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All Journal Riau Journal of Computer Science JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF SCIENCE AND SOCIAL RESEARCH Indonesian Journal of Electrical Engineering and Computer Science ARSY : Jurnal Aplikasi Riset kepada Masyarakat Jurnal Ilmiah MADIYA: Masyarakat Mandiri Berkarya Internasional Journal of Data Science, Computer Science and Informatics Technology (InJODACSIT) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Electronic Integrated Computer Algorithm Journal JGEN : Jurnal Pengabdian Kepada Masyarakat Jurnal Kecerdasan Buatan dan Teknologi Informasi
Yuyun Yusnida Lase
Politeknik Negeri Medan
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences

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Analysis of Educator Readiness in the Online Teaching Learning Process Using Naïve Bayes Yuyun Yusnida Lase; Yulia Fatmi; Haryadi Haryadi; Arif Ridho Lubis; Santi Prayudani
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 5, No 2 (2022): Issues January 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v5i2.5964

Abstract

This study discusses the readiness of educators in the online teaching and learning process. Samples of data were taken randomly as many as 100 (one hundred) people who were carried out using a questionnaire for educators at the junior high school level in the city of Medan. The variables used in the research are human resources, facilities and infrastructure, skills in applying technology, time management in online learning, the assessment process. Data processing and data analysis using nave Bayes algorithm. This algorithm is very well used for the process of classifying large amounts of data. The reason for using the nave Bayes algorithm in processing and analyzing data is because the way this algorithm works uses statistical and probability methods in predicting future results. The results of calculations using the nave Bayes algorithm based on the specified training data show that educators at the junior high school level are ready for the online learning process.
Analisis Rule Kualitas Ayam Petelur Menggunakan Metode Simple Additive Weighting Yuyun Yusnida Lase
RJOCS (Riau Journal of Computer Science) Vol. 4 No. 1 (2018): Riau Jurnal of Computer Science
Publisher : RJOCS (Riau Journal of Computer Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (417.169 KB) | DOI: 10.30606/rjocs.v4i1.1443

Abstract

Decision-making is the process of selecting alternative actions to achieve a certain goal or goal. Decision-making is done with a systematic approach to the problem through the process of collecting data into information and coupled with the factors that need to be considered in decision making. In the decision-making process, decision makers are often exposed to various criteria, such as chicken farmers, who often face difficulty in determining priorities in decision-making processes and policies regarding the quality of laying hens. This is influenced by the number of criteria determined in determining the quality of chicken eggs age, weight, nutritional food, environmental temperature and disease. In connection with this, the authors conducted a process of rules analysis to determine the quality of laying hens with Simple Additive weighting method (SAW). The process of analysis of the rules with Simple Additive Weighting (SAW) method is done by finding the weight of value for each attribute, then conducted a ranking process that will determine the optimal alternative in determining the quality of laying hens based on the criteria used, by Using this method will be able to produce chicken laying eggs where the egg quality is good.
WEB Based Design Of Building Materials Marketplace In Percut Sei Tuan District Yuyun Yusnida Lase; Fildzah Nadiah
International Journal of Data Science, Computer Science and Informatics Technology (InJODACSIT) Vol. 1 No. 1 (2021): InJODACSIT
Publisher : Politeknik Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (594.549 KB)

Abstract

Marketplace is an internet-based (web-based) online medium for conducting business activities and transactions between buyers and sellers. One business that can take advantage of marketplace technology is a building shop. Transaction activities at building shops in Percut Sei Tuan District are still done manually. Buyers still have to come to the store to shop or just find out information about products. Existing data in a building shop, such as product data to transaction data, are still recorded in a book. In this study, a web-based application for building materials marketplace in Percut Sei Tuan District was developed using the PHP programming language and MySQL database. The results of this study are expected to assist the building shop in processing existing data, ranging from product data to transaction data, as well as helping customers to shop for building materials without having to come to the store, so as to simplify the transaction process that occurs
Pelatihan Penggunaan Media Ajar Di Yayasan Hajjah Siti Syarifah Kecamatan Medan Tembung Hikmah Adwin Adam; Yuyun Yusnida Lase; Yulia Fatmi; Arif Ridho Lubis
ARSY : Jurnal Aplikasi Riset kepada Masyarakat Vol. 3 No. 2 (2023): ARSY : Jurnal Aplikasi Riset kepada Masyarakat
Publisher : Lembaga Riset dan Inovasi Al-Matani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/arsy.v3i2.395

