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All Journal Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Riset Informatika Technologia: Jurnal Ilmiah Jurnal AbdiMas Nusa Mandiri Jurnal Abdimas Perbanas
Widi Astuti
Universitas Nusa Mandiri
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Environmental Science Mathematics Physics Social Sciences Other

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NURANI MEMBERI NEGERI: MENYUSUN MATERI PRESENTASI UNTUK BERBICARA DI DEPAN UMUM Widi Astuti; Lia Mazia; Johan Hendri Prasetyo; Fajar Sarasati; Aisyah Aisyah; Muhamad Rizki Bahtiar; Kadafi Akbar; Adelia Rizki Nur Azizah; Dani Fikri Ramadhan
Jurnal AbdiMas Nusa Mandiri Vol 4 No 1 (2022): Periode April 2022
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/abdimas.v4i01.3001

Abstract

Pandemi Covid-19 dewasa ini masih berlanjut sampai dengan saat ini. Hal tersebut menyebabkan dampak yang luar biasa bagi semua jenis industri, termasuk dalam industri pendidikan. Dengan adanya pandemi tersebut, semua elemen dalam dunia pendidikan baik guru, peserta didik, dosen, mahasiswa, maupun institusi pendidikan itu sendiri yang harus dapat menyesuaikan diri dengan kondisi yang ada, termasuk perubahan pembelajaran tatap muka menjadi pembelajaran secara online atau daring. Dengan adanya pembelajaran secara daring tersebut, menyebabkan seluruh proses pembelajaran harus disiapkan dengan matang, termasuk materi presentasi yang dilakukan oleh peserta didik agar dapat diserap oleh para audiens dengan baik. Melalui kegiatan pengabdian ini diharapkan para peserta dapat menyusun materi presentasi yang baik dan menarik, sehingga pesan yang disampaikan dapat dipahami dan tidak menyebabkan kebosanan bagi audiens. Metode kegiatan pengabdian ini dilakukan secara hybrid berupa penyampaian materi pelatihan secara keseluruhan yang kemudian dilanjutkan dengan praktikum pemilihan slide presentasi yang baik melalui Slidesgo.com dan penyusunan materi presentasi dengan PowerPoint, serta diakhiri dengan pengisian angket. Hasil dari pengabdian ini pelajar SMP-SMA binaan LAZGIS Bekasi dapat meningatkan kemampuan dalam menyusun poin-poin dan materi presentasi serta layout presentasi yang baik dan dapat dimengerti audiens.
COMPARISON OF ACCURACY MEASUREMENTS IN MOTION SENSORS AND HEART RATE MEASUREMENTS USING ANALYTICAL HIERARCHY PROCESS METHODS Tomi Lifti Novier; Nurmalasari Nurmalasari; Widi Astuti; Siti Masturoh; M. Rangga Ramadhan Saelan
Techno Nusa Mandiri: Journal of Computing and Information Technology Vol 18 No 2 (2021): TECHNO Period of September 2021
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v18i2.2547

Abstract

The use of motion sensors in measuring heart rate using smartwatch applications is currently a trend. Everyone is very helpful for measuring their own heart rate. This research is about the comparison of accuracy in motion sensors and measuring heart rate using the Analytical Hierarchy Process (AHP) method. Every technology and application in motion sensor measurement in heart rate measurement has almost the same features and uses as Xiaomi, Samsung, and Apple Inc. From the calculations carried out by the researcher, it shows that the field/stadium that is the most chosen by the community (respondents) is by Random Sampling, with the acquisition of a value of 0.490 aka 49.00%. The second is Treadmill with a value of 0.294 aka 29.40%. the overall value is 0.216 aka 21.60% The alternative that is most chosen by the community (respondents) is the field/stadium. The Analytical Hierarchy Process method can make it easier for prospective technology users to be able to measure the accuracy of motion sensors and detect heart rates, the AHP method makes product decisions based on criteria and alternatives contained in the hierarchy, the results of the study are Apple Inc. as the respondent's choice for technology that is trusted to measure better accuracy on the motion sensor and measure heart rate.
KLASIFIKASI DATA MINING DENGAN ALGORITMA MACHINE LARNING UNTUK PREDIKSI PENYAKIT LIVER F. Lia Dwi Cahyanti; Fajar Sarasati; Widi Astuti; Elly Firasari
Technologia : Jurnal Ilmiah Vol 14, No 2 (2023): Technologia (April)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/tji.v14i2.10093

Abstract

Liver merupakan organ tubuh manusia yang memiliki peranan sangat penting seperti mencerna, menyerap, membantu proses pencernaan makanan serta menghancurkan racun di dalam darah. Penyakit hati atau liver yang sudah akut sangat mempengaruhi fungsi-fungsi hati, penyakit hati dapat diketahui dari munculnya gejala klinis maupun fisik yang timbul pada pasien. Penelitian ini membahas tentang klasifikasi penyakit liver pada dataset ILPD yang diambil dari UCI Machine learning Repository menggunakan algoritma machine learning. Dataset terdiri dari 583 record data, 10 kriteria, dan 1 variable kelas berjenis multivariate. Penelitian ini menggunakan beberapa tahapan preprocessing yang dilakukan, diantaranya : Preprocessing Data Dan Eksplorasi Data, Penanganan missing value, feature selection, menerapkan feature correlation dan feature scaling, Analisis menggunakan Algoritma Machine learning. Berdasarkan hasil pengujian yang dilakukan dalam memperoleh nilai akurasi perhitungan klasifikasi menggunakan Algoritma Random Forest memiliki performa  keakuratan yang diukur dengan akurasi sebesar 78,63% sehingga disimpulkan akurasi tersebut lebih unggul dari algoritma lainnya dalam klasifikasi penyakit liver.
Optimalisasi Digital Marketing Sebagai Media Informasi dan Pemasaran Produk Bagi Anggota Komunitas UMKM Naik Kelas Widi Astuti; Lia Mazia; Johan Hendri Prasetyo; Fajar Sarasati; Jeri Dabi; Safira Maharani; Nabil Hanif Leksmono; Danang Rusdawindra Samiaji; Dennis Fathurahman
Jurnal Abdimas Perbanas Vol. 4 No. 1 (2023): Jurnal Abdimas Perbanas
Publisher : Perbanas Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56174/jap.v4i1.517

