Article Per Year (5 Year)
p-Index From 2021 - 2026
1.037
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) SAINTEK
Zaenur Rozikin
Unknown Affiliation
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
Klasifikasi Kondisi Pasar Harga Emas ANTAM Indonesia Menggunakan Algoritma Decision Tree Kamalia, Antika Zahrotul; Choiriyatun Nisa Latansa; Zaenur Rozikin
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 4 No. 3 (2026): Februari 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i3.800

Abstract

This study aims to classify Indonesian ANTAM gold market states using a Decision Tree model built on daily price data from 2010–2024. Market conditions are categorized into three classes: bullish, bearish, and sideways, based on forward returns with an adaptive quantile-based thresholding scheme. The feature set comprises multi-horizon rolling volatility indicators (e.g., std_5, std_10, std_20) and momentum measures (e.g., mom_5, mom_10, mom_20). A time-based split is applied, allocating 80% of observations for training and 20% for testing. Evaluation on the test set yields an accuracy of 0.337 with a macro-F1 of approximately 0.34, indicating limited predictive performance in a three-class setting. Interpretability analysis reveals that std_20 is the most influential feature, followed by std_10 and mom_5, while one-day returns contribute marginally. These findings suggest that aggregated volatility and momentum patterns are more informative than single-day fluctuations for market regime mapping. Overall, the Decision Tree is best positioned as an interpretable baseline for transparent market-state analysis, providing a foundation for future work involving richer features and more robust models.
Pengembangan Sistem Informasi Laporan Produksi Berbasis Web Menggunakan Metode Rapid Application Development (RAD) Pada PT. Nichias Metalwork Indonesia Zaenur Rozikin; Edi Hotman Sijabat
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In general, production management consists of several functions in which management experts give their respective opinions. From the problems that exist in PT. Nichias Metalwork Indonesia in production, the process of inputting production report data still uses sheets of paper which are done manually and then collected at the supervisor's desk, and hinders the process of inputting data by the admin, because the admin has to take the report sheets that are on the supervisor's desk. The method used in this study is the Rapid Application Development (RAD) method. The Rapid Application Development method is a software development method that emphasizes development in a short time and uses iterative (repetitive) methods where the working model is constructed at the early stages of development to determine user requirements. In making the production report system the author uses the PHP Programming Language and MySQL database. The purpose of this study is to design and build a production reporting information system to make it easier to check and input goods to minimize the difference in production inventory and speed up the process of inputting and reporting production at PT. Nichias Metalwork Indonesia
Penggunaan Naïve Bayes Dalam Implementasi Prediksi Tingkat Curah Hujan Zaenur Rozikin; Irma Nurmaulida
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Precipitation forecasting has been one of the most challenging scientific and technological problems worldwide in the last century. Rain is an event where water drops fall from the sky to the surface of the earth. Rain is also the water cycle on planet earth. Another definition of rain is an event of precipitation (the fall of liquid originating from the atmosphere that is liquid or frozen to the earth's surface) in the form of liquid. Rain requires the presence of a thick layer of the atmosphere in order to meet temperatures above the melting point of ice near and above the surface of the Earth. Throughout the year, rainfall has an erratic pattern making it difficult to predict manually. The amount of rainfall that is large enough cannot be determined with certainty, but this can be estimated. Thus, data mining allows machines to recognize and study complex data patterns. Therefore machine learning can study patterns of rainfall data to make predictions, so a rainfall prediction study was carried out using the Naïve Bayes method and the data used in this study is data taken from the official BMKG Indonesia website which can be accessed by all groups, both among children, adolescents, adults and even parents.
Sistem Pendukung Keputusan Status Gizi Balita Menggunakan Metode Simple Additive Weighting Berbasis Web (Studi Kasus: Posyandu Gandasari 16) Zaenur Rozikin; Sinta Ayu Lestari
Jurnal SIGMA Vol 14 No 4 (2023): Desember 2023
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/sigma.v14i4.7320

Abstract

Gizi buruk pada balita dapat menyebabkan gangguan kekebalan tubuh, peningkatan risiko infeksi, serta keterlambatan kognitif dan psikomotor sehingga diperlukan pemantauan pertumbuhan secara berkala. Di Posyandu Gandasari 16, penentuan status gizi masih dilakukan secara manual dan bergantung pada tenaga medis, sehingga dibutuhkan sistem pendukung keputusan untuk meningkatkan akurasi dan efisiensi penilaian. Penelitian ini bertujuan membangun sistem pendukung keputusan berbasis web menggunakan metode Simple Additive Weighting (SAW) untuk menentukan status gizi balita berdasarkan data antropometri seperti berat badan, tinggi badan, lingkar lengan, dan lingkar perut. Sistem dikembangkan menggunakan PHP dan MySQL dengan perancangan UML serta metode Rapid Application Development (RAD). Hasil penelitian menunjukkan bahwa sistem mampu memberikan keputusan status gizi yang lebih spesifik dan akurat, dengan nilai persentase tertinggi 99,41% pada balita usia 3 tahun 8 bulan. Sistem ini diharapkan dapat membantu kader posyandu dalam proses pengambilan keputusan dan dapat dikembangkan lebih lanjut dengan metode lain serta cakupan wilayah yang lebih luas.
Pengembangan Chatbot Untuk Deteksi Tingkat Stres Menggunakan NLP Berdasarkan Perceived Stress Scale (PSS) Dengan Metode TF-IDF Dan Cosine Similarity Zaenur Rozikin; Ravansa Rahman Santosa
Jurnal SIGMA Vol 16 No 2 (2025): September 2025
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/sigma.v16i2.7329

Abstract

Stres merupakan masalah kesehatan mental yang umum terjadi pada remaja dan dewasa muda sehingga deteksi dini sangat diperlukan untuk mendukung langkah pencegahan yang tepat. Penelitian ini bertujuan mengembangkan chatbot berbasis web untuk mendeteksi tingkat stres menggunakan Perceived Stress Scale versi 10 item (PSS-10) dalam Bahasa Indonesia. Sistem dibangun dengan pendekatan Natural Language Processing (NLP) menggunakan metode TF-IDF dan Cosine Similarity untuk mengklasifikasikan respons pengguna ke dalam kategori skor tertentu. Pengembangan dilakukan menggunakan framework Flask dengan integrasi database MySQL untuk menyimpan data interaksi. Dataset disusun dari berbagai variasi sinonim jawaban agar sistem mampu memahami bahasa alami secara lebih akurat. Pengujian dilakukan melalui black-box testing untuk memastikan fungsionalitas sistem serta uji akurasi skor dengan membandingkan hasil klasifikasi chatbot terhadap data acuan. Hasil menunjukkan seluruh fitur berjalan dengan baik dan sistem mampu memberikan klasifikasi skor yang akurat dengan tingkat akurasi 100% pada data uji. Penelitian ini membuktikan bahwa pendekatan NLP sederhana berbasis aturan tetap efektif untuk mendukung asesmen mandiri, serta menunjukkan bahwa chatbot “Tenangin” berpotensi menjadi solusi digital yang praktis dan mudah diakses untuk skrining awal tingkat stres.
Co-Authors Antika Zahrotul Kamalia Choiriyatun Nisa Latansa Edi Hotman Sijabat Irma Nurmaulida Ravansa Rahman Santosa Sinta Ayu Lestari