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All Journal Jurnal Kolaboratif Sains Jurnal Sistim Informasi dan Teknologi
Muhamad Ziaul Haq
Universitas Muhammadiyah Palu
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Other

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Prediksi Indeks Prestasi Komulatif Mahasiswa berdasarkan Nem dengan Menggunakan Algoritma Neural Network Berbasis Particle Swarm Optimization : Prediction of Student Comulative Achievement Index Based on NEM Using Particle Swarm Optimization Based Neural Network Algorithm Muhamad Ziaul Haq; Nursalim
Jurnal Kolaboratif Sains Vol. 6 No. 2: FEBRUARI 2023
Publisher : Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/jks.v6i2.3303

Abstract

Proses Penerimaan Mahasiswa Baru (PMB) pada berbagai perguruan tinggi di Indonesia baik itu perguruan tinggi negeri ataupun swasta melakukan seleksi terhadap calon mahasiswanya dengan melihat pada Nilai Ebtanas Murni (NEM). Guna menganalisis hubungan antara nilai NEM calon mahasiswa dengan prestasi akademik yang dicapai di STMIK Adhi Guna (dalam hal ini digunakan indeks prestasi kumulatif (IPK) dengan analisis korelasi dan regresi linier ganda. Variabel penelitian yang digunakan adalah hasil IPK kelulusan mahasiswa sebagai variabel dependen (terikat), dan nilai mata pelajaran Bahasa Indonesia, Bahasa Inggris, dan Matematika sebagai variabel independent (bebas). Penelitian ini menggunakan 2 algoritma yang berbeda yaitu Neural Network (NN) dan Particle Swarm Optimization (PSO) untuk membandingkan hasil dan mencari tingkat akurasi terbaik diantara kedua algoritma tersebut. Dari penelitian yang telah dilakukan dapat disimpulkan bahwa Neural Network berbasis Particle Swarm Optimization adalah algoritma yang paling baik dibandingkan dengan Neural Network untuk mengukur tingkat korelasi antara NEM dan Indeks Prestasi Kumulatif (IPK) mahasiswa. Neural Network pada penelitian ini menghasilkan akurasi terkecil 0,214 dengan Time = 4 s. Neural Network berbasis PSO menghasilkan akurasi terkecil 0,132.
The Implementation of Simple Additive Weighting Method for Designing A Web-Based Waste Management Saving Transaction System Nursalim; Muhamad Ziaul Haq; Nalis Hendrawan; Roy Mubarak; I Putu Dody Suarnatha
Jurnal Sistim Informasi dan Teknologi 2023, Vol. 5, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jsisfotek.v5i2.244

Abstract

The Garbage Bank is an organization initiated for all students to support the management of inorganic waste into something of value so as to create additional income. The increasing number of customers has caused the treasurer to be overwhelmed in ranking customer rankings and to not be on target in determining the best customer with the same amount of waste. In addition, there is no system security in handling the transaction process, so unwanted access can occur. The purpose of this research is to develop a savings transaction system for waste management so that it becomes a green Campus. The decision-making method uses Simple Additive Weighting. The system development methodology used is Rapid Application Development (RAD). The tools used in system design are the Unified Modeling Language. The implementation of this system uses the PHP programming language with the Laravel and MySQL frameworks for database processing. The resulting system can simplify and speed up the process of recording and managing waste bank data.
Co-Authors I Putu Dody Suarnatha Nalis Hendrawan Nursalim Roy Mubarak