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All Journal Techno.Com: Jurnal Teknologi Informasi JUITA : Jurnal Informatika Jurnal Informatika dan Teknik Elektro Terapan JAIS (Journal of Applied Intelligent System) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal ICT : Information Communication & Technology Infotekmesin JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Innovation Information Technology and Application (JINITA) Brahmana : Jurnal Penerapan Kecerdasan Buatan JOINT (Journal of Information Technology Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknik Informatika (JUTIF) Informatics and Digital Expert (INDEX) Jurnal Puan Indonesia Tedc Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat Journal of Informatics and Electronics Engineering Journal Of Artificial Intelligence And Software Engineering Competitive Jurnal Informatika: Jurnal Pengembangan IT IPSIKOM Scientific Journal of Informatics Journal of New Trends in Sciences JPPkM: Jurnal Pengabdian dan Pemberdayaan kepada Masyarakat Journal of Applied Information Technology and Innovation
Castaka Agus Sugianto
Politeknik TEDC
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Pelatihan Pemanfaatan Smartphone untuk Digital Marketing di SMK Negeri 3 Cimahi Dini Rohmayani; Arya Aditya; Castaka Agus Sugianto; Ayu Hendrati Rahayu; Aris Haris Rismayana
JPPkM: Jurnal Pengabdian dan Pemberdayaan kepada Masyarakat Vol. 2 No. 1 (2026): JPPkM:Januari
Publisher : Yayasan Pemimpin Inovasi Science

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Abstract

This community service activity aims to provide training on utilizing smartphones for digital marketing to 70 students of SMK Negeri 3 Cimahi through introducing basic concepts, Shopee features, and practical sessions on creating online stores. The training was conducted on August 23, 2022, using methods of counseling, demonstration, and hands-on practice with participants' smartphones. Results showed high enthusiasm among participants, who successfully understood the material and created their own Shopee stores, thereby enhancing digital entrepreneurship skills in the industry 4.0 era.
Algoritma Naive Bayes untuk Klasifikasi Ketepatan Waktu Kelulusan Mahasiswa Politeknik TEDC Bandung Nandhita Ayusari; Castaka Agus Sugianto
Journal of Applied Information Technology and Innovation Vol. 1 No. 1 (2025): Maret
Publisher : Yayasan Pemimpin Inovasi Science

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Polytechnic TEDC Bandung  is a higher education institution that is committed to increasing efficiency and effectiveness in the education and teaching process by implementing various policies and programs. One of the aims of this is to produce quality student graduates who are useful for society. One of the steps that students need to take to become quality graduates is to graduate on time. However, in its implementation, there are still some students who experience obstacles in achieving this. This is caused by several factors, so efforts are needed to reduce or even overcome this. This research aims to apply the Naive Bayes algorithm to be able to classify student data that is on time and not on time when attending the final assignment session, in order to obtain solutions and efforts that can help the campus to overcome this problem. The test results using the naïve Bayes method without validation produced 218 data that were included in the on-time class and 33 data that were included in the not-on-time class. Meanwhile, the results of testing using the naïve Bayes method using validation produced 216 data that were included in the on-time class and 35 data that were included in the not-on-time class. Test results using the Naïve Bayes method using validation with RapidMiner produced an accuracy level of 92.05%, precision had a value of 92.40%, Recall had a value of 98.52% and F1-Score had a value of 95.71%.
Aplikasi Penjualan Berbasis Web (Studi Kasus Kedai “The Susumurni Inc “) Dini Rohmayani; Castaka Agus Sugianto; Novita Lestari Anggreini; Aqmal Mulqy Bagja Laksana
Journal of Applied Information Technology and Innovation Vol. 1 No. 2 (2025): September
Publisher : Yayasan Pemimpin Inovasi Science

