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All Journal Syntax Jurnal Informatika Jurnal Informatika dan Teknik Elektro Terapan Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi INTECOMS: Journal of Information Technology and Computer Science J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Riset Informatika JOISIE (Journal Of Information Systems And Informatics Engineering) Journal of Information System, Applied, Management, Accounting and Research Jurnal Abdimas Mahakam METIK JURNAL Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jusikom: Jurnal Sistem Informasi Ilmu Komputer Systematics Zonasi: Jurnal Sistem Informasi Jurnal Informasi dan Teknologi Buana Information Technology and Computer Sciences (BIT and CS) JURSIMA (Jurnal Sistem Informasi dan Manajemen) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer JIKA (Jurnal Informatika) Jurnal Sistem Komputer dan Informatika (JSON) Infotek : Jurnal Informatika dan Teknologi Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) International Journal of Engineering, Science and Information Technology Djtechno: Jurnal Teknologi Informasi Jurnal Tika Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Jurnal Minfo Polgan (JMP) Society: Jurnal Pengabdian Masyarakat Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Komtekinfo Jurnal Buana Pengabdian Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Malcom: Indonesian Journal of Machine Learning and Computer Science JUSIFOR : Jurnal Sistem Informasi dan Informatika Golden Ratio of Data in Summary Jurnal Ilmiah Teknik Informatika dan Komunikasi Innovative: Journal Of Social Science Research JURSIMA Journal Of Artificial Intelligence And Software Engineering VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Sistem Informasi dan Manajemen Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial
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Socialization of Digital Literacy and Artificial Intelligence to Improve Knowledge and Skills in Rangdumulya Village Voutama, Apriade; Maulana, Iqbal; Yusup, Dadang; Garno, Garno; Novalia, Elfina
Society : Jurnal Pengabdian Masyarakat Vol 4, No 3 (2025): Mei
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/jpm.v4i3.524

Abstract

The socialization of Digital Literacy and Artificial Intelligence was carried out in Randumulya Village, Karawang Regency, which focused on increasing the community's insight into skills so that they can train and create creative ideas and opportunities. The socialization was carried out by two targets, namely to village officials and the community and students at elementary schools in the village. This activity was carried out in the Village Hall with resource persons who were expert lecturers in their fields and activities with students were carried out at the school and accompanied by students to be more interactive. The results of the satisfaction of 55 respondents who were carried out by distributing questionnaires reached 85% who stated that they were satisfied. With this training, it can help the village community to know and get benefits from digital literacy and technological intelligence so that it has a positive impact and standard of living in the village.
Prediksi Volume Penjualan Gadget Berdasarkan Promo dan Channel Penjualan Menggunakan Random Forest Agustina, Alvi; Tukino, Tukino; Huda, Baenil; Novalia, Elfina
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 1 (2025): JUSIFOR - Juni 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i1.6962

Abstract

Volume penjualan gadget dipengaruhi oleh berbagai faktor seperti harga, rating pengguna, keberadaan promo, serta channel distribusi yang digunakan. Pemahaman terhadap pengaruh faktor-faktor tersebut sangat penting untuk merumuskan strategi pemasaran yang efektif. Penelitian ini bertujuan untuk memprediksi volume penjualan gadget menggunakan algoritma Random Forest berdasarkan fitur promo dan channel penjualan. Data yang digunakan merupakan catatan transaksi aktual dari sebuah toko gadget yang melayani penjualan secara online dan offline di wilayah Jabodetabek dalam periode tertentu. Tahapan penelitian meliputi data preprocessing, pembentukan target klasifikasi volume penjualan menjadi tiga kategori (rendah, sedang, dan tinggi), pelatihan model Random Forest, serta evaluasi performa model menggunakan metrik akurasi, precision, recall, dan F1-score. Pembagian data latih dan data uji dilakukan dengan teknik stratified sampling untuk menjaga keseimbangan distribusi kelas. Hasil evaluasi menunjukkan bahwa model Random Forest mencapai akurasi sebesar 49,5%, dengan performa terbaik dalam mengklasifikasikan kategori volume penjualan "sedang". Angka ini mengindikasikan bahwa akurasi prediksi model masih terbatas, dengan hanya sekitar separuh dari keseluruhan data uji yang dapat diprediksi dengan benar. Meskipun demikian, temuan ini menunjukkan bahwa penerapan algoritma machine learning, khususnya Random Forest, berpotensi mendukung pengambilan keputusan berbasis data dalam meningkatkan efektivitas penjualan gadget.
Prediksi Penjualan Barang Menggunakan Metode K-Means dan Regresi Linear Henry Adam; Tukino; Elfina Novalia; Hananto, April Lia
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.541

