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Lasarudin, Alter
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Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Evaluasi Sistem Informasi Menggunakan Model HOT-FIT Pada Sistem Penerimaan Mahasiswa Baru di Lingkungan Universitas Muhammadiyah Gorontalo Syahrial, Syahrial; Larote, Yonis; Lasarudin, Alter; Olii, Muhammad Ramdhan
Jurnal Ilmu Komputer (JUIK) Vol 4, No 2 (2024): JUNE 2024
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v4i2.3315

Abstract

This research was conducted to evaluate the website for new student admissions at the Universitas Muhammadiyah Gorontalo. Evaluation was carried out by applying the HOT-Fit model method to 4 components. Focus evaluation on technological, human, organizational and benefits components. The aim is to determine the level of usability of the Universitas Muhammadiyah Gorontalo New Student Admissions System. The research method was carried out quantitatively by collecting questionnaire data from the committee and registrants. The HOT-Fit model is applied in determining system evaluation indicators. The results of the HOT-Fit model approach on 8 variables are good. There is a test value for System Quality (KS) with a value of 73.8 (Good), then Service Quality (KL) with a value of 82.0 (Very Good), then Information Quality (KI) with a value of 72.3 (Good), then System Usage (PS) with a value of 77.9 (Good), then User Satisfaction (KP) with a value of 74.2 (Good), then Organizational Environment (LO) with a value of 82.7 (Very Good), then Organizational Structure (SO ) with a score of 66.7 (Good), and System Benefits (MS) with a score of 82.2 (Very Good). Categories in 8 variables are good to use based on the HOT-Fit method with a value obtained of 76.5. The Usability Testing results are good for use based on the HOT-Fit method and the assessment of new students as respondents.
Digital Library Universitas Muhammadiyah Gorontalo Antupetu, Rastin; Abas, Mohamad Ilyas; Lasarudin, Alter; Lamusu, Rizal
Jurnal Ilmu Komputer (JUIK) Vol 4, No 1 (2024): FEBRUARY 2024
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v4i1.2797

Abstract

This research was conducted at the Library of Universitas Muhammadiyah Gorontalo. The aim is to design a web-based library information system with a digital concept (Digital Library). The design of the Digital Library information system of Universitas Muhammadiyah Gorontalo, with a system design model using the prototyping model, provides a forum for students and lecturers, especially those on the campus of Universitas Muhammadiyah Gorontalo to publish research results in the form of theses, journals, and theses into this digital library system. With this digital library it will facilitate access for prospective graduates, both the academic community and academics outside the campus, who will take literature as a reference for the final report or thesis. Provide convenience in disseminating useful information or knowledge and help students conduct research.
O OPTIMALISASI NEURAL NETWORK BERBASIS PARTICLE SWARM OPTIMIZATION UNTUK MEMPREDIKSI LAMA PENYINARAN MATAHARI DALAM MEMENUHI KEBUTUHAN ENERGI Hasyim, Wahyudin; Lasarudin, Alter
Jurnal Teknologi Informasi Indonesia (JTII) Vol 4 No 2 (2019): Jurnal Teknologi Informasi Indonesia (November)
Publisher : JURNAL TEKNIK INFORMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30869/jtii.v4i2.391

Abstract

Tingginya beban listrik yang mencapai 325 MegaWatt, hal ini merupakan perhatian penting bagi pemerintah Provinsi Gorontalo dalam kebutuhan energi listrik, maka perlu memprediksi lama penyinaran matarahari pada suatu daerah, Energi sel surya salah satunya bergantung pada lamanya penyinaran cahaya matahari. Diantaranya dengan melakukan perancangan model prediksi. Metode prediksi yang mimiliki nilai error terkecil adalah Neural Network, akan tetapi masih adanya kelemahan pada waktu pelatihan untuk mencapai konvergen dan overfitting. Maka perlu dilakukan optimalisasi pada bobot jaringan dengan menggunakan Particle Swarm Optimazition, yang merupakan salah satu metode terbaik dalam optimasi. Dengan penggunaan optimasi yang diukur melalui hasil peroleha Root Mean Square Error (RMSE). Hasil pengujian terhadap algoritma menunjukkan bahwa nilai RMSE mengunakan Neural Network 0,131, sedangkan dengan penerapan optimasi dengan particle swarm optimization hasil RMSE 0,127. Dengan penerapan metode optimasi terserbut dapat mengurangi nilai error
Co-Authors Antupetu, Rastin Lamusu, Rizal Larote, Yonis Mohamad Ilyas Abas Olii, Muhammad Ramdhan SYAHRIAL SYAHRIAL Wahyudin Hasyim