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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) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JISKa (Jurnal Informatika Sunan Kalijaga) JATI (Jurnal Mahasiswa Teknik Informatika) Scientific Journal of Informatics Teknomatika (Jurnal Teknologi dan Informatika) Brilliance: Research of Artificial Intelligence Algoritme Jurnal Mahasiswa Teknik Informatika Green Intelligent Systems and Applications Informatics and Enginering Dedication Jurnal Teknologi Sistem Informasi Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Digital Transformation Technology (Digitech) Publikasi Hasil Pengabdian Kepada Masyarakat. DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY MDP Student Conference Jurnal Sains Student Research 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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Peran Artificial Intelligence dalam Meningkatkan Personalisasi Rekomendasi Produk pada Platform E-Commerce Calvin_Steven Chandra; Novan Wijaya
JURNAL MULTIDISIPLIN ILMU AKADEMIK Vol. 3 No. 3 (2026): JUNI
Publisher : CV. KAMPUS AKADEMIK PUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jmia.v3i3.10364

Abstract

Abstrak. The development of e-commerce platforms has significantly increased the need for personalized recommendation systems. To resolve this issue many studies have applied Artificial Intelligence (AI) methods to improve recommendation personalization. This study reviews research related to the implementation of AI in e-commerce recommendation systems by analyzing 42 publications from 2018 to 2026. The review focuses on collaborative filtering, content-based filtering, hybrid models, reinforcement learning, and Graph Neural Networks (GNNs). Based on the reviewed studies, AI-based recommendation systems provide better performance than traditional rule-based methods, particularly in increasing click-through rates (CTR). Deep learning models process large-scale and sparse interaction data effectively, while Explainable AI (XAI) addresses black-box issues. The findings suggest that future studies should focus on explainable AI and federated learning to improve transparency and data security. Keywords: Artificial Intelligence; Collaborative Filtering; Deep Learning; E-Commerce; Recommendation System Abstrak. Perkembangan pesat e-commerce menghadirkan tantangan dalam menyajikan rekomendasi produk yang personal. Studi ini mengkaji bagaimana teknologi Artificial Intelligence (AI) dapat digunakan untuk mengatasi masalah tersebut. Dengan metode Systematic Literature Review (SLR) terhadap 42 artikel ilmiah (2018-2026), kami meninjau pendekatan collaborative filtering, content-based filtering, model hybrid, reinforcement learning, dan Graph Neural Networks (GNN). Hasil analisis menunjukkan implementasi AI mampu meningkatkan click-through rate (CTR) dan konversi penjualan secara signifikan dibandingkan sistem tradisional. Model deep learning terbukti efektif memproses data berskala besar yang sparse, sementara Explainable AI (XAI) menjadi solusi mutakhir menerjemahkan prediksi algoritma agar transparan. Tinjauan ini menemukan kendala seperti cold-start problem, privasi data, dan bias algoritma. Ke depannya, riset ini merekomendasikan eksplorasi pengembangan federated learning dan explainable AI. Kata Kunci: Artificial Intelligence; Collaborative Filtering; Deep Learning; E-Commerce; Sistem Rekomendasi
Analisis Tingkat Literasi Artificial Intelligence pada Mahasiswa Menggunakan Instrumen SNAILS Michael Felix Chandra; Novan Wijaya
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 1 (2026): Juni 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i1.1085

Abstract

Perkembangan teknologi Artificial Intelligence pada era digital saat ini memberikan kemudahan bagi kita dalam berbagai bidang. Penerapan AI telah dimanfaatkan penggunaan secara luas dari berbagai sektor khususnya di bidang akademik. Tetapi, tingginya penggunaan teknologi AI tidak selaras dengan tingkat literasi Artificial Intelligence yang memadai. Hal ini menunjukkan bahwa pentingnya pemahaman mahasiswa terhadap pemanfaatan teknologi tersebut agar dapat digunakan secara lebih tepat, kritis, dan bertanggung jawab. Sehingga penelitian ini bertujuan dalam menganalisis tingkat literasi AI kepada mahasiswa dengan latar belakang teknologi menggunakan instrumen SNAILS (Scale for the Assessment of Non-Experts AI Literacy). Dalam instrumen tersebut terdapat dimensi Technical Understanding, Crictical Appraisal, serta Practical Application. Pada penelitian ini menggunakan metode deskriptif kuantitatif dengan teknik pengumpulan data yaitu kuesioner yang diikuti sebanyak 58 responden melalui Google Form. Analisis data menggunakan statistika deskriptif berupa mean dan standar deviasi. Secara keseluruhan item pernyataan, didapatkan bahwa hasil penelitian untuk dimensi Technical Understanding mendapat nilai mean 4,98 dan standar deviasi 1,39, Crictical Appraisal mendapat nilai mean 5,78 dan standar deviasi 1,08, serta Practical Application mendapat nilai mean 5,66 dan standar deviasi 1,13. Sehingga hasil dari penelitian menunjukkan bahwa mahasiswa memiliki tingkat literasi AI yang cukup baik dalam memahami, mengevaluasi, dan menerapkan teknologi AI dalam aktivitas akademik maupun kehidupan sehari-hari.
Penerapan Artificial Intelligence Pada Sistem E-Learning Di Perguruan Tinggi Erika Putri Say; Novan Wijaya
JOURNAL SAINS STUDENT RESEARCH Vol. 4 No. 4 (2026): Agustus: Jurnal Sains Student Research
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jssr.v4i4.11218