Abstract

Yayasan Pendidikan Islam Hajjah Siti Syarifah terletak di Jln. Kemenangan No. 76-A Medan Tembung Kota Medan. Lembaga pendidikan ini didirikan untuk memberi pelajaran agama Islam tambahan untuk melengkapi pelajarah agama yang diberikan pada sekolah formal. Yayasan Hajjah Siti Syarifah memiliki jenjang Pendidikan dari tingkat RA dan MDA. Proses belajar mengajar di Yayasan Siti Syarifah masih memiliki banyak kendala, salah satu yang menjadi kendala pada saat ini adalah kurangnya pemahaman dan pengetahuan tenaga pendidik dalam menggunakan media ajar, sehingga proses belajar mengajar yang dilaksanakan masih kurang optimal. Dari kendala yang telah penulis uraikan diatas, penulis mencoba memberikan solusi dengan cara memberikan pelatihan mengenai penggunaan media ajar menggunakan canva kepada tenaga pendidik. Dengan adanya pelatihan tersebut diharapkan tenaga pendidik dapat membuat media ajar yang dapat membantu dalam proses pembelajaran, sehingga materi yang disampaikan lebih interaktif. Dari hasil pelatihan yang dilakukan pada Yayasan tersebut dapat ditarik kesimpulan bahwa pelatihan yang diberikan kepada tenaga didik dapat memberikan pengetahuan dan keterampilan yang baru mengenai penggunaan media ajar menggunakan canva dan tanggapan tenaga pendidik terhadap pelatihan yang diberikan sangat positif dan pelaksanaan pelatihan yang diberikan dapat dikategorikan sangat baik.
Classification Analysis of Product Sales Results at Alfamart Using the Naïve Bayes Method Yuyun Yusnida Lase; Citra Wasti Silaban; Alex Sander Sitepu; Reza Kavarin Telaumbanua
Electronic Integrated Computer Algorithm Journal Vol. 1 No. 2 (2024): VOLUME 1, NO 2: APRIL 2024
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v1i2.18

Abstract

This research focuses on the analysis of the number of products sold, especially stock items from the distribution center to Alfamart stores. The main problem discussed in this study is the result of the number of unsold and sold products, which causes overstocking in the warehouse area. To overcome this problem, it will be solved using the Naive Bayes classification method. This research uses sample data of 100 products and uses data collection techniques such as observation and interviews. The collected data is analysed through a classification approach. This research aims to predict goods that sell and do not sell using Rapidminer using the NaïveBayes method. And to produce more accurate data for the product sales process. The reason for using this naïve bayes algorithm in the process of processing and analysing data is because the way this algorithm works uses statistical methods and probability in predicting future results. The validation results show that the Naive Bayes classification method implemented through Rapidminer provides a significant explanation with a fairly high accuracy and a positive effect on the prediction of sales of goods based on consumer demand and needs.
Deep neural networks approach with transfer learning to detect fake accounts social media on Twitter Arif Ridho Lubis; Santi Prayudani; Muhammad Luthfi Hamzah; Yuyun Yusnida Lase; Muharman Lubis; Al-Khowarizmi Al-Khowarizmi; Gabriel Ardi Hutagalung
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp269-277

