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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) ComEngApp : Computer Engineering and Applications Journal Computer Engineering and Applications Journal (ComEngApp) Jupiter Jurnal Sistem Komputer Jurnal Algoritma ICON-CSE Annual Research Seminar JURNAL NASIONAL TEKNIK ELEKTRO Proceeding of the Electrical Engineering Computer Science and Informatics Computer Engineering and Applications Journal (ComEngApp) JPSriwijaya Science and Technology Indonesia Jusikom : Jurnal Sistem Komputer Musirawas Dinamisia: Jurnal Pengabdian Kepada Masyarakat KOMPUTIKA - Jurnal Sistem Komputer JTT (Jurnal Teknologi Terapan) Jurnal Generic Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Algoritma Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS ABDIKOM The Indonesian Journal of Computer Science
Rossi Passarella
Jurusan Sistem Komputer Faklultas Ilmu Komputer Universitas Sriwijaya
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Neuroscience Physics Public Health Social Sciences Other

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Implementasi User Centered Design dan Software Requirements Specification pada Perancangan Website Kurniawan, Dedy; Passarella, Rossi; Fardinelly, Syahria; Anggraini, Febrina Hedy; Mattjik, Hani Alifia; Rahmayuni, Septa
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1608

Abstract

Significant changes in learning approaches, methods and tools in the digitalization era have given rise to the need for Student E-Worksheets (E-LKPD) which can advance students' critical and creative thinking abilities. This research designs E-LKPD based on government regulations using the User Centered Design (UCD), Software Requirements Specification (SRS) and System Usability Scale (SUS) methods. Through the UCD design stages, E-LKPD succeeded in creating a user-friendly website that complies with the learning rules for students in secondary schools. This research aims to produce digital-based teaching materials in the form of E-LKPD by implementing User Centered Design (UCD) and Software Requirements Specification (SRS). The results were proven through Usability Testing using the System Usability Scale (SUS) approach, obtaining a score of 80.667 with the grade A category, Excellent in Adjective, Acceptable, and the Promoter category in the Net Promoter Score (NPS) which shows that E-LKPD has been successfully designed with good usability and suitable for use according to user needs.
Improving the performance for automated brain tumor classification on magnetic resonance imaging deep learningbased Fachrurrozi, Muhammad; Darmawahyuni, Annisa; Samsuryadi, Samsuryadi; Passarella, Rossi; Archibald Hutahaean, Jerrel Adriel
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1679-1686

Abstract

Brain tumor is an uncontrolled growth of abnormal cell in the brain. Early diagnosis of brain tumor has a crucial step in this type of cancer, which is fatal. Magnetic resonance imaging (MRI) is one of the examination tools to examine brain anatomy in clinical practice. The high resolution and clear separation of the tissue enable medical experts to identify brain tumor. The earlier of brain tumor is detected, the wider of treatment options. However, manually analysed of brain anatomy on MRI images are time-consuming. Computer-aided diagnosis with automated way is helpful solution to help management with unreliable degrees of automation to trace various tissue boundaries. This study proposes convolutional neural network (CNN) with its excellences to automated features extraction in convolution layer. The popular architectures of CNN, i.e., visual geometry group16 (VGG16), residual network-50 (resNet-50), inceptionV3, mobileNet, and efficientNetB7 in medical image processing are compared to brain tumor classification task. As the results, VGG16 outperformed other architectures of CNN in this study. VGG16 yields 100% accuracy, precision, sensitivity, specificity, and F1-score for testing set data. The results show the excellent performance in classifying brain tumor and no tumor from MRI images that demonstrate the efficiency of system suggested.
Implementasi User Centered Design dan Software Requirements Specification pada Perancangan Website Kurniawan, Dedy; Passarella, Rossi; Fardinelly, Syahria; Anggraini, Febrina Hedy; Mattjik, Hani Alifia; Rahmayuni, Septa
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1608