Abstract

MSME Community Class Up is an organizational forum which established with sense of togetherness as a result of the Covid-19 Pandemic, where MSME players really affected by significant decline in their business, within the Class Up of UMKM Community, those MSMEs are given training and workshops which can help them in turnover the decline in sales and choosing the right market strategies after the Covid-19 pandemic. By Optimizing the Digital Marketing as one of Information and Product Marketing Media for MSME Members of the MSME Community class up which seems very beneficial for MSMEs because by the use of digital marketing, MSMEs can make decisions about the sustainability of their business by applying digital-based marketing strategies for the businesses that they run. Good response from partners towards training are very useful in increasing partners' skills in introducing digital marketing and the participants were very enthusiastic and active in participating in the training by asking questions related to business strategy, as well as the implementation of digital marketing in business. The results of this training indicated that the participants had increase their ability in the use of various types of digital marketing media and their sales was increased by 80%. Through the capabilities which possessed by the partners in managing the optimization of digital marketing, so that they can assess their owned marketing performance periodically.
Classification for Papaya Fruit Maturity Level with Convolutional Neural Network Nurmalasari Nurmalasari; Yusuf Arif Setiawan; Widi Astuti; M Rangga Ramadhan Saelan; Siti Masturoh; Tuti Haryanti
Jurnal Riset Informatika Vol 5 No 3 (2023): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.541

Abstract

Papaya California (Carica papaya L) is one of the agricultural commodities in the tropics and has a very big opportunity to develop in Indonesia as an agribusiness venture with quite promising prospects. So the quality of papaya fruit is determined by the level of maturity of the fruit, the hardness of the fruit, and its appearance. Papaya fruit undergoes a marked change in color during the ripening process, which indicates chemical changes in the fruit. The change in papaya color from green to yellow is due to the loss of chlorophyll. During storage, the papaya fruit is initially green, then turns slightly yellow. The longer the storage color, the changes to mature the yellow. The process of classifying papaya fruit's ripeness level is usually done manually by business actors, that is, by simply looking at the color of the papaya with the normal eye. Based on the problems that exist in classifying the ripeness level of papaya fruit, in this research, we create a system that can be used to classify papaya fruit skin color using a digital image processing approach. The method used to classify the maturity level of papaya fruit is the Convolutional Neural Network (CNN) Architecture to classify the texture and color of the fruit. This study uses eight transfer learning architectures with 216 simulations with parameter constraints such as optimizer, learning rate, batch size, number of layers, epoch, and dense and can classify the ripeness level of the papaya fruit with a fairly high accuracy of 97%. Farmers use the results of the research in classifying papaya fruit to be harvested by differentiating the maturity level of the fruit more accurately and maintaining the quality of the papaya fruit.
Classification for Papaya Fruit Maturity Level With Convolutional Neural Network Nurmalasari Nurmalasari; Yusuf Arif Setiawan; Widi Astuti; M. Rangga Ramadhan Saelan; Siti Masturoh; Tuti Haryanti
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1169.294 KB) | DOI: 10.34288/jri.v5i3.225

Abstract

Papaya California (Carica papaya L) is one of the agricultural commodities in the tropics and has a very big opportunity to develop in Indonesia as an agribusiness venture with quite promising prospects. So the quality of papaya fruit is determined by the level of maturity of the fruit, the hardness of the fruit, and its appearance. Papaya fruit undergoes a marked change in color during the ripening process, which indicates chemical changes in the fruit. The change in papaya color from green to yellow is due to the loss of chlorophyll. The papaya fruit is initially green during storage, then turns slightly yellow. The longer the storage color, the changes to mature the yellow. The process of classifying papaya fruit's ripeness level is usually done manually by business actors, that is, by simply looking at the color of the papaya with the normal eye. Based on the problems that exist in classifying the ripeness level of papaya fruit, in this research, we create a system that can be used to classify papaya fruit skin color using a digital image processing approach. The method used to classify the maturity level of papaya fruit is the Convolutional Neural Network (CNN) Architecture to classify the texture and color of the fruit. This study uses eight transfer learning architectures with 216 simulations with parameter constraints such as optimizer, learning rate, batch size, number of layers, epoch, and dense and can classify the ripeness level of the papaya fruit with a fairly high accuracy of 97%. Farmers use the results of the research in classifying papaya fruit to be harvested by differentiating the maturity level of the fruit more accurately and maintaining the quality of the papaya fruit.
Co-Authors Adelia Rizki Nur Azizah Aisyah Aisyah Danang Rusdawindra Samiaji Dani Fikri Ramadhan Dennis Fathurahman F. Lia Dwi Cahyanti Fajar Sarasati Firasari, Elly Jeri Dabi Johan Hendri Prasetyo Kadafi Akbar Lia Mazia, Lia M Rangga Ramadhan Saelan M. Rangga Ramadhan Saelan Muhamad Rizki Bahtiar Nabil Hanif Leksmono Nurmalasari Nurmalasari Safira Maharani Siti Masturoh Tomi Lifti Novier Tuti Haryanti Yusuf Arif Setiawan