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All Journal Infotech Journal Phenomenon : Jurnal Pendidikan MIPA JOIN (Jurnal Online Informatika) Sistemasi: Jurnal Sistem Informasi Faktor Exacta DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Community Empowerment ELECTRA : Electrical Engineering Articles Abditeknika - Jurnal Pengabdian Kepada Masyarakat EPSILON: Journal of Electrical Engineering and Information Technology J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) Jurnal INFOTEL Jurnal Pendidikan Teknologi Informasi (JUKANTI) Telecommunications, Networks, Electronics, and Computer Technologies (TELNECT) Integrated : Journal Of Information Technology and Vocational Education
Endah Setyowati
Universitas Pendidikan Indonesia
Aerospace Engineering Arts Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Physics Public Health Social Sciences Other

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Analisis Sampling Efek Aliasing Pada Audio Menggunakan MATLAB maulidia sita; andi muhammad; muhammad wildan; endah setyowati
Telecommunications, Networks, Electronics, and Computer Technologies (TELNECT) Vol 3, No 2 (2023): Desember 2023
Publisher : Program Studi S1 Sistem Telekomunikasi Universitas Pendidikan Indonesia Kampus Purwakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/telnect.v3i2.59583

Abstract

Lingkungan pemrograman MATLAB menyediakan platform yang nyaman untuk merepresentasikan sinyal audio digital. Mirip dengan sinyal diskrit waktu, sinyal audio digital dapat dinyatakan sebagai vektor yang terdiri dari bilangan real. Di ranah digital, kita hanya mampu memanipulasi pola yang ada di dunia nyata. Sampling merupakan tahap awal dalam mengubah sinyal audio menjadi sinyal digital. Ini melibatkan perekaman sinyal audio secara terpisah dan selanjutnya mengukur sampel. Misalnya, sampel pertama diambil pada awal pengukuran pada waktu 0, diikuti sampel kedua pada 0,001 detik, dan sampel ketiga pada 0,002 detik. Dalam hal ini, interval waktu antar sampel seragam, dan perbedaan antara dua titik waktu berurutan dikenal sebagai periode pengambilan sampel. Intinya, sampling melibatkan pengambilan sampel pada interval waktu yang teratur, yang disebut sebagai frekuensi sampling. Frekuensi pengambilan sampel diukur dalam Hertz, dan dalam contoh ini adalah 1000 sampel per detik. Aspek penting dari pengambilan sampel adalah frekuensi pengambilan sampel harus cukup tinggi, setidaknya dua kali frekuensi maksimum sinyal, untuk menangkap sinyal audio secara akurat dalam waktu diskrit.
Potensi pemanfaatan teknologi 5g guna mendukung pembelajaran daring Endah Setyowati; Galura Muhammad Suranegara; Fauziyah Rhaudhatul Jannah
INTEGRATED (Journal of Information Technology and Vocational Education) Vol 3, No 1 (2021)
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/integrated.v3i1.32702

Abstract

Pandemi Covid-19 sangat berpengaruh terhadap beberapa sektor. Salah satunya adalah sektor pendidikan. Dunia pendidikan mengalami perubahan yang sangat signifikan semenjak pandemi Covid-19 melanda. Proses kegiatan belajar mengajar luring beralih menjadi pembelajaran daring. Maka pendidikan saat ini sangat membutuhkan akses jaringan yang reliabel. Hadirnya teknologi 5G berpotensi untuk menjawab tantangan tersebut. Teknologi 5G menjanjikan kecepatan yang mencapai 1 Gbps, latency sub-milisekon dan jangkauan sinyal yang lebih baik. Selain itu, teknologi 5G juga mendukung Augmented Reality atau Virtual Reality yang dapat mendukung kegiatan pembelajaran berbasis teknologi dalam rangka digitalisasi dunia pendidikan. Untuk mencapai hal tersebut, dibutuhkan bandwidth yang lebih lebar, round trip time yang lebih kecil dan penggunaan antenna Massive-MIMO. Paper ini bertujuan untuk mengetahui potensi pemanfaatan Teknologi 5G dan teknologi pembangunnya guna mendukung pembelajaran daring yang reliabel. Sehingga pembelajaran daring dapat dilakukan dimanapun, tanpa hambatan dan gangguan internet.
Rain Effect to A 60 GHz Broadband Wireless System’s Performance: Study Case In Purwakarta Endah Setyowati; Galura Muhammad Suranegara; Ichwan Nul Ichsan
JURNAL INFOTEL Vol 13 No 1 (2021): February 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i1.556

