Garuda - Garba Rujukan Digital

PELATIHAN PEMANFAATAN TEKNOLOGI SEO UNTUK PENINGKATAN TRAFFIC PROMOSI DENGAN SOSIAL MEDIA Yuniar, Eka .; Rahmawati, Linda Suvi; Utsalina, Dwi Safiroh
PEDULI: Jurnal Ilmiah Pengabdian Pada Masyarakat Vol 3 No 1 (2019)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Search Engine Optimization adalah serangkaian proses yang dilakukan secara sistematis yang bertujuan untuk meningkatkan volume dan kualitas trafik kunjungan melalui mesin pencari menuju situs web tertentu dengan memanfaatkan mekanisme kerja atau algoritme mesin pencari tersebut. Tujuan dari SEO adalah menempatkan sebuah situs web pada posisi teratas, atau setidaknya halaman pertama hasil pencarian berdasarkan kkata kunci tertentu yang ditargetkan. Secara logis, situs web yang menempati posisi teratass pada hasil pencarian memiliki peluang lebih besar untuk mendapatkan pengunjung. Metode yang digunakan pelatihan, pendampingan, dan praktik yang dilakukan kepada UMKM Kota Malang. Hasil yang dicapai terjadi peningkatan pengetahuan yang dimiliki dengan sosial media yang telah dibuat oleh masing-masing peserta pelatihan

SISTEM INFORMASI LAYANAN KESEHATAN DENGAN MENGGUNAKAN CODEIGNITER PADA PUSKESMAS BULULAWANG Eka Yuniar; Mochamad Hasanudin Muslim
Antivirus : Jurnal Ilmiah Teknik Informatika Vol 12 No 1 (2018): Mei 2018
Publisher : Universitas Islam Balitar

Penelitian ini bertujuan untuk membuat Sistem Informasi Layanan Kesehatan pada Puskesmas Bululawang dengan menggunakan Codeigneter. Hal ini dikarenakan pada Puskesmas Bululawang belum memiliki sistem yang terintegrasi dalam hal pelayanan administrasi kepada pasien dan pengolahan laporan kepada Dinas yang kurang efektif dan efisien. Pembuatan sistem informasi layanan kesehatan ini dengan menggunakan codeigneter dengan berorientasi dengan objek, sedangkan metode penelitian dengan menggunakan metode prototype. Adapun data yang digunakan dalam penelitian ini adalah data pasien dan data rekam medis pada Puskesmas Bululawang. Adapun pengujian sistem menggunakan metode blacbox dengan menguji fungsionalitas sistem, sedangkan variabel pengujian lain dengan menggunakan pengukuran waktu proses untuk menilai pengukuran metode kerja sistem. Penelitian ini menghasilkan proses pelayanan kesehatan pada Puskesmas lebih cepat sampai dengan 87,5% untuk proses pendaftaran pasien, 99,7 % untuk proses pencarian data rekam medis, dan 97,02 % untuk proses pembuatan Laporan Medis.

IMPLEMENTASI CHATBOT "ALITTA" ASISTEN VIRTUAL DARI BALITTAS SEBAGAI PUSAT INFORMASI DI BALITTAS Eka Yuniar; Heri Purnomo
Antivirus : Jurnal Ilmiah Teknik Informatika Vol 13 No 1 (2019): Mei 2019
Publisher : Universitas Islam Balitar

Conversational Bot atau Chatbot adalah sebuah konten yang divisualisasikan dalam format obrolan dan pengguna dapat berinteraksi dengan sistem menggunakan teks. Teknologi cerdas ini merupakan salah satu perkembangan dari Revolusi Industri 4.0 yang harus diimplementasikan guna meningkatkan pelayanan pada information service di segala industri terutama di BALITTAS (Balai Penelitian Tanaman Pemanis dan Serat) yang dinamakan ALITTA. ALITTA diimplementasi dengan tujuan untuk membantu pelayanan informasi dengan mesin penjawab otomatis, yang dapat melayani satu per satu pertanyaan yang dikeluhkan oleh pelanggan maupun pencari informasi BALITTAS secara cepat dan tidak terkendala waktu seperti jam kerja kantor, maupun terkendala dengan jumlah tenaga kerja. Chatbot ini dibangun dengan menerapkan sistem pakar dengan menggunakan metode forward chaining. Metode forward chaining digunakan untuk mencari kesimpulan dari fakta-fakta yang terkumpul. Metode forward chaining yang digunakan dalam sistem ALITTA menyelesaikan proses pencarian jawaban berdasarkan kata kunci dari pertanyaan user, dengaan cara mencari kata kunci yang digunakan sebagai jawaban atas respon pertanyaan user yang telah didaftarkan sebagai intents. Hasil penelitian ini adalah terciptanya chatbot “ALITTA” sebagai asisten virtual dari BALITTAS yang dapat membantu masyarakat dalam mencari informasi secara flexibel dan tidak terikat waktu yang berkaitan dengan tanaman,hama, dan kegiatan-kegiatan lainnya yang terdapat di BALITTAS.

