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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Proceeding of the Electrical Engineering Computer Science and Informatics JITK (Jurnal Ilmu Pengetahuan dan Komputer) TERANG : Jurnal Pengabdian Pada Masyarakat Menerangi Negeri Tematik : Jurnal Teknologi Informasi Komunikasi JoMMiT : Jurnal Multi Media dan IT Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Prosiding SeNTIK STI&K
Koyimatu, Muhamad
Institut Teknologi Bandung
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering

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Fully Convolutional Variational Autoencoder For Feature Extraction Of Fire Detection System Herminarto Nugroho; Meredita Susanty; Ade Irawan; Muhamad Koyimatu; Ariana Yunita
Jurnal Ilmu Komputer dan Informasi Vol 13, No 1 (2020): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (579.884 KB) | DOI: 10.21609/jiki.v13i1.761

Abstract

This paper proposes a fully convolutional variational autoencoder (VAE) for features extraction from a large-scale dataset of fire images. The dataset will be used to train the deep learning algorithm to detect fire and smoke. The features extraction is used to tackle the curse of dimensionality, which is the common issue in training deep learning with huge datasets. Features extraction aims to reduce the dimension of the dataset significantly without losing too much essential information. Variational autoencoders (VAEs) are powerfull generative model, which can be used for dimension reduction. VAEs work better than any other methods available for this purpose because they can explore variations on the data in a specific direction.
Robust Principal Component Analysis for Feature Extraction of Fire Detection System Herminarto Nugroho; Muhamad Koyimatu; Ade Irawan; Ariana Yunita
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v5.1716

Abstract

Fire detection system with deep learning-based computer vision (DLCV *) algorithm is proposed in this paper. It uses visible light sensor charged-coupled device (CCD) which can be usually found in closed circuit television camera (CCTV). The performance of this DLCV fire detection depends on how many fire image datasets are trained that might lead to the curse of dimensionality. To tackle the curse of dimensionality, Principal Component Analysis (PCA) will be used. PCA is a technique for feature extraction in which the dimensionality of such datasets is reduced significantly. This will results in increasing interpretability but at the same time minimizing information loss.
Peningkatan Literasi Komputer Melalui Pelatihan Micosoft Excel Advanced Untuk Efisiensi Pekerjaan di Instansi Pemerintahan Meredita Susanty; Erwin Setiawan; Wahyu Kunto Wibowo; Herminarto Nugroho; Ade Irawan; Tasmi Tasmi; Muhamad Koyimatu; Aulia Rahma Annisa; Teguh Aryo Nugroho; Ariana Yunita
Terang Vol 4 No 2 (2022): TERANG : Jurnal Pengabdian Pada Masyarakat Menerangi Negeri
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33322/terang.v4i2.1528

Abstract

Era digital melahirkan berbagai potensi dan tantangan yang memasuki berbagai bidang seperti politik, ekonomi, sosial budaya, pertahanan dan keamanan serta teknologi informasi. Pemerintahan atau sistem birokrasi di Indonesia juga tidak luput dari potensi dan tantangan perkembangan era digital ini. Salah satu tantangan besar yang harus dihadapi oleh sistem birokrasi Indonesia adalah tuntutan lahirnya inovasi yang berorientasi pada teknologi digital, sehingga inovasi ini diharapkan dapat memudahkan Aparatur Sipil Negara (ASN) dalam melaksanakan tugas dan fungsinya. Kemudahan segala pekerjaan dengan berbasis aplikasi dan teknologi ini selanjutnya diharapkan mampu memberikan pelayanan yang lebih optimal kepada masyarakat. Menanggapi tantangan ini, civitas Universitas Pertamina melalui program Pengabdian Kepada Masyarakat (PKM) berbagi pengetahuan, ilmu dan keahlian dalam penggunakan Microsoft Excel untuk mendukung efektivitas pengerjaan pekerjaan harian pada ASN Kantor Pelayanan Kekayaan Negara dan Lelang (KPKNL) Bekasi. Kegiatan ini diharapkan meningkatkan kemampuan Sumber Daya Manusia di kalangan KPKNL Bekasi, meningkatkan efektifitas dan efisiensi pelaksanaan tugas dan fungsi sehari-hari, serta menjadi katalis dalam munculnya inovasi yang berorientasi pada teknologi digital.
Pengembangan Media Promosi Program Studi Ilmu Komputer Universitas Pertamina Berbasis Virtual Reality Tour 3600 Koyimatu, Muhamad; Varlina, Vivi; Oktafiani, Intan; Tiar Albani, Bargas; Putri jagat, Anjani; Marietta Fau, Sri Olivia; Luqmanul Hakim, Ahmad
JoMMiT Vol 7 No 2 (2023): Artikel Jurnal Volume 7 Issue 2, Desember 2023
Publisher : Politeknik Negeri Media Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46961/jommit.v7i2.872