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The Susumurni Inc merupakan perusahaan yang bergerak dalam bidang minuman dengan menu yang disajikan ialah susu murni. Hasil observasi pada kedai the susumurni inc dari segi sulitnya merekap data dan buku menu yang terkadang menunggu untuk menggunakannya. Beberapa transaksi penjualan yang tidak diketahui serta jumlah total pendapatan penjualan yang tidak diketahui keseluruhan nominalnya, maka penulis melakukan penelitian di kedai susu murni yang dapat membantu pemilik usaha dalam mengetahui perkembangan pendapatan pada usahanya, serta membantu mempercepat waktu dalam melakukan pencatatannya, maka dibuatlah aplikasi berbasis web. Metode yang diimplementasikan yaitu metode waterfall dengan tahapan analisis, desain, pengodean, pengujian. Menggunakan pemodelan berorientasi objek menggunakan Unified Modeling Language (UML). Aplikasi The Susumurni Inc berbasis web dan dibangun menggunakan bahasa pemrograman PHP, CSS, JavaScript, framework Laravel dan database MySQL. Aplikasi UMKM Studi Kasus The Susumurni Inc Berbasis Web dapat membantu pemilik dalam mengatur sistem perusahaan untuk merekap data serta memudahkan dalam persediaan menu yang bisa diakses oleh semua pelanggan tanpa menunggu antrian. Hasil uji Black Box telah mengindikasikan bahwa fitur dalam sistem telah berjalan sesuai dengan yang diharapkan. Hasil User Acceptance Test (UAT) berdasarkan 3 parameter uji dengan presentasenya yaitu desain (96,00%), fitur (94.67) dan kepuasan (92,89%) memperoleh skor rata-rata keseluruhan (88,61%).
Algoritma C4.5 Untuk Klasifikasi Penerima Bantuan Covid-19 Pada Desa Cimareme, Bandung Barat Castaka Agus Sugianto; Muhammad Ridwan; Dini Rohmayani; Novita Lestari Anggreini; Ayu Hendrati Rahayu
Journal of Applied Information Technology and Innovation Vol. 1 No. 2 (2025): September
Publisher : Yayasan Pemimpin Inovasi Science

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Desa Cimareme yang terletak di Kabupaten Bandung Barat merupakan salah satu desa penerima bantuan pemerintah. Namun, beberapa warga mengeluhkan ketidakadilan dalam pendistribusian bantuan, di mana ada warga yang dianggap mampu justru menerima bantuan, sedangkan yang membutuhkan tidak mendapatkannya. Untuk menghindari kesalahan sasaran, diperlukan pengklasifikasian data yang dilakukan secara ilmiah dan sistematis guna menentukan siapa saja yang berhak menerima bantuan dan siapa yang tidak. Berdasarkan hal tersebut, peneliti melakukan pengolahan data menggunakan metode data mining untuk mengklasifikasikan penerima dan bukan penerima bantuan COVID-19 dengan menggunakan Algoritma Decision Tree dan Algoritma Naïve Bayes sebagai pembanding. Tujuannya adalah untuk menemukan pola dalam program bantuan pemerintah COVID-19 serta mengetahui tingkat akurasi Algoritma Decision Tree (C4.5)  jika dibandingkan dengan algoritma lainnya. Penelitian ini menggunakan data kependudukan dari Desa Cimareme, Kecamatan Ngamprah, Kabupaten Bandung Barat. Model data mining dikembangkan menggunakan perangkat RapidMiner. Berdasarkan hasil pengujian dan validasi, Algoritma Decision Tree menghasilkan akurasi sebesar 99,97%, precision 100,00%, recall 99,71%, dan nilai AUC sebesar 0,967. Sedangkan Algoritma Naïve Bayes menghasilkan akurasi 99,93%, precision 99,71%, recall 99,71%, dan AUC sebesar 0,997. Hasil uji T-test menunjukkan nilai alpha sebesar 0,643, yang berarti tidak terdapat perbedaan signifikan antara hasil Algoritma Decision Tree dan Naïve Bayes dalam klasifikasi penerima bantuan.
ANALISIS SENTIMEN MASYARAKAT TERHADAP PINJAMAN ONLINE DI APLIKASI X MENGGUNAKAN LONG SHORT-TERM MEMORY Hafizh Maalik Falah; Castaka Agus Sugianto
IPSIKOM Vol. 13 No. 2 (2025): Jurnal Ipsikom
Publisher : LPPM UNIVERSITAS INSAN PEMBANGUNAN INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58217/ipsikom.v13i2.429

