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All Journal Semantik TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer Pro Bisnis Telematika Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Jurnal Pilar Nusa Mandiri JITK (Jurnal Ilmu Pengetahuan dan Komputer) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan ILKOM Jurnal Ilmiah JURTEKSI Jurnal Teknologi Terpadu Building of Informatics, Technology and Science Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal Pendidikan dan Teknologi Indonesia JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Algoritma Electronic Journal of Education, Social Economics and Technology Jurnal Informatika: Jurnal Pengembangan IT Journal of Informatics and Interactive Technology (JIITE) Journal of Digital Market and Digital Currency
Fandy Setyo Utomo
Universitas AMIKOM Purwokerto
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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MUSIC RECOMMENDATION SYSTEM BASED ON COSINE SIMILARITY AND SUPERVISED GENRE CLASSIFICATION Jamie Mayliana Alyza; Fandy Setyo Utomo; Yuli Purwati; Bagus Adhi Kusuma; Mohd Sanusi Azmi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 9 No. 1 (2023): JITK Issue August 2023
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v9i1.4324

Abstract

Categorizing musical styles can be useful in solving various practical problems, such as establishing musical relationships between songs, similar songs, and finding communities that share an interest in a particular genre. Our goal in this research is to determine the most effective machine learning technique to accurately predict song genres using the K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM) algorithms. In addition, this article offers a contrastive examination of the K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM) when dimensioning is considered and without using Principal Component Analysis (PCA) for dimension reduction. MFCC is used to collect data from datasets. In addition, each track uses the MFCC feature. The results reveal that the K-Nearest Neighbors and Support Vector Machine offer more precise results without reducing dimensions than PCA results. The accuracy of using the PCA method is 58% and has the potential to decrease. In this music genre classification, K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM) are proven to be more efficient classifiers. K-Nearest Neighbors accuracy is 64,9%, and Support Vector Machine (SVM) accuracy is 77%. Not only that, but we also created a recommender system using cosine similarity to provide recommendations for songs that have relatively the same genre. From one sample of the songs tested, five songs were obtained that had the same genre with an average accuracy of 80%.
Rectified Linear Units and Adaptive Moment Estimation Optimizer on ANN with Saved Model Prediction to Improve The Stock Price Prediction Framework Performance Sekhudin Sekhudin; Yuli Purwati; Fandy Setyo Utomo; Mohd Sanusi Azmi; Pungkas Subarkah
ILKOM Jurnal Ilmiah Vol 15, No 2 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i2.1586.271-282

Abstract

A stock is a high-risk, high-return investment product. Prediction is one way to minimize risk by estimating future prices based on past data. There are limitations to solving the stock prediction problem from previous research: limited stock data, practical aspects of application, and less than optimal stock price prediction results. The main objective of this study is to improve the prediction performance by formulating and developing the stock price prediction framework. Furthermore, the research provides a stock price prediction framework that can produce better prediction results than the previous study with fast computation time. The proposed framework deals with data generation, pre-processing and model prediction. In further, the proposed framework includes two prediction methods for predicting stock closing prices: stored model prediction and current model prediction. This study uses an artificial neural network with Rectified Linear Units as an activation function and Adam Optimizer to predict stock prices. The model we have built for each forecasting method shows a better MAPE value than the model in previous studies. Previous research showed that the lowest MAPE was 1.38% for TLKM shares and 0.81% for BBRI. Our proposed framework based on the stored model prediction method shows a MAPE value of 0.67% for TLKM shares and 0.42% for BBRI. While the current model prediction method shows a MAPE value of 0.69% for TLKM shares and 0.89% for BBRI. Furthermore, the stored model prediction method takes 1.0 seconds to process a single prediction request, while the current model prediction takes 220 seconds.
AN INNOVATIVE LEARNING ENVIRONMENT: G-MOOC 4D TO ENHANCE VISUAL IMPAIRMENTS LEARNING MOTIVATION Rujianto Eko Saputro; Berlilana Berlilana; Wiga Maulana Baihaqi; Sarmini Sarmini; Yuli Purwati; Fandy Setyo Utomo
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 9 No. 2 (2024): JITK Issue February 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v9i2.5037

