Article Per Year (5 Year)
p-Index From 2021 - 2026
7.445
P-Index
This Author published in this journals
All Journal Teknika Jurnal SOLMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi JURIKOM (Jurnal Riset Komputer) 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 Brilliance: Research of Artificial Intelligence TECHSI - Jurnal Teknik Informatika Jurnal Teknologi Terapan and Sains 4.0 Electronic Journal of Education, Social Economics and Technology MEUSEURAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Jurnal Pengabdian Masyarakat Ilmu Komputer Journal Serambi Engineering (JSE) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
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 Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 59 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 59 Documents
Search

 2   3   4   5   6 
Sistem Pendeteksi Tingkat Kesegaran Daging Ayam pada Citra Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Android Naturizal, Rayhan; Fuadi, Wahyu; Rosnita, Lidya
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp301-312

Abstract

This research develops a chicken meat freshness detection system based on image processing, implemented on an Android platform using the Convolutional Neural Network (CNN) method optimized with TensorFlow Lite. The system classifies chicken meat into three categories: fresh, less fresh, and rotten. The CNN model uses 32 filters to enhance feature extraction from the meat images. Testing on 30 samples, with each category tested 10 times, showed an accuracy of 90%, with 27 correct detections and 3 errors in the less fresh category. While the system effectively identifies fresh and rotten categories, there is a challenge in distinguishing the less fresh category due to its ambiguous visual characteristics. One limitation is the lack of a bounding box, causing the application to still provide detection results even when the scanned object is not chicken meat. This application is specifically designed to detect chicken meat pieces, so it is not recommended for use outside this context.
Penerapan Metode Content-Based Filtering dalam Sistem Rekomendasi Objek Wisata di Aceh Tamiang Pratiwi, Dinda; Asrianda, Asrianda; Rosnita, Lidya
Jurnal Ilmu Komputer dan Informatika Vol 4 No 2 (2024): JIKI - Desember 2024
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54082/jiki.169

Abstract

Pariwisata berbasis teknologi informasi menjadi semakin penting dalam era digital untuk mempermudah wisatawan menemukan destinasi yang sesuai dengan preferensi mereka. Penelitian ini bertujuan mengembangkan sistem rekomendasi objek wisata berbasis web di Aceh Tamiang menggunakan metode content-based filtering. Sistem ini dirancang untuk menganalisis ulasan dari Google Maps agar memberikan rekomendasi yang relevan dengan preferensi pengguna. Data ulasan dikumpulkan melalui SerpApi, kemudian diproses melalui tahapan preprocessing, perhitungan bobot TF, IDF, dan TF-IDF, serta analisis kesamaan menggunakan cosine similarity. Hasil penelitian menunjukkan bahwa sistem ini mampu memberikan rekomendasi yang sesuai dengan preferensi wisatawan, khususnya untuk atribut seperti "pantai", "piknik", "sepi", dan "sungai". Sistem ini diharapkan dapat membantu pengambilan keputusan wisatawan secara lebih efisien dan memberikan kontribusi positif terhadap pengembangan pariwisata di Aceh Tamiang.
The Implementation of a Chatbot and Website Interface in Department of Development Economic Mulyadi, Rizki; Rosnita, Lidya; Rachman, Aulia; Azhari, Muhammad
Journal of Advanced Computer Knowledge and Algorithms Vol. 2 No. 2 (2025): Journal of Advanced Computer Knowledge and Algorithms - April 2025
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v2i2.21315

Abstract

The issue arising from this activity is the need to optimize the existing CMS Joomla-based website to make it more responsive and interactive in line with modern technological developments. The update was carried out using SP Page Builder as the main tool for interface development, while the chatbot was implemented using JavaScript technology with the Levenshtein Distance algorithm to provide automatic information services to users. The result of this practical work includes updates to several key components of the website, including the homepage, which is now equipped with a dynamic banner, a message from the head of the department, highlights of the study program, and a news and announcement section. The faculty and staff pages have been optimized with more comprehensive information, while the gallery page has been redesigned with a responsive grid layout. The chatbot implementation successfully provides automated information services for common academic questions, such as class schedules, KRS (course registration), and scholarships. Overall, these updates have improved the accessibility of information and the user experience in accessing the Deparment of Development Economics website.
Decision Support System for Plantation Land Recommendations in Mandailing Natal Regency Using The TOPSIS Method Rosnita, Lidya; Bustami, Bustami; Samosir, Dini Kairiyah; Aidilof, Hafizh Al Kausar
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 6, No 1 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v6i1.22387

