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All Journal Jurnal Informatika dan Teknik Elektro Terapan CESS (Journal of Computer Engineering, System and Science) Informatics for Educators and Professional : Journal of Informatics Network Engineering Research Operation [NERO] KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Indonesian Journal of Applied Informatics Antivirus : Jurnal Ilmiah Teknik Informatika Jurnal ICT : Information Communication & Technology Jurnal Sistem Informasi Kaputama (JSIK) JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Informatika dan Rekayasa Perangkat Lunak JSR : Jaringan Sistem Informasi Robotik JURSIMA (Jurnal Sistem Informasi dan Manajemen) JATI (Jurnal Mahasiswa Teknik Informatika) JIKA (Jurnal Informatika) MEANS (Media Informasi Analisa dan Sistem) Jurnal Teknik Informatika (JUTIF) Jurnal Mahasiswa Sistem Informasi (JMSI) International Journal of Social Science Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Jurnal Janitra Informatika dan Sistem Informasi Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) INFORMATIKA Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Mahasiswa Ilmu Komputer TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Wawasan : Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahaan Manajemen Kreatif Jurnal JURSIMA Jurnal Ekonomi Manajemen Akuntansi BULLET : Jurnal Multidisiplin Ilmu AMMA : Jurnal Pengabdian Masyarakat NERO (Networking Engineering Research Operation) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Sistem Informasi dan Manajemen INTERNAL (Information System Journal) Intechno Journal : Information Technology Journal
Yudhistira Arie Wijaya
STMIK IKMI Cirebon
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Digitalisasi Administrasi Desa Melalui Pelatihan Pengelolaan Data Berbasis Sistem Informasi Willy Prihartono; Yudhistira Arie Wijaya; Arya Hadi Wicaksana; Astri Amelia
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 4 (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Digitalization of village administration is a solution to improve the efficiency and transparency of data management at the village level. This transformation allows village governments to manage information more systematically, reduce administrative errors, and improve services to the community. This research focuses on training on data management based on information systems implemented in villages, to provide village officials with an understanding of the importance of digitization in governance. The method used in this training includes a participatory approach with a combination of theory and hands-on practice in the use of information systems. The results of the training showed that the majority of participants experienced improved understanding and skills in operating digital systems for village administration. The implementation of digitalization also contributed to improving transparency, data accuracy, and accelerating the process of administrative services to village communities. The challenges faced include limited technological infrastructure, resistance to change, and the need for continuous assistance. Therefore, policies that support the development of human resource capacity and investment in information technology infrastructure in villages are needed. Thus, the digitization of village administration can run optimally and sustainably to support technology-based village development.
Digitalisasi Administrasi Desa Melalui Pelatihan Pengelolaan Data Berbasis Sistem Informasi Yudhistira Arie Wijaya; Tati Suprapti; Athaullah Abrar Bayan; Beby Maryam
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 4 (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

