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Sinaga, Anita Sindar
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Agriculture, Biological Sciences & Forestry Automotive Engineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Social Sciences Other

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EKSTRAKSI KOMUNIKASI NONVERBAL MENGGUNAKAN GRAY LEVEL CO-OCCURRENCE Sinaga, Anita Sindar
Jurnal Ilmiah Informatika Komputer Vol 25, No 3 (2020)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2020.v25i3.3080

Abstract

Penilaian komunikasi nonverbal dapat diterapkan pada rekrutmen keja secara online. Pemanfaatan aplikasi rekrutmen mulai dipergunakakan beberapa perusahaan swasta untuk efisiensi waktu dan biaya. Untuk mengetahui konsistensi antara ekspresi emosional dengan gerakan wajah diperlukan skill biasanya ditangani seorang psikiologis. Dalam penelitian ini data set berbentuk frame dari video pelamar kerja dilakukan penilaian komunikasi nonverbal yang fokus pada gerakan mata, mulut dan wajah. Formula dan filter GLCM diterapkan untuk ekstraksi ciri bertujuan menemukan pola berdasarkan distribusi statistik dan intensitas piksel.  Ekstraksi komunikasi nonverbal bertujuan menganalisa pola gerakan wajah. Formula ektraksi ciri terdiri dari feature, contras, energi, entropy dan homogenitas. Filter ekstraksi dirotasi pada sudut 00, sudut 450, sudut 900, dan sudut 1350. Sumber data 10 video, diambil 10 frame bagian wajah, mata dan mulut per video untuk diekstrak dan dianalisa. Berdasarkan perhitungan formula dan filter GLCM diperoleh formula Homogenity mempunyai nilai tinggi, rata-rata 4,0 menunjukkan tepi citra yang terdeteksi jelas.
ANALISA BIG DATA PENYEBARAN COVID-19 DENGAN BUSINESS INTELLIGENCE (BI) Sinaga, Anita Sindar
Jurnal Ilmiah Teknologi dan Rekayasa Vol 26, No 3 (2021)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/tr.2021.v26i3.4067

Abstract

Data total sebaran Covid-19 ter-update setiap hari pada media online mencapai puncaknya pada bulan Mei 2021. Lonjakan kasus ini dapat dipelajari guna mengetahui trend penyebaran dan menemukan pola sebaran Covid-19  di wilayah Indonesia. Analisis Business Intelligence (BI) dapat membantu pengambilan keputusan. BI berfungsi mengubah data transaksional menjadi informasi bermanfaat bagi perusahaan. Dalam Big Data digunakan teknologi dan inisiatif yang melibatkan data beragam, cepat berubah, atau berukuran super besar. Hasil cleansing data dari teknik BI menjadi sumber membangun model Big Data Analytics. Big Data memiliki volume, velocity, variety diolah melalui tahapan acquired, accessed, analytic, dan application. Olahan data divisualisasikan dalam bentuk grafik atau dashboard agar memudahkan menginformasikan sebaran Corona. Big Data Analytics menganalisa informasi, mengidentifikasi untuk keputusan bisnis saat ini dan masa datang. Penelitian bertujuan menemukan pola sebaran Covid-19, berdasarkan data peta sebaran dan peraturan protokol. Dengan menerapkan clustering Big Data ditemukan 3 pola cluster penyebaran virus Corona pada 32 provinsi selama Mei 2021 yaitu Cluster 1 menunjukkan Kasus Rendah, Cluster 2 menunjukkan Kasus Sedang, Cluster 3 menunjukkan Kasus Tinggi.
MULTIVARIATE ANALYSIS OF COMMODITY AVAILABILITY OF STAPLE FOODS USING COMPLETE LINKAGE HIERARCHICAL CLUSTERING METHOD Sitio, Arjon; Sinaga, Anita Sindar; Haikal, Akhyar; Dewi, Sumitra
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 7 No 2 (2022): JITK Issue February 2022
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1008.315 KB) | DOI: 10.33480/jitk.v7i2.2830

Abstract

The government directly supervises 11 basic food commodities. The system of interplay between the price of goods and the availability of staple food directly has an impact on the high price of food at certain times. It is necessary to classify the food that is most needed by the community on big holidays in Indonesia so that it can be a reference for the government in preparing market needs in the coming year. In this study, the grouping of staple food availability was based on hierarchical cluster analysis with complete linkage method. The availability of food commodities in the discussion of this research is sourced from production materials and daily prices for meat, eggs, cooking oil and rice commodities. Cluster interpretation results in cluster 1 indicating Fulfilled Availability of 88-89%, Cluster 2 showing Sufficient Commodity Availability of 90-93% and Cluster 3 showing Availability of Rare Commodities of 87%. The three clusters formed are depicted in the form of a dendogram as a visualization of the relationship between food availability groupings.
Teknik Ensemble Dalam Machine Learning Untuk Menentukan Tingkat Akurasi Perkembangan Motorik Bayi 0-12 Bulan : Teknik Ensemble Dalam Machine Learning Untuk Menentukan Tingkat Akurasi Perkembangan Motorik Bayi 0-12 Bulan Sinaga, Anita Sindar; Sethu Ramen; Sri Mulyani
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 23 No 2 (2024): Agustus 2024
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v23i2.10059