Abstract

The use of artificial intelligence (AI) in online learning (e-learning) systems at universities is currently a critical topic, as traditional systems are considered too one-sided and unable to adequately accommodate the unique learning styles of individual students. However, if not carefully managed, the use of AI could threaten the security of students’ personal data and undermine their ability to think critically. This study aims to summarize and map out the best strategies to ensure that the implementation of AI on campus can proceed safely, effectively, and fairly. The method used in this study is a Systematic Literature Review (SLR), which examined 10 indexed scientific articles published from 2020 to 2026. The results show that AI has been proven to help students by increasing their daily self-study hours by up to 52% and raising their average exam scores by 15%. On the other hand, excessive reliance on AI also has negative consequences, such as making students reluctant to think critically, increasing the risk of cheating or plagiarism, creating vulnerabilities to data breaches online, and reducing face-to-face social interaction on campus. As a solution, universities are advised to strengthen their cybersecurity systems, shift from rote-memorization exams to practical assessments such as e-portfolios and group project assignments, and improve faculty members’ digital teaching skills.
KLASIFIKASI TINGKAT KEMATANGAN BUAH KAKAO MENGGUNAKAN EFFICIENTNET-B7 Wilcent Wilcent; Novan Wijaya
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 10 No. 1 (2026): JATI Vol. 10 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v10i1.16756

Abstract

Kakao (Theobroma cacao L.) merupakan salah satu komoditas penting bagi perekonomian Indonesia karena berperan dalam sektor perkebunan dan industri olahan cokelat. Penentuan tingkat kematangan buah kakao memiliki peran penting dalam menjaga kualitas biji kakao dan hasil olahan cokelat, yang secara langsung memengaruhi nilai jual dan mutu produksi. Namun, proses penilaian kematangan buah kakao di tingkat petani masih banyak dilakukan secara manual melalui pengamatan visual, sehingga bersifat subjektif dan sering menimbulkan ketidakkonsistenan dalam penentuan waktu panen. Penelitian ini bertujuan untuk mengembangkan sistem klasifikasi tingkat kematangan buah kakao yang lebih akurat, objektif, dan efisien menggunakan arsitektur EfficientNet-B7. Penelitian ini menggunakan dataset CocoaMFDB yang terdiri dari citra buah kakao dengan dua kelas, yaitu mature dan unmature. Tahapan penelitian meliputi preprocessing citra berupa resizing, normalisasi, dan augmentasi data, kemudian dilanjutkan dengan pelatihan model menggunakan pendekatan transfer learning dan fine-tuning masing-masing selama 25 epoch. Hasil pengujian menunjukkan bahwa model EfficientNet-B7 mampu mencapai akurasi sebesar 98,41% dengan nilai precision, recall, dan F1-score masing-masing sebesar 0,98 pada kedua kelas. Hasil ini menunjukkan kemampuan generalisasi model yang sangat baik dan membuktikan bahwa EfficientNet-B7 efektif digunakan dalam klasifikasi tingkat kematangan buah kakao
Pengembangan Aplikasi Manajemen Stok Berbasis RUP pada PT Anugerah Pelangi Nusantara Siska Amelia; Migel Orvin Febryan; Novan Wijaya
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 Siti Fatimah Az Zahrah; Veraldo Veraldo; Novan Wijaya
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 Femmy Johan; Jennifer Verty; Novan Wijaya
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.
Aplikasi Pengelolaan Tagihan Pembeli pada CV Apolindo Jaya Semesta Menggunakan Metode RUP Serenity Devina Suryanto; Dina Lestari Putri; Novan Wijaya
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.v5i2.14481

Abstract

This project aims to develop a buyer bill management application at CV Apolindo Jaya Semesta in Mobile form in order to overcome the shortcomings and problems of manual management methods and help companies manage buyer bills quickly and efficiently. This project focuses on project initialization, designing user interface designs and UML Use Case diagrams, and testing with the Black Box Testing method and users who use the application are admins and company leaders. The method used is the Rational Unified Process (RUP) which organizes the project iteratively and gradually. The results of this project development show that this application is proven to be able to solve the company's problems and shortcomings with a test result rate of 100%, can solve 90% of manual problems, save time by 70%, and costs up to 60%, although there are still opportunities for further development in the aspect of expanding features and application coverage.
Pengembangan Aplikasi Scanning Barcode untuk Manajemen Stok pada Kantin Alwi College Felix Gunawan; Fadhel Muhammad; Novan Wijaya
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.v5i2.14503