The rapid development of information technology has encouraged educational institutions and village government institutions to improve the efficiency of administrative services, one of which is in terms of recording attendance. This research aims to develop a QR Code-based attendance system implemented for schools and village institutions as a solution to the manual attendance system that is still vulnerable to fraud and inefficiency. The system development method used is the waterfall method which includes the stages of needs analysis, system design, implementation, testing, and maintenance. This system is designed using PHP programming language and MySQL database, and integrated with QR Code technology that allows users to scan through mobile devices. The test results show that this system is able to record attendance in real-time, generate reports automatically, and improve the accuracy and efficiency of the attendance process. Users also responded positively to the system's simple and easy-to-use interface. With this system, educational institutions and villages can manage attendance data more effectively and transparently. In conclusion, this QR Code-based attendance system is a relevant and applicable innovation in supporting administrative digitization at the local level. This research is expected to be a reference for the development of similar systems in other environments.
Optimalisasi Infrastruktur Jaringan Internet Desa untuk Mendukung Digitalisasi UMKM dan Pendidikan Willy Prihartono; Yudhistira Arie Wijaya; Aliya Anisa Rahma; Irma Agustina
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 04 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Digital transformation is a crucial element in improving the quality of education and developing Micro, Small and Medium Enterprises (MSMEs), especially in rural areas. However, limited internet network infrastructure is a major challenge that must be overcome. This research aims to identify problems and propose strategies for optimizing village internet networks to support the digitalization of the education sector and MSMEs. The method used was direct observation in Ketapanrame Village, Trawas District, Mojokerto Regency, as well as a literature study approach to network technology solutions. The results showed that although the availability of internet networks already exists, the quality and equity of access is still low. Therefore, it is necessary to strengthen the infrastructure through increasing bandwidth, placing strategic access points, and utilizing technologies such as wireless mesh networks (WMN). In addition, community empowerment through digital literacy training is also very important to ensure optimal utilization of the available infrastructure. The implementation of this strategy is expected to encourage the improvement of the quality of digital-based learning and expand the MSME market through online platforms. Optimizing village internet networks is not only about technical aspects, but also includes strengthening human resource capacity and local government policy support. Thus, the digitization of education and MSMEs can be an important pillar in the economic and social development of villages.
Pelatihan Penggunaan Smartphone dan Aplikasi Komunikasi Digital untuk Peningkatan Kompetensi Lansia Yudhistira Arie Wijaya; Riri Narasati; Mifta Almaripat; Mita Amelia
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 04 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Advances in digital technology have had a significant impact in various aspects of life, including for the elderly. However, limited digital knowledge and skills cause many elderly people to not be able to utilize technology optimally. This community service activity aims to improve the digital competence of the elderly through training on the use of smartphones and daily communication applications such as WhatsApp and Google Meet. The methods used include a participatory approach, direct assistance, and repeated practice of using digital applications in a friendly and fun atmosphere. The activity was carried out at Posyandu Lansia Kelurahan Jatimakmur, Bekasi, involving 30 elderly participants aged 60-75 years. The results of the activity showed a significant improvement in the participants' ability to use smartphones, access communication applications, and understand digital communication ethics. Evaluation was conducted through pre-test and post-test, as well as direct observation during the training. The majority of participants stated that they felt more confident and motivated to continue learning to use technology. Supporting factors for the success of this activity included the personal approach, the patience of the facilitators, and the use of visual and practical methods. Meanwhile, the challenges faced included participants' physical limitations, such as visual and hearing impairments, and memory limitations. This activity makes a real contribution to the digital empowerment efforts of the elderly, and opens up opportunities for the development of similar programs in other regions. Hopefully, this kind of training can be the first step towards comprehensive digital inclusion for all levels of society.
ADAPTIVE CLASS WEIGHTING DAN AUGMENTATION UNTUK KLASIFIKASI BATIK KERATON Witriyani Witriyani; Dian Ade Kurnia; Yudhistira Arie Wijaya; Mulyawan Mulyawan; Irfan Ali
Informatika: Jurnal Teknik Informatika dan Multimedia Vol. 6 No. 1 (2026): MEI : JURNAL INFORMATIKA DAN MULTIMEDIA
Publisher : LPPM Politeknik Pratama Kendal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/informatika.v6i1.1516

Abstract

This study aims to improve the performance of Batik Keraton motif classification on an imbalanced dataset through the integration of adaptive class weighting and data augmentation within a transfer learning framework. The dataset consists of 1,799 images across four classes (Kawung, Mega Mendung, Parang, Truntum), preprocessed to 224×224 pixels and split stratifiedly into training, validation, and test sets (80/10/10). Three transfer learning architectures—ResNet50V2, VGG16, and EfficientNetB0—were evaluated with adaptive class weighting and geometric augmentation to enhance minority-class representation. The results indicate that ResNet50V2 with pretrained weights achieved the best performance, reaching a test accuracy of 92.78%, macro precision of 93.13%, macro recall of 92.79%, and a macro F1-score of 92.83%. Adaptive class weighting improved sensitivity toward minority classes, while augmentation contributed to model stability and generalization. These findings demonstrate that combining adaptive weighting and augmentation effectively enhances Batik Keraton motif classification under imbalanced data conditions.  
Optimalisasi Convolutional Neural Network Kontra VGG16 Klasifikasi Citra Daun Sawi Rio Febriyan; Ade irma Purnamasari; Denni Pratama; Puji Pramudya Marta; Yudhistira Arie Wijaya
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 6 No 1 (2026): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol6No1.pp30-34