Abstract

The development of online loans in Indonesia has led to various public opinions spread across social media, one of which is the X platform. This research aims to analyze public sentiment towards online loans using the Long Short-Term Memory (LSTM) method. The data used consists of 702 Indonesian tweets collected through a crawling process with Tweet Harvest. Of these, 480 tweets were classified as positive sentiment and 222 as negative. The research process includes preprocessing, manual labeling, model training, and evaluation stages. The model was built using Sequential architecture from Keras, consisting of embedding layer, LSTM layer 128 units, 30% dropout, and output layer with softmax activation function. The model was trained using 562 tweets as training data and 140 tweets as validation data with a ratio of 80:20, for 10 epochs and batch size 64. The final evaluation using the entire dataset resulted in 92.59% accuracy, with 79.06% precision, 79.43% recall, and 79.14% F1-score. These results show that LSTM is able to classify sentiment stably and effectively, and has strong potential in sentiment analysis on short text data such as tweets.
DETEKSI KESEGARAN IKAN BANDENG DENGAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK (CNN) Rudi Riansyah; Castaka Agus Sugianto
IPSIKOM Vol. 13 No. 2 (2025): Jurnal Ipsikom
Publisher : LPPM UNIVERSITAS INSAN PEMBANGUNAN INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58217/ipsikom.v13i2.442

Abstract

Fish freshness is a key indicator in ensuring food quality and safety, especially in milkfish (Chanos chanos) which is widely consumed in Indonesia. Manual freshness assessment is subjective and requires special skills, so an accurate automated approach is needed. This study aims to develop a digital image-based milkfish freshness classification application using the Convolutional Neural Network (CNN) method with a transfer learning approach. The dataset used consists of 445 milkfish images in two classes: fresh and not fresh, with an augmentation process to enrich the visual variety. Two models were compared: Model A (baseline) and Model B (enhancement with Dropout and fine-tuning). The evaluation results show that Model A has 33% accuracy, 50% precision, and 50% recall, In contrast, Model B has 67% accuracy, 50% precision, and 100% recall, showing more stable prediction in Streamlit-based applications. These findings suggest that the integration of CNN and transfer learning can be effectively applied to support the digitization of fish-based food product quality. Further development is suggested through the addition of training data, multi-class classification, and integration to mobile or IoT devices.
Pengembangan Media Pembelajaran Virtual Reality untuk Meningkatkan Pemahaman Konsep Fisika pada Siswa SMA Dini Rohmayani; Castaka Agus Sugianto
Journal of New Trends in Sciences Vol. 2 No. 1 (2024): Februari: Journal of New Trends in Sciences
Publisher : CV. Aksara Global Akademia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59031/jnts.v2i1.783

Abstract

The learning of physics, particularly mechanics, poses significant challenges for high school students. Concepts such as Newton’s laws, energy, and three-dimensional vectors are often difficult to grasp using traditional teaching methods. Virtual Reality (VR) has emerged as a promising solution by providing an immersive and interactive learning environment. This study aims to evaluate the effectiveness of VR-based learning media in enhancing students’ understanding of physics concepts, with a specific focus on mechanics. An experimental design was employed, consisting of two groups: an experimental group using VR for learning and a control group receiving traditional instruction. Pre-test and post-test assessments were used to measure the improvement in students' conceptual understanding of physics. The findings indicate that students in the experimental group demonstrated a significant improvement in their understanding of complex physics concepts, such as projectile motion, force, and Newton’s laws, compared to the control group. Students in the experimental group also exhibited higher levels of engagement and motivation, with VR's immersive nature encouraging active participation in learning. The study concludes that VR is an effective tool for enhancing students’ comprehension of abstract and complex physics concepts, improving their visualization and problem-solving skills. Furthermore, VR-based learning provides students with opportunities to conduct virtual experiments and simulations that may not be possible in traditional classroom settings. The implications of this study suggest that VR should be integrated into the physics curriculum to improve learning outcomes, especially in schools with access to the necessary technology. Educators and curriculum developers are encouraged to explore VR’s potential in fostering a more engaging and effective physics education.
Analisis Big Data dalam Deteksi Dini Wabah Penyakit Menular untuk Mendukung Sistem Kesehatan Publik Ayu Hendrati Rahayu; Castaka Agus Sugianto; Dini Rohmayani
Journal of New Trends in Sciences Vol. 2 No. 1 (2024): Februari: Journal of New Trends in Sciences
Publisher : CV. Aksara Global Akademia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59031/jnts.v2i1.785

