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All Journal Teknika Jurnal SOLMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Building of Informatics, Technology and Science Vocatech : Vocational Education and Technology Journal JOURNAL OF INFORMATICS AND COMPUTER SCIENCE G-Tech : Jurnal Teknologi Terapan Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) JINAV: Journal of Information and Visualization Rambideun : Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology ARRUS Journal of Engineering and Technology Instal : Jurnal Komputer Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Jurnal Ilmu Komputer dan Informatika TECHSI - Jurnal Teknik Informatika Jurnal Teknologi Terapan and Sains 4.0 MEUSEURAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Jurnal Pengabdian Masyarakat Ilmu Komputer Serambi Engineering JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Lidya Rosnita
Universitas Malikussaleh
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Analysis of Public Sentiment Towards Celebrity Endorsment On Social Media Using Support Vector Machine Syahputra, M Oriza; Bustami, Bustami; Rosnita, Lidya
International Journal of Engineering, Science and Information Technology Vol 4, No 3 (2024)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i3.543

Abstract

Analysis of public sentiment towards celebrity endorsements on social media is very important to understand the public's response to promotional campaigns involving celebrities. In this study, we combine the VADER labeling method with the Support Vector Machine (SVM) method to analyze public sentiment toward celebrity endorsements on social media. Data is taken from various social media sources such as Twitter, Instagram, and Facebook. The data is pre-processed to ensure data accuracy and relevance and then labeled with the VADER method to determine the positive, negative, or neutral sentiment of the text. The labeled data is then extracted for features and used to train the SVM model. The trained SVM model is then validated using test data to measure its accuracy and performance. The results of the analysis provide useful insight into public sentiment towards celebrity endorsements on social media and can provide recommendations for stakeholders regarding this matter. Overall, combining the VADER labeling method with SVM in analyzing public sentiment towards celebrity endorsements on social media shows more accurate results and can provide practical benefits in marketing and promotional strategies. The results shown using the Support Vector Machine method with a ratio of 80:20 can provide average precision results of 77%, recall of 100%, f1-score of 87%, and accuracy of 76.92%. Twitter application user sentiment shows that 77% (338 data) of Twitter user reviews provide positive sentiment and 23% (119 data) provide negative sentiment reviews from a total of 517 data. Suggestions from researchers are that in future research they can add more data to make modeling easier to provide higher accuracy values. Using other classification and performance evaluation methods, such as Naive Bayes, Decision Tree, Fuzzy, or Deep Learning. Use other data processing tools, such as RapidMiner, Jupyter Notebook, RStudio, or others.
Edukasi K3 Bidang Kelistrikan Bagi Anak-Anak di Desa Cot Mee, Kecamatan Nisam, Kabupaten Aceh Utara Nurfebruary, Nanda Sitti; Nisa, Fidyatun; Ikhwani, Muhammad; Dian Putri, Yohana; Maimunah, Siti; Rosnita, Lidya
Jurnal Malikussaleh Mengabdi Vol 3, No 1 (2024): Jurnal Malikussaleh Mengabdi, April 2024
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v3i1.16200

Abstract

Pengetahuan mengenai Kesehatan dan Keselamat Kerja (K3) bidang kelistrikan sangat penting dalam kehidupan sekarang ini. Ditambah lagi dengan semakin banyaknya penggunaan peralatan elektronik. Ketergantungan pada listrik tidak hanya terbatas pada aktivitas rumah tangga, tetapi juga berdampak pada anak-anak yang tentunya bisa membahayakan bagi anak-anak tersebut jika tidak dibekali dengan pemahaman yang baik mengenai penggunaan peralatan elektronik. Desa Cot Mee merupakan salah satu desa di Kecamatan Nisam, Kabupaten Aceh Utara, Provinsi Aceh memiliki kurang lebih 50 anak-anak usia sekolah dalam rentang usia 5-14 tahun. Kegiatan sehari-hari banyak dihabiskan dengan menggunakan peralatan elektronik dan juga kegiatan bermain di luar ruangan yang dekat area aliran listrik seperti gardu listrik. Apabila anak-anak tidak diberikan pengetahuan mengenai penggunaan peralatan elektronik yang benar, maka akan sangat rentan terhadap kecelakaan. Oleh karena itu, dilakukan kegiatan pengabdian kepada masyarakat untuk mengedukasi K3 kelistrikan bagi anak-anak di Desa Cot Mee. Diharapkan melalui kegiatan edukasi ini, anak-anak di Desa Cot Mee menjadi lebih paham tentang K3 kelistrikan dan selalu waspada terhadap pengunaan peralatan elektronik dalam kehidupan sehari-hari.
Water Quality Monitoring and Control System for Tilapia Cultivation Based on Internet of Things Rosnita, Lidya; Ikhwani, Muhammad; Aidilof, Hafizh Al Kautsar; Salamah, Salamah; Hamsi, Widia; Rangkuti, Haris Yunanda
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.566