Abstract

Sales data analysis plays an important role in supporting business decision making, especially to optimise stock management and improve operational efficiency. the main problem faced by Vapestore XYZ in Karawang is the difficulty in accurately predicting the number of product sales, so there is often an imbalance between inventory and market demand. This can cause losses due to overstocks or shortages of goods. Currently, the estimation of stock requirements still relies on intuition and personal experience, without the support of objective data analysis. This research aims to build a sales prediction model by combining the K-Means method for product clustering and Linear Regression for sales quantity prediction. Sales data is taken directly from the store POS application, then goes through the stages of cleaning, labelling, and clustering into three groups, namely ‘Less Sold’, “Sold”, and ‘Very Sold’. Sales prediction is performed using Linear Regression by utilising the clustering results and time variables as inputs. Model performance evaluation is performed using error metrics, namely Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). Based on the test results, the developed Linear Regression model obtained MAE of 3.20, MSE of 52.34, and RMSE of 7.23. These error values indicate that the model is able to provide sales estimates that are close enough to the actual data to be reliable in stock planning. Visualisation of the prediction results in the form of tables and heatmaps makes it easy to identify sales trends and compare performance between products. The findings of this study prove that the combination of K-Means and Linear Regression methods is effectively used to support stock decision making and marketing strategies in vape retail stores. Further development is recommended by enriching the dataset and exploring other prediction methods to improve model performance.
User Experience Design Analysis of the Karawang Job Vacancy Website using the User-Centered Design Method and System Usability Scale Sopian, Jajang; Huda, Baenil; Novalia, Elfina; Hananto, April Lia
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5303

Abstract

An optimized User Experience (UX) design plays a significant role in creating a comfortable browsing experience, ensuring good accessibility, and enhancing user satisfaction. This study analyzes the UX design of the Info Loker Karawang website by applying the User-Centered Design (UCD) method and evaluating the resulting prototype using the System Usability Scale (SUS) to assess the website’s ease of use. The UCD method was selected because it places the user at the center of the design process, enabling the development of solutions that align closely with users’ needs, expectations, and characteristics. This approach has proven effective in producing relevant and intuitive interfaces through stages of analysis, design, and evaluation involving active user participation. Following the design phase, the prototype was tested using the SUS instrument to measure how well the design solution met usability and user satisfaction criteria. The evaluation results indicate that applying UCD in website design significantly improves usability, achieving a SUS score of 72.5, which falls into Grade B and is categorized as “Good” on the adjective rating scale. This research provides insights into the importance of user-centered approaches in website development and demonstrates the effectiveness of SUS in evaluating and measuring the success of UX design outcomes.
Pengenalan Enterpreunership Multimedia Pada Santri Pondok Pesantren At-Taubah Tirta Mulya Agustia Hananto; Elfina Novalia; Tukino Tukino
Masyarakat Berkarya : Jurnal Pengabdian dan Perubahan Sosial Vol. 2 No. 2 (2025): Mei : Masyarakat Berkarya : Jurnal Pengabdian dan Perubahan Sosial
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/karya.v2i2.1384

Abstract

This community service activity aims to introduce the concept of multimedia entrepreneurship to students of the At-Taubah Tirta Mulya Islamic Boarding School, Karawang, in order to improve their knowledge and skills in utilizing multimedia as a tool for entrepreneurship. Held on March 2, 2024, this activity involved 50 students who attended lecture sessions, discussions, and multimedia content creation practices. The research method used was participatory action research, which allowed participants to be actively involved in the learning process. Data were collected through observation, interviews, and questionnaires to measure changes in knowledge before and after the activity. The results of the analysis showed a significant increase in students' understanding and skills related to multimedia entrepreneurship. The implications of this activity highlight the importance of collaboration between higher education institutions and Islamic boarding schools to create a creative and independent generation in the digital era.
UI/UX Design of Mobile-Based Employee Performance Monitoring Using User-Centered Design Method PT Citra Digital Lintas Wirlandika, Devri; Prayono, Tukino; Novalia, Elfina
Journal of Artificial Intelligence and Software Engineering Vol 5, No 2 (2025): June
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i2.6401