Abstract

The rapid spread of infectious diseases remains a major global health threat, and early detection is vital to minimize their impact. This research investigates the role of predictive modeling using big data in the early detection of infectious disease outbreaks. The primary objective of this study is to assess the effectiveness of big data systems in forecasting potential outbreaks and the implications of these forecasts for public health systems. The study employs machine learning-based predictive models to process large health datasets, including electronic health records, sensor data, and social media information. The results demonstrate that the predictive model achieved an accuracy rate of 87%, significantly surpassing traditional methods in terms of early detection. By integrating various data sources such as medical records, sensor networks, and real-time digital traces, the system is capable of providing more accurate, timely predictions, which can greatly improve the ability of public health authorities to respond effectively to emerging health threats. Furthermore, the application of big data in public health not only improves the speed of response but also enhances the allocation of resources, allowing for more targeted and efficient interventions. Despite these successes, challenges remain, particularly in relation to data quality, privacy, and regulatory issues, which could hinder the broader implementation of such systems. Thus, collaboration between government agencies, healthcare institutions, and technology developers is essential to overcome these obstacles and ensure the sustainable integration of big data into public health infrastructures. This research highlights the significant potential of big data to transform public health responses, offering valuable insights for future epidemic management strategies.
Pengembangan Decentralized Application (Dapp) Berbasis Web 3.0 untuk Minting Non-Fungible Token (NFT) Menggunakan Smart Contract Erc-721 dan InterPlanetary File System (IPFS) Dini Rohmayani; Ilham Alfath; Castaka Agus Sugianto

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Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i5.9867

Abstract

Abstrak - Implementasi Non-Fungible Token (NFT) sering menghadapi masalah permanensi data karena ketergantungan pada penyimpanan terpusat yang rentan terhadap penghapusan dan perubahan. Penelitian ini mengembangkan aplikasi web berbasis Decentralized Application (DApp) untuk pembuatan Non-Fungible Token (NFT) yang mengintegrasikan InterPlanetary File System (IPFS) dengan Smart Contract ERC-721 pada blockchain Ethereum. Metode pengembangan menggunakan pendekatan waterfall dengan implementasi React.js dan Next.js untuk frontend serta Solidity untuk smart contract. Sistem dirancang dengan arsitektur three-tier yang memfasilitasi pembuatan koleksi Non-Fungible Token (NFT) melalui kontrak Factory dan pengelolaan token melalui NFTCollection, dengan metadata dan aset digital disimpan menggunakan Content Identifier (CID) pada InterPlanetary File System (IPFS). Pengujian blackbox menunjukkan seluruh fungsi sistem berjalan sesuai spesifikasi, sementara User Acceptance Testing (UAT) dengan 24 responden menghasilkan tingkat penerimaan 90%. Hasil penelitian membuktikan bahwa integrasi InterPlanetary File System (IPFS) dengan smart contract ERC-721 dapat mengatasi permasalahan permanensi metadata dan aset digital, sekaligus menyederhanakan proses minting Non-Fungible Token (NFT) bagi pengguna non-teknis melalui antarmuka yang intuitif.Kata kunci: Non-Fungible Token (NFT); ERC-721; IPFS; Kontrak Pintar; Blockchain; Abstract - Podo Practical implementations of Non-Fungible Tokens (NFTs) often face data permanence issues due to reliance on centralized storage systems vulnerable to deletion and modification. This research develops a web-based Decentralized Application (DApp) for NFT creation that integrates the InterPlanetary File System (IPFS) with ERC-721 Smart Contracts on the Ethereum blockchain. The development methodology employs a waterfall approach with React.js and Next.js for frontend implementation and Solidity for smart contracts. The system is designed with a three-tier architecture facilitating NFT collection creation through the NFTFactory contract and token management through NFTCollection, with metadata and digital assets stored using Content Identifiers (CID) on IPFS. Black box testing demonstrates that all system functions operate according to specifications, while User Acceptance Testing (UAT) with 24 respondents yields an acceptance rate of 90%. The research findings prove that integrating IPFS with ERC-721 smart contracts addresses metadata and digital asset permanence issues while simplifying the NFT minting process for non-technical users through an intuitive interface.Keywords: Non-Fungible Token (NFT); ERC-721; IPFS; Smart Contract; Blockchain;
Pelatihan Visual Thinking dan Dasar Desain Grafis Sejak Dini bagi Siswa MI Nurul Huda Kota Cimahi Dini Rohmayani; Castaka Agus Sugianto; Akbar Maulana; Aris Haris Rismayana; Ayu Hendrati Rahayu
JPPkM: Jurnal Pengabdian dan Pemberdayaan kepada Masyarakat Vol. 2 No. 2 (2026): JPPkM:Juli
Publisher : Yayasan Pemimpin Inovasi Science