Abstract

The proliferation of visual impairment among school-age children in Indonesia has prompted the need for specialized online learning solutions. The G-MOOC 4D platform, a novel Learning Management System (LMS), is designed to address this need by leveraging gamification and artificial intelligence to enhance accessibility for visually impaired users. This study reports on the development and testing of two AI models within the G-MOOC 4D framework: a facial recognition model for secure user authentication and a voice command model for interactive learning. User Acceptance Testing (UAT), conducted with expert users, namely teachers at a special needs school, showed high approval rates for the platform's features. The results show that all metrics, accuracy, precision, and recall reach their optimal values at a distance of 40 cm for face detection. The respective metric scores at that distance, precision: 100%, accuracy: 98%, and recall: 97%. Additionally, the voice command functionality tested achieved a 100% recognition rate, reflecting the platform’s potential to significantly ease the learning process for visually impaired students. The findings underscore the importance of integrating assistive technologies into educational platforms to ensure all students have equal access to learning opportunities.
K-MEANS ALGORITHM TO DETERMINE MARKETING STRATEGY AT CODEVERSE COMPUTER ACCESSORIES STORE Muhamad Naufal Burhanuddin Balit; Fandy Setyo Utomo
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 10, No 2 (2024): Maret 2024
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i2.3064

Abstract

Abstract: Artificial Intelligence (AI) is currently gaining popularity across various industries, including healthcare, finance, and others. In this study, AI technology is employed to devise an optimal marketing strategy for Code Verse Computer Accessories Store using the K-Means algorithm. As part of machine learning, the K-Means algorithm, categorized under unsupervised learning, is implemented to cluster sales data for computer accessory products over the last three months of 2023. The results of the K-Means analysis identify two main clusters. Cluster one (Cluster 1) comprises products such as Mouse, Keyboard, Monitor, Headset, and Speaker, indicating consistent purchasing patterns and high consumer interest. Recommendations are made to increase stock for Cluster 1. Meanwhile, Cluster two (Cluster 2) consists of Mic products with lower interest, and it is not advisable to increase stock. The implementation of K-Means provides insights into purchasing patterns, enabling Code Verse to develop more effective marketing and inventory management strategies. Keywords: K-Means algorithm; artificial intelligence; clustering  Abstract: Kecerdasan Buatan (AI) kini meraih popularitas dalam berbagai industri, termasuk sektor kesehatan, keuangan, dan lainnya. Pada penelitian ini, teknologi AI digunakan untuk merancang strategi pemasaran optimal bagi Toko Aksesoris Komputer CodeVerse dengan menggunakan Algoritma K-Means. Sebagai bagian dari machine learning, Algoritma K-Means, yang termasuk dalam kategori unsupervised learning, diimplementasikan untuk mengelompokkan data penjualan produk selama tiga bulan terakhir tahun 2023. Hasil dari analisis K-Means mengidentifikasi dua cluster utama. Cluster pertama (Cluster 1) terdiri dari produk Mouse, Keyboard, Monitor, Headset, dan Speaker, menunjukkan pola pembelian yang konsisten dan tingginya minat konsumen. Rekomendasi untuk menambah stok diberikan. Sementara itu, Cluster kedua (Cluster 2) terdiri dari produk Mic dengan minat lebih rendah, dan tidak disarankan untuk menambah stok. Implementasi K-Means memberikan wawasan tentang pola pembelian, memungkinkan CodeVerse mengembangkan strategi pemasaran dan manajemen persediaan yang lebih efektif.            Keywords: Algoritma k-means; kecerdasan buatan; clustering
COMPARATIVE ANALYSIS OF EXPONENTIAL SMOOTHING MODELS FOR SALES PREDICTION AND SUPPLY MANAGEMENT IN E-COMMERCE Aji Saeful; Fandy Setyo Utomo; Yuli Purwati; Mohd Sanusi Azmi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 1 (2024): JITK Issue August 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i1.5035

