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Improving K-Means clustering performance on non-linear data using variance-weighted distance metrics Elsya Sabrina Asmita Simorangkir; Efori Bu'ulolo
Journal of Intelligent Decision Support System (IDSS) Vol 9 No 2 (2026): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v9i2.366

Abstract

K-Means is one of the most widely used clustering algorithms because of its simplicity and computational efficiency. However, its performance often decreases when handling non-linear data due to the assumption that all attributes contribute equally to the distance calculation process. This study proposes a Variance-Weighted Distance Metrics K-Means (VWDM-KMeans) method that assigns attribute weights based on variance values to improve clustering quality. The proposed approach consists of Min-Max Normalization, variance calculation, weight generation, and integration of variance-based weights into the distance metric used by K-Means. Experiments were conducted on a non-linear dataset containing 103 records and 3 attributes (x, y, and z) with K = 3 clusters. The generated attribute weights were 0.3207, 0.3342, and 0.3451 for attributes x, y, and z, respectively. The performance of VWDM-KMeans was compared with conventional K-Means and K-Medoids using the number of iterations, Sum of Squared Errors (SSE), and Silhouette Score (SS). The results showed that VWDM-KMeans converged in 5 iterations, compared to 6 iterations for K-Means and 3 iterations for K-Medoids. In terms of cluster compactness, VWDM-KMeans achieved the lowest SSE value of 2.7932, outperforming K-Means (8.2429) and K-Medoids (8.9602). Furthermore, VWDM-KMeans obtained a Silhouette Score of 0.4854, equal to K-Means and higher than K-Medoids (0.4696). These findings demonstrate that incorporating variance-based attribute weighting into the distance calculation process improves cluster compactness while maintaining cluster separation quality and stability. Therefore, VWDM-KMeans can serve as an effective and computationally efficient alternative for clustering non-linear data.
Data Mining Sistem Stock Opname Bahan Baku Catering Makanan Sehat Menggunakan Metode Min Max Stock Chyntia Kesuma; Efori Buulolo; Hukendik Hutabarat
Bulletin of Information System Research Vol 1 No 1 (2022): Desember 2022
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/bios.v1i1.33

Abstract

Competition in today's business world is increasing, there are more and more innovations made by every entrepreneur to increase sales of the products they make so that they can be accepted in the market and in the community. One of them is Healthy Food Medan, a company engaged in healthy food catering. In making healthy food, it is necessary to stock up on good raw materials, so that one day the company does not lack stock of raw materials. Healthy Food Medan itself will not be separated from the so-called stock taking of raw materials. Of course, it is very interesting to be used as research material. Because of this, a computer program was created to determine the stock of raw materials so that there is no shortage of raw materials. In the application with the Min-Max method, it is expected that the user will no longer have difficulties in terms of stock of raw materials. The Min-Max method itself is a method that determines the maximum amount of inventory and minimum inventory so that there are no shortages and excess goods. Aims to avoid excess and shortage of raw materials by calculating the amount of raw material inventory
Pelatihan Pembuatan Ujian Online Menggunakan Aplikasi Kahoot Rian Syahputra; Efori Buulolo; Hukendik Hutabarat
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol. 1 No. 2 (2021): Desember 2021
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v1i2.792