Implementasi Scrapping Data Untuk Sentiment Analysis Pengguna Dompet Digital dengan Menggunakan Algoritma Machine Learning Eka Yuniar; Dwi Safiroh Utsalinah; Dian Wahyuningsih
Jurnal Janitra Informatika dan Sistem Informasi Vol. 2 No. 1 (2022): April - Jurnal Janitra Informatika dan Sistem Informasi
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/janitra.v2i1.145

Analysis of social media is an effective tool for understanding people's attitudes, preferences and opinions. For a company, social media analysis can help companies to make decisions about needs, attitudes, opinions or trends about potential customers or potential customers. Hootsuite's Wearesocial research results show that out of 150 million Indonesians, 88% are actively using social media. As a result, a lot of information that was once difficult to obtain is now very easy to obtain. With so much data, data collection can be made easier by using an automated data collection system. The use of Machine Learning Algorithm as a method is used to find out how far the level of search from social media data collected is to get accurate results related to changes in behavior, lifestyle, and community activities in dealing with this pandemic. Scraping data is done using Twitter social media data with various hashtags that support opinion mining contained in the community. The results obtained are the analysis of gopay users having a positive sentiment level of 79,6%, negative sentiment of 20,4% from total of 250 data. Meanwhile, Linkaja users have a positive sentiment level of 62,1%, 37,9% negative comments from 250 data comments taken. The test results also carried out a process of calculating the level of accuracy with recall and precision, namely 87% for Gopay and 89% for LinkAja.

Masked Face Detection Automation System Using Mask Threshold and Viola Jones Method Aminurachma Aisyah Nilatika; Khoerul Anwar; Eka Yuniar
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.470

Reducing or even breaking the chain of Covid-19 virus infections during a pandemic is important. The techniques that are encouraged are mandatory hand washing, social distancing, and mandatory wearing of masks. Wearing masks is urgent, therefore requiring people to wear masks is the right policy. This study aims to detect people who use masks or do not use masks by applying the Viola Jones method. In this study, modification of the tresholder algorithm was carried out by applying a mask thresholder for optimization of facial segmentation. Meanwhile viola jones was built by combining several concepts of Haar Feature, Integral Image, AdaBoost, classivier Cascade into a main method for detecting objects. The performance of the proposed method for face detection has an accuracy of 95%, a precision of 94.73%, and a recall of 100%. 5. The masked face detection test has an accuracy of 94%, precision 100%, and recall 90.90%

Peramalan Harga Crude Oil dengan Model Double Exponensial Smoothing-Holts Mohamad As’ad; Eka Yuniar; Sujito; Eni Farida; Sigit Setyowibowo
G-Tech: Jurnal Teknologi Terapan Vol 7 No 1 (2023): G-Tech, Vol. 7 No. 1 Januari 2023
Publisher : Universitas Islam Raden Rahmat, Malang

Kenaikan harga bahan bakar minyak (BBM) oleh pemerintah sangat ramai sekali di respon masyarakat. Crude oil merupakan bahan baku BBM. Harga crude oil tergantung pasar dunia. Penelitian ini bertujuan untuk meramalkan harga crude oil bulanan secara cepat dan akurat dengan menggunakan model yang mudah dan dengan software yang mudah didapat. Penelitian ini memakai model double exponensial smoothing dari Holts (DES-H). Data sekunder diperoleh dari “Spot Crude Oil Price: West Texas Intermediate (WTISPLC)”. Hasil penelitian ini dengan model DES-H mendapatkan parameter alpha sebesar 0,9999 dan parameter beta sebesar 1e-04. Nilai akurasi peramalan yaitu RMSE sebesar 5.813075 dan MAPE sebesar 7.451311 % (sangat bagus). Penambahan data terbaru sangat penting untuk update model dan digunakan untuk peramalan jangka pendek.