Abstract

Perkembangan teknologi multimedia terus berkembang, salah satunya adalah teknologi format video 360° yang menangkap seluruh sudut pandang pada video. Konsep 360° dapat dimanfaatkan sebagai media promosi atau virtual tour, terutama di era pandemic Covid-19. Program Studi Ilmu Komputer Universitas Pertamina memanfaatkan konsep video 360° untuk mempromosikan dan memberikan informasi kepada khalayak ramai mengenai prodinya. Proses pembuatan video 360° mirip dengan video konvensional dengan metode MDLC (Multimedia Development Life Cycle). Namun diperlukan penyesuain karena fitur lensa kamera 360° yang berbeda dengan lensa kamera biasa. video 360° yang dihasilkan mendapatkan respon yang cukup baik, walaupun masih diperlukan perbaikan pada beberapa bagian.
Penerapan Metode SDLC Waterfall Pada Sistem Pemesanan Makanan Menggunakan QR-Code Berbasis Website Yolla Putri Ervanisari; Muhamad Koyimatu; Kristine Angelina Simanjuntak; Intan Oktafiani
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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

Abstract

Café Sudut Temu by Toastea, located in Cirahayu Tegalega Street, Central Bogor, was established in 2015. The manual booking system in place at Café Sudut Temu is currently inefficient and vulnerable to error, resulting in lengthy waiting times, order errors, and challenges in inventory management. Therefore, this research is planning to build a QR code-based food ordering system through a website. The ordering system in this study was developed using the Waterfall methodology and the application was designed using the Laravel PHP framework. The design phase begins with the collection of requirements, the creation of design, the implementation or development of the system and ends with testing. This research results in a system that simplifies the ordering process, reduces errors, and improves operational efficiency.In addition, the responsive design with a mobile-friendly interface allows customers to order directly without having to wait for the help of the server. The system is expected to increase customer satisfaction and contribute to coffee growth amid increasing competition in the industry. The results of this research are a website-based application for ordering food and beverages using a QR Code on Café Sudut Temu.
Identifikasi Opini Publik Terhadap Kendaraan Listrik dari Data Komentar YouTube: Pemodelan Topik Menggunakan BERTopic Kristine Angelina Simanjuntak; Muhamad Koyimatu; Yolla Putri Ervanisari; Tasmi
TEMATIK Vol. 11 No. 2 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Desember 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i2.2096

Abstract

The Indonesian government is encouraging the transition to electric vehicles to reduce the use of fossil fuels and the negative environmental impact. This transition sparked controversy because Indonesia is still heavily dependent on coal-fired power plants, and many argue that the transition is not ready without adequate renewable energy and supporting infrastructure. Public opinion analysis is crucial in considering the introduction of electric vehicles in Indonesia due to the controversial nature of the transition. The opinion is transmitted through YouTube by taking comment data, then grouped into a topic to identify public opinion. The topic modeling method used is a BERTopic transformer model using IndoBERTweet in embedding. Once public opinion is modeled into a topic, changes in public opinion are evaluated using coherence score metrics and topic diversity as a measure of the consistency and diversity of the topic. The resulting topics have a coherence value of around 0.6 to 1 and a diversity value of 0.95838. This indicates that the resulting themes have strong semantic similarities and high diversity in terms of word usage and capture various aspects of text documents well.
Implementasi Metode Multithreading Pada Pengembangan Gim Multiplayer Online Menggunakan Java Virtual Machine Muhammad Nezha Alfatah Chandrawisesa; Muhamad Koyimatu; Erwin Setiawan
Prosiding Seminar SeNTIK Vol. 7 No. 1 (2023): Prosiding SeNTIK 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

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

Abstract

Gim multiplayer online telah menjadi sangat populer di seluruh penjuru dunia saat ini. Namun, pengembangan gim seperti itu memiliki tantangan teknis yang serius, terutama dalam hal pengelolaan dan sinkronisasi data antara pemain. Dalam upaya untuk mengatasi tantangan ini, metode multithreading diusulkan sebagai pendekatan yang efektif dalam meningkatkan kinerja gim multiplayer online. Tujuan penelitian ini adalah untuk menganalisis implementasi metode multithreading dalam pengembangan gim multiplayer online pada sisi server. Metode penelitian yang digunakan adalah eksperimen dengan menggunakan Java Virtual Machine sebagai alat pembantu. Eksperimen dilakukan dengan menerapkan metode multithreading dengan memanfaatkan fitur dan mekanisme multithreading yang disediakan oleh Java Virtual Machine, seperti pengelolaan thread, sinkronisasi data, dan pengaturan prioritas kemudian dilakulan pengumpulan data kinerja gim, dan responsivitas pada gim yang telah ada. Hasil penelitian menunjukkan bahwa implementasi metode multithreading pada sisi server dapat meningkatkan kinerja gim dan responsivitas pemain sebanyak 55.22%
DEVELOPMENT OF GRAPH GENERATION TOOLS FOR PYTHON FUNCTION CODE ANALYSIS Bayu Samodra; Vebby Amelya Nora; Fitra Arifiansyah; Gusti Ayu Putri Saptawati Soekidjo; Muhamad Koyimatu
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 3 (2025): JITK Issue February 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i3.6177