Abstract

In the growing era of e-commerce, stock management is crucial. Problems arise in forecasting sales in order to achieve effective stock management. This research uses the time series analysis method by focusing on comparing the accuracy of three forecasting methods: Single Exponential Smoothing (SES), Double Exponential Smoothing (DES), and Triple Exponential Smoothing (TES/Holt-Winter). This research provides a solution by comparing the performance of the three methods based on the Mean Absolute Error (MAE) results and prediction graphs. The goal is to determine the most accurate forecasting method using the time series analysis method with several stages, namely data preprocessing, train/test split, modeling, and performance metrics measurement. based on the test results show MAE SES 1077, DES 96, and TES (Holt-Winter) 101. Although DES has a lower MAE, TES (Holt-Winter) provides better accuracy, especially through prediction graph analysis. Holt-Winter is recognized as the most effective method in forecasting future sales, reliable for proper stock management in the dynamic e-commerce industry. This approach is expected to improve efficiency and accuracy in enterprise stock management, support the growth of online businesses, and contribute to the literature and practice of stock management. The use of time series analysis methods, especially Holt-Winter, is considered an important strategic step to optimize sales prediction, positively impact stock management, and create a competitive advantage in a growing market
Analisis dan Perancangan Antarmuka Aplikasi Wisata Menggunakan Metode User Centered Design (UCD) Purbo, Yevi Septiray; Utomo, Fandy Setyo; Purwati, Yuli
Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v9i2.977

Abstract

Lampung has many tourist attractions and natural areas that attract the attention of tourists, both domestic and foreign. However, there are still challenges in optimizing Lampung's tourism potential. One of the challenges is limited access to information regarding tourist destinations, accommodation and available activities. Apart from that, coordination between tourists and related parties such as destination managers and tourism services also need to be improved. To overcome this problem, a prototype of the VACALAM (Vacation Lampung) application was designed using Figma with the User-Centered Design (UCD) method. This research aims to increase user comfort and satisfaction in using the Vacalam application and encourage tourists to visit Lampung. In this application there are several features including ticket booking features, tour lists, trending tours, and a list of events in Lampung. The results of this research are user interface designs that follow good design principles, including simplicity, consistency, and readability. The use of colors, typography, and icons are also considered to improve the clarity and visual appearance of the application. The good user interface design and user experience have been tested using the System Usability Scale (SUS), with a final score of 71.75. These results provide guidance for other application developers in designing engaging and responsive user interfaces and user experiences using Figma.
Desain Aplikasi Mobile Smart Farming dengan Pendekatan Design Thinking untuk Meningkatkan Produktivitas Pertanian Muaziz, Imam; Utomo, Fandy Setyo; Krisbiantoro, Dwi; Setiawan, Ito
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 12, No 2 (2024)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v12i2.75319

Abstract

Di era transformasi digital, sektor pertanian Indonesia masih dihadapkan dengan sejumlah, seperti produktivitas yang rendah, kualitas produk yang   buruk, dan kurangnya akses informasi dan teknologi, hal ini menyebabkan dampak negatif   yang cukup signifikan terhadap produktivitas pertanian, oleh karena itu penerapan smart farming sebagai sistem pertanian yang memanfaatkan teknologi informasi dan komunikasi (TIK), dapat menjadi solusi untuk meningkatkan kualitas dan produktivitas pertanian. Fokus   penelitian ini adalah perancangan desain User Interface (UI) dan User Experience (UX) untuk aplikasi mobile smart farming. Penelitian ini menggunakan metode design thinking   yang meliputi empathize, define, ideate, prototype, dan testing. Pengujian dilakukan dengan   wawancara langsung dan kuisioner Single   East   Question (SEQ), dan dihitung menggunakan System Usability Scale (SUS), hasil pengujian memperoleh rata-rata 85.5, dimana angka ini menunjukkan bahwa desain UI/UX telah memenuhi kebutuhan pengguna dengan baik. Dengan demikian penerapan metode design thinking membantu pengembang aplikasi dalam memahami kebutuhan pengguna untuk menciptakan solusi yang tepat sebelum aplikasi disebarluaskan.
DEVELOPMENT OF CINEVERSE FILM WEBSITE UTILIZING THEMOVIEDB'S API FOR DYNAMIC CONTENT MANAGEMENT Fadhilah, Siti Nur; Utomo, Fandy Setyo
Jurnal Pilar Nusa Mandiri Vol. 20 No. 1 (2024): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v20i1.5210

