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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) Jurnal Mantik Penusa Jurnal Informatika Universitas Pamulang Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Indonesian Journal of Applied Informatics 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 Inkofar Jurnal Komtekinfo

Sinaga, Anita Sindar R M

STMIK Pelita Nusantara

Author-ID : 2985031

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Medicine & Pharmacology Public Health Social Sciences Transportation

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Sistem Pakar Diagnosa Penyakit Kacang Kedelai Menggunakan Metode Certainty Factor Novi Sri Wanti Ginting; Anita Sindar RMS
Jurnal KomtekInfo Vol. 5 No. 2 (2018): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Tanaman kedelai yang sedang tumbuh biasanya tidak muncul penyakit yang menyerang tanaman sehingga mengakibatkan gagal panen. Umumnya petani mengetahui gejala penyakit yang bermasalah tetapi tidak memiliki pengetahuan untuk mendiagnosis penyakit tanaman dan membutuhkan modal yang besar untuk memusnahkan tanaman pengganggu. Penerapan sistem informasi pakar merupakan salah satu implementasi dari sistem komputerisasi di bidang pertanian. Sistem pakar juga dapat memberikan alasan atas saran atau kesimpulan yang ditemukannya. Sistem pakar digunakan untuk memecahkan masalah yang sulit diselesaikan dengan pemrograman biasa. Dengan Certainty Factor, mengasumsikan nilai kepercayaan seorang ahli. Berdasarkan studi kasus diperoleh hasil perhitungan Certainty Factor dengan nilai tertinggi yaitu 0,870418 yang artinya penyakit kedelai memiliki penyakit menggulung daun dengan nilai kepercayaan 87,0%.

Perkiraan Harga Beras Premium DKI Jakarta Menggunakan Regresi Linier Ricky Eka Putra; Anita Sindar Sinaga
JIEET (Journal of Information Engineering and Educational Technology) Vol. 6 No. 2 (2022)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jieet.v6n2.p80-85

Kebutuhan masyarakat DKI Jakarta terhadap beras cukup tinggi. Hal ini berdasarkan kegemaran masyarakat Indonesia untuk memilih nasi sebagai makanan pokoknya sehingga daya beli masyarakat terhadap beras cukup besar. Beras premium merupakan salah satu jenis beras yang memiliki kualitas terbaik. Banyak kalangan dari masyarakat yang memilih beras tipe ini sebagai bahan pokok di tempatnya masing-masing . Sebagai negara yang memproduksi beras serta berada di lingkungan negara-negara tetangga yang juga memproduksi beras, Indonesia melalui bagian pemerintah terkait juga turut mengontrol harga dari beras tersebut khususnya beras premium. Hal ini dilakukan agar harga beras premium yang ada di masyarakat sesuai dengan kondisi perekonomian di wilayah sekitar. Peluang para pedagang untuk berbuat curang dalam memainkan harga juga dapat direduksi dengan adanya kebijakan dari pemerintah terkait harga tersebut. Oleh karena itu, pemerintah memerlukan suatu dukungan dari sebuah metodologi sains data untuk memperkirakan harga beras premium sebagai masukan untuk menetapkan harga beras premium ke masyarakat. Penelitian ini memilih sebuah metode regresi linier untuk melakukan prediksi terhadap harga beras premium. Metode regresi linier ini diyakini dapat cocok dan sesuai dengan data harga beras yang bersifat time series. Pengembangan aplikasi perkiraan harga beras ini juga mengadopsi metodologi Cross Industry Standard Process – Data Mining (CRISP-DM) yang cukup populer dalam berbagai penelitian terkait. Regresi linier masuk dalam bagian pengembangan model pada salah satu tahapan di CRISP-DM tersebut. Hasil performa dari metode Regresi Linier tersebut dengan Mean Absolute Error (MAE) sebesar 275.55 dan Mean Squared Error (MSE) sebesar 103169.10, masih membuat metode ini dapat dihandalkan dalam memperkirakan harga beras di DKI Jakarta.