Abstract

Plantations have great potential to be developed because they are a source of income for the community, farmers and PTPN in the area because Indonesia has the largest plantation land in the world. Mandailing Natal Regency is the district with the largest area in North Sumatra province, but Mandailing Natal has not been able to surpass crop production from plantation land in North Sumatra. The method for determining plantation land to produce good harvests is the TOPSIS algorithm for recommending plantation land. In this research, recommendations were made for plantation land with the aim of finding out what land is suitable in each subdistrict in Mandailing Natal Regency. The data method for this plantation land was taken at the Mandailing Natal Central Statistics Agency with the variables used, namely land area, area height, topography and rainfall. In implementing The decision support system using the TOPSIS algorithm on plantation land in Mandailing Natal Regency, the Recommendation results based on the type of plantation land in each sub-district are as follows: Rubber Plantation Land is highly recommended in Siabu District with a preference value of 0.56938682730811 and highly not recommended in Penyabungan District with preference value 0.33537499293319. Then, Palm Oil Plantation Land is highly recommended in Batang Natal sub-district with a preference value of 0.53467087652891 and not highly recommended in Tambangan sub-district with a preference value of 0.33181406496882. And the last one is Cocoa Farm which is highly recommended in Tambangan District with a preference value of 0.62855110465075 and highly not recommended in East Panyabungan District with a preference value of 0.25592982445435.
Clustering of Data Monitoring Water Quality Using Mean-Shift Clustering Method Aidilof, Hafizh Al Kautsar; Rosnita, Lidya; Kurniawati, Kurniawati; Ikhwani, Muhammad
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 6, No 1 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v6i1.22390

Abstract

This study aims to cluster water quality data from Nile tilapia ponds using the Mean Shift Clustering method. The parameters used to analyze water quality include temperature, pH, turbidity, and salinity, which are crucial factors for the growth and health of Nile tilapia. The data used in this research consist of water quality measurements from several Nile tilapia ponds. The clustering process seeks to identify groups of data with similar water quality characteristics, providing insights into optimal environmental conditions for tilapia farming. The clustering results reveal several distinct groups of water quality based on variations in temperature, pH, turbidity, and salinity. Results of the experiment show that a bandwidth value of 400 successfully identifies a relatively simple number of clusters, specifically four clusters. The Mean Shift Clustering method proves effective in grouping data without requiring assumptions about data distribution and can detect clusters with arbitrary shapes. Consequently, the findings of this study can be used to provide recommendations for improving water quality to enhance tilapia pond productivity.
Klastering Sayuran Unggulan Menggunakan Algoritma K-Means Lina Mardiana Harahap; Wahyu Fuadi; Lidya Rosnita; Eva Darnila; Rini Meiyanti
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.5277

Abstract

Horticulture, especially vegetables, has great potential to be developed because it becomes a source of income for the community and small farmers in each region because Indonesia is called an agrarian country with most of them working in agriculture. Mandailing Natal Regency is the district with the largest area in North Sumatra province, but Mandailing Natal has not been able to outperform vegetable crop production in North Sumatra. Data mining methods can find interesting and invisible patterns in data sets. One of the methods is the K-Means clustering algorithm which groups data into clusters based on the similarity of data characteristics. In this study, vegetable data was clustered which aims to determine the potential commodities in each area in Mandailing Natal Regency, plants that have potential in the area will be maintained and their production increased, while vegetable crops whose production is still low will be a priority to increase their production. The research method used in this study was to collect vegetable data from the Badan Pusat Statistik in the form of data on harvested area, production, plant area, and new planting area. In addition, data collection was carried out by conducting theoretical studies in journals. The results of clustering superior vegetables using the K-Means Algorithm are in the form of potential grouping into 3 clusters, namely low, medium, and high clusters and the output is a web-based system in its application. The results of the clustering analysis were obtained with each total data of 69 data, namely big chili with C1 81%, C2 16% and C3 3%. Cayenne C1 29%, C2 48% and C3 23%. Long Beans C1 26%, C2 38% and C3 36%. Kale C1 39%, C2 36% and C3 25%. Eggplant C1 43%, C2 29% and C3 28%. Tomato C1 41%, C2 58% and C3 1%.  
SISTEM PENDETEKSI POLA LAFADZ MUHAMMAD PADA CITRA AL-QURAN MENGGUNAKAN METODE PEIRCE Rosnita, Lidya
Jurnal Teknologi Terapan and Sains 4.0 Vol 1 No 3 (2020): Jurnal Teknologi Terapan & Sains
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/tts.v1i3.3267