Abstract

Nowadays, world wide telecommunication researchers are developing 5G technology. One of most important key technology in 5G is Milimeter-Wave (mmWave). This study measure 60 GHz broadband wireless system performance because of it’s promising potentials. However, the use of these frequencies is quite sensitive to rain that resulting an atenuation in the channel. Therefore, this study proposes two schemes to address the problem. The first scheme is the use of QAM modulation (Quadrature Amplitude Modulation) and the second scheme is an addition of LDPC (Low Density Parity Check) code techniques. From the results of this study, by using 4-QAM modulation and LDPC coderate 1/2, the broadband wireless system’s performance on the second scheme is better compared to the first scheme with 8.33 dB Signal to Noise Ratio (SNR) value to provides BER (Bit Error Rate) 10-4
Sentiment Analysis of the MyTelkomsel App based on Support Vector Machines: A Kernel Performance Comparison Fitri Novianti Hidayah; Endah Setyowati
Sistemasi: Jurnal Sistem Informasi Vol 15, No 5 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i5.6289

Abstract

MyTelkomsel is a customer service application developed by one of the largest cellular operators, with more than 100 million users. Due to the high volume of application users, sentiment analysis is essential for examining user opinions to optimize service quality. However, sentiment classification often faces challenges caused by imbalanced sentiment class distributions, which can affect model performance. This study analyzes sentiment toward the MyTelkomsel application using the Support Vector Machine (SVM) algorithm, focusing on evaluating the performance of Linear, RBF, and Polynomial kernels. The dataset consisted of 1,000 user reviews randomly collected from the Google Play Store, with positive and negative labels assigned based on the Indonesia Sentiment Lexicon (InSet). The dataset was divided into training and testing sets using an 80:20 ratio. The model development process was carried out using RapidMiner. The optimal performance was achieved by the Linear kernel through the implementation of the Synthetic Minority Over-sampling Technique (SMOTE) and K-Fold Cross Validation, resulting in an accuracy of 100%, precision of 100%, recall of 100%, and F1-score of 100%. These results indicate that the data can be effectively separated using a linear boundary. SMOTE was applied to address class imbalance in the dataset, while K-Fold Cross Validation (k = 10) was used to ensure the absence of overfitting by testing the entire dataset divided into 10 folds. The findings of this study can serve as a foundation for optimizing application services, enabling improvement strategies to be implemented in accordance with feedback derived from user reviews.
Performance Evaluation of OTFS over EVA, ETU, and UAV Channels with Delay Doppler Grid Variations for High-Mobility Communications Muhammad Idrus Syaban; Endah Setyowati
SISTEMASI Vol 15, No 6 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Universitas Islam Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i6.6307

Abstract

Orthogonal Time Frequency Space (OTFS) is a modulation scheme designed to improve the reliability of wireless communications in high-mobility environments, where transmission performance is significantly affected by Doppler effects. This study evaluates the performance of OTFS over three high-mobility channel models: Extended Vehicular A (EVA), Unmanned Aerial Vehicle (UAV), and Extended Typical Urban (ETU), with a particular focus on the impact of Delay-Doppler grid size on the bit error rate (BER). Simulations were conducted using Quadrature Phase Shift Keying (QPSK) modulation with a carrier frequency of 5.9 GHz, user mobility of up to 350 km/h, and a signal-to-noise ratio (SNR) ranging from 0 to 20 dB. The results show that increasing the Delay-Doppler grid size from 16 × 16 to 32 × 32 reduced the BER from the order of 10⁻³ to 10⁻⁴ across all channel models. However, further increasing the grid size beyond 32 × 32 resulted in only marginal performance improvements, indicating a saturation effect. These findings demonstrate that a 16 × 16 Delay-Doppler grid is sufficient to achieve reliable performance in high-mobility communication environments. Nevertheless, increasing the grid size to 32 × 32 provides superior performance by further reducing the BER, thereby offering an optimal balance between transmission reliability and computational complexity.
Performance Limit of Handcrafted Features in Cassavia LSB Steganalysis Mukhamad Salman Nurdin; Endah Setyowati; Galura Muhammad Suranegara
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 2 (2026): August
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i2.3983

