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Iwan Setiawan Wibisono
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INDONESIA
Jurnal Ilmu Komputer
Published by Universitas Ngudi Waluyo
ISSN : -     EISSN : 26556316     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Multimatrix ini sebagai media publikasi artikel penelitian, pengabdian masyarakat dalam bidang ilmu komputer
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 4 Documents
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Search results for , issue "Vol. 4 No. 2 (2022)" : 4 Documents clear
Pengembangan Model Evaluasi Berbasis Sistem Menggunakan Moodle di Komunitas e-guru Semarang Abdul Rohman
Multimatrix Vol. 4 No. 2 (2022)
Publisher : Universitas Ngudi Waluyo

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Abstract

E-guru merupakan komunitas guru seluruh indonesia yang memiliki anggota 19.763 orang dari kalangan guru, dosen dan tenaga pengajar lainnya. Dalam pembelajaran, komponen evaluasi merupakan tahapan yang sangat penting untuk mengukur kemampuan siswa/mahasiswa dalam mempelajari materi yang disampaikan oleh pengajar dan evaluasi dijadikan sebagai umpan balik guru/dosen untuk mengembangan model pembelajaran yang sesuai kebutuhan masyarakat. Selain itu seorang guru dituntut untuk melek teknologi informasi dalam pengembangan evaluasi berbasis sistem terutama pemafaatan aplikasi/program moodle. Moodle merupakan aplikasi/program yang efektif dan efisien untuk melaksanakan pembelajaran secara blended learning terutama dalam pengembangan model evaluasi. Dengan adanya pengembangan model berbasis sistem menggunakan moodle bagi guru/dosen di komuniatas guru dalam bentuk pelatihan dan pendampingan, dapat memberikan pengetahun dan keterampilan dalam melaksanakan evaluasi berbasis digital. Kata kunci: Evaluasi, Sistem, Moodle
PENERAPAN BINARY SEARCH PADA APLIKASI PENJUALAN BERBASIS WEB STUDI KASUS PADA TOKO MORE SHOP AMBARAWA anggita maharani donal; Iwan Setiawan Wibisono
Multimatrix Vol. 4 No. 2 (2022)
Publisher : Universitas Ngudi Waluyo

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Abstract

Aplikasi website ini merupakan salah satu layanan berbelanja online berbasis web yang memudahkan orang – orang yang tidak bisa datang ke tokonya langsung bisa berbelanja melalui website ini tanpa harus mengantri. Terlebih di masa pandemi seperti sekarang ini yang tidak boleh pergi ke mall ,aplikasi ini sangat membantu berbelanja lebih gampang dan tidak perlu mengantri lagi. Kata kunci: Web, Binary Search, Penjualan
Evaluasi Usability pada SIMPEL SMAN 12 Semarang dengan Metode Usability Testing Wahyuningtyas Hesti; Iwan Setiawan Wibisono
Multimatrix Vol. 4 No. 2 (2022)
Publisher : Universitas Ngudi Waluyo

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Abstract

Abstrct — The Learning Management System (SIMPel) of SMAN 12 Semarang is a system that provides features that are used to facilitate online learning. The online learning system in a school plays a significant role because it can improve the learning process. This study aims to measure the usability of SIMPel SMAN 12 Semarang. There are four aspects of usability used in this study: effectiveness, efficiency, learnability, and satisfaction, which are then used as aspects of assessment. This research was conducted to determine the usability of the system for users by analyzing the problems faced by users when using the system. A total of 13 research respondents consisting of 3 administrative staff respondents, five teacher respondents, and five student respondents, were selected to perform usability testing on the system. From the results of the system evaluation conducted with administrative staff and teacher respondents, it was found that the effectiveness aspect reached 97.5%, the efficiency aspect was 95.5%, the learnability aspect was 94%, and the satisfaction aspect got 88%. Meanwhile, the results of tests carried out on the system with alumni respondents showed that the effectiveness aspect reached 100%. The ef_ciency aspect was 100%, the learnability aspect was 93.6%, and the satisfaction aspect was 88.8%. From these results, it can be concluded that SIMPel SMAN 12 Semarang is a very feasible system to use, and the system can be used according to user needs. The results of interviews with respondents resulted in recommendations that could then be used to improve the system. Keywords: Evaluation, The Learning Management System, Usability, Usability Testing
Komparasi Algoritma Machine Learning dan Ensemble Methods dalam Prediksi Penyakit Jantung dengan Dataset yang Bervariasi Abdul Rohman; Sri Mujiyono
Multimatrix Vol. 4 No. 2 (2022)
Publisher : Universitas Ngudi Waluyo

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Abstract

This study aims to compare the performance of various machine learning algorithms and ensemble methods in predicting heart disease, using two different datasets: datasets from the UCI Machine Learning Repository and Kaggle. Nine algorithms were tested, including Logistic Regression (LR), K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF), XGBoost, LightGBM, CatBoost, Support Vector Machine (SVM), and Naive Bayes (NB). The data were processed through data cleaning, normalization, and splitting the dataset into training and test data. The experimental results showed that K-Nearest Neighbors (KNN) performed best with an accuracy of 91.80%, followed by Support Vector Machine (SVM) and Random Forest (RF), which also demonstrated stable and effective results in handling complex datasets. Although Decision Tree (DT) and Naive Bayes (NB) performed lower, these results demonstrate that basic machine learning algorithms can provide adequate results for heart disease classification. This study recommends the use of ensemble algorithms and further exploration in feature engineering to improve predictions.

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