Abstract

Significant changes in learning approaches, methods and tools in the digitalization era have given rise to the need for Student E-Worksheets (E-LKPD) which can advance students' critical and creative thinking abilities. This research designs E-LKPD based on government regulations using the User Centered Design (UCD), Software Requirements Specification (SRS) and System Usability Scale (SUS) methods. Through the UCD design stages, E-LKPD succeeded in creating a user-friendly website that complies with the learning rules for students in secondary schools. This research aims to produce digital-based teaching materials in the form of E-LKPD by implementing User Centered Design (UCD) and Software Requirements Specification (SRS). The results were proven through Usability Testing using the System Usability Scale (SUS) approach, obtaining a score of 80.667 with the grade A category, Excellent in Adjective, Acceptable, and the Promoter category in the Net Promoter Score (NPS) which shows that E-LKPD has been successfully designed with good usability and suitable for use according to user needs.
PENINGKATAN KEMAMPUAN SISWA SMKN 1 TANJUNG PANDAN BELITUNG DALAM SIMULASI ONLINE SISTEM PALANG PINTU KERETA API Fali Oklilas, Ahmad; Abdurahman; Rossi Passarella; Sukemi; Muhammad Ali Buchari
Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Vol. 1 No. 5 (2023): Oktober
Publisher : CV. Alina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jpki2.v1i5.136

Abstract

Sekolah Menengah Kejuruan atau SMK sangat membutuhkan praktik lebih banyak dibandingkan teori. Untuk praktikum diperlukan sarana dan prasarana yang menunjang, namun tidak semua sarana dapat terpenuhi mengingat keterbatasan dana yang disediakan pihak sekolah dan pemerintah daerah. Permasalahan inilah perlu diatasi agar siswa SMK dapat mengikuti perkembangan zaman dan teknologi terakhir. Untuk memecahkan masalah ini dapat dengan cara menggunakan simulasi online sebagai pengganti peralatan praktikum. Dosen Jususan Sistem Komputer Fakultas Ilmu Komputer dalam rangka pengabdian masyarakat memecahkan masalah di sekolah SMK Negeri 1 Tajung Pandan Belitung dengan cara memberi pelatihan kepada siswa disana berupa pemanfaatan simulasi online sistem palang pintu otomatis untuk studi kasus pintu kereta api. Metode pengajaran yang digunakan full praktik menggunakan komputer karena dilaksankan secara luring di laboratorium sekolah yang bersangkutan. Hasil yang didapat pemahaman siswa dapat menyelesaikan studi kasus dari simulasi yang ditugaskan serta banyak mendapat sambutan yang antusian dari siswa. Pelatihan ini sangat membawa manfaat dan pengetahuan baru karena keterbatasan sarana dan prasarana yang ada di sekolah dapat diatasi dengan pemanfaat praktikum menggunakan simulasi online.
Lightweight Solar Vehicle Impact Analysis Using ABAQUS/EXPLICIT Passarella, Rossi; Taha, Zahari
Computer Engineering and Applications Journal (ComEngApp) Vol. 1 No. 2 (2012)
Publisher : Universitas Sriwijaya

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

Abstract

This paper described the Abaqus/Explicit 6.7 simulation work performed to study the frontal crash impact condition for an in-house designed and produced lightweight solar vehicle main structural body. The structural body was fabricated from aluminum hollow pipes welded together. The analysis is needed to safeguard the safety of the vehicle driver. The dynamic response of the vehicle structure when subjected to frontal impact condition was simulated, according to NASA best practice for crash test methodology. The simulated speed used was based on the NHTSA standard. Comparison of the analysis with the standard Head Injury Criteria (HIC) and Chest Injury Criteria (CIC) revealed that the driver of the designed vehicle would not be risk because the acceleration resultant was found to be lower than 20 G.  The analysis also proved that structural component was able to protect the driver during any frontal collision incident. However, to ensure the safety of the driver, safety precautions such as the use of seatbelt and helmet as well as driving below the speed limit are recommended.DOI: 10.18495/comengapp.12.085096
Littering Activities Monitoring using Image Processing Husni, Nyayu Latifah; Handayani, Ade Silvia; Passarella, Rossi; Abdurrahman; Rahman, A.; Felia, Okta
Computer Engineering and Applications Journal (ComEngApp) Vol. 12 No. 3 (2023)
Publisher : Universitas Sriwijaya

