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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Jurnal Pekommas Elkawnie Computatio : Journal of Computer Science and Information Systems Knowledge Engineering and Data Science Jurnal CoreIT Jurnal Pengabdian Pada Masyarakat JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) JUTIM (Jurnal Teknik Informatika Musirawas) Jurnal Nasional Komputasi dan Teknologi Informasi Kurawal - Jurnal Teknologi, Informasi dan Industri JUSIM (Jurnal Sistem Informasi Musirawas) JISKa (Jurnal Informatika Sunan Kalijaga) Scientific Journal of Informatics Teknomatika (Jurnal Teknologi dan Informatika) Economics and Digital Business Review Brilliance: Research of Artificial Intelligence Algoritme Jurnal Mahasiswa Teknik Informatika Informatics and Enginering Dedication Jurnal Teknologi Sistem Informasi Digital Transformation Technology (Digitech) DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY MDP Student Conference Nusantara Journal of Multidisciplinary Science Journal Information & Computer (JICOM) Jurnal Software Engineering and Computational Intelligence JURNAL MULTIDISIPLIN ILMU AKADEMIK Jurnal Ilmiah Sistem Informasi MERDEKA: Jurnal Ilmiah Multidisiplin Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Jurnal Ilmiah Multidisiplin
Novan Wijaya
Universitas Multi Data Palembang
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Classification of Cassava Leaf Diseases Using ResNet50 CNN Architecture Based on Digital Images Malik, Maulana; Wijaya, Novan
Brilliance: Research of Artificial Intelligence Vol. 6 No. 1 (2026): Brilliance: Research of Artificial Intelligence, Article Research May 2026
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v6i1.7686

Abstract

Cassava (Manihot esculenta) is an important agricultural commodity in Indonesia, but its productivity can decline due to leaf diseases such as Cassava Mosaic Disease (CMD), Cassava Green Mottle (CGM), Cassava Bacterial Blight (CBB), and Cassava Brown Streak Disease (CBSD). These four diseases exhibit overlapping visual symptoms such as chlorosis, spots, and leaf discoloration, making them difficult to distinguish manually. This study aims to create a digital- based cassava leaf image classification system using the Convolutional Neural Network (CNN) algorithm and ResNet50 architecture. The dataset used consists of 9,436 cassava leaf images taken from the TensorFlow platform and processed through resizing, normalization, selective augmentation, and the application of transfer learning. The experiment compared various optimizer configurations, learning rates, batch sizes, and balanced and unbalanced dataset scenarios. The evaluation was conducted using accuracy, precision, recall, and F1-score. The results show that the best performance was obtained on an unbalanced dataset using the Adam optimizer (learning rate 0.001; batch size 64) with an accuracy of 80.69% and an F1-score of 79.76%. Meanwhile, balancing the dataset actually reduced performance to an accuracy of 77.14% and an F1-score of 76.48%. Analysis of the loss curve and confusion matrix confirmed that the natural data distribution provided more stable generalization, although misclassification still occurred in classes with similar visual symptoms. These findings indicate that ResNet50 is effective for classifying cassava leaf diseases and has the potential to support early detection in digital agriculture practices.
Systematic Literature Review : Pemanfaatan Artificial Intelligence Oleh Mahasiswa dalam Mendukung Aktivitas Akademik Wendy Steven; Novan Wijaya
JURNAL MULTIDISIPLIN ILMU AKADEMIK Vol. 3 No. 2 (2026): JURNAL MULTIDISIPLIN ILMU AKADEMIK (JMIA)  April 2026
Publisher : CV. KAMPUS AKADEMIK PUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jmia.v3i2.9393

Abstract

Perkembangan Artificial Intelligence (AI) telah membawa perubahan signifikan dalam dunia pendidikan, khususnya dalam aktivitas akademik mahasiswa. AI dimanfaatkan untuk membantu berbagai kegiatan seperti pencarian informasi, penyusunan tugas, serta pemahaman materi pembelajaran. Namun, di balik kemudahan tersebut, penggunaan AI juga menimbulkan berbagai tantangan seperti ketergantungan, penurunan kemampuan berpikir kritis, serta berpotensi melakukan pelanggaran etika dalam akademik. Penelitian ini bertujuan untuk menganalisis pemanfaatan AI oleh mahasiswa, mengidentifikasi dampak penggunaan AI, serta mengkaji manfaat dan tantangan dalam penggunaannya. Metode yang digunakan adalah Systematic Literature Review (SLR) dengan menganalisis 23 artikel ilmiah yang relevan. Hasil penelitian menunjukkan bahwa AI memberikan dampak positif seperti meningkatkan efisiensi belajar, motivasi, serta pemahaman materi. Namun, penggunaan AI juga memiliki dampak negatif seperti ketergantungan, penurunan kemampuan berpikir kritis, serta risiko plagiarisme. Oleh karena itu, penggunaan AI perlu dilakukan secara bijak dan disertai dengan pemahaman etika yang baik agar manfaatnya dapat dimaksimalkan dan dampak negatifnya dapat diminimalkan.
Application of Gost Algorithm For The Safety of Data Sending of General Election Novan Wijaya
Elkawnie Vol. 6 No. 1 (2020)
Publisher : Faculty of Science and Technology Universitas Islam Negeri Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/ekw.v6i1.6211