Abstract

This research analyzes the quality of water for tilapia habitat which is a type of brackish water fish that is currently widely cultivated by pond farmers. This fish is the choice because of its flexibility regarding habitat. However, despite having flexibility in terms of habitat, each harvest of tilapia that lives in a different habitat will produce tilapia with different quantity and quality. Currently, many tilapia farmers still carry out the cultivation process using traditional methods using ponds. Kuala Kerto Village, Lapang District, North Aceh is one of the locations where many tilapia fish farmers use ponds as a habitat for this fish. Not infrequently, changes in natural conditions such as rain and floods have an impact on tilapia fish ponds in this village. Thus, crop yields are very varied, often even resulting in losses. One of the reasons for this is that there is still minimal use of technology in tilapia cultivation in this village. The design of a water quality monitoring and control system for IoT-based tilapia cultivation in this research was carried out to help the problems of tilapia pond farmers. Through this research, a tool was produced in the form of a prototype IoT device that can be used to monitor and control water quality in tilapia fish ponds. This device utilizes several sensors such as turbidity sensors, ammonia sensors, salinity sensors, pH sensors, and several other sensors as data takers which will later be transmitted and displayed via a web application. Research and development of this device uses the RD method, namely research and development.
Grouping Sales Levels Smartphone Of Offline Store Using BIRCH Clustering Algorithm Rahmadani Sari, Putri Dwi; Qamal, Mukti; Rosnita, Lidya
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.558

Abstract

From 2020 to 2024, TM_Store and Jaya Com exhibited different sales patterns based on cluster analysis using the BIRCH algorithm. The background of this research is to provide strategic insights to both stores for improving their sales performance through data analysis. The sales data used includes brand, type, month, year, stock quantity, quantity sold, unit price, and total sales. The BIRCH method was chosen for its effectiveness in handling large datasets and providing accurate clustering results. The clustering results indicate a significant increase in the "Moderate" category, from 12 sales in 2020 to 354 sales in 2023. Meanwhile, the "Very High" category also saw an increase from 5 sales in 2020 to 97 sales in 2023, with sales in the "Very Low" category remaining high at 70 sales in 2023. On the other hand, Jaya Com was dominated by the "Very High" category, with a sharp increase from 25 sales in 2020 to 597 sales in 2023. The "High" category also showed significant growth, from 6 sales in 2020 to 98 sales in 2023. This data indicates that Jaya Com focuses on high-performance products, while TM_Store shows a more balanced distribution across various sales categories. Based on the analysis, Jaya Com had 1988 data points with 1984 cluster points, whereas TM_Store had 2012 data points with 1811 cluster points. Overall, the study concludes that the BIRCH algorithm can identify significant sales patterns in both stores, aiding in the development of more effective and efficient promotional strategies tailored to each sales category's performance.
SOSIALISASI UU ITE BAGI SISWA SMA NEGERI 4 LHOKSEUMAWE "CERDAS MENANGKAL HOAX DALAM MENGGUNAKAN INTERNET" Fidyatun Nisa; Nanda Sitti Nurfebruary; Muhammad Ikhwani; Zalfie Ardian; Lidya Rosnita; Habib Muharry Yusdartono
Jurnal Pengabdian Masyarakat Ilmu Komputer Vol. 1 No. 2 (2024): Mei
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jpmik.v1i2.714