Abstract

The massive use of social media makes people take actions that have a negative impact on cyberspace, such as creating fake accounts that aim to commit crimes such as spam and fraud to spread false information. Fake accounts are difficult to detect in the traditional way because fake accounts always use photos, names, and unreal information, there are several criteria that can identify a fake account such as no information, few followers, and minimal activity. In the traditional model, it is difficult to detect fake accounts on many Twitters social media accounts, so the application of the deep learning model with the convolutional neural network (CNN) algorithm and the application of deep learning can help detect fake accounts. This study will use data on Twitter social media so that this research produces good accuracy for the scenarios described at the methodology stage. This research produces an accuracy of 86% for the deep learning model with the CNN algorithm, and with the traditional model, it produces an accuracy of 51% while the use of transfer learning produces an accuracy of 93.9%.
Upaya Mencegah Tindak Kriminal pada Lingkungan Tempat Tinggal dengan Pemasangan CCTVdi Desa Selayang Ramdani Safitri, Habibi; Aminuddin, Harris; Adwin Adam , Hikmah; Lase, Yuyun Yusnida
Jurnal Ilmiah Madiya (Masyarakat Mandiri Berkarya) Vol. 5 No. 1 (2024): Edisi Mei 2024
Publisher : Politeknik Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

A peaceful, safe, and comfortable living environment is a dream for people who want to settle in an area. Interactive socialization between residents based on equality and high social morals is a condition for achieving harmony and happiness. However, the insecurity that comes from theft, loss, and other activities felt by the community has led to unrest. This activity is the basis for joint activities with the Village Community in Selayang, Deli Serdang Regency, to carry out village security through the Selayang Village Cooperation with the Medan State Polytechnic Service Team through the means of village monitoring technology (PANDES) by utilizing CCTV. The existence of location monitoring technology that can detect moving objects in the village monitoring area is used to access the community that inhabits the former oil palm plantation area. PANDES is essential because the distance between residents' houses is relatively far, between 6-10 m; many vacant lots are overgrown with large trees and dense bushes. This condition makes crime opportunities quickly arise by utilizing the conditions of the community's residence. The existing problems are solved through community service activities by presenting PANDES through the provision of Closed Circuit Television (CCTV) monitors. CCTV is designed to detect moving objects within a radius of 20 meters.
Analisa dan Implementasi Sistem Absensi Siswa SMK Al Washliyah Kecamatan Hamparan Perak, Kabupaten Deli Serdang, Provinsi Sumatera Utara Prayudani, Santi; Friendly, Friendly; Harizahayu, Harizahayu; Lase, Yuyun Yusnida; Fatmi, Yulia
JGEN : Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 1 (2025): JGEN : Jurnal Pengabdian Kepada Masyarakat, Februari 2025
Publisher : Lumbung Pare Cendekia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60126/jgen.v3i1.699

Abstract

Kehadiran siswa merupakan salah satu hal yang penting diperhatikan. Rekapitulasi kehadiran di sekolah SMK Hamparan Perak saat ini dilakukan secara manual dan diperoleh di setiap pertengahan dan akhir semester pada saat pembagian rapor. Pelaksanaan rekapitulasi data ini membuat interaksi antara guru dan orang tua terkait kehadiran siswa menjadi kurang rutin, sehingga permasalahan siswa terkadang terlambat ditangani. Selain untuk memantau keaktifan belajar siswa, kehadiran siswa di sekolah memiliki hubungan yang signifikan dengan kemampuan belajar mereka. Oleh karena itu diperlukan suatu sistem untuk melakukan pencatatan terhadap kehadiran siswa. Pencatatan kehadiran dilakukan dengan menggunakan pembaca QR code yang akan membaca kartu siswa. Setiap siswa akan diberikan kartu yang dapat dicetak dari sistem dengan QR code yang unik. Kode ini akan diterjemahkan ke dalam sistem berbasis web saat siswa akan hadir maupun keluar masuk dari dan ke lingkungan sekolah. Dengan sistem ini, maka data kehadiran siswa dapat tercatat dan terrekapitulasi dengan cepat bila dibandingkan dengan metode manual.
IMPLEMENTASI SISTEM PREDIKSI GAYA BELAJAR MAHASISWA MENGGUNAKAN NAÏVE BAYES BERBASIS WEB Lase, Yuyun Yusnida; Syafli, Sekar Arini; Fatmi, Yulia; Prayudani, Santi; Lubis, Arif Ridho; Haryadi, Haryadi
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 4 (2024): November 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i4.2327

