Muhammad Iqbal
STMIK Nusa Mandiri

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IMPLEMENTATION OF PARTICLE SWARM OPTIMIZATION BASED MACHINE LEARNING ALGORITHM FOR STUDENT PERFORMANCE PREDICTION Muhammad Iqbal; Irwan Herliawan; Ridwansyah Ridwansyah; Windu Gata; Abdul Hamid; Jajang Jaya Purnama; Yudhistira Yudhistira
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 2 (2021): JITK Issue February 2021
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1716.24 KB) | DOI: 10.33480/jitk.v6i2.1695

Abstract

Education plays an important role in the development of a country, especially educational institutions as places where the educational process has an important goal to create quality education in improving student performance. Based on research conducted in the last few decades the quality of education in Portugal has improved, but statistics show that the failure rate of students in Portugal is high, especially in the fields of Mathematics and Portuguese. On the other hand, machine learning which is part of Artificial Intelligence is considered to be helpful in the field of education, one of which is in predicting student performance. However, measuring student performance becomes a challenge since student performance has several factors, one of which is the relationship of variables and factors for predicting the performance of participating in an orderly manner. This study aims to find out how the application of machine learning algorithms based on particle sworm optimization to predict student performance. By using experimental research methods and the results of empirical studies shown in each model, namely random forest, decision tree, support vector machine and particle swarm optimization based neural network can improve the accuracy of student performance predictions.
DETERMINATION OF PERMANENT LECTURERS IN IBM ASMI INFORMATION SYSTEM PRODUCT WITH SAW AND CURRENT METHOD Rendi Septian; Istiqal Hadi; Ridwansyah Ridwansyah; Windu Gata; Widiastuti Widiastuti; Muhammad Iqbal
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 2 (2021): JITK Issue February 2021
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1295.058 KB) | DOI: 10.33480/jitk.v6i2.1740

Abstract

Abstract— Determining the quality standards of lecturers refers to the criteria of education, research, and community service. The campus can carry out the first process for selecting permanent lecturers effectively by looking at several criteria. By using a Decision Support System (DSS), the four categories can be used as guidelines for decision-makers to choose permanent lecturers. The goal of writing this journal is to support the effectiveness of the time for decision-makers to choose permanent lecturers in the early stages by combining the Additive Ratio Assessment (ARAS) and Simple Additive Weighting (SAW) methods. Where the SAW method has the advantage of accurate assessment because the value of criteria and weights have been determined, while the ARAS method compares each criterion value to each optimal alternative as a whole to get an ideal alternative. The result of combining the two methods can describe the prospective lecturers who are suitable to be used as permanent lecturer criteria. Judging from the ranking results in calculations, the values obtained are 0.146341, 0.134146, and 0.121951. These results prove that ranking with an assessment using the combination of SAW and ARAS methods results in an effective, accurate, and efficient assessment. Keywords: Additive Ratio Assessment, Decision Support Systems, Permanent lecturer, Simple Additive Weighting. Intisari— Menentukan standar kualitas dosen mengacu kepada kriteria pendidikan, penelitian, dan pengabdian kepada masyarakat. Pihak kampus dapat melakukan proses pertama untuk pemilihan dosen tetap secara efektif dengan melihat beberapa kriteria. Dengan menggunakan Sistem Penunjang Keputusan (SPK), keempat kategori tersebut bisa dijadikan pedoman bagi pengambil keputusan untuk memilih dosen tetap. Tujuan penulisan jurnal ini adalah untuk membantu keefektifan waktu bagi pengambil keputusan untuk memilih dosen tetap tahap awal dengan penggabungan metodeAdditive Ratio Assessment (ARAS) dan Simple Additive Weighting (SAW).Dimana metode SAW mempunyai keunggulan penilaian akurat karena untuk nilai kriteria dan bobot telah ditentukan, sementara metode ARASmelakukan perbandingan setiap nilai kriteria terhadap masing alternatif optimal secara keseluruhan untuk mendapatkan alternatif yang ideal. Hasil penggabungan dua metode tersebut dapat menggambarkan calon dosen yang sesuai untuk dijadikan kriteria dosen tetap.Dilihat dari hasil perangkingan dalam perhitungan, nilai yang didapat 0,146341 ,0,134146 dan 0,121951. Hasil ini membuktikan bahwa perangkingan dengan penilaian menggunakan penggabungan metode SAW dan ARAS menghasilkan penilaian yang efektif, akurat dan efisien. Kata Kunci: Additive Ratio Assessment, Sistem Penunjang Keputusan, Dosen Tetap, Simple Additive Weighting.
MOBILE-BASED ONLINE EXAM APPLICATIONS USING PROBLEM WEIGHT CLASSIFICATION TECHNIQUES, GROUPING AND RANDOMIZING Muhammad Iqbal; Abdul Hamid; Nuraeni Herlinawati; Mochammad Abdul Azis; Muhammad Rezki; Ali Mustopa
Techno Nusa Mandiri: Journal of Computing and Information Technology Vol 17 No 1 (2020): TECHNO Period of March 2020
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1360.688 KB) | DOI: 10.33480/techno.v17i1.1229

Abstract

Education is an agenda for designing the country's development. Implementation in the field of education is a joint responsibility of both the government and the community, educational institutions are one that plays an important role in the ongoing learning process activities one of which is the examination activities. The test is an evaluation of the learning process to obtain learning outcomes as a form of achievement recognition or completion in an educational unit. The test is still cheating, it is triggered by the lack of confidence in working on the exam questions and the same type of exam questions will provide an opportunity to chat and work together. The author aims to provide a solution in the form of the application of online-based online test applications using question weight classification techniques, grouping and randomization. This mobile-based online exam application was developed using the waterfall model. The results obtained from research on this mobile-based exam application has features to prevent screen capture or screenshots, prevent video recording or video recorder and prevent switching applications that can run multiplatform on Android and iOS. This application has been through the process of testing the user and distributing questionnaires to determine the feasibility of using the weight classification technique with a percentage of 80% so it is suitable for use in examination activities.