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All Journal Technomedia Journal Journal of Applied Engineering and Technological Science (JAETS) Jurnal Pengabdian Masyarakat Journal of Digital Literacy and Volunteering
Agung Muliawan
Institut Teknologi Dan Sains Mandala
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences

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Membangun Sistem Rekomendasi Hotel dengan Content Based Filtering Menggunakan K-Nearest Neighbor dan Haversine Formula Agung Muliawan; Tessy Badriyah; Iwan Syarif
Technomedia Journal Vol 7 No 2 October (2022): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (546.579 KB) | DOI: 10.33050/tmj.v7i2.1893

Abstract

Peningkatakan pertumbuhan industri hotel pada tiap tahunnya dan preferensi konsumen yang bervariasi dalam kebutuhan layanan hotel mengakibatkan konsumen lebih konsumtif dalam memilih hotel. Kurangnya pilihan kriteria bobot pada penyedia layanan hotel mengakibatkan konsumen mengalami kesulitan dalam memilih hotel yang sesuai dengan preferensinya, sehingga diperlukan sebuah sistem rekomendasi hotel sebagai pilihan alternatif dalam memilih hotel. Dalam penelitian ini digunakan permodelan Case Based Reasoning (CBR) untuk memberikan pembelajaran kepada sistem. Pilihan dari user pada pilihan hotel secara otomatis akan disimpan ke dalam database dan dijadikan sebagai data training sehingga sistem akan mendapatkan informasi secara berkelanjutan. Pada penelitian ini diberikan tiga jenis kebutuhan antara lain Kebutuhan Prioritas (KP), Kebutuhan Umum (KU) dan Kebutuhan Tambahan (KT) dan atribut yang digunakan terdapat enam yaitu: fasilitas, lokasi, harga, tipe kamar, bintang dan skor yang sangat mempegaruhi hasil rekomendasi. Untuk setiap nilai bobot yang ada, dilakukan uji validitas bobot kepentingan menggunakan pairwise comparison matrix (PCM) sehingga nilai bobot menjadi valid dengan rentang nilai 0-1. Selain itu penerapan content based filtering menggunakan metode haversine formula dan K-Nearest Neighbor (KNN) dalam menentukan nilai terdekat dengan data training. Dari eksperimen, didapatkan hasil pengukuran performansi yang memuaskan berupa rata-rata kemiripan (similarity) sebesar 84.50% Kata kunci  : Case Based Reasoning, Content Based Filtering, Haversine Formula, K-Nearest
Heart Disease Prediction based on Physiological Parameters Using Ensemble Classifier and Parameter Optimization Agung Muliawan; Achmad Rizal; Sugondo Hadiyoso
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 1 (2023): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v5i1.2169

Abstract

This study describes the prediction of heart disease using ensemble classifiers with parameter optimization. As input, a public dataset was taken from UCI machine learning repository, which refers to the dataset at UCI Machine learning. The dataset consists of 13 variables that are considered to influence heart disease. Particle swarm optimization (PSO) was used for feature selection and principal component analysis (PCA) for feature extraction to reduce the features' dimensions. The application of parameter optimization on several machine learning methods such as SVM (Radial Basis Function), Deep learning, and Ensemble Classifier (bagging and boosting) to get the highest accuracy comparison. The results of this study using PSO dimensionality reduction in the public dataset of heart disease resulted in the slightest accuracy compared to PCA. In contrast, the highest accuracy was obtained from optimizing Deep Learning parameters with an accuracy of 84.47% and optimization of SVM RBF parameters with an accuracy of 83.56%. The highest accuracy in the ensemble classifier using bagging on SVM of 83.51%, with a difference of 0.5% from SVM without using bagging.  
Meningkatkan Literasi Teknologi melalui Webinar Pintu Gerbang Menuju Digital Masud Hermansyah; Nur Andita Prasetyo; Abdul Wahid; Difari Afreyna Fauziah; Agung Muliawan
JURNAL PENGABDIAN MASYARAKAT Vol 3 No 2 (2023)
Publisher : Institut Teknologi dan Sains Mandala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31967/jpm.v3i2.871

Abstract

In the ever-evolving digital era, technology has become a major driving force in social, economic and educational change. Information and communication technologies (ICTs) have changed the way people work, communicate, and learn. As technology advances, it is important for individuals to have sufficient technological literacy to be able to participate actively in a digital society. The aim of this webinar is to provide an in-depth understanding of digital technology and teach practical skills in using it wisely. This webinar presents a series of topics related to digital technology, including digital transformation of Internet of Things (IoT) Technology in the Industrial World, Information Security Culture, and Computer and Network Security. By using the Zoom Video Communications application, webinar participants can easily participate from their respective locations, thus enabling broad participation and more flexibility for students to learn about technology. This webinar succeeded in increasing high school and vocational students' interest in the field of technology, as well as opening their insights about various career opportunities in the digital era. In addition, students also become more aware of the importance of ethics and responsibility in using technology, and are aware of its impact on society.
Penerapan Metode Analytical Hierarchy Process (AHP) Pada Penilaian Pegawai Teladan Agung Muliawan; Iqbal Sabilirrasyad; Difari Afreyna Fauziah
Journal of Digital Literacy and Volunteering Vol. 2 No. 2 (2024): July (In Progress)
Publisher : Puslitbang Akademi Relawan TIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57119/litdig.v2i2.76

Abstract

One of the factors supporting the success of a business place is productive employees who have maintained and improved qualification standards. The company's appreciation for exemplary employees can be given by giving gifts or awards. Employee performance assessment can be done to determine employees who are qualified and highly dedicated to the company. However, many companies experience difficulties in evaluating employee performance because the calculations are still manual so that they are less effective and objective, one of which is SMK Visi Global Jember. The research will apply the Analytical Hierarchy Process (AHP) method in determining the best employees at SMK Visi Global Jember so that the selection process is right on target with the needs of the criteria given. The required criteria include honesty, loyalty, commitment, discipline and cooperation which will be processed to produce the highest rank for determining recommendations for exemplary employees. The results of this study produce a Consistency Ratio (CR) value of 0.083 so that the value of giving preferences is consistent and can be used in determining exemplary employees at SMK Visi Global Jember
Co-Authors Abdul Wahid Achmad Rizal Difari Afreyna Fauziah Iqbal Sabilirrasyad iwan Syarif Masud Hermansyah Nur Andita Prasetyo Sugondo Hadiyoso Tessy Badriyah, Tessy