33% with a macro-average F1-score of 0.856, indicating relatively stable performance across multiple emotional categories. Feature importance analysis further reveals that lower-order MFCC coefficients play a dominant role in emotion classification. These findings demonstrate that MFCC features combined with Random Forest classification provide an effective baseline approach for SER and offer valuable insights for future research involving more advanced machine learning models.
Co-Authors Abi, Bayu Setia Abu Qosim Almisfalah Agatha Saputri Aris Rakhmadi Arya Veda Setyanindito Ayu Khoirotul Umaroh Bachtiar, Andi Bethari Mukti Kusumaningtyas Budi Murtiyasa Choiriyah Widyasari Christina Kartika Sari Dewi Soyusiawaty Dhina Mustika Sari Dimara Kusuma Hakim Dimara Kusuma Hakim Dini Amalia Putri Dwi Jayanti Eko Prasetyo Evita Anggraini Farihatul Faizah Laela Fassha Rahmadina Mauliza Sihar Fitriyana Fitriyana, Fitriyana Gunawan Ariyanto Guntur Nurcahyanto Hanifa, Muhammad Dzaki Hardika Dwi Hermawan Husni Thamrin Ihsanuddin, Irsyad Ika Candra Sayekti Ipin Prasojo, Ipin Iqbal , Muh Irawan, Irman Iskandar Iskandar Isnaeni Umi Machromah Joko Handoyo Kasatri, Dinda Eya Putri Khotimah, Nur Ahlul Lestari, Riska Yulia Ayu Marliza, Widya Naurah Qolbia Salamah Nazzilah Maluha Risalam Nonalisa, Septiarida Noor, Zakky Muhammad Nuqthy Faiziyah Nur Indah Sari Pratama, Kharisma Jayak Qisty Dzakiyyatu Husna Qonitah Faizatul Fitriyah Rahmat Misbiyantoro Purnomo Ramadhan, Dafa Rizki Purna Ramadhan, Fakhri Aulia Wildan Ramadhani, Noti Armyta Retno Palupi Rosyada, Aulia Qisthi Septiani, Jelita Intan Septiarini, Anita Dwi Shandy Yusril Fadlullah Siska Ningtyas Prabasari Siti Azizah Susilawati Sri Rejeki Sujalwo, S Sukirman Sukirman Sukirman Titik Ulfatun Toyib, Muhamad Tri Asmawulan Wawan Joko Pranoto Zalfa Nur Eka Safira