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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Journal of Telematics and Informatics Fountain of Informatics Journal Format : Jurnal Imiah Teknik Informatika JIEET (Journal of Information Engineering and Educational Technology) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Mantik Penusa SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Informatika Universitas Pamulang Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Informatika : Jurnal Informatika, Manajemen dan Komputer CSRID (Computer Science Research and Its Development Journal) CCIT (Creative Communication and Innovative Technology) Journal JSAI (Journal Scientific and Applied Informatics) JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Komtekinfo Jurnal Informatika dan Rekayasa Perangkat Lunak
Sinaga, Anita Sindar R M
STMIK Pelita Nusantara
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Seleksi Wajah Digital Menggunakan Algoritma Camshift Anita Sindar R M Sinaga
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 5 No. 1 (2020): Mei 2020
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (243.839 KB) | DOI: 10.14421/jiska.2020.51-01

Abstract

Real time for digital face database selection using camshift algorithm] Education taken 4-5 years affects physical development. This study uses student digital video data. The recording results are used to identify certain characteristics possessed by a student later stored in the digital file database catalog. The stages of the study consisted of identification, recognition and matching of faces. It starts from converting .mp4 videos to .AVI format. The CAMShift algorithm uses basic HSV colors for tracking face position (tracking) and faces recognition. 1-2 seconds video produces 45-200 frames PNG file. The face matching test results were carried out on several video play, the success of detection: 100% selected, 45%-60%, 80-90%, concluded around 50%-100% successful. Face movements will be caught by the centroid bounding box, if the color of the face is dominant in Hue.  
Pemanfaatan teknologi blockchain pada kelompok tani melalui solusi inovatif Supply Chain Finance (SCF) Anita Sindar Sinaga; Nuraisana Nuraisana; R. Mahdalena Simanjorang; Amalia Rossa; Dini Auliah
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 10, No 3 (2026): June
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v10i3.39577

Abstract

Abstrak Keterbatasan akses pembiayaan menjadi kendala utama bagi kelompok tani pada musim tanam padi. Pada musim panen tanpa ada monitoring dari pemerintahan desa harga gabah maupun beras menjadi tidak stabil. Blockchain menawarkan sistem pencatatan transaksi yang terdesentralisasi, transparan, dan sulit dimanipulasi. Pengawasan harga penjualan padi dapat dimonitoring langsung pada kelompok tani desa melalui pencatatan transaksi secara transparan dan real time. Pengawasan harga padi di tingkat desa umumnya dilakukan secara manual melalui papan informasi kelompok tani (posko), musyawarah warga atau rembug desa. Penting edukasi bagi pengurus kelompok tani mengenai cara kerja buku besar digital dan pentingnya integritas data. Pemerintah Desa (Pemdes) dapat bertindak sebagai salah satu pengawas dalam sistem. Pemdes mendapatkan data harga yang akurat dan tidak bisa dimanipulasi, sehingga bisa langsung mendeteksi jika harga gabah di bawah harga pembelian pemerintah. Kegiatan pemanfaatan teknologi terkini seperti Blockchain digabungkan dengan sistem pembiayaan SCF pada bidang pertanian dapat meningkatkan perputaran uang dikalangan petani sehingga kesejahteraan petani tercapai. Capaian dari penggunaan teknologi ini pada pengawasan harga padi dan beras dikalangan anggota kelompok tani pada setiap musim. Kata kunci: solusi inovatif; kelompok tani; teknologi blockchain; SCF. Abstract Limited access to financing is a major obstacle for farmer groups during the rice planting season. During the harvest season, without monitoring from the village government, the price of unhusked rice and rice is unstable. Blockchain offers a decentralized, transparent, and difficult-to-manipulate transaction recording system. Monitoring of rice sales prices can be directly monitored by village farmer groups through transparent and real-time transaction recording. Monitoring of rice prices at the village level is generally carried out manually through farmer group information boards (posko), community meetings or village discussions. Educating farmer group administrators about how digital ledgers work and the importance of data integrity is crucial. Pemdes can act as one of the supervisors in the system. Pemdes obtains accurate, unmanipulated price data, enabling them to immediately detect if the price of unhusked rice is below the government's purchase price. Utilizing the latest technology, such as Blockchain, combined with the SCF financing system in agriculture, can increase cash flow among farmers, thereby achieving farmer welfare. The achievements of using this technology in monitoring the price of rice and paddy among members of farmer groups in each season. Keywords: innovative solutions; farmer groups; blockchain technology; SCF.  
Comparison of Modern NLP with Classical Machine Learning Algorithms in Evaluating Food Security Programs Anita Sindar Sinaga; Dameria Esterlina Sijabat; Bella Saputri; Nadia Aulia
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 4 (2025): Volume 6 Number 4 Desember 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v6i4.1395