Abstract

Manual detection of pests on mustard greens (caisim) is a major constraint in reducing harvest productivity, as manual methods are inefficient, time-consuming, and require specialized expertise. Furthermore, deep learning models often suffer from overfitting when applied to limited agricultural datasets. This study aimed to develop and compare the effectiveness of a Convolutional Neural Network (CNN) from scratch model versus the VGG16 transfer learning architecture for automatic classification of healthy and pest-affected mustard leaf images. A dataset of 1,000 images was used for training and testing across four experimental scenarios (A to D), with Percobaan C being the optimized CNN from scratch model (using data augmentation) and Percobaan D using VGG16. The results showed that the VGG16 transfer learning model achieved the highest test accuracy of 95.0% (F1-score: 0.95), while the optimized CNN from scratch model achieved 92.0% (F1-score: 0.92). Therefore, transfer learning with VGG16 is the most effective and optimal approach, demonstrating superior performance and efficiency by achieving high accuracy without complex data augmentation.
PENINGKATAN AKURASI KLASIFIKASI KEMATANGAN KELAPA SAWIT BERBASIS CITRA DENGAN ENSEMBLE DEEP LEARNING TEROPTIMASI DIMENSI RASIO Ahmad Rifai Ikhsanudin; Dian Ade Kurnia; Yudhistira Arie Wijaya; Dodi Solihudin; Tati Suprapti
Jurnal Mahasiswa Sistem Informasi (JMSI) Vol. 7 No. 2 (2026): Jurnal Mahasiswa Sistem Informasi (JMSI)
Publisher : Program Studi DIII Sistem Informasi - Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/jmsi.v7i2.11181

Abstract

Penentuan tingkat kematangan buah kelapa sawit secara manual sering menimbulkan subjektivitas dan menurunkan efisiensi. Penelitian ini mengembangkan metode klasifikasi berbasis citra menggunakan ensemble averaging pada tiga arsitektur MobileNetV2 dengan ukuran input berbeda (224×224, 224×300, dan 300×300) untuk mengurangi varians prediksi akibat variasi dimensi dan rasio aspek citra. Dataset yang digunakan berasal dari Kaggle berjumlah 1.380 citra, dengan pembagian 80% data latih dan 20% data validasi. Proses pengolahan mencakup rescaling, aspect-ratio-aware resizing, augmentasi, serta pelatihan menggunakan transfer learning dengan optimizer Adam dan early stopping. Hasil menunjukkan bahwa model berukuran 300×300 memberikan performa terbaik dengan akurasi 95,22% dan F1-score 0,9523. Ensemble averaging menghasilkan akurasi 94,71% dan F1-score 0,9475, yang meskipun sedikit lebih rendah dari model terbaik, memberikan stabilitas prediksi yang lebih baik dibanding model individual. Temuan ini menunjukkan bahwa resolusi input yang lebih tinggi meningkatkan kualitas ekstraksi fitur, sementara ensemble averaging tetap efektif dalam mereduksi varians dan meningkatkan ketahanan sistem klasifikasi di kondisi lapangan.
NAÏVE BAYES SENTIMENT ACCURACY WITH CHI-SQUARE AND INFORMATION GAIN Muhamad Fahrurozi; Dian Ade Kurnia; Yudhistira Arie Wijaya; Puji Pramudya Marta; Khaerul Anam
Antivirus : Jurnal Ilmiah Teknik Informatika Vol 20 No 1 (2026): Mei 2026
Publisher : Universitas Islam Balitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35457/1nmksc45

Abstract

This study aims to evaluate the effectiveness of the Chi-Square and Information Gain feature selection techniques in improving the accuracy of sentiment classification on application reviews using the Naive Bayes algorithm. The main issue addressed in this research is the high dimensionality of features in Indonesian-language text data, which may potentially affect model performance. To address this, the study applies a text preprocessing pipeline consisting of sentiment labeling, normalization, and feature extraction using TF-IDF with an initial 5000 features. The dataset contains 225,043 Gojek application reviews, which were reduced to 220,860 valid entries after cleaning, and subsequently divided into training and testing sets using a stratified split. Experimental results show that Chi-Square achieved the highest accuracy of 0.877864 with 3000 features, while Information Gain reached an accuracy of 0.877751 with 4000 features. Both values are slightly lower than the model without feature selection, which achieved an accuracy of 0.878045. These findings indicate that feature reduction does not improve the performance of Naive Bayes, as the algorithm performs more effectively when retaining a broader distribution of words and more complete contextual representations. In conclusion, feature selection for probabilistic models should be applied cautiously, especially on Indonesian-language review data that are informal and exhibit high variation in expression.
PENINGKATAN MODEL SEGMENTASI PENGGUNA TERMINAL TIPE B SUMBER KABUPATEN CIREBON DALAM PERBAIKAN SARANA DAN PRASARANA DENGAN ALGORITMA K-MEANS Agesty Kusmiyaty; Rudi Kurniawan; Yudhistira Arie Wijaya; Umi Hayati
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 1 (2025): JATI Vol. 9 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i1.12466