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

Abstract

Littering is a human behavior that become a habit since childhood. Even though there are rules that prohibit this behavior, the community still continues to do so. In order to limit this bad behavior, a device that can monitor and provide notifications is needed. In this research, proposed device can identify human activities by utilizing webcam-based image processing. It is processed by machine learning using the Recurrent Neural Network (RNN). The monitoring device produced in this research works by comparing the captured image data with dataset. The captured image data are extracted into figures and form several coordinate points on the human body. Then, the system classifies the human activities into two categories, i.e., normal or littering. This device will provide an output in the form of a ewarning every time the activity of littering is detected.
Design Concept of Convexity Defect Method on Hand Gestures as Password Door Lock Passarella, Rossi; Fadli, Muhammad; Sutarno
Computer Engineering and Applications Journal (ComEngApp) Vol. 2 No. 3 (2013)
Publisher : Universitas Sriwijaya

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Abstract

In this paper we purpose a several steps to implement security for locking door by using hand gestures as password. The methods considered as preprocessing image, skin detection and Convexity Defection. The main components of the system are Camera, Personal Computer (PC), Microcontroller and Motor (Lock). Bluetooth communication are applied to communicate between PC and microcontroller to open and lock door used commands character such as “O” and “C”. The results of this system show that the hand gestures can be measured, identified and quantified consistently.
Analisis Hubungan Antara Jumlah Bus dan Jumlah Penumpang Menggunakan Unsupervised Learning: Analysis of Passenger and Bus Numbers Using Unsupervised Learning Sinaga, Aurell Octaviona; Passarella, Rossi
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 5 No. 3 (2025): MALCOM July 2025
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v5i3.2005

Abstract

Hubungan antara jumlah bus dan jumlah penumpang merupakan aspek penting dalam analisis transportasi perkotaan. Namun, pola distribusi dan kelompok data yang terbentuk sering kali tidak merata, sehingga menyebabkan ketidakseimbangan dalam hubungan tersebut. Penelitian ini bertujuan untuk mengidentifikasi pola distribusi dan mengelompokkan data jumlah bus dan penumpang menggunakan pendekatan unsupervised learning. Metode yang diuji coba terdiri dari empat model yaitu K-Means, Fuzzy C-Means (FCM), Gaussian Mixture Model (GMM), dan Spectral Clustering. Keempat model tersebut dibandingkan untuk mengukur seberapa baik model dapat mengelompokkan data dan mengungkap hubungan antara jumlah bus dan jumlah penumpang. Keempat model akan dievaluasi menggunakan Calinski-Harabasz Index, Silhouette Score, dan Davies-Bouldin Index untuk menemukan klaster optimal. Berdasarkan uji coba keempat model clustering menggunakan ketiga matriks evaluasi, semua model menunjukkan klaster optimalnya adalah 2 namun  model K-Means memberikan kinerja terbaik dalam mengelompokkan data karena model K-Means memiliki nilai terbaik untuk setiap metrik evaluasi tersebut. Skor model K-Means pada Silhouette Score sebesar 0.5175, nilai model K-Means pada Davies-Bouldin Index sebesar 0.7241, dan skor untuk K-Means terhadap Calinski-Harabasz Index sebesar 1414.3874. Klaster 1 merepresentasikan jumlah bus dan jumlah penumpang yang tinggi sedangkan Klaster 2 merepresentasikan jumlah penumpang dan jumlah bus yang rendah. 
ANALISIS MODEL PREDIKSI UNTUK LAYANAN BUS SEKOLAH JAKARTA MENGGUNAKAN PENDEKATAN MACHINE LEARNING Wahyuni, Sri; Passarella, Rossi
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.4074