Abstract

Development of mobile-based employee performance monitoring application interface at PT Citra Digital Lintas using User-Centered Design (UCD) method and usability testing with Single Ease Question (SEQ). The results of the user needs analysis showed a priority on transparency and ease of access. In the evaluation phase, 7 key tasks were tested with 10 respondents. An average SEQ score of 7.0 indicated the interface was easy to use, with T8 (real-time monitoring) being the best task (average 7.0; 50% scored 7/very easy). A total of 80% of respondents scored 6/easy on tasks T3 (data input) and T7 (performance report), reflecting design consistency. However, T1 (multi-role login) had 20% scoring 4/difficult, the highest among the other tasks, although the average was still 5.1/quite easy. Overall, 7 out of 8 tasks fell into the moderately easy category (scores 5-6.9), while T8 was the only one to reach the easy category (scores ≥7). Improvement recommendations focused on T1 to reduce user barriers, while the design of T8 was retained as an intuitive reference. Implementation of the app improved monitoring efficiency (85% positive response) and supported performance transparency, with potential for increased accuracy (90% satisfaction) and employee engagement. These results confirm that the UCD approach and SEQ validation were effective in creating a solution that aligned with user and organisational needs.
KLASIFIKASI DAN PREDIKSI ULASAN E-COMMERCE MENGGUNAKAN ALGORITMA NAÏVE BAYES Nuriza, Adjeng Putri; Novalia, Elfina
JOISIE (Journal Of Information Systems And Informatics Engineering) Vol 9 No 1 (2025)
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/joisie.v9i1.4993

Abstract

Penelitian ini bertujuan untuk mengklasifikasikan ulasan pengguna aplikasi Tokopedia ke dalam empat kategori utama: fitur aplikasi, layanan, pembayaran, dan promosi. Sebanyak 1.500 ulasan dikumpulkan melalui teknik web scraping dari Google Play Store dan diolah menggunakan tahapan preprocessing seperti tokenization, stopword removal, dan stemming. Klasifikasi dilakukan dengan menggunakan algoritma Multinomial Naive Bayes. Dari 458 data uji, model menghasilkan akurasi sebesar 83,41%, dengan nilai precision tertinggi pada kategori fitur aplikasi sebesar 0,89 dan recall tertinggi pada kategori pembayaran dan promosi sebesar 0,97. Hasil tersebut menunjukkan bahwa algoritma Naive Bayes efektif dalam mengelompokkan ulasan secara otomatis dengan rata-rata kinerja makro sebesar 0,84 (precision), 0,83 (recall), dan 0,83 (f1-score). Kontribusi utama dari penelitian ini adalah penerapan metode klasifikasi teks yang dapat membantu Tokopedia mengidentifikasi aspek layanan yang paling sering dibicarakan oleh pengguna, sehingga dapat mendukung pengambilan keputusan yang lebih terarah.
IMPLEMENTASI USER INTERFACE PADA WEBSITE COMPANY PROFILE MENGGUNAKAN METODE DESIGN THINKING Tamala, Evi; Huda, Baenil; Novalia, Elfina; Hananto, Agustia
ZONAsi: Jurnal Sistem Informasi Vol. 7 No. 2 (2025): Publikasi artikel ZONAsi: Jurnal Sistem Informasi Periode Mei 2025
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/9pwc1780

Abstract

CV. Smart Motecare Mandiri bergerak di bidang penyedia perangkat teknologi informasi serta layanan instalasi dan perawatan peralatan tersebut. Seiring dengan pesatnya perkembangan teknologi informasi, perusahaan ini menyadari pentingnya keberadaan sebuah website sebagai sarana komunikasi dan promosi yang efektif. Website menjadi platform penting untuk menyampaikan informasi mengenai produk, layanan, serta profil perusahaan. Penelitian ini bertujuan untuk merancang website company profile CV. Smart Motecare Mandiri dengan memanfaatkan metode Design Thinking, yang mengarah pada pengetahuan yang komprehensif mengenai keperluan pengguna serta penyelesaian masalah yang dihadapi perusahaan. Proses perancangan mencakup tahapan Empathize, Define, Ideate, serta pembuatan desain dan prototype, yang kemudian diimplementasikan dalam pembuatan website menggunakan platform WordPress. Setelah website selesai dibuat, pengujian dilakukan dengan metode SUS untuk mengukur tingkat kegunaan website. Hasil pengujian menunjukkan skor akhir SUS sebesar 68,00, yang termasuk dalam kategori "marginal high" dan menunjukkan bahwa website yang dirancang efektif dalam memenuhi tujuan perusahaan. Website ini diharapkan dapat menjadi sarana promosi digital yang meningkatkan citra profesional perusahaan dan mempermudah calon pelanggan dalam memperoleh informasi.
Text Data Classification Using the SVM Model on the LMDB Minecraft Dataset Bayu Yoga Astario; Tukino; Agustia Hananto; Fitria Nurapriani; Elfina Novalia
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.620