Abstract

Undang Undang Nomor 11 tahun 2008 tentang Informasi Transaksi Elektronik atau UU ITE merupakan undang-undang atau peraturan yang sering kali bersentuhan langsung dengan berbagai orang, terutama pada era teknologi yang sedang berkembang saat ini. Secara umum, UU ITE masih belum tersosialisasikan dengan baik ke semua kalangan, termasuk pada kalangan siswa/siswi Sekolah Menengah Atas. Oleh karena itu, SMA Negeri 4 Lhokseumawe menjadi sasaran tim Pengabdian kepada Masyarakat Universitas Malikussaleh sebagai sarana untuk mensosialisasikan UU ITE. Hal ini dianggap penting karena pada saat ini kalangan muda (terutama siswa/siswi SMA) tidak terpisahkan dari teknologi internet. Sehingga perlu disampaikan bahwa ada sanksi atau hukuman yang berlaku apabila tidak waspada dalam memakai internet. Kegiatan sosialisasi ini diharapkan menjadi pembelajaran bagi siswa/siswi maupun guru-guru di SMA Negeri 4 Lhokseumawe agar lebih cerdas dan bijak dalam memakai internet, terutama untuk mencegah penyebaran berita hoax melalui social media maupun aplikasi chatting. Dari hasil sosialisasi yang dilaksanakan, dapat disimpulkan bahwa kesadaran dan pengetahuan siswa/siswi dan guru SMA Negeri 4 Lhokseumawe mengenai UU ITE masih rendah, sehingga sosialisasi ini diharapkan menjadi pembekalan agar mereka dapat waspada dalam menggunakan internet, terutama untuk menangkal berita hoax.
Applying TF-IDF and K-NN for Clickbait Detection in Indonesian Online News Headlines Afif, Muhammad Athallah; Ula, Munirul; Rosnita, Lidya; Rizal, Rizal
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 2 (2024): Journal of Advanced Computer Knowledge and Algorithms - April 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i2.15810

Abstract

This research explores the application of TF-IDF (Term Frequency-Inverse Document Frequency) and K-Nearest Neighbor (K-NN) in constructing a clickbait detection system for Indonesian online news headlines. The TF-IDF method is employed to ascertain the significance of words in news headlines, utilizing a tokenization process to generate numeric representations. The TF-IDF matrix serves as features in the K-NN classification model, with k=1 determining the most similar class. Model evaluation yields outstanding results, achieving accuracy, precision, recall, and F1-Score all reaching 1.0. The confusion matrix unveils no misclassifications, affirming the model's adeptness in correctly classifying all samples.
Decision Support System for Selecting the Best Facial Wash Brand for Acne-Prone Skin Using the Fuzzy Analytical Hierarchy Process (F-AHP) Method Armaya, Devira Yuda; Rosnita, Lidya; Asrianda, Asrianda; Rachman, Aulia; Azhari, Muhammad
Journal of Advanced Computer Knowledge and Algorithms Vol 2, No 1 (2025): Journal of Advanced Computer Knowledge and Algorithms - January 2025
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v2i1.19542

Abstract

Acne is a problem that is often experienced by women. The factors that trigger acne skin problems are due to the pores on the facial skin that are clogged with oil, and the presence of bacteria. This research was conducted to provide a decision support system in recommending brands facial washthe best for acne prone skin types through the value of the intensity of importance of criteria such as price, packaging form, packaging size, active ingredient content, and packaging design. The final result of the calculation process using the method fuzzy AHP produces the lowest to the highest weight value for each brandfacial wash. And the final ranking data shows that there are 5 brand recommendations facial wash with the highest value of the other alternatives. That is there is an alternative code A04 which has the highest value asfacial wash the best for acne prone skin types, namely the brand is The Body Shop Tea Tree Skin Clearing Facial Wash with a total value of 7.663, and followed by alternative code A13 namely is Some By Mi AHA BHA PHA with a total value of 7.663, alternative code A07 is Miracle Cleansing with a total value of 7.337, the alternative code A15 is Ponds Anti Bacterial Facal Foam with a total value of 7.326, and the last alternative code A14 is Emina MS Pimple Acne Solutonwith a total score of 6.663.
Pelatihan Pembuatan Sabun Cuci Piring Serta Pemasaran Online Sebagai Peningkatan Peluang Wirausaha Masyarakat di Desa Bale, Kecamatan Syamtalira Bayu, Kabupaten Aceh Utara Rosnita, Lidya; Nisa, Fidyatun; Nurfebruary, Nanda Sitti; Ikhwani, Muhammad; Rachman, Aulia; Azhari, Muhammad
Jurnal Malikussaleh Mengabdi Vol 3, No 2 (2024): Jurnal Malikussaleh Mengabdi, Oktober 2024
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v3i2.19100