Abstract

The success of food security programs faces various challenges. Most of the available data is in the form of unstructured text reports, news, and policy documents. The BERT (Bidirectional Encoder Representations from Transformers) model allows the system to read reports and news by considering the relationship between words in sentences. Compared to Support Vector Machines (SVMs) that rely on numerical data. The dataset is expanded to improve the generalization of the IndoBERT Classifier. There are 6 commodity data and 3 labels used in IndoBERT Modeling, represented by a 768-dimensional feature vector resulting in Accuracy 0.8333 (83.33%) indicating 5 correct predictions, with one misclassification. Tuned Min-Max on Support Vector Machines (SVM) is used in each dimension to find the optimal hyperplane contributing. The feature matrix x with size (39,10) and the target variable y with size (39) show Accuracy 0.92 (92.0%) that the data division process maintains the class proportion consistently. SVM performed better than IndoBERT. Classification evaluation of the models showed IndoBERT with Accuracy 83% and SVM Sccuracy 87%.
Synthetic Data Pattern Simulation of Patient Care Journey Using K-Means Clustering Arjon Samuel Sitio; Richard Parlindungan; Anita Sindar Sinaga
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 4 (2025): Volume 6 Number 4 Desember 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v6i4.1498

Abstract

Heterogeneous synthetic data is artificial data that can include many types of features (demographics, examinations, therapies). Complex patients (many procedures & medications) but fast service process and low complications. All patients are divided into 4 clusters, patient segmentation includes cluster 1 including mild patients, Cluster 2 including complex patients, Cluster 3 including high costs, Cluster 4 including high readmission risk. The highest silhouette score is 0.2187, which is obtained when the number of clusters (k) is 2. Based on previous calculations, the Davies-Bouldin Index result for the current clustering solution is 2.33. The Calinski-Harabasz index for the clustering solution with k=4 is 367.72. Clustering results are simply groups, without labels. Further analysis is needed to assign clinical meaning to each cluster.
Predictive Analytics of Food Retail Seasonal Trends with Advanced Forecasting Modeling Anita Sindar Sinaga; Dameria Esterlina Br Jabat; Amalia Rossa; Dini Auliah
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.13173

Abstract

Food sales in food retailers generally increase on certain days. Three food categories served as data sources in this study: staple foods, ready-to-eat foods, and dairy products. Predictive analysis of seasonal trends in food retailers shows that macroeconomic factors, seasonal patterns, and religious holiday indicators play a significant role in shaping sales. Staples is the highest-revenue category, while frozen foods has the lowest volume of the three. Each highlighted sector, including dairy, is expected to experience a measurable increase in turnover over the coming period. All models exhibit varying accuracy in predicting 2026 sales compared to actual 2025 sales, evaluated using MAPE, RMSE, and MAE for key products. Moving Average and LSTM tend to be conservative, while ETS and ARIMA are more optimistic but remain limited by limited data. Random Forest also struggles to capture complex relationships. Prophet stands out for its ability to incorporate exogenous variables and handle seasonality, although caution is needed when interpreting future values. The MAPE values ranged from 1.89% to 5.34%, indicating excellent predictive accuracy, as MAPE values below 10% are generally considered high accuracy. The low RMSE and MAE values also indicate a relatively small difference between the 2026 prediction and the actual 2025 values.
Co-Authors Amalia Rossa Arjon Samuel Sitio Arjon Samuel Sitio Arjon Samuel Sitio Bella Saputri Bosker Sinaga Dameria Esterlina Br Jabat Dameria Esterlina Sijabat Desimeri Laoli Dewi Simanjuntak Dini Auliah Endra Marpaung Jimmi Herdianda Gurusinga Julkari Sinta Parapat Murni Marbun Nadia Aulia Novi Sri Wanti Ginting Nuraisana Nuraisana Priskilla Parimanen R. Mahdalena Simanjorang Ravindran Ravindran Richard Parlindungan Ricky Eka Putra Suciana Rahayu Sumitra Dewi