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Abstract

The development of graphic design in Indonesia is currently growing rapidly alongside the high industrial demand and educational interest. Introducing graphic design at an early age is crucial, as it can trigger children's creativity and interest through visual activities such as drawing. This study aims to introduce graphic design to elementary school students using Canva and Adobe Illustrator software. The method used is the delivery of material designed code-simplicity to be easily understood by children. Through this program, children are expected to understand the fundamentals of graphic design in an engaging and applicable manner.
Co-Authors Ade Yuliana Aditia Gusman Akbar Maulana Aldy Noer Tjahyo Apnena, Riri Damayanti Aqmal Mulqy Bagja Laksana Ari Sudrajat Aris Haris Rismayana Arya Aditya Ayu Hendrati Rahayu Candra Irawan Christy Atika Sari Dadan Saepul Ramdan Dahlan Dahlan Dini Rohmayani Dini Rohmayani Dwi Putra Ramadhan Eko Hari Rachmawanto Faishal Fachruddin Febianto, Aldi Kristiawan Firdhani Faujiyah Fitrah, La Ode Muhammad Fredricka, Jhoanne Gerinata Ginting Hafizh Maalik Falah Hamimah Nur Hidayah Heldi Akbar Kosasih Hidayah, Hamimah Nur Himawan, Aldi Ilham Alfath Iqna Aulia Iskandar, Rachmat Juniardi, Trianda Kosasih, Heldi Akbar La Ode Muhammad Fitrah Lela Kesmasari Maulana, Firdi Rizky Melani Nur Astita Mohamed Doheir Muhammad Ridwan Nadya Selvi Pujiyanita Nafea, Mohammed Mansoor Nandhita Ayusari Nia Ekawati, Nia Novita Lestari Anggreini Pebriana, Sela Perdana, Rangga Satria Pujiyanita, Nadya Selvi Putri Nurlaela Sari Rahmawan, Septiadi Ramdan, Dadan Saepul Riansyah Ramadhan, Gery Riri Damayanti Apnena Riyan Riyan Rizqy Dimas Monica Rosdianti, Elfi Rudi Riansyah Safira, Rifa Sari, Putri Nurlaela Septiadi Rahmawan Shandy Tresnawati Sukmawati, Dini Syaefuloh, Herman Syams, Fawwaz Muhammad Syifa Fauzia Tahir Tahir, Syifa Fauzia Tati Ernawati Taufik Fajar Mustafa Tresnawati, Shandy Tri Herdiawan Apandi Tri Pratiwi Olivia Riska Bokings Wanaziana, Keny Kirana Zulkipli . Zulkipli ., Zulkipli Zundi, Teguh Muhammad