Abstract

Setiap tahap perkembangan seorang bayi umumnya ditunjukkan oleh pergerakan fisik atau badan. Ada kesulitan mengenali keterlambatan pergerakan motoric bayi pada usia 0 – 12 bulan. Jika terdapat gangguan pada gerak bayi, maka perlu dilakukan pemeriksaan kesehatan fisik bayi agar dapat segera ditangani sesuai tahap perkembangan balita. Tingkat keakuratan kondisi gerak motorik terlambat pada bayi dapat diketahui dengan Teknik Ensamble. Pembelajaran ensemble digunakan untuk memperbaiki kinerja dan hasilnya menunjukkan tingkat yang benar dari Pembelajaran Mesin menangani analisis data dengan menggabungkan hasil prediksi dari tidak banyak kesepakatan berbeda dengan algoritma analisis data. Penelitian ini bertujuan untuk menghasilkan model pembelajaran ansambel dalam mengidentifikasi tingkat kebenaran gerak motorik bayi 0-12 bulan. Pemodelan pembelajaran Ensemble menghasilkan model baru dengan menggunakan Optimizable Ensemble dengan nilai Ketepatan menilai kemiripan model Optimizable Ensemble 93% dengan nilai MRSE 9.8 R-Squared 0.73 MSE 82.26.
Pemanfaatan Teknologi Internet of Things dalam Meningkatkan Hasil Pertanian Tanaman Melinjo Sinaga, Anita Sindar; Nuraisana, Nuraisana; Panggabean, Erwin; Mulyani, Sri; Damayanti, Alfina
Jurnal Pengabdian Inovasi Masyarakat Indonesia Vol. 4 No. 1 (2025): Edisi Februari
Publisher : Program Studi Pendidikan Kimia FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpimi.v4i1.6234

Abstract

Increasing productivity in the agricultural sector increasingly requires modernization of plant planting technology. This can be done by encouraging human resources such as helping farmers to be interested in knowledge about better and more appropriate agricultural techniques. Good agricultural technology must have a positive impact on the surrounding environment, not have a negative impact on human health and the surrounding environment, and be accessible and affordable to farmers. IoT tools are able to monitor soil through sensors that can measure soil conditions in real time. Sensors can observe various aspects of soil conditions, such as pH, humidity, temperature, and nutrients. IoT technology in the agricultural sector is utilized to achieve progress in melinjo plant production. Sensors as devices used can provide information on conditions such as soil humidity, air temperature, and humidity levels. Data obtained from sensors are sent via the internet to an intelligent system for analysis. The results of this analysis can provide information for farmers to make the right decisions to provide appropriate nutrition. Community service activities contribute to increasing melinjo plant agricultural yields in Dalu Sepuluh Village through the use of IoT technology for automatic plant watering.
Analisis Pengurangan Derau Pada Restorasi Citra Ulos Sinaga, Anita Sindar; Alfina Damayanti; Sofi Febriyanti
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 24 No 1 (2025): Februari 2025
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v24i1.10704

Abstract

Restorasi citra mengacu pada pengapusan atau pengurangan degradasi citra yang dihasilkan dari proses pengambilan data atau proses akuisisi citra. Degradasi meliputi derau atau efek optik misalnya blur karena kamera yang tidak fokus. Kain Ulos merupakan kain tenun khas suku Batak dan secara turun temurun terus dikembangkan oleh suku ini. Pengolahan kain ulos menjadi gambar ulos yang memiliki kualitas gambar (digital) didukung oleh kamera. Perubahan warna digital dengan warna ulos asli. Kain ulos dibuat dengan menggunakan alat tenun bukan mesin. Warna yang dominan pada kain ulos adalah merah, hitam dan putih yang dihiasi ragam tenunan dari benang emas atau perak. Noise pada citra dibedakan menjadi beberapa macam Gaussian, Speckle, dan Salt & Pepper. Derau Gaussian mengikuti distribusi Gaussian (normal) untuk mengatasi derau Gaussian, berbagai filter seperti filter Gaussian.
Pemodelan Classification and Regression Tree (CART) Pada Klasifikasi Gaya Hidup Sehat Menggunakan Pendekatan User-Based Classification Sinaga, Anita Sindar; Bella Saputri; Nadia Aulia
Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Vol. 4 No. 4 (2025): EDISI JULI 2025
Publisher : STMIK Triguna Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jursi.v4i4.11677