Pemodelan Deteksi Black Campaign Sumber Media Berita Online Menggunakan Long Short Term Memory Anita Sindar Sinaga; Priskilla Parimanen
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 22, No 1 (2023): Februari 2023
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v22i1.7554

Developed a black campaign detection model to obtain an accuracy level of classifying online news using the LSTM (Long Short Term Memory) algorithm.Aggregation of neural networks in sheet layers to iteratively learn from the data collected by emulating the workings of the like human brain does the job so computers can be trained in abstraction with the problem is not well defined. The LSTM (Long Short Term Memory) text-processing learning method is used for text classification through the stages of data collection, data preprocessing, word representation, classification, and evaluation. LSTM adds capability and erases information from the cell state. Gates consist of a sigmoid part of layers and multiplication operation. Hyperparameter value is determined from Vocab_size, Embedding_dim Activation Function, Number of epoc, and Learning rate. Evaluation of the showing of the data training performance on data testing shows that the value of LSTM is in identifying online news MAPE 8%. The RMSE evaluation shows that the parameter Number of epochs has a high value of 0.053728.

Sistem Pendukung Keputusan Menentukan Karyawan Terbaik Dengan Metode AHP Anita Sindar R M Sinaga
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 3 No. 2 (2018): September 2018
Publisher : UIN Sunan Kalijaga Yogyakarta

Giving the best employee nicknames to spur other employees competing to provide the best, especially service to customers. Many things affect productivity and quality and comfort in the working environment. Then there needs to be clear and objective criteria in determining the best employees, not just based on qualitative values. In order to award the right target, the method for decision support systems can be applied in determining the best employees. The Analytical Hearachy Process (AHP) method requires criteria in making a decision so that the best employees can be chosen more quickly and objectively. There are 4 criteria: Attitude, Attendance, Performance and Work Period. of the 4 alternatives (4 employees) obtained by SRI RAHAYU: 0.419 or 41.9%, most deserve to be the best employee.

Sistem Pakar Diagnosa Penyakit Pohon Karet dengan Metode Certainty Factor Anita Sindar R M Sinaga
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 4 No. 2 (2019): September 2019
Publisher : UIN Sunan Kalijaga Yogyakarta

The low production of smallholder rubber is caused by various factors, one of the causes is interference from various diseases. Building a system (computer) that is intelligent to analyze problems, observe the work system of an expert or expert. Expertise comes from the development of knowledge of someone who is competent and directly provides instructions to solve a problem. Certainty Factor is a method to prove whether a fact is certain or not certain in the form of metrics that are usually used in expert systems. This method is very suitable for expert systems that diagnose something that is uncertain. To apply the Certainty Factor method to the expert system, data is needed that will be input into the system, processed and display the results of the diagnosis of rubber plant diseases. Input: rubber plant disease type data and disease symptom data. Process: carry out analysis and calculation to get the diagnosis results using the Certainty Factor method. Output: information on the diagnosis of rubber plant diseases and percentage of confidence level in the diagnosis results in accordance with the rules of the Certainty Factor method. Keywords : Rubber Disease, Symptoms Diagnosis, Value Combination, Certainty Factor

Penerapan Algoritma Hill Cipher dan Least Significant Bit (LSB) untuk Pengamanan Pesan pada Citra Digital Desimeri Laoli; Bosker Sinaga; Anita Sindar R M Sinaga
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 4 No. 3 (2020): Januari 2020
Publisher : UIN Sunan Kalijaga Yogyakarta

Nowadays people exchange information in digital media such as text, audio, video and imagery. The development of Information and Communication makes the delivery of information and data more efficient. Current developments in technology which are very significant have an impact on the community in exchanging information and communicating. Confidential hidden data can also be in the form of image, audio, text, or video. The Hill Chiper algorithm uses a matrix of size m x m as a key for encryption and decryption. One way to recover the original text is of course to guess the decryption key, so the process of guessing the decryption key must be difficult. break ciphertext into palintext without knowing which key to use. The LSB part that is converted to the value of the message to be inserted. After affixing a secret message, each pixel is rebuilt into a whole image that resembles the original image media. The Hill Cipher algorithm is used to determine the position of the plaintext encryption into a random ciphertext. 2. Testing text messages using the hill cipher algorithm successfully carried out in accordance with the flow or the steps so as to produce a ciphertext in the form of randomization of the letters of the alphabet.

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

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.

Co-Authors Arjon Samuel Sitio Arjon Samuel Sitio Bosker Sinaga Desimeri Laoli Dewi Simanjuntak Endra Marpaung Jimmi Herdianda Gurusinga Julkari Sinta Parapat Murni Marbun Novi Sri Wanti Ginting Priskilla Parimanen Ravindran Ravindran Ricky Eka Putra Suciana Rahayu Sumitra Dewi

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