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Journal Of Computer Science And Technology
Published by PT. Padang Tekno Corp
ISSN : 29855772     EISSN : 29854318     DOI : https://doi.org/10.59435/jocstec
Core Subject : Science,
Computer Science & IT
Journal of Computer Science And Technology (JOCSTEC) is a scientific journal that publishes research results and thoughts in the field of computers and information technology. JOCSTEC focuses on publishing research results that contribute to understanding theory and applications in the field of computers and information technology, including computer systems, computer networks, data processing, information security, and other information technologies.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 73 Documents
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Penerapan Data Mining Dalam Estimasi Harga Emas Menggunakan Algoritma Trend Moment Pada PT Victoeria Vici Erika Fahmi Ginting; Husna Gemasih; Suci Andriyani; Mutiara S. Simanjuntak; Chindi Dwi Lestari Nainggolan
Journal of Computer Science and Technology (JOCSTEC) Vol 4 No 2 (2026): JOCSTEC - Mei
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jocstec.v4i2.754

Abstract

Emas merupakan salah satu jenis komoditi yang paling banyak diminati untuk tujuan investasi, karena dipandang sebagai instrumen yang lebih aman dibandingkan saham serta memiliki nilai jual yang selalu bergerak mengikuti kondisi pasar. PT Victoeria Vici, sebagai pelaku usaha perhiasan emas custom, menghadapi kendala dalam menentukan estimasi harga jual kepada pelanggan, sebab proses pengerjaan pesanan custom membutuhkan waktu hingga 14 hari, sementara harga emas bergerak fluktuatif dan tidak terstruktur setiap harinya sehingga estimasi harga menjadi tidak akurat dan tidak efektif. Berdasarkan permasalahan tersebut, penelitian ini menerapkan konsep Data Mining dengan algoritma Trend Moment untuk mengestimasi harga emas pada rentang waktu tertentu. Data yang digunakan merupakan data historis harga emas per gram pada PT Victoeria Vici periode Agustus–Oktober 2021 sebanyak 92 data. Tahapan penelitian meliputi pengumpulan data, penentuan variabel X dan Y, eliminasi untuk memperoleh nilai konstanta a dan slope b, serta penerapan persamaan Y = a + bX untuk memperoleh nilai estimasi. Hasil perhitungan menunjukkan nilai a = 720.871,725 dan b = 3,108 sehingga model estimasi mampu menghasilkan proyeksi harga emas yang mendekati pola data historis. Model ini kemudian diimplementasikan ke dalam aplikasi berbasis desktop menggunakan Microsoft Visual Basic 2010 dan basis data Microsoft Access, dilengkapi Crystal Report untuk pencetakan laporan hasil estimasi. Hasil penelitian menunjukkan bahwa algoritma Trend Moment dapat membantu PT Victoeria Vici dalam memperoleh estimasi harga emas secara lebih cepat, konsisten, dan terdokumentasi. Gold is one of the most sought-after commodities for investment purposes, as it is regarded as a safer instrument compared to stocks and has a selling value that constantly fluctuates with market conditions. PT Victoeria Vici, a custom gold jewelry business, faces difficulty in determining the estimated selling price offered to customers because the production process for custom orders takes up to 14 days, while gold prices move in an unstructured and fluctuating manner every day, making manual price estimation inaccurate and ineffective. Based on this problem, this study applies the concept of Data Mining using the Trend Moment algorithm to estimate gold prices over a certain period of time. The data used is historical daily gold price data per gram from PT Victoeria Vici for the period of August–October 2021, consisting of 92 records. The research stages include data collection, determination of the X and Y variables, elimination to obtain the constant value a and the slope b, and the application of the equation Y = a + bX to obtain the estimated value. The calculation results show a value of a = 720,871.725 and b = 3.108, so that the estimation model is able to produce gold price projections that closely follow the pattern of historical data. This model was then implemented into a desktop-based application using Microsoft Visual Basic 2010 and a Microsoft Access database, equipped with Crystal Report for printing estimation result reports. The results show that the Trend Moment algorithm can help PT Victoeria Vici obtain gold price estimations more quickly, consistently, and in a well-documented manner.
Peningkatan Akurasi Klasifikasi Sentimen Pengguna Dompet Digital Menggunakan Stacking Ensemble Machine Learning Ilmawati; Nadya Alinda Rahmi; Elvira Sawitri
Journal of Computer Science and Technology (JOCSTEC) Vol 4 No 2 (2026): JOCSTEC - Mei
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jocstec.v4i2.759