Water Pressure Data Recording System On Pipes Based On The Internet Of Things Networking Khoerul - Anwar; Mahmud - Yunus; Eka - Yuniar
International Journal of Applied Business and International Management Vol 8, No 2 (2023): August 2023
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/ijabim.v8i2.2181

Measurement system technology is increasing along with the development of digital technology today. Because of this, currently various kinds of measurement tools can be made in digital versions. Likewise, the technology for measuring water pressure in pipes is also made digitally, although there are still many conventional measurements, for example the flow meter that we usually see in housing in general. The purpose of the system being built is to monitor the water pressure sensor nodes installed in various water sources to ensure sufficient compressive power in an effort to push water up to the customers. Each water pressure sensor node can be monitored from the system dashboard in real time. In this paper, the author offers an IoT-based measurement system for microcontroller technology on a smart pressure meter using a water pressure sensor controlled by the NodeMCU and the pressure bar is calculated then the data is sent to the cloud with the GPRS module, then the results will be displayed on the monitoring system dashboard. The implementation of DWM IoT technology is able to monitor pressure in several PDAM nodes by recording data and display pressure data in graphical form on the DWM IoT dashboard

Masked Face Detection Automation System using Mask Threshold and Viola Jones Method Aminurachma Aisyah Nilatika; Khoerul Anwar; Eka Yuniar
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.185

Reducing or breaking the chain of Covid-19 virus infections during a pandemic is essential. The techniques encouraged are mandatory hand washing, social distancing, and wearing masks. Wearing masks is urgent. Therefore, requiring people to wear masks is the right policy. This study aims to detect people using or not using masks by applying the Viola-Jones method. This study modified the threshold algorithm by applying a masking threshold to optimize facial segmentation. Meanwhile, viola jones was built by combining several concepts of Haar Feature, Integral Image, AdaBoost, and classifier Cascade into the main method for detecting objects. The performance of the proposed method for face detection has an accuracy of 95%, a precision of 94.73%, and a recall of 100%. 5. The masked face detection test has an accuracy of 94%, a precision of 100%, and a recall of 90.90%

Water Pressure Data Recording System On Pipes Based On The Internet Of Things Networking Khoerul - Anwar; Mahmud - Yunus; Eka - Yuniar
International Journal of Applied Business and International Management Vol 8, No 2 (2023): August 2023
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/ijabim.v8i2.2181

Measurement system technology is increasing along with the development of digital technology today. Because of this, currently various kinds of measurement tools can be made in digital versions. Likewise, the technology for measuring water pressure in pipes is also made digitally, although there are still many conventional measurements, for example the flow meter that we usually see in housing in general. The purpose of the system being built is to monitor the water pressure sensor nodes installed in various water sources to ensure sufficient compressive power in an effort to push water up to the customers. Each water pressure sensor node can be monitored from the system dashboard in real time. In this paper, the author offers an IoT-based measurement system for microcontroller technology on a smart pressure meter using a water pressure sensor controlled by the NodeMCU and the pressure bar is calculated then the data is sent to the cloud with the GPRS module, then the results will be displayed on the monitoring system dashboard. The implementation of DWM IoT technology is able to monitor pressure in several PDAM nodes by recording data and display pressure data in graphical form on the DWM IoT dashboard

Model Sistem Cerdas untuk Rekomendasi Market Matching Negara Tujuan Ekspor bagi UMKM Eka Yuniar; Weda Adistianaya Dewa; Fakhruddin Arozi; Ahmad Mihdan Advani
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 13 No 02 (2023): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v13i02.943

Export is one way to improve the performance and growth of the MSME business. However, entering the export market is not as easy as one might think. MSMEs have to consider many factors such as regulatory requirements of the destination country, consumer preferences, and competition with local producers in the destination country. In addition, some of the obstacles to the export of MSME products are slow product turnover in importing countries because product stocks do not sell out immediately in these countries and sometimes reach the expiration date. The number of Indonesian MSMEs has reached 65.5 million, which is the largest in ASEAN countries. In addition, the contribution of MSMEs is recorded at around 61% of the national PDP and absorbs 97% of the total workforce in 2021. To assist MSMEs in choosing export destination countries, an intelligent system is needed that can recommend the right destination countries based on the characteristics of MSME products. As for how to determine the Export Destination country by using one of them based on the Trademap site. The urgency of this research aims to build an intelligent system model based on machine learning using the KNN method to recommend the right export destination countries for MSMEs. This machine learning-based intelligent system model is expected to be one of the solutions for MSMEs to effectively expand their markets abroad. This research is also expected to contribute to the development of an intelligent system that can assist MSMEs in choosing the right export destination countries and increasing export effectiveness. The results showed an accuracy rate of 99%, with a precision level of 100%, 100% recall, 100% f1-score.

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