Abstract

Abstract : The rapid development of the internet has an impact on the security of data sent using internet media. One government agency that uses the internet as data transmission includes the KPU. Data transmission becomes very risky especially the data sent is very important and even confidential. In the internet world, there are many threats and ways to change or retrieve data sent via the internet. Indonesia in particular has conducted direct elections but the data that are in the regions which are the results of recapitulation of the elections will be sent via the internet with a system provided by the KPU. Data from the recapitulation of regional elections becomes very important because it can be changed by intruders. Secure the data sent, methods such as cryptographic techniques that can minimize interference from intruders are needed. One algorithm that can be applied as data security is the GOST algorithm. The GOST algorithm is designed to take a balance between data efficiency and security. Cryptographic techniques that use the GOST algorithm are expected to be able to increase the security of sending election results from various threats without reducing the performance of sending data. The rapid development of the internet has the impact of the security of data sent using internet media. One government agency that uses the internet as data transmission includes the KPU. Data transmission becomes very risky especially the data sent is very important and even confidential. In the internet world, there are many threats and ways to change or retrieve data sent through internet media. Indonesia in particular has conducted direct elections but the data that are in the regions which are the results of recapitulation of the elections will be sent via the internet with a system provided by the KPU. Data from the recapitulation of regional elections becomes very important because it can be changed by intruders. Secure the data sent, methods such as cryptographic techniques that can minimize interference from intruders are needed. One algorithm that can be applied as data security is the GOST algorithm. The GOST algorithm is designed to take a balance between data efficiency and security. Cryptographic techniques that use GOST algorithm can improve the security of sending election results from various threats without reducing the performance of sending data. Election result data that was conducted during the testing was the Ogan Ilir regional election recap data. Tests that have been carried out using the GOST algorithm using WireShark produce stream files sent over the network are not easily identified because they are converted into random strings, so it takes a long time to analyze them.Abstrak : Perkembangan internet yang sangat cepat mempunyai dampak diantranya keamanan data yang dikirim menggunakan media internet. Salah satu instansi pemerintahan yang menggunakan internet sebagai pengiriman data diantaranya KPU. Pengiriman data menjadi sangat beresiko terlebih data yang dikirimkan sangat penting bahkan bersifat rahasia. Didunia internet terdapat banyak ancaman serta cara dalam mengubah atau mengambil data yang dikirimkan melalui media internet. Indonesia pada khususnya telah melakukan pemilu secara langsung tetapi data-data yang berada pada daerah yang merupakan hasil rekapitulasi dari pemilu akan dikirimkan melalui internet dengan sistem yang telah disediakan oleh KPU. Data hasil rekapitulasi pemilu suatu daerah menjadi sangat penting dikarenakan bisa diubah oleh intruder. Untuk mengamankan data yang dikirimkan diperlukan metode seperti teknik kriptografi yang bisa meminimalisir gangguan dari para intruder. Salah satu algoritma yang bisa diterapkan sebagai keamanan data yaitu algoritma GOST. Algoritma GOST dirancang agar mengambil keseimbangan antara efisiensi dan keamanan data. Teknik kriptografi yang menggunakan algoritma GOST mampu meningkatkan keamanan pengiriman data hasil pemilu dari berbagai ancaman tanpa mengurangi performansi dari pengiriman data. Data hasil pemilu yang dilakukan saat pengujian ialah data rekap pilkada Ogan Ilir. Pengujian yang telah dilakukan menggunakan algoritma GOST menggunakan wireshark menghasilkan stream file yang dikirim melalui jaringan tidak mudah diidentifikasi dikarenakan diubah menjadi string acak sehingga membutuhkan waktu yang lama untuk menganalisanya.
IMPLEMENTASI DUA ARAH MACHINE TRANSLATION MENGGUNAKAN MODEL MBART6 PADA APLIKASI POLYCHAT UNTUK KOMUNIKASI LINTAS BAHASA Bryant Ansky; Novan Wijaya
JUTIM (Jurnal Teknik Informatika Musirawas) Vol 11 No 1 (2026): JUTIM (Jurnal Teknik Informatika Musirawas) Maret
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jutim.v11i1.2891