Abstract

This research aims to predict the types of school buses in Jakarta using machine learning methods. Data from 2017 to 2019 includes the number of passengers, number of schools, and bus types. Exploratory data analysis identified patterns and trends, with feature engineering generating three main variables. Seven machine learning models were tested, including SVM, Logistic Regression, KNN, Gaussian Naive Bayes, Decision Tree, AdaBoost, and Gradient Boosting, with a focus on f1-score to handle data imbalance. The evaluation shows that Gradient Boosting has the best performance with the highest accuracy, precision, recall, and f1-score. The results provide insights into the factors that influence school bus types and offer an effective predictive model to support decision-making in school transportation management in Jakarta. Gradient Boosting proved to be the most reliable in predicting school bus types, providing a basis for strategies to improve the safety and efficiency of school transportation.
Co-Authors ., Sutarno A. Rahman Abdul Wahid Sempurna Abdurahman Abdurahman Abdurahman Abdurrahman Ade Iriani Sapitri Ade Murdiansyah Ade Silvia Handayani Adiansyah Adiansyah Aditya Putra Perdana Prasetyo Ahmad Fadhil Ahmad Fali Oklilas Ahmad Fali Oklilas Ahmad Heryanto Ahmad Rezqy FF Ahmad Rifai Ahmad Rifai Ahmad Zarkasi Ambarwati, Ayu Anggraini, Febrina Hedy Annisa Darmawahyuni Archibald Hutahaean, Jerrel Adriel Arif Tumpal Leonardo Sianturi Atika Mailasari Ayu Ambarwati Bambang Tutuko Bangun Sudrajat Barzan Trio Putra Chandra Irsan Danny Matthew Saputra Darmawahyuni, Annisa Dedy Kurniawan Deris Stiawan Des Alwine Zayantii Eka Fasilah Emaria Melati Erwin, Erwin Fardinelly, Syahria Fatimah, Sayyidatina Felia, Okta Firdaus Firdaus Fri Murdiya, Fri Hendra Setiawan Holyness Nurdin Singadimedja Huda Ubaya Huda Ubaya Husnawati Husnawati Husnawati Husnawati Husnawati Husnawati Husnawati Iman Saladin B. Azhar Irsyadi Yani Izzati Millah Hanifah Kemahyanto Exaudi MARIA BINTANG Mattjik, Hani Alifia Muflika Amini Muhammad Ali Buchari Muhammad Fachrurrozi Muhammad Fadli Muhammad Fadli Muhammad Fadli Muhammad Naufal Rachmatullah Nabillah Selva Setiawan Nadya Lucyana Neni Frimayanti Nyayu Latifah Husni, Nyayu Latifah Osvari Arsalan Purwita Sari Purwita Sari Rahmad Fadli Isnanto Rahmat Fadli Isnanto Rahmayuni, Septa Ranti Eftika Rendyansyah Reza Firsandaya Malik Rezqy FF, Ahmad Rian Rahmanda Putra Rido Zulfahmi Rifkie Primartha Roswitha Yemima Tiur Mediswati Rouzan Fiqri Abdullah Samsuryadi - Samsuryadi Samsuryadi Sarmayanta Sembiring Sayyidatina Fatimah Sinaga, Aurell Octaviona Siti Nurmaini Sri Desy Siswanti Sri Desy Siswanti Sri Wahyuni Sukemi Sutarno Sutarno Sutarno - Sutarno . Sutarno Sutarno Sutarno Sutarno Sutarno Sutarno Sutarno, Sutarno Tarida Mathilda Tharisa Antya Perdani Titin Wahdania Tunnisa Wahyu Gunawan Winda Kurnia Yandi Prasetia Yandi Prasetia Yulia Resti Yusak Maryunianta Zahari Taha Zahari Taha