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All Journal TEKNIK INFORMATIKA Seminar Nasional Aplikasi Teknologi Informasi (SNATI) TEKNOLOGI INFORMASI POSITIF SMATIKA Jurnal Ilmiah KOMPUTASI Edu Komputika Journal Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika JIEET (Journal of Information Engineering and Educational Technology) JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) SENTIA 2016 G-Tech : Jurnal Teknologi Terapan Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Polinema Kepada Masyarakat Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Pengabdian Kepada Masyarakat
Ulla Delfana Rosiani
Politeknik Negeri Malang
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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An Experimental Study on Deep Learning Technique Implemented on Low Specification OpenMV Cam H7 Device Asmara, Rosa Andrie; Rosiani, Ulla Delfana; Mentari, Mustika; Syulistyo, Arie Rachmad; Shoumi, Milyun Ni'ma; Astiningrum, Mungki
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2299

Abstract

This research aims to identify and recognize the OpenMV Camera H7. In this research, all tests were carried out using Deep Machine Learning and applied to several functions, including Face Recognition, Facial Expression Recognition, Detection and Calculation of the Number of Objects, and Object Depth Estimation. Face Expression Recognition was used in the Convolutional Neural Network to recognize five facial expressions: angry, happy, neutral, sad, and surprised. This allowed the use of a primary dataset with a 48MP resolution camera. Some scenarios are prepared to meet environment variability in the implementation, such as indoor and outdoor environments, with different lighting and distance. Most pre-trained models in each identification or recognition used mobileNetV2 since this model allows low computation cost and matches with low hardware specifications. The object detection and counting module compared two methods: the conventional Haar Cascade and the Deep Learning MobileNetV2 model. The training and validation process is not recommended to be carried out on OpenMV devices but on computers with high specifications. This research was trained and validated using selected primary and secondary data, with 1500 image data. The computing time required is around 5 minutes for ten epochs. On average, recognition results on OpenMV devices take around 0.3 - 2 seconds for each frame. The accuracy of the recognition results varies depending on the pre-trained model and the dataset used, but overall, the accuracy levels achieved tend to be very high, exceeding 96.6%.
Comparison of Criteria Weight Determination Using MEREC and CRITIC Methods in Choosing The Best Student Accommodation with the MOORA Method Case Study: Coventry University M. Thosin Yuhaililul Hilmi; Ulla Delfana Rosiani; Ely Setyo Astuti
JURNAL TEKNIK INFORMATIKA Vol 17, No 2: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i2.41097

Abstract

One of the challenges faced by IISMA Awardees and students in general in Coventry University is choosing a comfortable place to live. Although various student accommodations are provided, differences in facilities and considerations from other parties such as parents and friends make the selection process complicated. This study develops a decision support system to help students choose student accommodation objectively without any intervention from others and provides a comparison of the use of different combinations of methods as additional guidance in the decision-making process. Two methods, Method Based on the Removal Effects of Criteria (MEREC) and Criteria Importance Through Intercriteria Correlation (CRITIC), are used to weight the criteria. The Multi-Objective Optimization (MOORA) method is used to determine the best alternative after the weight calculation is known. The results using a combination of the MEREC-MOORA method and a combination of the CRITIC-MOORA method place Alternative 5 (A5) in first place, while the remaining alternatives show a similar ranking order. In this study, scenario testing was also carried out by deleting and adding criteria and alternatives which then provided ranking results with a positive correlation even though different combinations of methods were used in determining the ranking.
Pengenalan Ekspresi Mikro Wajah Berdasarkan Point Feature Tracking Menggunakan Fase Apex Pada Database Ekspresi Mikro Choirina, Priska; Rosiani, Ulla Delfana; Fitriani, Indah Martha
Edu Komputika Journal Vol 9 No 1 (2022): Edu Komputika Journal
Publisher : Jurusan Teknik Elektro Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edukomputika.v9i1.56600

Abstract

Ekspresi mikro merupakan ekspresi wajah yang terjadi secara tidak disengaja untuk menyembunyikan perasaan sebenarnya (emotional leakage). Penelitian sebelumnya menggunakan seluruh area wajah dan seluruh frame pada dataset video, hal ini menghasilkan waktu komputasi tergolong lama dan terjadinya redundancy data. Kontribusi utama penelitian ini menerapkan analisa pengenalan ekspresi mikro menggunakan perbandingan frame apex dengan pilihan manual (handcrafted) dan secara acak (random sampling) dan menerapkan pelacakan titik fitur pada area alis mata dan sudut bibir. Discriminative Response Map Fitting (DRMF) sebagai metode yang membentuk titik fitur dan selanjutnya dilakukan pelacakan titik-titik fitur wajah dengan Kanade-Lucas-Tomasi (KLT). Hasil pelacakan titik-titik fitur tersebut menghasilkan data motion features sebagai data ekstraksi fitur dan dilakukan analisa perbandingan metode klasifikasi menggunakan Support Vector Machine (SVM) dan MLP-Backpropagation menggunakan dataset CASME II. Hasil eksperimen penelitian ini menunjukkan hasil yang signifikan dengan akurasi sebesar 81,3% pada MLP-Backpropagation dan waktu komputasi rata-rata 1,45 detik pada setiap video. Hal ini menunjukkan bahwa informasi pada fase apex memberikan informasi yang penting untuk pengenalan ekspresi mikro pada wajah.
Application of Double Exponential Smoothing Method for Forecasting Laptop Sales Nurhayati, Rafika; Yusron, Rizqi Darma Rusdiyan; Sabilla, Wilda Imama; Rosiani, Ulla Delfana
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (2025): 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.v14i1.4368

