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All Journal Jurnal DISPROTEK Jurnal Teknologi dan Sistem Tertanam Jumat Pendidikan: Jurnal Pengabdian Masyarakat J-Innovation
Muhammad Mahrus Ali
Universitas Merdeka Pasuruan
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences Other

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KLASIFIKASI MUTU BERAS MENGGUNAKAN K-NN BERBASIS BACKWARD ELIMINATION Muhammad Faishol Amrulloh; Muhammad Mahrus Ali; Mochamad Sirodjudin
Jurnal Disprotek Vol 14, No 2 (2023)
Publisher : Universitas Islam Nahdlatul Ulama Jepara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34001/jdpt.v14i2.3676

Abstract

CLASSIFICATION RICE QUALITY USING K-NN BACKWARD-BASED ELIMINATIONRice is one of the most important agricultural products. And it is a strategic commodity because almost all Indonesian people need it. Because of the importance of the function of rice as a staple food ingredient, the quality of the rice to be consumed must be ensured to be of high quality. Determination of the quality or quality of rice until now has been done by many previous researchers. However, of the several methods that have been selected, the majority use image processing. Rice quality data processing using data mining is still rarely done. In this study, the dataset that will be used comes from the Probolinggo Regency Agriculture Service database which has 1 special attribute and 9 regular attributes. The attributes are: variety, length, shape, color, taste, rice planting technique, season, pests, PH and quality. The method that will be used in this study is the backward elimination-based K-NN method.From the results of the analysis and computation of several methods, it can be concluded that the backward elimination-based K-NN method used to increase the accuracy of rice classification resulted in several conclusions. Namely the attributes that affect the determination of rice quality are variety, shape, color, technique, season, pests and PH. While the features that are considered to have no effect are taste and length. As for the data as much as 4952, the best accuracy is 83.08% when k = 1, while for the data as much as 2000, then the best accuracy is 87.70% at k = 1, while for the data as much as 1000, the best accuracy is 98.60%, namely when k=1.
Peningkatan Daya Jual Produk UMKM Berbasis Inovasi dan Kreativitas di Kelurahan Krapyakrejo Kecamatan Gadingrejo Kota Pasuruan Muhammad Mahrus Ali
Jumat Pendidikan: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2023): Agustus
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat UNWAHA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32764/abdimaspen.v4i2.3889

Abstract

Digitalisasi telah menciptakan sebuah era perdagangan bebas yang menghadirkan berbagai tantangan yang dapat mengancam eksistensi bagi para pelaku UMKM. Tantangan yang akan dihadapi berupa kegiatan ekonomi yang bergantung terhadap persaingan global yang bebas terbuka sehingga hanya pelaku bisnis yang kuat yang akan bertahan. Digitalisasi juga telah menyebabkan dunia ekonomi mengalami pergesaran paradigma menjadi ekonomi berbasis pengetahuan dan kreativitas. Kegiatan ini bertujuan untuk melakukan peningkatan daya saing UMKM di Kelurahan Krapyakrejo berbasis inovasi Teknologi sebagai jawaban atas dampak yang dihadirkan oleh era digital. Pelaksanaan kegiatan ini menggunakan metode survei. Berdasarkan hasil survei, para pelaku UMKM yang ada di Kelurahan Krapyakrejo masih belum siap untuk menghadapi tantangan yang dihadirkan oleh Digitalisasi. Maka dari itu, KKN Universitas Merdeka Pasuruan Kelompok 2 mengupayakan peningkatan daya saing UMKM berbasis inovasi dan kreativitas berupa pembuatan NIB dan melakukan inovasi terhadap produk melalui upgrading kemasan dan pemasaran melalui pemanfaatan media social digital. Untuk mewujudkan hal tersebut kegiatan pengabdian ini menggunakan metode yang terdiri dari tiga tahapan yaitu tahap persiapan, tahap pelaksanaan dan tahap evaluasi. Adapun hasil dari kegiatan ini mampu memberikan perubahan terhadap produk UMKM di Kelurahan Krapyakrejo Kecamatan Gadingrejo Kota Pasuruan ‘ ‘berupa produk siap untuk di jual di marketplace karena sudah memiliki Nomor Induk Berusaha (NIB) serta produk dikemas dengan kemasan yang lebih menarik
APPLICATION OF AUGMENTED REALITY TECHNOLOGY AS A LEARNING MEDIA Ali, Muhammad Mahrus
Jurnal Teknologi dan Sistem Tertanam Vol 5, No 2 (2024): Vol 5 No 02, Agustus 2024
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jtst.v5i2.4575

Abstract

Augmented Reality (AR) is a concept of combining virtual reality with world reality. The benefits of technology at this time have greatly influenced human life, with the creation of sophisticated machines or tools that humans use to achieve human needs. Augmented Reality is an environment that incorporates virtual 3D objects into a real environment. Augmented Reality is growing very rapidly so that it supports the development of this application in various fields including learning media. Elementary school students find it difficult to understand the material of geometry, because without teaching aids students are only able to imagine or imagine the object of the geometry. Because this requires a learning application for geometry by applying Android-based Augmented Reality technology that can display 3d space shapes along with elements and formulas that apply to the material. Seeing these objectives, the researcher took the type of Research and Development Method or what in English is called R&D (Research and Development), which is a method used to produce a certain product and test the effectiveness of the product (Sugiyono, 2009: 297). The calculation method uses the one-way ANOVA method. The trial was carried out at SD Islam Pasuruan. It was tested on students in grades VI A and B and 18 participants were taken randomly and divided into 3 groups consisting of 6 students in each group. The results obtained from the calculation analysis using one-way Anova with F_count = 4.68 greater than F table = 3.68 with a significant level of 5% (0.05). Furthermore, the Scheffe test was performed to compare the values between groups. With the results, the first group (5.30) has a greater value than the second (2.65) and third (2.652) groups. This application can be installed and running on all types of android used in testing, and the recommended best distance between mobile devices to detect markers is 40 cm - 90 cm for all marker sizes, namely 10 cm, 15 cm and 20 cm in size.
Evaluasi Sentimen Review Produk Roundup Menggunakan Algoritma Support Vector Machine: Evaluasi Sentimen Review Produk Roundup Menggunakan Algoritma Support Vector Machine Mohamad Khoiron; Dian Ahkam Sani; Mohammad Zoqi Sarwani; Muhammad Mahrus Ali; Khoirul Anwar; Muhammad Udin
J-Innovation Vol. 13 No. 2 (2024): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55600/jipa.v13i2.313

Abstract

In today's digital era, more and more internet users are sharing their experiences and opinions about certain products. Sentiment analysis can be used to extract valuable information from the data generated by the shopee application users. This study aims to conduct a sentiment analysis of Roundup product reviews. The method used is the Support Vector Machine (SVM). SVM is an effective machine learning method for classifying text based on positive or negative sentiments. The purpose of this study is the SVM model which can be used to perform sentiment analysis automatically on Roundup product reviews. The results of this analysis can provide important insights for Roundup producers in understanding consumer perceptions of their products. In addition, this research can also be a guide for consumers in choosing and understanding weed killer products that suit their needs and preferences. In this study, the accuracy value was 80%, the precision value was 80%, the recall value was 100% and the value F1 score of 88.89%.
Co-Authors Dian Ahkam Sani KHOIRUL ANWAR Mochamad Sirodjudin Mohamad Khoiron Mohammad Zoqi Sarwani Muhammad Faishol Amrulloh Muhammad Udin