Abstract

Al-Quran adalah firman Allah yang diturunkan kepada Nabi Muhammad SAW melalui perantaraan malaikat Jibril dan disampaikan kepada umat manusia untuk dijadikan pedoman dalam kehidupan di dunia ini. Program ini dibangun untuk mendeteksi pola lafazh Muhammad  pada citra Al-Quran sehingga dapat mempermudah pengguna dalam mengetahui dan mencari letak dan jumlah lafadz Muhammad pada setiap halaman citra Al-Quran. Dalam penelitian ini metode Peirce  digunakan untuk menghitung jarak keakuratan pola lafadz Muhammad pada citra Al-Quran. Sistem ini bekerja dengan cara menginput citra Al-Quran berformat bitmap (.bmp) kemudian terjadi proses resizing, grayscale, konvolusi. Pada tahap pengujian, metode ini mencari kemiripan antara citra Al-Quran uji dan citra Al-Quran latih sehingga terdeteksi pola lafazh Muhammad pada citra Al-Quran. Hasil Pelatihan sistem ini akan menyimpan dua pola yang dilatih yaitu lafadz Muhammad. Hasil pengujian Sistem Pendeteksi lafadz Muhammad  menunjukan bahwa keakuratan sistem ini sebesar 97,5 %, persentase detection rate tersebut menunjukkan bahwa metode Peirce dapat  digunakan sebagai salah satu pendekatan untuk pendeteksian pola lafadz Muhammad pada citra Al-Quran. Kata kunci: Pengolahan citra, risize, grayscale, konvolusi, peirce, lafadz Muhammad.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN LAPTOP PADA E-COMMERCE MENGGUNAKAN METODE SIMPLE MULTI ATTRIBUTE RATING TECHNIQUE Furqan, Hafizul; Risawandi, Risawandi; Rosnita, Lidya
Jurnal Teknologi Terapan and Sains 4.0 Vol 3 No 1 (2022): Jurnal Teknologi Terapan & Sains
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/tts.v3i1.6851

Abstract

Virus corona yang mewabah di Indonesia telah mengubah berbagai aspek dalam kehidupan, salah satunya adanya perubahan yang signifikan pada ekonomi digital. Masyarakat yang awalnya bertransaksi di toko konvensional mulai beralih ke toko digital, namun beberapa kelompok masyarakat masih kesulitan pada saat membeli laptop di e-commerce, karena tidak dapat memeriksa langsung produk dengan spesifikasi yang dibutuhkan. Oleh karena itu, penulis merancang suatu sistem pendukung keputusan yang dapat membantu untuk merekomendasikan laptop yang sesuai secara efektif dan efisien. Beberapa kriteria yang digunakan adalah rating produk, kondisi barang, harga, merek, garansi, tipe prosesor, kapasitas memori (RAM), tipe penyimpanan, kapasitas penyimpanan, kartu grafis, ukuran layar, dan sistem operasi. Simple Multi Attribute Rating Technique (SMART) adalah metode yang digunakan dalam proses perhitungan, pembobotan yang dapat dilakukan secara fleksibel merupakan kelebihan dari metode SMART yang mempermudah masyarakat memberikan nilai terhadap masing-masing kriteria berdasarkan preferensi yang diinginkan, nilai bobot juga tidak akan berpengaruh jika ada penambahan ataupun pengurangan alternatif. Setelah menggunakan 20 data alternatif dari salah satu e-commerce (shopee), sistem berhasil memberikan keluaran berupa peringkat setiap alternatif dan hasil yang didapat menunjukkan nilai alternatif tertinggi sebesar 0,639841521 dan nilai terkecil sebesar 0,345627506.
Multi-criteria K-nearest neighbor in the classification of eye diseases at Dr. Fauziah Bireuen Hospital asrianda, asrianda; Rosnita, Lidya; Jange, Beno; Zulfadli, Zulfadli
Bahasa Indonesia Vol 15 No 02 (2023): Instal : Jurnal Komputer Periode (Juli-Desember)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalkomputer.v15i02.168

