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All Journal Jurnal Matematika JTAM (Jurnal Teori dan Aplikasi Matematika) Innovative: Journal Of Social Science Research
Kencana, Eka N.
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Humanities Computer Science & IT Law, Crime, Criminology & Criminal Justice Mathematics Public Health Other

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Penerapan Metode K-means Pada Klasterisasi Provinsi di Indonesia Berdasarkan Indikator Indeks Kebahagiaan Damayanthi, Ni Wayan Rita; Suciptawati, Ni Luh Putu; Jayanegara, Ketut; Sukarsa, I Komang Gde; Kencana, Eka N.; Wijayakusuma, I Gusti Ngurah Lanang
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p172

Abstract

The happiness index is a measure that reflects individual well-being, thus playing an important role in the development of a region. The level of happiness in Indonesia is still significantly lower compared to other ASEAN countries. In relation to efforts to improve the happiness index in Indonesia, this study applies the K-means method to cluster the 34 provinces of Indonesia based on the indicators of the happiness index for the year 2021. The data used is sourced from publications by the Indonesian Central Bureau of Statistics with seven happiness index indicators and employing the Minkowski distance. The clustering results of the 34 provinces using the K-means method obtained four clusters with a cluster accuracy value of 71 percent. Cluster 1 consists of seven provinces with a fairly high average of seven attributes, cluster 2 consists of seven provinces is a cluster with a low average level of internal and external satisfaction, cluster 3 consists of four provinces with a high average of seven attributes, and cluster 4 consists of 16 provinces is a cluster with provinces with a fairly high average level of external satisfaction, but a low level of internal satisfaction.
Seleksi Fitur Information Gain Untuk Klasifikasi Kualitas Susu Sapi Menggunakan Metode K-Nearest Neighbor Dan Naïve Bayes Ali, Fauzi Wardah; Sumarjaya, I Wayan; Kencana, Eka N.
Innovative: Journal Of Social Science Research Vol. 5 No. 1 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i1.17477

Abstract

Kemajuan dalam komputasi modern, khususnya klasifikasi, telah membantu manusia dalam mengklasifikasikan berbagai tugas yang memakan waktu dan komputasi yang mahal, salah satunya adalah klasifikasi kualitas susu sapi. Pengklasifikasian ini penting dilakukan untuk mengurangi kemungkinan beredarnya susu dengan kualitas buruk di masyarakat. Data pada penelitian ini terdiri dari 429 susu kualitas rendah, 374 susu kualitas menengah, dan 256 susu kualitas tinggi. Penelitian ini menguji performa algoritma klarifikasi K-nearest neighbor dan naïve Bayes dengan menggunakan teknik seleksi fitur information gain dan tanpa seleksi fitur information gain. Hasil penelitian ini menunjukkan performa KNN mengalami peningkatan rata-rata akurasi sebesar 1,04 persen dengan perhitungan jarak Euclid dan 0,92 persen dengan perhitungan jarak Manhattan ketika menggunakan lima fitur. Sedangkan performa naïve Bayes mengalami penurunan akurasi sebesar 3,48 persen. Perlakuan yang berbeda tersebut memiliki perbedaan akurasi yang signifikan.
Tourism Development Priorities in Lombok Eastern with Analytical Hierarchy Process Kurniawan, Rinaldi; Kencana, Eka N.; Gandhiadi, G. K.
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 6, No 4 (2022): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v6i4.8734

Abstract

East Lombok is a regency that has tourism potential to be developed. In accelerating the pace of tourism development in East Lombok Regency, a decision support system is needed to make it easier to determine development priorities in the tourist sector. Analytical Hierarcy Process is a decision-making method that can solve the problem of multicriteria in the aspect of tourism in East Lombok. The data used are 50 data by prioritizing the opinions of experts and policy makers, namely the East Lombok Tourism Office, Head of tourism awareness groups and people involved in the tourism sector. The results showed that the value of index consistency was below 10% for each indicator and subindicator with infrastructure indicators as the highest priority with a value of 29.4545% and the highest subindicator was accessibility with a value of 17.8381%. The result of the calculation are expected to help policy makers in determining the strategy in the development of the tourism sector in Eaast Lombok district and in the future it can be developed by considering other factors.
Co-Authors Ali, Fauzi Wardah Damayanthi, Ni Wayan Rita G. K. GANDHIADI I KOMANG GDE SUKARSA I WAYAN SUMARJAYA Ketut Jayanegara Kurniawan, Rinaldi Ni Luh Putu Suciptawati Wijayakusuma, I Gusti Ngurah Lanang