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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 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) Jurnal Mandiri IT Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Jurnal Minfo Polgan (JMP) Society: Jurnal Pengabdian Masyarakat Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Informatika Teknologi dan Sains (Jinteks) 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 Bulletin of Network Engineer and Informatics (BUFNETS) 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 Jurnal Abdimas Mahakam
Novalia, Elfina
Universitas Buana Perjuangan Karawang
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Sistem Pemilihan Supplier Obat Menerapkan Metode Additive Ratio Analysis (ARAS) Al Khadzik, Fahmi; Huda, Baenil; Novalia, Elfina; Hilabi, Shofa Shofiah
Jurnal Sistem Komputer dan Informatika (JSON) Vol 5, No 3 (2024): Maret 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i3.7499

Abstract

Qita Sehat pharmacy provides a wide range of medicines that are supplied by more than 30 suppliers and 100 buyers every month, but not all suppliers can meet the criteria set by pharmacies and suppliers are often late in the process of supplying drugs to pharmacies so that the stock in pharmacies is running low. From these problems, a solution is made, namely a drug supplier selection system is made by determining the priority order of drug suppliers with several criteria that match the availability of drugs at Qita Sehat pharmacies. The method used is the method of ARAS (Additive Ratio Analysis). The criteria considered are price, quality, lead time, communication systems, performance history and repair services. The result of this method is the order of priority of drug suppliers and knowing the results of the questionnaire through the sensitivity test that is the influence of changes in the value of the importance of the criteria. From the data generated in research using the ARAS method, the results obtained are that PT Javas Karya is the best supplier with the first rank of alternative A6 with a total value of 0.120.
Pengelompokkan Data Obat-Obatan Pada Pelayanan Kesehatan Menggunakan Algoritma K-Means Clustering Saptiani, Anita; Huda, Baenil; Novalia, Elfina; Purba, Arif Budimansyah
JURSIMA Vol 10 No 3 (2022): Jursima Vol.10 No.3
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.510

Abstract

ABSTRACT In planning accurate drug needs, the drug procurement becomes more effetive and efficient, so that it can be available with the type and amount that is needed. Clustering data mining can be used to analyze drug usage, drug palnning and management at the health center. The method that will be applied is the clustering method on drug data using the K-Means algorithm which can divide data into clusters so that data has similarities will be grouped into one group and different data will be combined in other groups. The purpose of this study was to classify drug data at the Karangsambung health center which could be used as a reference for decision making in planning and supplying drugs at the Karangsambung health center. The results of this study are classifying the level of drugs use at the Karangsambung health center, where the data was taken from 2019 to 2022. The resulting data was grouped into 3 clusters, which later collected high, medium and low usage.
Design of Interactive Media for Japanese M-Learning Based on Android Using UML and Waterfall Model Apriade Voutama; Elfina Novalia
Buana Information Technology and Computer Sciences (BIT and CS) Vol 6 No 1 (2025): Buana Information Technology and Computer Sciences (BIT and CS) (InProcess)
Publisher : Information System; Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/bit-cs.v6i1.8283

Abstract

The development of open source technology has created many innovations created by developers in creating Android-based applications. One of them is creating interactive media M-Learning Japanese language learning based on Android. Japanese M-Learning is made to facilitate students in the learning process and provide interactive convenience in improving Japanese language skills. M-Learning is made using the Android programming language with UML (Unified Modeling Language) design analysis tools and the waterfall model. The initial analysis uses the Usecase model to determine the actors involved in the system, and the flow of actor activities using the Activity and Sequence models and several other supporting models. The User Interface is made to describe the system being built and the Flowchart is designed to see the scheme running on the Japanese M-Learning interactive media system. The results of the analysis were carried out by taking satisfaction data from 30 student respondents, 81% stated that this Interactive Media was Good.
Pelatihan Penggunaan Paint Untuk Melatih Motorik Siswa Anak Sekolah Dasar Paryono, Tukino; Novalia, Elfina; Yoga Astario, Bayu; Hananto, Agustia
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 2 No. 2 (2024): Desember 2024
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v2i2.93