Abstract

Penggunaan dompet digital yang terus meningkat menghasilkan banyak ulasan pengguna yang dapat dimanfaatkan untuk mengevaluasi kualitas layanan. Penelitian ini bertujuan meningkatkan akurasi klasifikasi sentimen pengguna dompet digital menggunakan metode Stacking Ensemble Machine Learning yang mengombinasikan Support Vector Machine (SVM), Multinomial Naïve Bayes (MNB), dan AdaBoost dengan Logistic Regression sebagai meta-learner. Data ulasan diproses melalui tahapan text preprocessing meliputi case folding, cleaning, tokenizing, stopword removal, stemming, dan pembobotan fitur menggunakan TF-IDF. Penyeimbangan data dilakukan dengan SMOTE, sedangkan evaluasi model menggunakan 5-Fold Cross-Validation. Hasil penelitian menunjukkan bahwa model Stacking Ensemble memperoleh akurasi rata-rata 80,55%, lebih tinggi dibandingkan algoritma dasar. Evaluasi menggunakan Confusion Matrix, Classification Report, dan ROC Curve juga menunjukkan peningkatan nilai precision, recall, F1-score, dan kemampuan diskriminasi model. Hasil ini menunjukkan bahwa pendekatan Stacking Ensemble Machine Learning efektif untuk meningkatkan akurasi klasifikasi sentimen pengguna dompet digital serta mendukung evaluasi kualitas layanan berbasis opini pengguna. The rapid growth of digital wallet usage has generated a large volume of user reviews that can be utilized to evaluate service quality. This study aims to improve the accuracy of digital wallet user sentiment classification using a Stacking Ensemble Machine Learning approach that combines Support Vector Machine (SVM), Multinomial Naïve Bayes (MNB), and AdaBoost with Logistic Regression as the meta-learner. User reviews were processed through text preprocessing stages, including case folding, text cleaning, tokenization, stopword removal, stemming, and TF-IDF feature weighting. Synthetic Minority Over-sampling Technique (SMOTE) was employed to address class imbalance, while model performance was evaluated using 5-Fold Cross-Validation. The experimental results show that the proposed Stacking Ensemble model achieved an average accuracy of 80.55%, outperforming the individual base learners. Furthermore, evaluations based on the Confusion Matrix, Classification Report, and Receiver Operating Characteristic (ROC) Curve demonstrated improvements in precision, recall, F1-score, and the model's discriminative capability. These findings indicate that the proposed Stacking Ensemble Machine Learning approach is effective in improving the accuracy of digital wallet user sentiment classification and can serve as a reliable tool for supporting service quality evaluation based on user opinions.
Penerapan Metode MOORA Pada Sistem Pendukung Keputusan Pemilihan Ketua Badan Eksekutif Mahasiswa Lidya Rizki Ananda; Julianto Simatupang; Rio Bayu Sentosa; Nadia Astri Wulandari; Tika Christy
Journal of Computer Science and Technology (JOCSTEC) Vol 4 No 2 (2026): JOCSTEC - Mei
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jocstec.v4i2.761

Abstract

Pemilihan Ketua Badan Eksekutif Mahasiswa (BEM) merupakan proses penting dalam menentukan mahasiswa yang memiliki kompetensi terbaik untuk memimpin organisasi kemahasiswaan. Namun, proses seleksi yang masih bergantung pada popularitas dan penilaian subjektif berpotensi menghasilkan keputusan yang kurang optimal. Penelitian ini bertujuan membangun Sistem Pendukung Keputusan (SPK) menggunakan metode Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) untuk membantu proses pemilihan Ketua BEM secara objektif. Data penelitian diperoleh melalui wawancara dengan pembina BEM untuk menentukan kriteria dan bobot penilaian. Lima kriteria yang digunakan meliputi kepemimpinan, kemampuan komunikasi, pengalaman organisasi, integritas, dan indeks prestasi kumulatif (IPK). Tahapan metode MOORA terdiri atas penyusunan matriks keputusan, normalisasi, perhitungan nilai optimasi, dan proses perangkingan. Hasil penelitian menunjukkan bahwa alternatif K1 memperoleh nilai optimasi tertinggi sebesar 0,473 sehingga direkomendasikan sebagai Ketua BEM terpilih. Penerapan metode MOORA mampu menghasilkan proses pengambilan keputusan yang lebih objektif, sistematis, transparan, dan akurat sehingga dapat dijadikan sebagai alat bantu dalam menentukan Ketua BEM berdasarkan kriteria yang telah ditetapkan. The selection of the Student Executive Board (BEM) President is an important process in determining the most qualified student to lead the student organization. However, conventional selection processes often rely on popularity and subjective judgments, which may lead to less optimal decisions. This study aims to develop a Decision Support System (DSS) using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to support a more objective selection process. Research data were collected through interviews with BEM advisors to determine the assessment criteria and their corresponding weights. Five criteria were used, namely leadership, communication skills, organizational experience, integrity, and grade point average (GPA). The MOORA method consists of decision matrix construction, normalization, optimization value calculation, and ranking. The results indicate that candidate K1 achieved the highest optimization value of 0.473 and was therefore recommended as the selected BEM President. The implementation of the MOORA method provides a more objective, systematic, transparent, and accurate decision-making process, making it an effective tool for supporting the selection of the most suitable BEM President based on predetermined criteria.

Page 8 of 8 | Total Record : 73

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