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All Journal Jurnal Informatika Journal of Information Systems and Informatics Jurnal E-Komtek Blend Sains Jurnal Teknik Jurnal Pengabdian Teknik dan Sains (JPTS)
elindra ambar pambudi
Universitas Muhammadiyah Purwokerto
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Analysis Thresholding Sauvola pada Background Subtraction untuk Deteksi Objek Bergerak elindra ambar pambudi; Abid Yanuar Badarudin; Dimara Kusuma Hakim
Jurnal Informatika Vol 6, No 2 (2019): September 2019
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (674.054 KB) | DOI: 10.31294/ji.v6i2.6164

Abstract

Metode segmentasi kebanyakan digunakan dalam teknik pengolahan citra yang berkaitan dengan deteksi objek bergerak. Segmentasi pada objek bergerak sangat penting untuk menentukan proses selanjutnya berupa pengenalan atau klasifikasi. Metode yang paling umum digunakan dalam teknik-teknik segmentasi adalah metode pengambangan. Metode pengambangan dibagi menjadi dua yaitu global dan lokal. Pada penelitian kali ini akan mencoba menggunakan salah satu metode pengambangan lokal adaptif yaitu sauvola. Sauvola akan digunakan sebagai nilai ambang dari background subtraction. Garis besar dari metode yang diusulkan dalam penelitian ini adalah ekstraksi frame, inisialisasi background, preprocessing, background subtraction, sauvola, pemberian masking. Hasil terbaik rata-rata MSE dan PSNR adalah 0.0011 dan 53,6653. Pengambangan dengan sauvola mendapat hasil cukup baik dan layak sebagai nilai ambang dari background subtraction.
Forecasting Brown Sugar Production Using k-NN Minkowski Distance and Z-Score Normalization Elindra Ambar Pambudi; Akhitya Ghany Fahrezi; Abid Yanuar Badharudin
Journal of Information System and Informatics Vol 5 No 2 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i2.485

Abstract

The demand for brown sugar products often falls below the level of production, resulting in unsold goods when market demand surpasses the production capacity. This paper addresses the challenge faced by many brown sugar businesses in estimating production yields. Another issue, apart from production uncertainty, is the presence of a dataset with a significant nominal range. The study focuses on a specific brown sugar producing company in Indonesia. To address the production estimation problem, this research proposes the use of k-NN supervised learning as a forecasting method. However, instead of relying solely on k-NN, the study suggests employing z-score normalization to handle the dataset's large nominal range. The production data used for analysis spans from March 2019 to February 2022, comprising 144 weekly records. The dataset is divided into training and testing data, employing an 8:2 split validation ratio. The proposed method consists of several steps, including data normalization using z-score, processing k-NN based on the Minkowski distance, and concluding with the de-normalization process. The results demonstrate the successful implementation of the proposed method in predicting production levels. The evaluation indicates an average error margin of 3.34%, which is below the 5% threshold. The evaluation of predictive data for k-NN with z-score normalization proves effective in forecasting brown sugar production uncertainty and addressing the challenge of a large nominal range.
Pelatihan Penggunaan Mendeley pada Guru SLB Kuncup Mas Elindra Ambar Pambudi; Ermadi Satriya Wijaya
Jurnal Pengabdian Teknik dan Sains (JPTS) Vol 2, No 1 (2022): Januari 2022
Publisher : Lembaga Publikasi Ilmiah dan Penerbitan (LPIP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/jpts.v2i01.13281

Abstract

Berdasarkan tuntutan sertifikasi guru sesuai permendiknas No 18 th 2007 tersebut setiap guru mau tidak mau dihadapkan pada keharusan untuk mampu mengeluarkan karya tulis ilmiah seperti buku teks, modul, artikel, dan lain-lain yang berguna bagi pengembangan ilmu pengetahuan dan juga proses pendidikan. Permasalahan yang dihadapi para guru adalah pemahaman yang masih minim terkait referensi dalam pembuatan karya ilmiah, ditambah lagi keterbasan waktu yang dimiliki dan kurangya kreatifitas para guru di SLB Kuncup Mas dalam mengumpulkan referensi karya ilmiah. Dengan kesulitan yang dihadapi maka dalam pengabdian ini akan mencoba untuk memecahkan masalah dengan mengadakan pelatihan mengenai referensi manager. Metode yang diterapkan dari mulai survey lapangan, ceramah dan demo, dilanjutkan diskusi tanya jawab dan diakhiri praktik mandiri Bersama-sama. Hasil yang didapatkan dari pengabdian ini adalah terdapat sekitar 90 % keberhasilan dibuktikan dengan rata-rata peserta mendapatkan nilai rentang baik sampai dengan sangat baik dan 10% mendapatkan hasil kurang baik.
Performance Analysis of a Low-Pass Filter for Virtual Camera Rotation Stabilization Using a Gyroscope Sensor Dila Dahlia; Tito Pinandita; Sigit Sugiyanto; Elindra Ambar Pambudi
Jurnal E-Komtek Vol 10 No 1 (2026)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v10i1.3001