Abstract

The development of websites in this digital era is crucial to creating captivating and relevant online experiences. The combination of server-side programming and client-side technologies along with MySQL database management forms the foundation for a dynamic user interface emphasizes the significance of integrating various technologies to achieve this goal. This project involves the use of PHP, HTML, CSS, JavaScript, and MySQL, with the integration of The Movie Database (TMDB) API, showcasing the intricate fusion of creativity, technical prowess, and data integration. The resulting website offers a comprehensive list of films with detailed information and posters, enhancing the user experience and making it an essential read for those interested in crafting immersive online experiences. The abstract of this research aims to explore the process of website development using diverse technologies and data integration and to analyze its impact on user experience. By examining aspects such as security, performance, and routine maintenance, this study aims to provide in-depth insights into producing captivating and relevant online experiences in the context of modern web development.
Implementasi Metode Design Thinking dalam Proses Perancangan Desain UI/UX Aplikasi “Rumah Tani” Purwanto, Dedi; Fandy Setyo Utomo
Journal of Informatics and Interactive Technology Vol. 1 No. 1 (2024): April
Publisher : ACSIT

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63547/jiite.v1i1.15

Abstract

Pertanian merupakan salah satu sektor penting dalam mencukupi kebutuhan pangan bagi suatu negara. Namun seiring berjalannya waktu permasalahan seputar pertanian semakin meningkat sehingga dapat menjadi ancaman ketahanan pangan suatu negara. Salah satu permasalahan yang dihadapi oleh petani di Indonesia khususnya di daerah pedesaan adalah rendahnya informasi dan pengetahuan yang petani dapatkan mengenai teknologi terutama dalam bidang pertanian. Dalam upaya meningkatkan pemahaman petani mengenai teknologi, pengembangan aplikasi mobile menjadi salah satu solusi yang dapat digunakan. Perancangan desain aplikasi mobile harus memperhatikan kebutuhan pengguna agar aplikasi yang dikembangkan sesuai dengan harapan pengguna. Metode yang digunakan dalam perancangan aplikasi “Rumah Tani” ini adalah Design Thinking. Dengan menggunakan metode tersebut penelitian ini menggali permasalahan yang dihadapi pengguna, sudut pandang pengguna, mengidentifikasi permasalahan, menciptakan sebuah solusi, serta menguji prototipe dari aplikasi ini. Hasil penelitian ini menunjukan bahwa penggunaan metode design thinking dapat menghasilkan UI/UX yang lebih responsif, dan berfokus pada pengguna.
Program pendampingan pemilihan jurnal dan teknik submit artikel ilmiah melalui OJS bagi mahasiswa Fakultas Ilmu Komputer Universitas Amikom Purwokerto Fandy Setyo Utomo; Afit Ajis Solihin; Rifqi Arifin Ilham
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 8, No 3 (2024): September
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v8i3.26081

