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All Journal International Journal of Electrical and Computer Engineering Zero : Jurnal Sains, Matematika, dan Terapan Blend Sains Jurnal Teknik
Elveny, Marischa
Universitas Sumatera Utara
Agriculture, Biological Sciences & Forestry Automotive Engineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics

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Sensitivity of MAPE using detection rate for big data forecasting crude palm oil on k-nearest neighbor Al Khowarizmi; Rahmad Syah; Mahyuddin K. M. Nasution; Marischa Elveny
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2696-2703

Abstract

Forecasting involves all areas in predicting future events. Many problems can be solved by using a forecasting approach to become a study in the field of data science. Forecasting that learns through data in the light age is able to solve problems with large-scale data or big data. With the big data, the performance of the k-Nearest Neighbor (k-NN) method can be tested with several accuracy measurements. Generally, accuracy measurement uses MAPE so it is necessary to conduct sensitivity on MAPE by combining it with the detection rate which is the difference technique. In addition, the k-NN process has been developed for the sake of running sensitivity by performing normalized distance using normalized Euclidean distance so that in this paper using the crude palm oil (CPO) price dataset, it is able to forecast and become a future model and apply it to Business Intelligence and analysis. In the final stage of this paper, the accuracy value in doing big data forecasting on CPO prices with MAPE is 0.013526% and MAPE sensitivity combined with a detection rate of 0.000361% so that future processes using different methods need to involve detection rates.
Similarity of Competitive Merchant Behavior Using the Jaccard Coefficient Elveny, Marischa
ZERO: Jurnal Sains, Matematika dan Terapan Vol 4, No 2 (2020): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v4i2.8991

Abstract

Advanced installment innovation has brought a business pattern that makes it simpler to see income conditions or what is known as a productive contrast. Different new ways are utilized to make progress, one of which is with an electronic-based business, yet with a particularly number of varieties, vulnerability in business is likewise progressively hard to foresee. Particularly foreseeing in the following not many years what exercises will regularly happen. Forecast itself is an interaction of efficiently assessing something that is well on the way to occur later on dependent on at various times data. To stay aware of the advancement of the organization, it is important to enhance the measurements for the business. Similarity involves the process of characterizing each object or describing in detail the features of the object. A way to measure similarity by characterizing each object so as to produce a similarity in behavior. used the jaccard method in finding similarities.
Pengelompokan Pernyataan Misogini pada Media Sosial Berbahasa Indonesia Menggunakan TF-IDF dan Algoritma K-Means Umaya Ramadhani Putri Nasution; Ikhwanuddin Nasution; Lia Silviana; Fanindia Purnamasari; Marischa Elveny; Anandhini Medianty Nababan; Stephani Uli Basa Silitonga
Blend Sains Jurnal Teknik Vol. 5 No. 1 (2026): Edisi Juli
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/blendsains.v5i1.1776

Abstract

Penelitian ini bertujuan untuk mengidentifikasi pola tersembunyi pada komentar media sosial berbahasa Indonesia yang berkaitan dengan misogini menggunakan pendekatan clustering. Dataset yang digunakan terdiri atas komentar yang dikumpulkan dari beberapa platform media sosial. Tahapan penelitian meliputi preprocessing teks, ekstraksi fitur menggunakan metode Term Frequency–Inverse Document Frequency (TF-IDF), serta pengelompokan data menggunakan algoritma K-Means. Penentuan jumlah klaster optimal dilakukan melalui evaluasi menggunakan Silhouette Score, Davies-Bouldin Index, dan Calinski-Harabasz Index, yang menghasilkan jumlah klaster optimal sebanyak lima klaster. Hasil analisis top terms menunjukkan bahwa setiap klaster memiliki karakteristik semantik yang berbeda, meliputi objektifikasi seksual eksplisit, diskursus peran gender, benevolent sexism, interaksi relasional, dan objektifikasi fisik yang dinormalisasi. Hasil penelitian menunjukkan bahwa komentar yang berkaitan dengan misogini tidak bersifat homogen, tetapi membentuk beberapa kelompok berdasarkan pola bahasa dan konteks semantik yang berbeda. Temuan ini menunjukkan bahwa kombinasi representasi fitur berbasis TF-IDF dan algoritma K-Means mampu mengungkap struktur semantik laten pada komentar media sosial yang tidak dapat direpresentasikan secara memadai melalui kategorisasi biner misogini dan non-misogini.
Co-Authors Al Khowarizmi Anandhini Medianty Nababan Fanindia Purnamasari Lia Silviana Mahyuddin K. M Nasution Rahmad Syah Ramadhani, Umaya Stephani Uli Basa Silitonga