Abstract

Komunikasi lintas bahasa merupakan tantangan dalam era globalisasi, di mana perbedaan bahasa menjadi hambatan utama dalam penyampaian pesan dan interaksi antar individu dari berbagai negara. Dengan lebih dari 7000 bahasa yang ada di dunia, kebutuhan akan solusi penerjemahan yang efektif dan terintegrasi sangat dibutuhkan. Untuk mengatasi permasalahan tersebut, penelitian ini bertujuan mengimplementasikan sistem machine translation dua arah pada aplikasi PolyChat sebagai media komunikasi lintas bahasa secara real-time. Aplikasi ini menggabungkan fungsi chat dengan penerjemahan otomatis dalam satu platform, sehingga pengguna dapat berinteraksi menggunakan bahasa ibu mereka masing-masing tanpa perlu membuka aplikasi penerjemahan terlebih dahulu. Tujuan penelitian ini adalah merancang dan membangun sistem penerjemahan berbasis Neural Machine Translation (NMT) dengan menggunakan model mBART dengan dataset OPUS kategori OpenSubtitles, serta melakukan evaluasi hasil penerjemahan menggunakan metrik BLEU (Bilingual Evaluation Understudy) untuk mengukur seberapa akurat hasil penerjemahan. Sistem dirancang dengan mekanisme caching berlapis yang mencakup pencarian di dataset, corpus cache hasil terjemahan sebelumnya, dan eksekusi model mBART untuk mengoptimalkan kecepatan dan efisiensi penerjemahan. Metodologi penelitian meliputi beberapa tahap, yaitu studi literatur, pengumpulan dataset dari enam bahasa resmi PBB (Inggris, Mandarin, Spanyol, Prancis, Russia, dan Arab) yang menghasilkan 30 arah penerjemahan, perancangan arsitektur sistem dengan proses normalisasi teks dan tokenisasi, implementasi model penerjemahan dengan attention mechanism dan beam search, serta pengujian kinerja sistem berdasarkan nilai BLEU.
IDENTIFIKASI PENYAKIT MULTIPLE SCLEROSIS PADA CITRA MRI MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK Jihan Ghassani; Novan Wijaya
JUTIM (Jurnal Teknik Informatika Musirawas) Vol 11 No 1 (2026): JUTIM (Jurnal Teknik Informatika Musirawas) Maret
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jutim.v11i1.2893

Abstract

Multiple Sclerosis (MS) merupakan penyakit neurologis yang menyerang sistem saraf pusat yaitu otak dan sumsum tulang belakang. Penyakit ini merusak lapisan mielin sehingga mengganggu penghantaran impuls saraf dan menimbulkan gejala seperti gangguan penglihatan, koordinasi, dan fungsi kognitif. Diagnosis dini MS penting karena belum terdapat terapi yang dapat menyembuhkan penyakit ini. Magnetic Resonance Imaging (MRI) terbukti efektif dalam mendeteksi kerusakan jaringan otak, namun interpretasi citra masih bergantung pada keahlian radiolog. Penelitian ini bertujuan untuk mengembangkan sistem identifikasi otomatis MS pada citra MRI menggunakan Convolutional Neural Network (CNN) berbasis arsitektur ResNet50V2. Dataset yang digunakan berupa citra MRI axial dengan label MS dan non-MS dari platform Kaggle. Citra dilakukan preprocessing dan augmentasi, kemudian dibagi menjadi dua kombinasi pembagian data, yaitu 80% data training, 10% validation, dan 10% testing serta 90% data training, 5% validation, dan 5% testing. Model CNN dilatih menggunakan optimizer Adam dengan evaluasi performa menggunakan metrik akurasi, presisi, recall, dan F1-score. Hasil penelitian menunjukkan bahwa model mampu mengidentifikasi citra MS dan non-MS dengan akurasi pengujian sebesar 89% pada skenario pembagian data 90% data latih, 5% data validasi, dan 5% data uji, serta akurasi pengujian sebesar 90% pada skenario 80% data latih, 10% data validasi, dan 10% data uji. Akurasi validasi tertinggi yang diperoleh mencapai 96,34% pada skenario 90% data latih dan 96,36% pada skenario 80% data latih. Selain itu, hasil evaluasi menunjukkan bahwa model memiliki performa yang lebih stabil dalam mengidentifikasi citra non-MS dibandingkan citra MS, meskipun masih ditemukan beberapa kesalahan klasifikasi pada kelas MS.
Analisis Sistem Pendukung Keputusan dalam Penentuan Prioritas Pasien Hemodialisa Menggunakan Metode SAW Novan Wijaya; Molavi Arman; Meiriyama
BETRIK Vol. 17 No. 01 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/b748qz52