Abstract

Classification studies and maps each attribute in one of the predetermined classes. K-NN has several drawbacks such as high computational load in conducting training data, large memory when implemented. The selection of distance metrics and data pre-processing does not affect the increase in accuracy, but in this study the Euclidean distance metric is better than Manhattan in increasing accuracy. Finding the optimal number of neighbors varies between different distances, computation takes a long time. High noise for smaller k, the higher the value of k, the lower the accuracy and the smaller the computation time. K odd or even does not affect the high or low accuracy, but does affect the computation time.
A Random Forest-Based Predictive Model for Student Academic Performance: A Case Study in Indonesian Public High Schools Saputri, Rifa Andriani; Asrianda, Asrianda; Rosnita, Lidya
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9460

Abstract

The rapid advancement of information technology has transformed education by providing tools to accurately predict students' academic performance. This study aims to develop a system for predicting academic achievement using the Random Forest algorithm, with a case study at SMAN 1 Aceh Barat Daya and SMAN 3 Aceh Barat Daya. Data from 632 student report cards for grades X and XI in the second semester of the 2023/2024 academic year were used, covering subjects such as Mathematics, Indonesian Language, and others, divided into 80% training data (506 samples) and 20% test data (136 samples). The research methodology involved data preprocessing, training the Random Forest model using entropy and information gain to construct decision trees, and performance evaluation using metrics such as accuracy, precision, and recall. The implementation resulted in a web-based application using Python and Flask, featuring an interactive interface and decision tree visualization. Testing on 136 test samples achieved an accuracy of 87.40%, with 111 correct predictions, 16 false positives, and 0 false negatives, demonstrating the model's reliability in identifying high-achieving students without missing potential. This research is expected to assist schools in identifying outstanding students, making data-driven decisions, and designing more effective educational strategies.
Co-Authors Afif, Muhammad Athallah Afridah, Rita Aidilof, Hafizh Al Kausar Aidilof, Hafizh Al Kautsar Al Kautsar Aidilof, Hafizh Almaula, Marhaban Amelia, Ulva Amir Fauzi Ansyari, Taufik Habib Armaya, Devira Yuda Asrianda Asrianda Azwir, Andrea Micola Azzahra Iskandar, Farah Bancin, Udurta Budiman, Muji Bustami Bustami Dahlan Abdullah Deassy Siska Defry Hamdhana Dela, Monisa Dian Putri, Yohana Diana, Mhd. Arief Efendi, Syahril Efendi, Syahril Elma Fitria Ananda Eva Darnila Eva Darnila Fachry Abda El Rahman Fadlisyah Fadlisyah Fajar Satria Fasdarsyah Fasdarsyah Fidyatun Nisa Fuadi, Wahyu Furqan, Hafizul Habib Muharry Yusdartono Hafidh Rafif, Teuku Muhammad Hamsi, Widia Harahap, Ilham Taruna Harahap, Lina Mardiana Ikramina ikramina ikramina, Ikramina Jange, Beno Khairul Amna, Khairul Kurniawati Kurniawati Lina Mardiana Harahap Mara Wahyu Alamsyah Pane Micola Azwir, Andrea Mirsa, Rinaldi Muhammad Azhari Muhammad Fajri Muhammad Fikry Muhammad Ikhwani Muhammad Muaz Munauwar Muhammad Muhammad Muhammad Zarlis Muhammad Zarlis, Muhammad Muharry Yusdartono, Habib Mukti Qamal Mulyadi, Rizki Munirul Ula Muzaffar Rigayatsyah Nanda Sitti Nurfebruary Nasution, Wahidatunnisa Naturizal, Rayhan Naza Amarianda Nur Ismiza Nurdin Nurfebruary, Nanda Sitti Nurhaliza Bin Aras Nurqamarina Nurul Aula Nurwijayanti Pasaribu, Hafni Maya Sari Pratiwi, Dinda Pulungan, Fauzi Irham Putri, Rizka Hilmi Putri, Sri Raihan Rachman, Aulia Rachmat Triandi Tjahjanto Rahma Fitria, Rahma 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 Safriana Safriana 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 Yunanda Rangkuti, Haris Zalfie Ardian Zara Yunizar Zulfadli Zulfadli