Abstract

AbstrakPermasalahan yang dihadapi oleh mitra sasaran, yakni Fakultas Ilmu Komputer Universitas Amikom Purwokerto adalah rendahnya jumlah publikasi ilmiah yang dihasilkan oleh mahasiswa program sarjana dan magister sebagai luaran matakuliah. Berdasarkan permasalahan tersebut, kami memberikan solusi menyelenggarakan program pendampingan strategi pemilihan jurnal penelitian dan teknik submit artikel ilmiah melalui open journal systems bagi mahasiswa fakultas ilmu komputer. Target yang diharapkan dari program ini, yakni mahasiswa Fakultas Ilmu Komputer memiliki pemahaman dan berkemampuan untuk memilih target jurnal yang tepat sesuai dengan artikel ilmiah yang mereka tulis, mampu memahami persyaratan dan teknik tata tulis dari jurnal yang ditargetkan, serta mampu mengirimkan artikel ilmiah melalui OJS dengan benar. Berdasarkan target luaran yang telah ditetapkan, metode pengabdian masyarakat yang digunanakan dalam program ini mencakup 3 tahap utama, yaitu tahap persiapan kegiatan, implementasi kegiatan, dan pelaporan kegiatan. Setelah mengimplementasikan solusi yang diusulkan, kami mengevaluasi kemampuan peserta program pendampingan dalam memahami kriteria pemilihan jurnal ilmiah dan teknik submit artikel ilmiah melalui OJS. Hasil evaluasi menunjukkan bahwa 97% peserta mampu memahami kriteria pemilihan jurnal penelitian dan 94% mampu memahami teknik submit artikel ilmiah melalui OJS. Kata kunci: pendampingan; jurnal penelitian; artikel ilmiah; open journal system; OJS AbstractThe problem faced by our target partner, the Faculty of Computer Science at Universitas Amikom Purwokerto, is the low number of scientific publications produced by undergraduate and graduate students as course outputs. To address this issue, we proposed a mentoring program on strategies for selecting research journals and techniques for submitting scientific articles through open journal systems for computer science students. The expected outcome of this program is that the students of the Faculty of Computer Science will have the understanding and ability to select appropriate target journals for their scientific articles, understand the requirements and writing techniques of the targeted journals, and be able to submit their articles through OJS correctly. Based on the established outcome targets, the community service method used in this program includes three main stages: activity preparation, activity implementation, and activity reporting. After implementing the proposed solution, we evaluated the participants' ability to understand the criteria for selecting scientific journals and the techniques for submitting articles through OJS. The evaluation results showed that 97% of participants were able to understand the criteria for selecting research journals, and 94% were able to understand the techniques for submitting scientific articles through OJS. Keywords: mentoring; research journal; scientific article; open journal system; OJS
Co-Authors Adiatma, Febriansyah Husni Adiya, Az Zahra Dwi Nur Afit Ajis Solihin Aisha Hukama Setyowati Aji Saeful Aji Septa, Adrian Ajis Solihin, Afit Amar Al Farizi Anas Nur Khafid Anggini, Melisa Anggraeni, Mutia Dwi Anggraini, Nova Anggriani, Epri Azhari Shouni Barkah Azmi, Mohd Sanusi Bagus Adhi Kusuma Baihaqi, Wiga Maulana Balit, Muhamad Naufal Burhanuddin Berlilana Berlilana Berlilana Burhanuddin Balit, Muhamad Naufal Churil Aeni, Agustina Chyntia Raras Ajeng Widiawati Darmono Dedi Purwanto, Dedi Didi Prasetyo Dwi Krisbiantoro, Dwi Dzaky Candy Fahrezy Fadhilah, Siti Nur Filanzi, Shendy Giat Karyono Giat Karyono Hanif Hidayatulloh Hendra Marcos, Hendra hidayatulloh, hanif Ilham, Rifqi Arifin Imam Tahyudin Indriyani, Ria Jamie Mayliana Alyza Kafilla, Princess Iqlima Kusuma, Bagus Adhi Kusuma, Velizha Sandy Lasmedi Afuan Lubna, Zuhriyatul Lukita, Dita Maharani, Titi Safitri Maulana Baihaqi, Wiga Mohd Fairuz Iskandar Othman Mohd Nazrin Muhammad Mohd Sanusi Azmi Muaziz, Imam Muhamad Naufal Burhanuddin Balit Muhtyas Yugi Murtiyoso Murtiyoso Nandang Hermanto Nanna Suryana Nikmah Trinarsih Nugroho, Khabib Adi Nur Cholis Romadhon Octavia, Annisa Suci Prayoga, Fandhi Dhuga Pungkas Subarkah Purbo, Yevi Septiray Purwidiantoro, Moch. Hari Putranto, R. Vitto Mahendra Pyawai, Hero Galuh Ramadhan, Aziz Ramadhan, Rio Fadly Rifqi Arifin Ilham RR. Ella Evrita Hestiandari Rujianto Eko Saputro Safitri Maharani, Titi Sagita, Selvi Samsul Arifin Sarmini - Sarmini Sarmini Sarmini Sekhudin Sekhudin Setiabudi, Rizki Setiawan, Ito Shafira, Lulu Slamet Widodo Sofa, Nur Sri Hartini Subarkah, Pungkas Suryana, Nanna Trinarsih, Nikmah Turino, Turino Utomo, Dadang Wahyu Wahid, Arif Mu'amar Wibisono, Arif Cahyo Wiga Maulana Baihaqi Yuli Purwat Yuli Purwati Yulianto, Koko Edy