Abstract

Peningkatan kesejahteraan sosial dapat dilakukan melalui kegiatan pemberdayaaan masyarakat. Dalam kaitannya dengan upaya mengembangkan kemampuan serta potensi masyarakat, dilakukan berbagai alternatif kegiatan seperti pada bidang wirausaha. Salah satu contoh kegiatan wirausaha adalah pembuatan serta penjualan suatu produk. Namun, terdapat permasalahan yang mungkin timbul dari kegiatan tersebut seperti terbatasnya pengetahuan dan pelatihan untuk menunjang proses pembuatan serta pemasaran produk itu sendiri. Oleh karena itu, dilakukan kegiatan Pengabdian kepada masyarakat yang bertujuan untuk berbagi pengetahuan melalui pelatihan pembuatan dan pemasaran online sabun cuci piring dengan memanfaatkan media internet dan berbagai sosial media, serta marketplace seperti Shopee dan TikTok Shop. Kegiatan ini dilaksanakan di Desa Bale, Kecamatan Syamtalira Bayu, Kabupaten Aceh Utara. Pelatihan berjalan dengan lancar, semua peserta aktif dalam diskusi dan tanya jawab baik saat pemberian materi maupun saat praktek pembuatan sabun cuci piring. Hasil yang diperoleh dari kegiatan pengabdian kepada masyarakat ini adalah meningkatnya pengetahuan masyarakat tentang teknik pembuatan sabun cuci piring serta bagaimana cara melakukan pemasaran online terhadap suatu produk
Plagiarism Detection Application for Computer Science Student Theses Using Cosine Similarity and Rabin-Karp Ansyari, Taufik Habib; Abdullah, Dahlan; Rosnita, Lidya
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.686

Abstract

Plagiarism detection is critical in maintaining academic integrity, particularly in higher education. This study focuses on developing a plagiarism detection application for Computer Science student theses. The application leverages the Cosine Similarity and Rabin-Karp algorithms to accurately and efficiently detect textual similarities. Developed using JavaScript, the application provides an intuitive interface and reliable performance, making it a practical tool for educational institutions. The application includes features allowing users to upload thesis documents, analyze textual content, and measure plagiarism levels by comparing them to an existing dataset. The Cosine Similarity algorithm measures the overall similarity between documents, while the Rabin-Karp algorithm focuses on identifying exact matches in phrases and sentences. The results demonstrate the efficacy of both algorithms. For titles, the Cosine Similarity algorithm achieved a 100% similarity rate for identical documents while detecting minor plagiarism with a similarity level of 5.86% for other documents. For abstracts, it achieved 100% similarity for the first document, 2.78% for the second document, and 8.37% for the third document. These findings highlight the algorithm's ability to detect exact matches and partial overlaps in textual content. The Rabin-Karp algorithm showed comparable performance, particularly in detecting phrase-level similarities. For titles, it recorded 100% similarity for identical documents, 11.42% for the second document, and 16.92% for the third document. For abstracts, the algorithm also achieved 100% similarity for the first document, 11.42% for the second document, and 16.81% for the third document. The study confirms that both algorithms complement each other in detecting different forms of plagiarism. The Cosine Similarity algorithm excels in identifying global patterns of similarity, while the Rabin-Karp algorithm is more suited for finding exact matches in specific phrases or sentences. This dual approach provides a comprehensive solution for detecting plagiarism in academic theses. The findings from this research are promising and highlight the potential of the application as a reliable tool for ensuring academic integrity. Future improvements could include expanding the dataset, enhancing the user interface, and integrating additional algorithms for cross-language plagiarism detection. This application contributes to academic honesty and is a valuable resource for educators, researchers, and students in combating plagiarism effectively. 
Expert System For Diagnosis of Mental Health Disorders in Students Using Case-Based Reasoning Method With a Web-Based Positive Psychology Approach Bancin, Udurta; Bustami, Bustami; Rosnita, Lidya
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.592