Abstract

Text classification is a fundamental task in Natural Language Processing (NLP) aimed at categorizing text data into predefined classes. This study implements a Support Vector Machine (SVM) model to classify text data from the LMDB Minecraft Dataset, which contains user reviews of the Minecraft movie. The research involves text preprocessing, TF-IDF feature extraction, and SVM model training. The classification results are evaluated using accuracy, precision, recall, f1-score, and confusion matrix metrics. The comment data is also analyzed based on the timing of their appearance in the movie. All processes are visualized in diagrams; the final results are saved in Excel format. The SVM model performs adequately on informal and domain-specific language data, providing a foundation for future research in similar text classification contexts.
Implementation of The Seasonal Autoregressive Integrated Moving Average Predictive Model on Raw Material Usage Data at PT. Plastik Karawang Flexindo Alfiansyah, Muhammad Rindra; Tukino, Tukino; Hananto, Agustia; Novalia, Elfina
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.867

Abstract

Fluctuations in raw material utilization in the manufacturing industry significantly impact production process efficiency, operational costs, and supply chain stability. Inaccurate planning and management of raw material inventories can lead to two extreme conditions: excess stock, which increases storage costs and the risk of expiration, or stock shortages, which could halt the production process and reduce productivity. To improve the accuracy of raw material consumption planning, this study applies the Seasonal Autoregressive Integrated Moving Average (SARIMA) model to predict raw material needs periodically based on historical data. The dataset used includes the consumption of Polyethylene (PE), High Density Polyethylene (HDPE), and Polypropylene (PP) from 2019 to 2025. The data is analyzed using a time series forecasting approach to identify trends and seasonal patterns. The SARIMA model is developed and optimized using three methods to search for the best parameters: Grid Search, Random Search, and Bayesian Optimization, to enhance prediction performance. The model's evaluation calculates the Mean Absolute Percentage Error (MAPE) as an accuracy indicator. The evaluation results show that although SARIMA can recognize seasonal patterns in raw material consumption, the prediction accuracy varies, with the best MAPE value being 16% and the highest being 34%. This indicates that external factors, such as market dynamics, government policies, global price fluctuations, and internal variables such as production schedules and customer demand, need to be considered to improve the model's precision. Overall, the application of SARIMA in this context provides a strategic contribution to supply chain management in the manufacturing industry, particularly in anticipating raw material needs, reducing uncertainty, and supporting more efficient and adaptive data-driven decision-making.
Co-Authors Abdul Hafiz Agung Susilo Yuda Irawan Agustina, Alvi Ahmad Fauzi Ahmad, Sandi Al Khadzik, Fahmi Alfiansyah, Muhammad Rindra Anita Saptiani Apriade Voutama April Hananto April Lia Hananto Arif Budimansyah Purba atikah, dwi Aurel Adhitya Anwar Aviv Yuniar Rahman Awal, Elsa Elvira Awaljan Situmorang Baenil Huda Baenil Huda baktria, leonyka Bayu Yoga Astario Desfianthy, Fatiya Hanifah Diningrat, Cahya Emilia Sukmawati, Cici Fadli, Muhammad Abil Faisal, Muhamad Agus Firdaus, Mohamad Ricky Fitri Nur Masruriyah, Anis Fitria Nurapriani Garno garno, Garno Garno, Garno Goenawan Brotosaputro Gugy Guztaman Munzi Hananto, Agustia Henry Adam Hilabi, Shofa Shofia Hilabi, Shofa Shofiah Hilabi, Shofa Shofiah Huban Kabir Huda, Baenil Indra, Jamaludin Iqbal Maulana Juwita, Ayu Ratna kastiawan, Nurhayadi Lestari, Renita Lutfiah, Siti Muhamad Djaka Permana Muhamad Helmi Fauzi Nijunnihayah, Uktupi Nur ‘Azah Nurapriani, Fitria Nuriza, Adjeng Putri Nurmayanti, Trisya Paryono, Tukino Prasetya, Rafli Pratama, Daffa Agung Prayono, Tukino Priyatna, Bayu Purba, Arif Budimansyah Rian Pratama Sandi Ahmad Saptiani, Anita Seia Piantara Setiawan, Pratama Wahyu Setiawan, Pratama Wahyu Setiawan, Revi Shofa Shofia Hilabi Shofiah Hilabi, Shofa Situmorang, Awaljan Sopian, Jajang Sukmawati, Cici Emilia Surala, Lyvia Syafana, Vinka Syahri Susanto Tamala, Evi TARMUJI TARMUJI, TARMUJI Tejayanda, Rigger Damaiarta Tita Puspita Sari Tukino Tukino, Tukino Tukino, Tukino Wahyu Aziz Ramadhani Wahyu, Pratama Widyanti, Tyas Wirlandika, Devri Yoga Astario, Bayu Yusup, Dadang Zhalifunas, Satria Dawas