Abstract

The increasing complexity of programs in software development requires understanding and analysis of code structure, especially in Python, which dominates machine learning and data science applications. Manual static analysis is often time-consuming and prone to errors. Meanwhile, static analysis tools for Python, like PyCG and Code2graph, are still limited to generating call graphs without including dependency and control flow analysis. This research addresses these shortcomings by proposing the development of a web-based tool that integrates the generation of function call graphs, function dependency graphs, and control flow graphs using Abstract Syntax Tree (AST), Graphviz, and Streamlit. With an iterative SDLC methodology, this tool was developed gradually to visualize Python function code as a heterogeneous graph. Evaluation of 11 Python function codes showed a success rate of 95.45% in analyzing and visualizing Python function codes with various levels of complexity. The limitations of Graphviz present an opportunity for future research to focus on improving scalability and Python code analysis.
Simplifikasi Graf Pemanggilan Fungsi: Pendekatan Community Detection Untuk Mempermudah Pemahaman Struktur Kode Tioria Marlini Purba, Risa; Purba, Risa Tioria Marlini; Tonang, Ari Sandy Putra Ari; Karim, Abdulah; Soekidjo, Gusti Ayu Putri Saptawati; Muhamad, Koyimatu; Arifiansyah, Fitra
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 2: April 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.132

Abstract

Dalam pengembangan perangkat lunak skala besar, pemahaman terhadap struktur kode sangat penting untuk menganalisis interaksi antar-fungsi dalam kode sumber. Graf pemanggilan fungsi (function call graph) merupakan kakas yang efektif untuk memetakan hubungan antar-fungsi, yang membantu pengembang dalam menelusuri jalur eksekusi dan memahami pola struktur kode modular yang kompleks. Namun, pada kode sumber yang rumit, graf pemanggilan fungsi sering kali menjadi sangat besar dan sulit diinterpretasi karena banyaknya node dan edge yang terlibat. Untuk mengatasi masalah ini, teknik simplifikasi graf melalui community detection diterapkan sebagai solusi untuk mengelompokkan fungsi-fungsi yang saling terkait dalam cluster, sehingga menghasilkan visualisasi yang lebih terstruktur dan mudah dipahami. Penelitian ini bertujuan untuk mengembangkan kakas berbasis Python yang mampu menyederhanakan graf pemanggilan fungsi menggunakan algoritma Girvan-Newman. Kakas ini memanfaatkan pustaka networkx untuk membentuk graf dan menerapkan deteksi komunitas, ast untuk parsing kode, serta matplotlib dan streamlit untuk visualisasi dan interaksi pengguna. Hasil eksperimen pada 10 program dengan ukuran 10-85 baris kode menunjukkan bahwa metode community detection mampu mereduksi jumlah node dan edge dalam graf pemanggilan fungsi hingga 60%, dengan skor modularitas tertinggi 0.6605. Evaluasi dengan 25 pengembang perangkat lunak menunjukkan tingkat kepuasan 80% dalam hal kemudahan penggunaan dan peningkatan produktivitas analisis kode.   Abstract In large-scale software development, understanding the code structure is crucial for analyzing the interactions between functions in the source code. A function call graph is an effective tool for mapping the relationships between functions, assisting developers in tracing execution paths and understanding object-oriented complex code structures. However, in complex source code, the function call graph often becomes very large and complicated to interpret due to the many nodes and edges involved. To address this issue, graph simplification techniques, such as community detection, are applied as a solution to group related functions into clusters, thereby producing a more structured and easier-to-understand visualization. This study aims to develop a Python-based tool that simplifies function call graphs using the Girvan-Newman algorithm. The tool utilizes the networkx library to construct graphs and apply community detection, ast for code parsing, and matplotlib and streamlit for visualization and user interaction. The results of experiments on 10 programs, ranging in size from 10 to 85 LOC, showed that the community detection method was able to reduce the number of nodes and edges in the function invocation graph by up to 60%, achieving the highest modularity score of 0.6605. An evaluation of 25 software developers revealed an 80% satisfaction rate in terms of ease of use and increased productivity in code analysis.
Co-Authors Ade Irawan Ade Irawan Ariana Yunita Arifiansyah, Fitra Aulia Rahma Annisa Bayu Samodra Erwin Setiawan Erwin Setiawan Fitra Arifiansyah Gusti Ayu Putri Saptawati Herminarto Nugroho Intan Oktafiani Karim, Abdulah Kristine Angelina Simanjuntak Luqmanul Hakim, Ahmad Marietta Fau, Sri Olivia Muhammad Nezha Alfatah Chandrawisesa Nugroho, Herminarto Purba, Risa Tioria Marlini Putri jagat, Anjani Susanty, Meredita Tasmi Tasmi Tasmi Teguh Aryo Nugroho Tiar Albani, Bargas Tioria Marlini Purba, Risa Tonang, Ari Sandy Putra Ari Varlina, Vivi Vebby Amelya Nora Wahyu Kunto Wibowo Yolla Putri Ervanisari