Abstract

Hemodialysis services for patients with chronic kidney disease require appropriate decision-making, especially in determining patient priorities when healthcare resources are limited. Subjective decision-making may lead to inaccuracies and potential inequality in healthcare services. Therefore, an information technology–based approach is needed to support a more objective and structured decision-making process. This study aims to implement the Simple Additive Weighting (SAW) method in a Decision Support System to determine the priority of hemodialysis patients. The study used sample data from five patients with five evaluation criteria, namely patient age, blood pressure, creatinine level, duration of kidney failure, and frequency of hemodialysis treatment. The analysis process includes the construction of a decision matrix, normalization of criteria values based on benefit and cost attributes, and calculation of preference values using weighted criteria. The results show that the SAW method can generate a clear priority ranking of patients. Based on the calculation results, patient A3 obtained the highest preference value of 0.92, followed by patient A1 with 0.88 and patient A5 with 0.87, indicating a higher urgency for receiving hemodialysis services. The implementation of this approach contributes to the development of health information technology, particularly in supporting more objective and transparent decision-making in hemodialysis patient management.
Implementasi Backup Image VM Pada Proxmox Virtual Environment (Promox VE) Untuk Kebutuhan Server Arman, Molavi; Novan Wijaya
BETRIK Vol. 17 No. 01 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/3zkkvt74

Abstract

Data availability and security are crucial aspects of information technology infrastructure management, especially in virtualization-based server environments. Proxmox Virtual Environment (Proxmox VE), as an open-source virtualization platform, provides Virtual Machine (VM) image backup features that can be used to improve system reliability. However, the implementation of scheduled backups integrated with external storage media has not been widely studied, particularly from the perspective of operational processes and system management. This study aims to describe the implementation of VM image backup on Proxmox VE using the scheduled backup feature combined with the Samba protocol as storage media on a separate server. This study employs a qualitative descriptive approach with the PPDIOO (Prepare, Plan, Design, Implement, Operate, Optimize) methodology as the research framework. Data were collected through system observation, configuration documentation, and analysis of backup operational  processes. System testing was carried out through SMB/CIFS storage access testing, scheduled backup execution testing on selected VMs, Proxmox VE log verification, and inspection of backup files stored on Samba storage. The implementation results show that Samba storage was successfully integrated with Proxmox VE and that the VM image backup process could run automatically according to the configured schedule, with backup files successfully stored on the target media and recorded in the system logs. This implementation improves backup storage reliability, minimizes the risk of data loss, and simplifies backup server management. This study is expected to provide a practical reference for implementing Proxmox VE-based backup servers for system administrators and institutions.
Pengembangan Aplikasi Manajemen Stok Berbasis RUP pada PT Anugerah Pelangi Nusantara Amelia, Siska; Febryan, Migel Orvin; Wijaya, Novan
MDP Student Conference Vol 5 No 2 (2026): The 5th MDP Student Conference 2026
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v5i2.14351

Abstract

A mobile-based inventory management application was developed for PT Anugerah Pelangi Nusantara to improve the accuracy and efficiency of stock management processes. The scope includes system analysis, design, implementation, and testing of an application that manages item data, stock-in and stock-out transactions, and inventory reports. The Rational Unified Process (RUP) methodology was applied through the inception, elaboration, construction, and transition phases. System modeling utilized Unified Modeling Language diagrams, while functional testing employed the black box testing method. The results indicate that the application successfully automates inventory recording, updates stock data in real time, and generates accurate inventory reports. All core system functions operated as expected during testing. Overall, the developed application reduces manual recording errors, accelerates reporting processes, and supports more efficient inventory control within the company.
Penerapan metode RUP dalam pengembangan website booking pada Hotel Sriwidjaya Palembang Az Zahrah, Siti Fatimah; Veraldo, Veraldo; Wijaya, Novan
MDP Student Conference Vol 5 No 2 (2026): The 5th MDP Student Conference 2026
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v5i2.14474