Abstract

Handcrafted feature based steganalysis remains widely used in resource constrained environments despite rapid progress in deep learning detectors. This study investigates the performance limit of compact handcrafted features for binary classification of cover and stego images in Least Significant Bit (LSB) steganalysis on the Cassavia dataset. Five representative models deep neural network (DNN), one dimensional convolutional neural network (1D CNN), random forest, Light Gradient Boosting Machine (LightGBM), and SMOTE enhanced DNN are trained on 44,000 images using 16 descriptors that combine statistical LSB measures with a reduced subset of Spatial Rich Model (SRM) residual features. All models converge to a narrow accuracy band of 72.58-75.50% with Area Under Curve (AUC) values close to 0.50 and pronounced overfitting in the training–validation curves, indicating that the dominant bottleneck arises from limited feature expressivity rather than model capacity or implementation errors. Feature importance analysis further reveals that only a small subset of descriptors contributes substantially, exposing strong redundancy in the handcrafted feature set. Within this CPU friendly LSB based setting, these results establish a practical performance ceiling that is shared across both classical and deep models, while highlighting LightGBM as an attractive option for embedded steganalysis and motivating future hybrid designs that combine handcrafted statistical priors with learned deep representations.
Optimasi Lingkungan Tenang dengan Sistem Monitoring Kebisingan Menggunakan Logika Fuzzy Diar Dwi Sutia; Endah Setyowati; Dewi Indriati Hadi Putri
Faktor Exacta Vol 18, No 1 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i1.24869

Abstract

Analisis Efek Aliasing Pada Sinyal Audio Dengan Variasi Frekuensi Sampling Pada Lagu ‘Terhebat’ Hasyyati Shabrina; Endah Setyowati; Inda Ahmayani; Khalifah Audya Eka Putri
ELECTRA : Electrical Engineering Articles Vol. 5 No. 1 (2024)
Publisher : UNIVERSITAS PGRI MADIUN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25273/electra.v5i1.21265

Abstract

Aliasing merupakan fenomena yang terjadi dalam pengolahan sinyal digital, termasuk sinyal audio, ketika frekuensi sampling yang digunakan tidak mencukupi untuk merepresentasikan frekuensi tertinggi dalam sinyal tersebut. Penelitian ini bertujuan untuk menganalisis efek aliasing pada sinyal audio dengan melakukan variasi frekuensi sampling pada lagu "Terhebat". Eksperimen dilakukan dengan menggunakan software MATLAB untuk memvisualisasikan dan menganalisis sinyal audio pada frekuensi sampling 11025 Hz, 22050 Hz, 44100 Hz, 88200 Hz, dan 32000 Hz. Hasil penelitian menunjukkan bahwa frekuensi sampling yang terlalu rendah, seperti 11025 Hz dan 22050 Hz, menyebabkan aliasing yang signifikan, ditandai dengan distorsi dan hilangnya detail frekuensi tinggi pada sinyal audio. Sebaliknya, frekuensi sampling yang terlalu tinggi, seperti 88200 Hz, tidak memberikan manfaat yang signifikan dalam meningkatkan kualitas audio. Frekuensi sampling 44100 Hz, yang umum digunakan dalam CD audio, menghasilkan kualitas audio yang baik dengan efek aliasing yang minimal. Penelitian ini menyimpulkan bahwa pemilihan frekuensi sampling yang tepat sangat penting untuk menghindari efek aliasing dan mempertahankan kualitas sinyal audio yang baik.
Penerapan Scratch dalam Pembelajaran Berbasis Proyek untuk Mengembangkan Computational Thinking Siswa Sekolah Dasar Farhan Taqi Ghani; Talitha Naila Citra; Alfin Syawalan; Arvina Putri Rachman; Fauzan Maulana Wijaya; Grace Septiana Magdalena Siagian; Karin Nisrina Andriyani; Raka Yudistira; Reyna Bethania Berutu; Silvy Zuhruffiatun Nissa; Zahra Zakiyatus Shalihah; Endah Setyowati
Abditeknika Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2026): April 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/abditeknika.v6i1.11202