Abstract

The use of mobile device cameras often suffers from rotational instability caused by jitter and sudden orientation changes, reducing visual quality and user experience in virtual camera applications. This study evaluates the effectiveness of a low-pass filter in stabilizing gyroscope-based virtual camera rotation. Experiments were conducted using an iPhone 12 under six movement scenarios: slow rotation, fast rotation, random movement, walking, stair climbing, and motorcycle riding. Euler angle and inter-frame jitter data were analyzed before and after filter implementation. The results show that the low-pass filter significantly reduces rotational jitter in five of the six scenarios. The greatest improvement was observed during walking, with an 86.55% reduction, followed by fast rotation (72.21%) and random movement (68.87%). These findings confirm that the low-pass filter effectively suppresses high-frequency rotational disturbances, enhancing virtual camera stability and providing a practical foundation for developing more reliable gyroscope-based rotation stabilization systems on mobile devices.
Chili Price Prediction Model in Banyumas and Cilacap Regencies Using Comparative Machine Learning Algorithm Fima Rizqina Mubaroka; Maulida Ayu Fitriani; Elindra Ambar Pambudi; Dimara Kusuma Hakim
Jurnal E-Komtek Vol 10 No 1 (2026)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v10i1.3003

Abstract

Fluctuations in chili prices as a strategic commodity often pose challenges to food price stability, particularly in Central Java regions such as Banyumas and Cilacap Regencies. This study aims to explore and compare the performance of three classical machine learning algorithms: Ridge Regression, Lasso Regression, and Random Forest Regressor. This study utilizes daily historical data spanning from January 2018 to June 2025 to identify market patterns and trends. Furthermore, this research projects chili prices for the next 365 days. Consistently, Lasso Regression demonstrated the best performance in both regions. The model achieved the highest accuracy in Banyumas Regency Banyumas (MAPE 2,75%) and Cilacap Regency (MAPE 5,08%). However, visual analysis of long-term predictions revealed that Ridge Regression produced a more realistic graph compared to Lasso Regression. Conversely, Random Forest Regressor failed to capture long-term trends as it yielded stable predictions. The prediction results were subsequently visualized in an interactive dashboard based on the Flask framework.
Implementasi Gamma Correction untuk Peningkatan Kualitas Citra Low-Light Real-Time pada Kamera Mobile Teguh Ahmad Prayogo; Tito Pinandita; Elindra Ambar Pambudi; Maulida Ayu Fitriani
Blend Sains Jurnal Teknik Vol. 5 No. 1 (2026): Edisi Juli
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/blendsains.v5i1.1820

Abstract

Kualitas citra pada kamera mobile sering mengalami penurunan pada kondisi pencahayaan rendah (low-light) sehingga citra terlihat gelap dan detail objek menjadi kurang jelas. Penelitian ini bertujuan untuk meningkatkan kualitas citra menggunakan metode Gamma Correction yang dikombinasikan dengan penyesuaian brightness, contrast, dan saturation. Sistem diimplementasikan menggunakan Unity dengan memanfaatkan WebCamTexture untuk memproses citra secara real-time. Pengujian dilakukan pada tiga kondisi pencahayaan, yaitu 5 lux, 10, dan 20 lux. Evaluasi dilakukan dengan membandingkan nilai brightness sebelum dan sesudah proses enhancement menggunakan perhitungan luminansi. Hasil pengujian menunjukkan bahwa nilai brightness mengalami peningkatan pada seluruh kondisi pencahayaan. Pada intensitas cahaya 5 lux, nilai brightness meningkat dari 0,031 menjadi 0,044, Pada intensitas cahaya 10 lux dari 0,102 menjadi 0,276, dan pada intensitas cahaya 20 lux dari 0,385 menjadi 0,580. Hasil tersebut menunjukkan bahwa metode yang diusulkan mampu meningkatkan kualitas citra, terutama pada kondisi low-light. Sistem juga mampu berjalan secara real-time dengan penerapan teknik frame skipping sehingga performa aplikasi tetap stabil tanpa lag yang signifikan.
Co-Authors Abid Yanuar Badarudin Abid Yanuar Badharudin Akhitya Ghany Fahrezi Dila Dahlia Dimara Kusuma Hakim Ermadi Satriya Wijaya Fima Rizqina Mubaroka Maulida Ayu Fitriani Sigit Sugiyanto Teguh Ahmad Prayogo Tito Pinandita