Abstract

This training program aims to assist elementary school students in developing their fine motor skills by utilizing Paint software. Fine motor skills, which involve coordinating small muscles like the hands and fingers, are essential for children's growth and development. In this activity, Paint is used as a tool to enhance both students' creativity and their motor abilities. Students engage in activities such as drawing, coloring, and pattern-making, which improve hand-eye coordination and establish fundamental artistic skills. The outcomes of this training reveal significant improvements in students' fine motor skills as well as their proficiency in using technology for creative purposes.
Pelatihan Pengembangan Website Sistem Penjualan Online Berbasis Content Menagement System (CMS) Wordpress Novalia, Elfina; Hananto, Agustia; Emilia Sukmawati, Cici; Wahyu, Pratama; Voutama, Apriade
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 2 No. 2 (2024): Desember 2024
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v2i2.104

Abstract

This WordPress Content Management System (CMS) based website development training activity is designed to help digitize the helmet washing service business in Karawang. The purpose of this training is to equip business owners with skills in managing online sales platforms to expand market reach and make it easier for customers to order services. The training is carried out offline with a direct practice method, including a basic introduction to WordPress, theme and plugin installation, to optimizing online store features. Based on the evaluation, this training received a participant satisfaction rate of 85%. Participants felt helped by the material provided and were able to practice creating and managing websites independently to support their business operations. This training is expected to be able to increase the competitiveness of the helmet washing business in Karawang by utilizing an effective digital platform to reach customers more widely.
Penerapan Algoritma Naive Bayes untuk Perbandingan Sentimen Ulasan Lazada dan Tokopedia Prasetya, Rafli; Hananto, April Lia; Novalia, Elfina; Tukino, Tukino
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 1: April 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i1.2666

Abstract

The e-commerce sector is one of many aspects of life influenced by advancements in information and communication technology. Tokopedia and Lazada, as two popular platforms in Indonesia, are increasingly accessed through mobile applications. User reviews serve as valuable input for improving service quality and user satisfaction. This study aims to evaluate user sentiment toward the Lazada and Tokopedia applications on the Google Play Store using the Naïve Bayes algorithm. A total of 2,000 review data were collected using web scraping methods and underwent preprocessing, resulting in 1,864 data points ready for analysis. The Hold-Out technique was applied for data splitting to assess model performance. The results show an accuracy of 89% for both applications. The majority of user sentiment is positive, with Lazada achieving a precision of 94%, recall of 93%, and F1-score of 94%, while Tokopedia achieved a precision of 97%, recall of 86%, and F1-score of 91%. These findings demonstrate the effectiveness of combining the Naïve Bayes algorithm and the Hold-Out technique in sentiment classification.Keywords: E-commerce; Sentiment Analysis; Google Play Store; Naïve Bayes AbstrakSektor e-commerce adalah salah satu dari banyak aspek kehidupan yang dipengaruhi oleh kemajuan teknologi informasi dan komunikasi. Tokopedia dan Lazada sebagai dua platform populer di Indonesia, semakin sering digunakan melalui aplikasi mobile. Ulasan pengguna menjadi masukan penting dalam meningkatkan kualitas layanan dan kepuasan pengguna. Penelitian ini bertujuan untuk mengevaluasi sentimen terhadap pengguna aplikasi Lazada dan Tokopedia di platform Google Play Store melalui algoritma Naïve Bayes. Sebanyak 2000 data ulasan dikumpulkan menggunakan metode web scraping, kemudian dilakukan preprocessing sehingga diperoleh 1864 data siap analisis. Teknik Hold-Out digunakan dalam pembagian data untuk mengukur performa model. Hasil menunjukkan akurasi sebesar 89% untuk masing-masing aplikasi. Sentimen pengguna mayoritas bersifat positif, dengan Lazada memperoleh presisi 94%, recall 93%, dan skor F1 94%, sedangkan Tokopedia memperoleh presisi 97%, recall 86%, dan skor F1 91%. Temuan ini menunjukkan efektivitas kombinasi algoritma Naïve Bayes dan Hold-Out dalam klasifikasi sentimen. 
Sistem Monitoring Dan Visualisasi Data Konsumsi Energi Listrik Rumah Berbasis IoT Dengan Aplikasi Blynk Setiawan, Pratama Wahyu; Hananto, April Lia; Novalia, Elfina; Hananto, Agustia
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 1: April 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i1.2675