Abstract

Pemahaman siswa sekolah dasar terhadap teknologi digital dan computational thinking (CT) masih rendah, salah satunya disebabkan oleh keterbatasan integrasi keterampilan digital dalam kurikulum serta kompetensi guru yang belum optimal. Untuk mengatasi permasalahan tersebut, penelitian ini menerapkan pendekatan Project-Based Learning (PBL) dengan integrasi CT melalui platform Scratch sebagai metode pembelajaran yang kontekstual dan interaktif. Pendekatan ini bertujuan meningkatkan pemahaman konsep CT dan literasi digital siswa secara aplikatif melalui pengembangan proyek berbasis pemrograman visual pada siswa kelas 5 SDIT Cendekia Purwakarta. Temuan penelitian menunjukkan peningkatan skor post-test sebesar 10% dibanding pre-test, dengan rata-rata skor naik dari 7 menjadi 8 dari 10 soal, serta peningkatan paling signifikan pada siswa dengan kemampuan awal rendah. Temuan juga mengindikasikan motivasi belajar meningkat dan tanggapan guru sangat positif terhadap implementasi modul CT, yang mendukung keberlanjutan metode pembelajaran ini. Penelitian ini menegaskan bahwa model PBL berbasis Scratch merupakan strategi yang efektif untuk membangun ekosistem pembelajaran digital di sekolah dasar.
Developing 21st-Century Skills Through Robotics-Enhanced STEM Learning: Effects on Prospective Elementary Teachers’ Computational Thinking Fitri Nuraeni; Nenden Permas Hikmatunisa; Endah Setyowati; Hafiziani Eka Putri; Afridha Laily Alindra
Phenomenon : Jurnal Pendidikan MIPA Vol. 15 No. 1 (2025): Phenomenon: Jurnal Pendidikan MIPA
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/phen.2025.15.1.28201

Abstract

Currently the integration of Computational Thinking (CT) has been promoted into learning since elementary school due to technology advancement. However, prospective elementary school teachers in Indonesia lack sufficient experience in implementing CT into practice, leading to unpreparedness in teaching these skills to students in the future. STEM Education course provide a strategic platform to equip prospective elementary school teachers with hands-on experience in developing CT. Robotics integration enable combination of science, technology, engineering, and mathematics in one unit, and also provides project-based problem-solving experiences that can enhance CT. Through a quasi-experimental design, this study explore the effectiveness of robotics integration in STEM Education course in improving prospective elementary school teachers' CT. A total of 95 prospective elementary teachers comprised the study sample, which was selected purposively. The Computational Thinking Scale, with twenty-two items, was tested and found to be valid and reliable. Mixed ANOVA analysis indicates that STEM-based robotics course had a significant effect on improving elements of CT that includes problem-solving and critical thinking indicators. Meanwhile, the treatment effects on creativity, algorithmic thinking, and cooperativeness were minimal, indicating that these three indicators did not significantly influenced by the intervention
Co-Authors AA Sudharmawan, AA Afridha Laily Alindra Alfin Syawalan andi muhammad Anggie Wijaya Arvina Putri Rachman Carissa Elfrida Cronica Better Marito Manurung Dhiya Lutfia Mahendro Diar Dwi Sutia Dwi Wahyu Riani Farhan Taqi Ghani Fauzan Maulana Wijaya Fauziyah Rhaudhatul Jannah Fitri Novianti Hidayah Fitri Nuraeni Galuh Inti Aulia Galura Muhammad Suranegara Grace Septiana Magdalena Siagian Hadi Putri, Dewi Indriati Hafiziani Eka Putri, Hafiziani Eka Hasyyati Shabrina Ichwan Nul Ichsan Inda Ahmayani Karin Nisrina Andriyani Khalifah Audya Eka Putri Khoirul Anwar maulidia sita Muhamad Dzikri Danuarteu Muhammad Gani Baihaqi Darussalam Muhammad Hilmi Assidiqi Muhammad Idrus Syaban muhammad wildan Mukhamad Salman Nurdin Nenden Permas Hikmatunisa Nissa Restyasari Pratama, Hafiyyan Putra Raka Yudistira Reyna Bethania Berutu Reza Nurfaudzan Ashsiddiq Salwa Tasya Fathira Purba Silvy Zuhruffiatun Nissa Syifaul Fuada Talitha Naila Citra Yasya Dwinida Zahra Zakiyatus Shalihah