Abstract

PT Indo Bismar is a retail company focused on laptop sales. The company experiences fluctuations in laptop sales each month, which impacts inventory management as it becomes challenging to predict demand accurately. Consequently, PT Indo Bismar faces financial losses due to unsold laptops. To address this issue, a sales forecasting system has been designed to optimize inventory management more effectively and efficiently.This study applies the double exponential smoothing method to forecast laptop sales and uses the Mean Absolute Percentage Error (MAPE) to measure forecasting accuracy. The double exponential smoothing method was tested through a trial-and-error approach. This process produced varying alpha and beta values for different laptop brands and models. It involved repeated iterations to test each combination until the optimal values that yielded the best forecasting accuracy were identified. After obtaining the MAPE results through the trial-and-error approach, the average system MAPE was calculated to evaluate the overall accuracy of the system, resulting in 16.58%. This indicates that the sales forecasting system demonstrates good accuracy, as the error rate falls within the range of 10% to 20%. Therefore, the use of the double exponential smoothing method can assist PT Indo Bismar in managing inventory and making strategic decisions for future laptop sales
INTEGRATED ROLE MODEL PENGOLAHAN SUSU MENJADI KEJU DENGAN APLIKASI PERHITUNGAN PRODUKSI Irfin, Zakijah; Hidayatinnisa, Nurul; Chrisnandari, Rosita Dwi; Rosiani, Ulla Delfana; Rulianah, Sri
Jurnal Pengabdian kepada Masyarakat Vol. 11 No. 2 (2024): JURNAL PENGABDIAN KEPADA MASYARAKAT 2024
Publisher : P3M Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/abdimas.v11i2.5412

Abstract

The purpose of this community service is to integrate a zero-waste model for processing milk into cheese with a production calculation application at KU Mustarika Jaya Makmur Ngantang. This project aims to address several key issues faced by the cooperative, such as unstandardized milk quality, lack of product diversification, and insufficient economic analysis of dairy products. By implementing supply chain management practices, conducting comprehensive training sessions, and developing a digital application for production calculations, the project seeks to enhance the cooperative's operational efficiency and product quality. The results of the project demonstrate a significant improvement in the cooperative members' knowledge and skills in supply chain management, cheese production techniques, and economic analysis. The integration of a zero-waste model has led to more efficient use of resources and reduced waste, contributing to environmental sustainability. The production calculation application has provided the cooperative with valuable insights into cost management and profitability, facilitating more informed business decisions. Overall, this community service initiative has successfully enhanced the operational, leading to increased productivity, better product quality, and improved economic outcomes for the cooperative members.
Sistem Manajemen Pengungsi Guna Meningkatkan Efektivitas Operasional BPBD Kota Batu Dalam Pendataan Dan Pemantauan Pengungsi Ardiansyah, Muhammad Rizqi; Rosiani, Ulla Delfana; Yunhasnawa, Yoppy
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.7488

Abstract

Batu City is a region known for its natural beauty but also faces high risks of natural disasters such as landslides, earthquakes, and floods. The primary challenge faced by the Regional Disaster Management Agency (BPBD) of Batu City is the manual processing of refugee data. In emergency situations, such as post-disaster scenarios, time is crucial, and manual data collection, processing, and reporting can hinder the rapid response needed to assist refugees. Additionally, data mismatches and inaccuracies in logistics and kitchen needs pose serious problems. Therefore, there is a need for a refugee management information system to enhance the operational effectiveness of BPBD Batu City in data processing, real-time data monitoring, and ensuring the accuracy of logistics and kitchen needs data. This study employs a combination of design thinking and the spiral method for system development. Based on testing the impact of the application on BPBD's response showed an increase in response speed by 87.1%. This proves that the implemented system effectively enhances BPBD Batu's operational efficiency in refugee data collection and monitoring.
Improved Micro-expression Recognition: An Apex Frame-Based Approach Feature Tracking and KLT Choirina, Priska; Fitriani, Indah Martha; Rosiani, Ulla Delfana; Mufti, Muhammad Nabil; Arsistawa, Firmanda Ahmadani; Darajat, Pangestuti Prima
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 2 (2025): JUTIF Volume 6, Number 2, April 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.2.4235