Abstract

Abstract: Currently the whole world is being hit by the spread of the COVID-19 virus, which makes all people inevitably stay at home to avoid contracting the virus. As a result, many office workers, including students and college students, are laid off or work and study at home using the online learning method. One method of distance learning is to use several platforms such as video conferencing, zoom, google meet, google classroom, moodle, and the like. As for taking the exam online, we can use the Kahoot application. This application allows all teaching staff to make exams online and can be accessed anywhere. So that using the Kahoot application can be a method that helps in carrying out online exams.         Keywords: Kahoot; Online Quiz; E-Learning  Abstrak: Saat ini seluruh dunia sedang dilanda penyebaran virus COVID-19 yang membuat seluruh masyarakat mau tidak mau untuk menetap di rumah masing-masing demi menghindari terjangkit virus tersebut. Akibatnya banyak pekerja kantoran, termasuk para siswa dan mahasiswa yang dirumahkan atau bekerja dan belajar di rumah masing-masing dengan metode online learning. Salah satu metode pembelajaran jarak jauh adalah dengan menggunakan beberapa platform seperti video conference, zoom, google meet, atau seperti google classroom, moodle dan sejenisnya. Adapun untuk melakukan ujian secara online kita dapat menggunakan aplikasi Kahoot. Aplikasi ini memungkinkan semua tenaga pengajar untuk membuat ujian secara online dan dapat diakses dimana saja. Sehingga dengan menggunakan aplikasi Kahoot ini dapat menjadi metode yang membantu dalam melaksanakan ujian secara online.Kata kunci: Kahoot; Ujian Online; Pembelajaran Online
Co-Authors A M Hatuaon Sihite A, Azanuddin Afnita, Devi Afri Nirmalasari Halawa Ahmad Fachriansyah Alan Bangun Siregar Alexander Pamdapotan Manullang Alwin Fau Amatilah Nasution Andreas Gerhard Simorangkir Ardi Kusuma Ari Pradana Arif Budiman Azhar Azhar Benny Sinaga Bernadus Gunawan Sudarsono Bister Purba Buulolo, Ananoma Chyntia Kesuma Defiyuliyanti Bazikho Desi Simanjuntak Devi Afnita Devi Sari Oktavia Panggabean Dito Putro Utomo Edizal Hatmi Eko Firdonal Simamora Elsya Sabrina Asmita Simorangkir Endang Rismawati Erlinda Simamora Ewit Purba Fadlina Fauziyah Fifto Nugroho Fince Tinus Waruwu Fince Tinus Waruwu Fince Tinus Waruwu Ginting, Fransiskus Ginting, Permanan Hasanah, Lailatun Hendra Gunawan Hosianna Saragih Hot Riris Siburian Hukendik Hutabarat Hukendik Hutabarat Hukendik Hutabarat Hutabarat, Hukendik Hutabarat, Sumiaty Adelina Ikhwan Lubis Ikwan Lubis Imam Saputra Iskandar Zulkarnain Khairunnisa Khairunnisa Kurnia Ulfa Laia, Delisman Laia, Delisman Lucius Yupiter Telaumbanua M. Ibrahim Maharani Maharani, Maharani Maringan Sianturi Matias Julyus Fika Sirait Mauhati Pardede Meryance V. Siagian Meryance Viorentina Siagian Mesran, Mesran Muasir Pagan Muhammad Abdul Rohim Muhammad Fahriat Muhammad Zarlis Mutiah Mutiah Nainel, Yane Laheroi Naomi Labora Saragi Nasib Marbun Natalia Silalahi Natalia Silalahi, Natalia Ndruru, Eferoni Nduru, Ewin Karman Nduru, Ewin Karman Nelly Astuti Hasibuan Noferianto Sitompul Nurdiyanto, Heri Ojahan Sihombing Permanan Ginting Pristiwanto, Pristiwanto Pristiwanto, Pristiwanto Purba, Bister Purba, Citra Verawati Rahmi Ras Fanny Reka Safarti Rian Syahputra Rico Albert Andika Saragih Rivalri Kristianto Hondro Rizky Meliani Astri Hasibuan Rohan Kristini Purba Saidi Ramadan Siregar Saragih, Hosianna Sari, Vingki Rapika Sarumaha, Lukas Siagian, Edward Robinson Sianturi, Lince T Siburian, Henry Kristian Sihombing, Ojahan Silalahi, Eci Marcelina Sinaga, Ali Sabany Sirait, Annisa Corry Nauli Siregar, Alan Bangun Siska Kristiana Simanullang Sitepu, Rahmad Dani Sitepu, Rahmad Dani Siti Maryam Soeb Aripin Sri Devi Manullang Suginam Surya Darma Nasution Sutiksno, Dian Utami Tampubolon, Tigor Barata Victor Gultom Vini Kristin Septiani Situmorang Wahyu Prismawan Wulan Juni Andari Yani, Ika Fitri Yosa`aro Zai Yuhandri Yuhandri, Yuhandri Zai, Evi Safyan Sari Zai, Viktor Frank Zega, Serta Kurniawan Zulkifli Nasution