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Perancangan Aplikasi Similarity Deteksi Kemiripan Judul Disertasi Berbasis Web Mayola, Liga; Hafizh, Muhammad; Putra, Deri Marse
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 6 No 2 (2024): April 2024
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v6i2.1164

Abstract

Education has a good goal and system, namely creating a generation that is trustworthy in its actions and scientific writing. An educated person must have ethics in writing work, one of which is avoiding plagiarism. Determining the title of the dissertation that will be submitted must pay attention to several aspects to avoid similarities or even the same title because taking someone's writing or ideas without citing the source is an action that is prohibited in the ethics of scientific work. To prevent this, you can check the similarity of titles, which can be done using several methods, one of which is the Jaccard similarity algorithm, which is an algorithm that functions to find similarities or similarity of a problem, with calculations that contain a formula for solving the problem. In simple terms, this algorithm calculation will be added with a certain weighting value to increase the similarity value of the previous case with the new case. [1] Comparing title by title is very time consuming if done manually, therefore application design needs to be done so that later it can help parties. related to determining the similarity of dissertation titles. This design will later become a direction in building a dissertation title similarity detection application with the results of the title similarity percentage with the minimum acceptable level of similarity being 10%, and the consideration being 11% to 15%.
Objektivitas Sumber Daya Dosen Menggunakan Metode Weight Product Putra, Deri Marse; Nurcahyo, Gunadi Widi
Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 1 (March 2020)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (273.777 KB) | DOI: 10.37034/infeb.v2i1.20

Abstract

Lecturers as one of the human resources who have an important role in higher education activities need to be maintained the quality of their performance. One of the activities carried out is evaluating and ranking lecturers to improve the quality of performance. There needs to be a Decision Support System that can help in assessing and evaluating lecturer performance. One method in decision support is the Weight Product Method. The purpose of this research is to create a decision support system to determine the best lecturers and rank of each lecturer. The subjects of this study were lecturers at Putra Indonesia University YPTK Padang using a data sample of 5 lecturers. Data collection techniques used in this study were observation and interviews. Comparison of the results of calculations carried out manually with the results of calculations using the Weight Product method of 5 sample data used found the best lecturer with a vector V value of 0.0819. This decision support system was created using the PHP programming language and MySQL database. So that this research is more efficient because the time required in the calculation is shorter and produces the best lecturer choice that matches the criteria.
Pengembangan Aplikasi Mobile Learning Sebagai Media Pembelajaran Menggunakan Android Studio Erdisna, Erdisna; Ningsih, Sri Restu; Suryana, Febriyanno; Hidayat, Rahmad; Putra, Deri Marse
Jurnal Teknologi Informasi dan Pendidikan Vol 17 No 2 (2024): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v17i2.923

Abstract

The rapid development of Science and Technology (IPTEK) has resulted in changes in the learning paradigm which are marked by changes in curriculum, media and technology. Technological innovation and information systems in the world of education, especially in universities, have their own attraction for students, because conventional learning sometimes makes students less creative in the learning process. In today's technological advances, Android cellphones have now become a necessity for society, especially among students and students. Smartphone media is very influential in the teaching and learning process between lecturers and students in the 21st century era and is one of the distance learning media solutions. The aim of this research is to develop a mobile learning application as a distance learning medium using Android Studio to simplify and increase the efficiency of the learning process in higher education. The method used in developing this system is the waterfall method with stages with the Unified Modeling Language (UML) system design tool. The result of this research is a mobile learning application using Android Studio which is effectively used as a distance learning medium in higher education. With this mobile learning application, Android-based learning has created interesting and dynamic learning for lecturers and students, so this creates many benefits and can minimize obstacles that have occurred in the learning process and help students like learning more.
MULTIPLE LINEAR REGRESSI PADA FUZZY NEURAL NETWORK (FNN) PENENTUAN KUALITAS DAGING SAPI Yanto, Musli; Arlis, Syafri; Putra, Deri Marse
JST (Jurnal Sains dan Teknologi) Vol. 11 No. 1 (2022)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (520.682 KB) | DOI: 10.23887/jstundiksha.v11i1.38267

Abstract

Tujuan penelitian ini membahas proses identifikasi kualitas daging sapi dengan implementasi metode multiple linear regressi (MLR) pada fuzzy neural network (FNN). Metode ini dikembangkan untuk menyempurnakan proses identifikasi yang sudah ada sebelumnya. MLR mampu melakukan proses pengukuran korelasi variable (X) dengan hasil keluaran (Y). Pendekatan dalam proses analisis tersebut menggunakan pendekatan kuantitatif untuk melakukan pengukuran dari beberapa aspek indikator yang digunakan dalam penentuan kualitas daging sapi.  Berdasarkan hasil uji korelasi dengan MLR membuktikan bahwa variabel kandungan zat kimia (X1), bau (X2), warna (X3), dan tekstur daging (X4) menghasilkan hubungan yang signifikan terhadap kualitas daging sapi (Y) dengan nilai sebesar 96.5%. Hasil analisis MLR mampu memberikan gambaran indikator variable yang tepat dalam proses analisis. Keluaran FNN juga menyajikan hasil yang cukup akurat dengan nilai sebesar 99.88%. Dengan hasil keluaran yang didapat, maka secara keseluruhan dapat disimpulkan bahwa model analisis MLR dan FNN memberikan hasil analisis dengan tingkat akurasi yang lebih baik dan efektif. Hasil tersebut mampu memberikan implikasi berupa sebuah rekomendasi dalam bentuk pengetahuan dan informasi yang didapat kepada masyarakat guna menentukan daging sapi yang baik dikonsumsi.