Abstract

This research develops a real-time facial micro-expression recognition system, focusing on analyzing the onset and apex phases of micro-expression on the Spontaneous Activity and Micro-Movements (SAMM) dataset. Micro- expressions are very brief (0.04 - 0.2 seconds) facial muscle movements that often occur when a person is trying to hide emotions. The developed system aims to improve computation time efficiency and micro-expression recognition accuracy by optimizing feature extraction techniques and selecting more specific facial areas, including facial components such as eyebrows, eyes, and mouth. This research successfully improved the computation time efficiency by 51.96%, almost half the time required by the previous method. In addition, this study shows an increase in efficiency compared to previous studies, with an increase of 34.3% for SVM with Manual Sampling technique and 32.6% for MLP-Backpropagation. In the Random Sampling technique, SVM efficiency increased by 6.1%, but MLP-Backpropagation accuracy decreased by 4.8%. This method achieved 77.9% accuracy for MLP- Backpropagation, which is higher than the previous method. This research contributes to accelerating micro- expression recognition systems and improving accuracy, which opens opportunities for real-time emotion analysis applications such as lie detection or human behavior monitoring in a broader context.
Comparison of Criteria Weight Determination Using MEREC and CRITIC Methods in Choosing The Best Student Accommodation with the MOORA Method Case Study: Coventry University Hilmi, M. Thosin Yuhaililul; Rosiani, Ulla Delfana; Astuti, Ely Setyo
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 2: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i2.41097

Abstract

One of the challenges faced by IISMA Awardees and students in general in Coventry University is choosing a comfortable place to live. Although various student accommodations are provided, differences in facilities and considerations from other parties such as parents and friends make the selection process complicated. This study develops a decision support system to help students choose student accommodation objectively without any intervention from others and provides a comparison of the use of different combinations of methods as additional guidance in the decision-making process. Two methods, Method Based on the Removal Effects of Criteria (MEREC) and Criteria Importance Through Intercriteria Correlation (CRITIC), are used to weight the criteria. The Multi-Objective Optimization (MOORA) method is used to determine the best alternative after the weight calculation is known. The results using a combination of the MEREC-MOORA method and a combination of the CRITIC-MOORA method place Alternative 5 (A5) in first place, while the remaining alternatives show a similar ranking order. In this study, scenario testing was also carried out by deleting and adding criteria and alternatives which then provided ranking results with a positive correlation even though different combinations of methods were used in determining the ranking.
Co-Authors Adi Atmoko Agung, Muhammad Helmi Permana Al Hazmi, Moch. Fariz Andjani, Bella Sita Ardiansyah, Muhammad Rizqi Ariadi Retno Ririd Arie Rachmad Syulistyo Arsistawa, Firmanda Ahmadani Aryo Bagus Kusumadewa Tutuko Astiningrum, Mungki Astuti, Ely Setyo Atika Prasetyawati Aulia Zahra Musthafawi Baqi, Rijalul Batubulan, Kadek Suarjuna Bella Sita Andjani Cadea Mikha Pasma Choirina, Priska Choirina, Priska Chrisnandari, Rosita Dwi Dyah Ayu Irawati Eka Larasati Amalia Elisiana, Malia Ely Setyo Astuti Fadlilah, Afi Fadlullah, Faqih Faisal Rahutomo Faqih Fadlullah Fitri Maharany Fitriani, Indah Martha Fitriani, Indah Martha Frangky Tupamahu Gunawan Budi Prasetyo Hidayatinnisa, Nurul Hilmi, M. Thosin Yuhaililul Ibnu Tsalis Assalam Irfin, Zakijah Khosyi Nasywa Imanda Krista Bella Dwi Rahayu Nur Widyasari Luthfansa, Zaky Maula M. Thosin Yuhaililul Hilmi Malia Elisiana Marcelina Alifia Rahmawati Maula, Ahmad Zaky Maulana Syarief Hidayatullah Moch. Fariz Al Hazmi Mufti, Muhammad Nabil Mustika Mentari Nadhifatul Laeily Noprianto Nor Wahid Hidayad Ulloh Nugraha W, Raphael Nur Afifi, Yunis Fiatin Nurhayati, Rafika Nurudin Santoso P., Mauridhy Hery PANGESTUTI PRIMA DARAJAT Pasma, Cadea Mikha Permatasari, Twisty Henras Pramana Yoga Saputra Pramudhita, Agung Nugroho Prasetyawati, Atika Putra Prima Arhandi, Putra Prima Putra, Rahardhiyan Wahyu Qonitatul Hasanah Rahardhiyan Wahyu Putra Rahmad, Cahya Raphael Nugraha W Rawansyah Rosa Andrie Asmara Rosa Andrie Asmara Rudy Ariyanto Rudy Ariyanto Santoso, Nurudin Septiar Enggar Sukmana Shoumi, Milyun Ni’ma Siti Romlah Siti Romlah Sri Rulianah, Sri Surya Sumpeno Twisty Henras Permatasari Vandry Eko Haris Setiyanto Wilda Imama Sabilla Yessy Nindi Pratiwi Pratiwi Yoppy Yunhasnawa Yushintia Pramitarini Yusron, Rizqi Darma Rusdiyan Zaky Maula Luthfansa