Abstract

Terminal Sumber, sebuah terminal tipe B di Kabupaten Cirebon, menghadapi tantangan dalam memenuhi kebutuhan pengguna akibat pengelolaan sarana dan prasarana yang belum optimal. Tingkat kepuasan pengguna terhadap fasilitas, kebersihan, kualitas layanan, dan infrastruktur sering kali beragam, mencerminkan kebutuhan perbaikan yang terarah. Penelitian ini bertujuan untuk menganalisis kepuasan pengguna dengan memanfaatkan algoritma K-Means Clustering. Data kepuasan pengguna dikumpulkan melalui survei langsung, menghasilkan dua klaster berdasarkan nilai Davies Bouldin Index (DBI) optimal sebesar 0,547. Klaster 0 merepresentasikan pengguna dengan tingkat kepuasan lebih rendah, sedangkan klaster 1 memiliki tingkat kepuasan lebih tinggi. Hasil ini menunjukkan bahwa segmentasi pengguna dapat membantu pengelola terminal merancang strategi perbaikan layanan yang lebih spesifik dan efektif. Dengan demikian, penelitian ini berkontribusi dalam penerapan metode clustering untuk meningkatkan kualitas layanan transportasi umum, baik secara praktis maupun akademis
PERBANDINGAN MODEL LSTM DAN GRU UNTUK PREDIKSI HARGA SAHAM TELEKOMUNIKASI INDONESIA Ahmad Jamalul Noor; Dian Ade Kurnia; Yudhistira Arie Wijaya; Heliyanti Susana
Jurnal Mahasiswa Ilmu Komputer Vol. 7 No. 1 (2026): Jurnal Mahasiswa Ilmu Komputer March 2026
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/ilmukomputer.v7i1.10651