Abstract

The development of information technology encourages hotels to improve their reservation services through digital platforms. Hotel Sriwidjaya Palembang still applies a manual booking process that may cause data inaccuracies and inefficiencies in service delivery. This research aims to implement the RUP (Rational Unified Process) method in developing a web-based hotel booking website to support online reservations and reservation management. The research scope focuses on the system development stages consisting of Inception, Elaboration, Construction, and Transition. The website is developed with features such as room availability information, online booking, and reservation management. The result show that the implementation of the RUP method can produce a structured and functional hotel booking website that improves reservation accuracy and service efficiency. In conclusion, the developed website is expected to assist Hotel Sriwidjaya in managing reservations more effectively and providing better services to customers.
Digitalisasi Sistem Absensi dan Informasi Karyawan di Perusahaan BJIB Johan, Femmy; Verty, Jennifer; Wijaya, Novan
MDP Student Conference Vol 5 No 2 (2026): The 5th MDP Student Conference 2026
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v5i2.14475

Abstract

BJIB still uses manual attendance, which can lead to potential recording errors, delays in recapitulation, and a lack of transparency in attendance data. This study aims to design and build a mobile-based employee service application that supports digital attendance using QR Codes and provides information in the form of employee data and attendance history. This study uses the waterfall method, which includes needs analysis, interface design, implementation using Laravel and MySQL, testing, and maintenance. Testing was carried out on the login feature, attendance entry and exit, and history display. The results of the study show that all features run well and are able to record attendance accurately and present data in real-time. This system improves administrative efficiency, reduces human error, and accelerates the recapitulation process. Thus, the developed application can be an effective solution for BJIB in supporting the digitalization of employee data management.
Co-Authors Adelia Rizky Febriyanti Adit Jansa Akhsani Taqwiym Akhsani Taqwiym Akhsani Taqwiym Aljabbar, Jodi Putra Alyssa Hasyim Ambar Yani, Siti Amirah, Syabina Najla Andrean Tjen andreyas Anisa Rahmawati Anton Wibowo Anugrah Ridwan Arman Pratama, Muhammad Atika, Rindi Az Zahrah, Siti Fatimah Bryant Ansky Cahayadi, Albert Dafid . Daniel Lim Daniel Udjulawa Darmawan, Dean Dedi Ferdinan Manalu Derry Alamsyah Devella, Siska Dicky Pratama Dicky Ryanto Fernandes Effendy, Qrizky Putra Eric Candra Febryan, Migel Orvin Felix Felix Felix Gunawan Firno Justira, Reinkar Georgerius Alesandro Christianto Hafiz Irsyad Hariyadi, Dyon Fillipo Agma Hasibuan, Citra Fadilah Heriyanto Heriyanto Inayatullah, Inayatullah Jefry Jihan Ghassani Johan, Femmy Kamaruddin Sanjaya, Herry Karolina, umi Kelvin Stepanus Kevin Susanto Lee, Raphael Lie, Kenny M Ezar Al Rivan M Rafli M. Gilang, Seftian Maulana Malik, Maulana Mawarni, Marselyna Fitri Meiriyama, Meiriyama Molavi Arman Mughny, Tria Nanda Muhammad Akbar Muhammad Wildan Muhammad, Fadhel Muliawan, Indra Musyaffa, Daffa Yudha Nabil Syawaludin Prima Nabila Nabila Nadya Putri Suryani Nicolas Jacky Pratama Hasan Olivia Patricia, Grace Putri, Dina Lestari Rahmad Firdaus Rajaguguk, M. Rifaldi Febriansyah Riadi, Safina Rizaldy, Alya Putri RR. Ella Evrita Hestiandari Siska Amelia, Siska Steven Tan, Steven Sudarsono, Ariel Suryanto, Serenity Devina Suwanto, Fredy Syeira, Khaerani Tandoballa, Lucky Taqwiym, Akhsani Taqwiym, Akhsani Taqwiym, Akhsani Tinaliah, Tinaliah Tri Buana Ayu Tri Wahyu Cahyo Septa Triana Elizabeth, Triana Veraldo, Veraldo Verta, Marselia Verty, Jennifer Vivin Oktavia Wahyu Putra Satrio Wendy Steven Wulandari, Selvi Putri Yohanes Billy Wicaksono Yohannes, Yohannes