Abstract

Household electricity consumption continues to increase, but monitoring of electricity use is still limited to the KwH meter which only shows the total usage without real-time details. This research aims to design an Internet of Things (IoT)-based electrical energy consumption monitoring system with the Blynk application as a data visualization medium. The system is designed using a PZEM-004T sensor to measure voltage, current, and power, as well as a ESP8266 NodeMCU microcontroller to transmit data to the Blynk application over a WiFi connection. System testing is carried out using the black box method to evaluate the functionality of each feature without looking at internal processes. The test results showed that the system can display electricity consumption data in real-time, work stably, and allow remote monitoring via smartphone. The system also helps users recognize electricity usage patterns, supports decision-making in energy savings, and provides historical data for long-term usage evaluation.Keywords: Internet Of Things; Monitoring Listrik; NodeMCU ESP8266; Blynk; PZEM-004T AbstrakKonsumsi energi listrik rumah tangga terus meningkat, namun pemantauan penggunaan listrik masih terbatas pada KwH meter yang hanya menunjukkan total pemakaian tanpa detail real-time. Penelitian ini bertujuan merancang sistem monitoring konsumsi energi listrik berbasis Internet of Things (IoT) dengan aplikasi Blynk sebagai media visualisasi data. Sistem dirancang menggunakan sensor PZEM-004T untuk mengukur tegangan, arus, dan daya, serta mikrokontroler NodeMCU ESP8266 untuk mengirimkan data ke aplikasi Blynk melalui koneksi WiFi. Pengujian sistem dilakukan dengan metode Black box untuk mengevaluasi fungsionalitas tiap fitur tanpa melihat proses internal. Hasil pengujian menunjukkan bahwa sistem dapat menampilkan data konsumsi listrik secara real-time, bekerja dengan stabil, dan memungkinkan pemantauan jarak jauh melalui smartphone. Sistem ini juga membantu pengguna mengenali pola penggunaan listrik, mendukung pengambilan keputusan dalam penghematan energi, serta menyediakan data historis untuk evaluasi penggunaan jangka panjang. 
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.
Co-Authors Abdul Hafiz Agustina, Alvi Ahmad Fauzi Ahmad, Sandi Al Khadzik, Fahmi Alfiansyah, Muhammad Rindra Ani Ani 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 Awaludin, Sidqi Baenil Huda Baenil Huda baktria, leonyka Bayu Yoga Astario Cahya Diningrat Desfianthy, Fatiya Hanifah Emilia Sukmawati, Cici Fadli, Muhammad Abil Faisal, Muhamad Agus Firdaus, Mohamad Ricky Fitri Nur Masruriyah, Anis Fitria Nurapriani Garno garno, Garno Gefira Rahmaifha Goenawan Brotosaputro Gugy Guztaman Munzi Hananto , Agustia Hananto, Agustia Henry Adam Hilabi, Shofa Shofiah Hilabi, Shofa Shofiah Huban Kabir Huda, Baenil Indra, Jamaludin Iqbal Maulana Irawan, Agung Susilo Yuda 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 tukino, tukino Wahyu Aziz Ramadhani Wahyu, Pratama Widyanti, Tyas Wirlandika, Devri Yoga Astario, Bayu Yusup, Dadang Zhalifunas, Satria Dawas