Abstract

Penelitian ini bertujuan untuk mengevaluasi dan membandingkan performa model Long Short-Term Memory (LSTM) dan Gated Recurrent Unit (GRU) dalam memprediksi harga saham harian pada sektor telekomunikasi Indonesia, sebuah sektor yang memiliki karakteristik volatilitas fluktuatif dan dipengaruhi oleh dinamika pasar jangka pendek. Dua emiten yang dianalisis adalah GHON dan EXCL dengan rentang data dua tahun yang diambil dari platform Investing.com. Proses penelitian mencakup tahapan preprocessing, normalisasi menggunakan MinMaxScaler, pembentukan sliding window sepanjang 30 hari, serta pembagian data secara kronologis menjadi data latih, validasi, dan uji. Optimasi hyperparameter dilakukan menggunakan KerasTuner dengan pendekatan Random Search untuk memperoleh konfigurasi terbaik bagi masing-masing model. Evaluasi performa menggunakan tiga metrik utama yakni Root Mean Square Error (RMSE), Mean Absolute Error (MAE), dan Mean Absolute Percentage Error (MAPE). Hasil eksperimen menunjukkan bahwa GRU memberikan performa yang lebih unggul pada saham EXCL yang memiliki volatilitas tinggi, ditunjukkan oleh nilai RMSE, MAE, dan MAPE yang lebih rendah dibandingkan LSTM. Sebaliknya, pada saham GHON yang lebih stabil, kedua model menghasilkan performa yang relatif sebanding. Temuan ini menegaskan bahwa efektivitas model sangat dipengaruhi oleh karakteristik data, di mana GRU lebih adaptif pada pola harga yang dinamis, sedangkan LSTM tetap kompetitif pada pola yang lebih konsisten. Secara keseluruhan, GRU dapat direkomendasikan sebagai model yang lebih efisien dan akurat untuk prediksi harga saham pada lingkungan pasar yang berfluktuasi tinggi.
Co-Authors Abubakar Sidik Ade Irma Purnama Sari Ade Irma Purnamasari Ade Irma Purnamasari Adi Hermawan Aditiya Arif Firmansyah Adiyanto, Alfian Adjie Setyadj, Mochammad Agesty Kusmiyaty Agni, Vega Putra Dwi Ahmad Faqih Ahmad Jamalul Noor Ahmad Rifai Ikhsanudin AKBAR, MUHAMAD DENI Akhmad Taukhid Alfirda Sofyan, Zahra Aliya Anisa Rahma Alwan Azhar Alya Fadia An-naziz Safaat, Wafik Andi Ardiansyah Andriyani, Wini Anggara, Doni Anjar Permadi Aprianto, Wili Arya Hadi Wicaksana ASEP SAEFUDDIN Asmana, Asmana Astri Amelia Athaullah Abrar Bayan Ayura Yufita Beby Maryam Cintia Putri Prasetia Dadang Sudrajat Danar Dana, Raditya Darma Irawan, Bobi Darussalam, Luthvi Nurfauzi Denni Pratama Denni Pratama Denni Pratama Dermawan, Hibrizi Dzaky Dian Ade Kurnia Dian Ade Kurnia Dodi Solihudin Edi Tohidi Edi Wahyudin Falih, Alfi Rizqi Falih FANDI ACHMAD Fauzan, Muhamad Nur Fianita Rusadi Fianita Rusadi Firmansyach, Wildan Attariq Hajijin Amri Hamonangan, Ryan Hayati, Umi Hegarmanah Muhabatin Heliyanti Susana Heliyanti Susana Herman Hermawan, Adi Hidayat, Zaids Syarif Ibnu Ubaedila Ikhwan Fahruddin, Yusuf Inawati, Windi Intan Wangi Nur Qibti Irfan Ali Irfan Ali Irma Agustina Jaelani Sidik Jayawarsa, A.A. Ketut Jurnal Konsera Khaerul Anam Khoeri, Yajid Komala, Wulan Kurniawan , Rudi Laela Laela Leli Oktaviani Lukmanul Hakim Manzis, Zian Marta, Puji Pramudya Martanto Martanto . Martanto Martanto Masjunedi, Masjunedi Maulana, Tedy Mifta Almaripat Mita Amelia Moh Nurdayat Dayat MUHAMAD DENI AKBAR Muhamad Fahrurozi Muhamad Nur Fauzan Muhammad Aditya Rabbani Adit Mulyawan Nabila, Aynun Nana Suarna Nana Suarna Narasati, Riri Narasati Nashir, Mukhtar Nining Rahaningsih Nisa Dieanwati Nuris Nisa Dienwati Nuris Nur Amalia, Yustika Nurazijah, Wulan Nurdiawa, Odi Nurholipah, Titin Nurrahman, Rizki Odi Nurdiawa Odi Nurdiawan Pebriyanto, Ramdhan Pratama, Denni Puji Pramudya Marta Puji Pramudya Marta Purnamasari, Ade Irma Restu Normalasari Rini Astuti Rini Astuti Rini Astuti Rio Febriyan Rizal Rizal Roni Saputra Rubangiya Rubangiya Rudi Kurniawan Rudi Kurniawan Rudi Kurniawan Rudi Kurniawan Saeful Anwar Saeful Anwar, Saeful Satria Turangga Septian Nugraha, Titan Septiani Gumilar, Tia Shifa Dwi Oktaviani Siti Sopiyah Suarna, Nana Sugianto, Nanda Putri Sulaeman, Muhammad Suteja Syach Putra, Yanuar Tati Suprapti Taufik Hidayat Tegar Lazuardi, Muhammad Thomas Agam Tiana Dewi Tri Anelia Trian Nurmansyah Triswanto, Triswanto Tuti Hartati Tuti Hartati Tuti Hartati Umi Hayati Wahyudi Wahyudi Wartumi Wartumi Willy Prihartono Winayah, Winayah Windy Astuti Witriyani Witriyani Yudis Firmansyah yulani, Yulani - Yulia, Yuli