Abstract

Manual stock recording in small-scale canteens often causes data inaccuracy, inefficiency, and difficulties in monitoring inventory levels. This study aims to develop a barcode scanning-based application for inventory management at Alwi College canteen. The application enables administrators to identify items through barcode scanning and update incoming stock data automatically. The system was developed using the Agile methodology to support iterative development and continuous user feedback. UML diagrams were used to model the system, including use case, activity, sequence, and class diagrams. The results show that the application improves the accuracy and efficiency of stock recording, simplifies item classification, and supports real-time stock monitoring. Black box testing indicates that all main features function properly.
Perancangan dan Pembangunan Aplikasi Mobile Manajemen Stok Material Proyek untuk CV Lingga Ariel Sudarsono; Raphael Lee; Novan Wijaya
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.v5i2.14519

Abstract

Amidst rapid digital development, the need for an efficient material management system has become increasingly important. This study aims to design and develop a mobile application for managing project material stock at CV Lingga. The previously used paper-based manual recording system caused various issues, including data inaccuracies, delays in information delivery, and difficulties in monitoring stock in real time. The development method applied in this study is the Waterfall model, which consists of requirements analysis, system design, implementation, and testing stages. The developed application provides project management features, recording of incoming and outgoing materials, and weekly report generation. The implementation of the system is proven to improve data accuracy, accelerate administrative processes, and facilitate centralized, real-time material stock monitoring.
Co-Authors Adelia Rizky Febriyanti Adit Jansa Akhsani Taqwiym Akhsani Taqwiym Akhsani Taqwiym Albert Cahayadi Aljabbar, Jodi Putra Alyssa Hasyim Amirah, Syabina Najla Andrean Tjen andreyas Anisa Rahmawati Anton Wibowo Anugrah Ridwan Ariel Sudarsono Atika, Rindi Attallah, Muhammad Syauqi Bryant Ansky Calvin_Steven Chandra Chandra, Yeremia Agung Daffa Yudha Musyaffa Dafid . Daniel Lim Daniel Udjulawa Darmawan, Dean Dedi Ferdinan Manalu Derry Alamsyah Devella, Siska Dicky Pratama Dicky Ryanto Fernandes Dina Lestari Putri Earlando Moza Effendy, Qrizky Putra Entarisa Asma Kartika Eric Candra Erika Putri Say Fadhel Muhammad Felix Felix Felix Gunawan Femmy Johan Ferry Salim, Nicklause Felix Georgerius Alesandro Christianto Hafiz Irsyad Hariyadi, Dyon Fillipo Agma Hartono, Jeremy Allegrato Hasibuan, Citra Fadilah Heriyanto Heriyanto Inayatullah Inayatullah Jefry Jennifer Verty Jeremy Allegrato Hartono Jhonsen, Rio Jihan Ghassani Kamaruddin Sanjaya, Herry Karolina, umi Kelvin Stepanus Kevin Susanto Lie, Kenny M Rafli M. Gilang, Seftian Marselia Verta Maulana Malik Mawarni, Marselyna Fitri Meiriyama, Meiriyama Michael Felix Chandra Migel Orvin Febryan Molavi Arman Mughny, Tria Nanda Muhammad Akbar Muhammad Arman Pratama Muhammad Dzaky Raihan Muhammad Ezar Al Rivan Muhammad Syauqi Attallah Muhammad Wildan Muliawan, Indra Nabil Syawaludin Prima Nabila Nabila Nadya Putri Suryani Nicklause Felix Ferry Salim Nicolas Jacky Pratama Hasan Olivia Pambudi, Readysna Krisna Patricia, Grace Raden George Samuel Budi Rajaguguk, M. Rifaldi Febriansyah Raphael Lee Reinkar Firno Justira Riadi, Safina Rio Jhonsen Rizaldy, Alya Putri RR. Ella Evrita Hestiandari Serenity Devina Suryanto Siska Amelia Siti Ambar Yani Siti Fatimah Az Zahrah Steven Tan, Steven Suwanto, Fredy Tandoballa, Lucky Taqwiym, Akhsani Taqwiym, Akhsani Taqwiym, Akhsani Tinaliah, Tinaliah Tri Buana Ayu Tri Wahyu Cahyo Septa Triana Elizabeth, Triana Veraldo Veraldo Vivin Oktavia Wahyu Putra Satrio Wendy Steven Wilcent Wilcent Wulandari, Selvi Putri Yeremia Agung Chandra Yohanes Billy Wicaksono Yohannes, Yohannes