Abstract

Aplikasi ini dibuat untuk memprediksi  gaya belajar mahasiswa, menggunakan algoritma naïve bayes, dibandingkan dengan algoritmanya naïve bayes sangat baik dalam  proses klasifikasi, untuk melakukan prediksi dimasa depan algoritma ini menggunakan probabilitas dan statistik. Data yang digunakan berupa data demografis mahasiswa seperti semester/tingkat studi, data gaya belajar seperti visual, kinestetik, auditori, dan data preferensi belajar seperti preferensi belajar visual, preferensi belajar auditori, dan preferensi belajar kinestetik. Metode pembelajaran yang diamati untuk menentukan gaya belajar metode synchoronous.  Sampel data yang digunakan adalah mahasiswa program studi teknologi rekayasa perangkat lunak. Bahasa yang digunakan dalam membuat aplikasi ini menggunakan  PHP dan database MySQL. Aplikasi ini nantinya dapat membantu tenaga pendidik dapat menyusun strategi pembelajaran yang sesuai dengan gaya belajar mahasiswa sehingga proses pembelajaran dapat berjalan dengan efektif dan efesien.
BERT SENTIMENT ANALYSIS FOR DETECTING FRAUDULENT MESSAGES Lase, Yuyun Yusnida; Nauli, Arif Aryaguna; Mahulae, Doni Ganda Marbungaran
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 4 No. 2 (2025): May 2025
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v4i2.225

Abstract

With the increasing prevalence of digital communication, fraudulent SMS messages have become a growing concern. This study employs a BERT-based sentiment approach to classify SMS messages into four categories: fraud, gambling, Unsecured Credit (KTA – Kredit Tanpa Agunan), and others. These categories were determined based on content analysis and common patterns found in high-risk messages, such as suspicious transaction invitations (fraud), betting promotions (gambling), offers for unsecured loans (KTA), and other messages that do not fall into the three main categories. The dataset used consists of approximately 20,000 message records, which underwent data cleaning, tokenization, and manual labeling based on the aforementioned criteria. The model was trained using the AdamW optimizer with CrossEntropyLoss as the loss function for multi-class classification. Training was conducted over 3 epochs, a number chosen based on observations of evaluation metrics on the validation data, which showed that model accuracy began to plateau after the third epoch, while overfitting started to occur in subsequent epochs. After training, the model achieved an average accuracy of 92%. This result indicates that the BERT model is effective in understanding patterns in text messages and capable of classifying message categories with a high level of accuracy. These findings support the application of BERT technology in the efficient detection and identification of fraudulent messages.
Co-Authors Adwin Adam , Hikmah Al Khowarizmi Alex Sander Sitepu Citra Wasti Silaban Fatmi, Yulia Fildzah Nadiah Friendly, Friendly Gabriel Ardi Hutagalung Gurning, Yohannes Christian Harizahayu, Harizahayu Harris Aminuddin Haryadi - Hikmah Adwin Adam Julham Julham Lubis, Arif Ridho Mahulae, Doni Ganda Marbungaran Muhammad Luthfi Hamzah Muharman Lubis Nauli, Arif Aryaguna Prayudani, Santi Ramdani Safitri, Habibi Reza Kavarin Telaumbanua Saragih, Samuel Cristian Syafli, Sekar Arini Syamsul Arifin Yulia Fatmi Yulia Fatmi