Abstract

Determining a healthy lifestyle is an important issue in public health, especially in efforts to prevent chronic diseases. The classification process is carried out by constructing a decision tree that divides data into lifestyle classes (healthy/unhealthy) recursively, based on the features that provide the best separation. The results show that the CART model is able to identify significant lifestyle patterns with fairly high classification accuracy, as well as provide a clear understanding of user factors that contribute to healthy lifestyle status. This approach supports decision making in data-based health promotion programs. From a total of 70 data, the average target value is 0.146. The tree will divide the data based on whether the Feature value is ≤ 3.25. If true to the left, if false to the right. This node shows 49 samples from the root following the condition Feature <= 3.25 and is now divided again based on Feature <= 2.538. This process continues recursively until it reaches the leaf node. There is only 1 sample, with target value = 0.3, so there is no variance (squared_error = 0). If new data enters this branch, the model will predict 0.3 as the regression value.
Diagnosa Penyakit Mata Berdasarkan Citra Ocular Disease Intelligent Recognition (ODIR) Dengan Gabor Filter Klasifikasi Levenberg-Marquardt Sinaga, Anita Sindar; Ginting, Feby; Ramen, Sethu -
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 22 No 2 (2023): Agustus 2023
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v22i2.8787

Abstract

Light captured by both eyeballs is passed on to the pupil, focused through the sensitive part of the eyeball. The retinal organ of the eye converts the light capture into nerve impulses, and delivers them to the brain through the nerve fibers contained in the impulses. There are several complications of disease in the sense of sight that can be diagnosed from the arrangement of the retina of the eye. Image segmentation stages are needed so that the fiber contained in the retinal optics can be changed. The initial stage is with the initialization of the arrangement for the contour movement stages. Using the Levenberg-Marquardt algorithm is able to improve the following results obtained as a basis for previously collected data. In this study eye disease only diagnosed eye disease in complaints of the retina of the eye. The purpose of this research is to diagnose early sight diseases that appear based on the symptoms shown by the composition of the retinal parts of the human eyeball and classify the level of danger of the results of eye disease diagnoses.
Prediksi Keberhasilan Penanganan Stunting Menggunakan Seleksi Fitur PSO Dengan SaaS Cloud Computing Sinaga, Anita Sindar; Ramen, Sethu; Mulyani, Sri
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 23 No 1 (2024): Februari 2024
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v23i1.9561

Abstract

Permasalahan stunting merupakan tugas pokok setiap pemerintahan dari perkotaan sampai desa-desa. Deep Learning dapat mengenal pola rumit yan ada pada gambar, dokumen, video, dan data lain untuk menghasilkan prediksi yang akurat. Pengolahan data tidak terstruktur seperti kata, kalimat dapat diekstrak menerapkan Particle Swarm Optimization (PSO). Pengolahan data tidak terstruktur pada kata dan kalimat bersumber dari media online diekstrak menerapkan Particle Swarm Optimization (PSO) mencakup swarm, partikel, Pbest, Gbest, dan Velocity. Melalui empat tahapan algoritma PSO dimulai dari Inisialisasi, Evaluation fungsi fitness, update dan Termination. Prediksi capaian penanganan program stunting berdasarkan dampak, pencegahan, dan penyebab stunting yang diekstrak dari berbagai media online menggunakan Neural Network Particle Swarm Optimization (PSO) yang dibangun pada layanan perangkat lunak SaaS Cloud menghasilkan persentase baik akurasi Seleksi Fitur PSO sebesar 85.36%. Aplikasi SaaS dapat menginformasikan tingkat keberhasilan penanganan program stunting dari pencarian kalimat tidak terstruktur yang terhubung dengan internet
Pemanfaatan Teknologi Internet of Things dalam Meningkatkan Hasil Pertanian Tanaman Melinjo Sinaga, Anita Sindar; Nuraisana, Nuraisana; Panggabean, Erwin; Mulyani, Sri; Damayanti, Alfina
Jurnal Pengabdian Inovasi Masyarakat Indonesia Vol. 4 No. 1 (2025): Edisi Februari
Publisher : Program Studi Pendidikan Kimia FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpimi.v4i1.6234

Abstract

Increasing productivity in the agricultural sector increasingly requires modernization of plant planting technology. This can be done by encouraging human resources such as helping farmers to be interested in knowledge about better and more appropriate agricultural techniques. Good agricultural technology must have a positive impact on the surrounding environment, not have a negative impact on human health and the surrounding environment, and be accessible and affordable to farmers. IoT tools are able to monitor soil through sensors that can measure soil conditions in real time. Sensors can observe various aspects of soil conditions, such as pH, humidity, temperature, and nutrients. IoT technology in the agricultural sector is utilized to achieve progress in melinjo plant production. Sensors as devices used can provide information on conditions such as soil humidity, air temperature, and humidity levels. Data obtained from sensors are sent via the internet to an intelligent system for analysis. The results of this analysis can provide information for farmers to make the right decisions to provide appropriate nutrition. Community service activities contribute to increasing melinjo plant agricultural yields in Dalu Sepuluh Village through the use of IoT technology for automatic plant watering.
Co-Authors Alfina Damayanti Bella Saputri Damayanti, Alfina Dewi, Sumitra Erwin Panggabean Ginting, Feby Haikal, Akhyar Nadia Aulia Nuraisana, Nuraisana Ramen, Sethu Ramen, Sethu - Sethu Ramen Sitio, Arjon Sofi Febriyanti Sri Mulyani Sri Mulyani