Abstract

Mental health issues among students have become a significant concern affecting their quality of life and academic performance. An effective expert system is needed to diagnose and provide appropriate interventions. This research develops a web-based expert system that utilizes the Case-Based Reasoning (CBR) method combined with a positive psychology approach to diagnose mental health disorders in students. The CBR method identifies similarities between new and previous cases, while the positive psychology approach focuses on individual strengths and potential for growth. The system integrates a database of student mental health cases and CBR algorithms to produce relevant diagnoses. This study investigates four types of mental health disorders: panic, anxiety, stress, and depression. The method used for data analysis is Case-Based Reasoning. The diagnosis results are based on calculations from symptom choices within the system, where each symptom has a weight. The highest similarity calculation obtained from past cases is used as a solution to address the problem. System testing, based on expert knowledge with 15 test data samples categorized by mental health disorders and 38 symptoms, achieved an accuracy rate of 85%.
Co-Authors Afif, Muhammad Athallah Afridah, Rita Aidilof, Hafizh Al Kausar Aidilof, Hafizh Al Kautsar Amelia, Ulva Andrea Micola Azwir Ansyari, Taufik Habib Armaya, Devira Yuda Asrianda Asrianda Azzahra Iskandar, Farah Bancin, Udurta Bustami Bustami Bustami Dahlan Abdullah Deassy Siska Dela, Monisa Dian Putri, Yohana Efendi, Syahril Efendi, Syahril Elma Fitria Ananda Eva Darnila Eva Darnila Fadlisyah Fadlisyah Fasdarsyah Fasdarsyah Fidyatun Nisa Fuadi, Wahyu Furqan, Hafizul Habib Muharry Yusdartono Hafidh Rafif, Teuku Muhammad Hafizh Al Kautsar Aidilof Hamsi, Widia Harahap, Ilham Taruna Harahap, Lina Mardiana Haris Yunanda Rangkuti Ikramina ikramina ikramina, Ikramina Jange, Beno Kurniawati Kurniawati Kurniawati Kurniawati Lina Mardiana Harahap Mara Wahyu Alamsyah Pane Muhammad Azhari Muhammad Fajri Muhammad Fajri Muhammad Fikry Muhammad Ikhwani Muhammad Muhammad Muhammad Zarlis Muhammad Zarlis, Muhammad Mukti Qamal Mulyadi, Rizki Munirul Ula Muzaffar Rigayatsyah Nanda Sitti Nurfebruary Nasution, Wahidatunnisa Naturizal, Rayhan Naza Amarianda Nurfebruary, Nanda Sitti Nurhaliza Bin Aras Nurqamarina Nurul Aula Pasaribu, Hafni Maya Sari Pratiwi, Dinda Pulungan, Fauzi Irham Putri, Sri Raihan Rachman, Aulia Rachmat Triandi Tjahjanto Rahmadani Sari, Putri Dwi Rahmat Triandi Rangkuti, Haris Yunanda Rian Kelana Putra Rini Meiyanti Risawandi, Risawandi Rizal Rizal Rizal Rizal Rizal S.Si., M.IT, Rizal Rizky Putra Fhonna Safwandi Safwandi, Safwandi Said Fadlan Anshari salamah salamah Samosir, Dini Kairiyah Saputri, Rifa Andriani Siti Maimunah Sujacka Retno Syahputra, M Oriza Ulva Ilyatin Wahyu Fuadi Yesy Afrillia Zara Yunizar Zulfadli Zulfadli