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Comparative Deep Learning Models for Indonesian Gold Price Forecasting
Putra, Albi Pernata Jomantara
; Williamsyah, Baginda Mi’raj
; Rizal, Achmad
; Dewanta, Favian
; Prasasti, Anggunmeka Luhur
; Ziani, Said
This study evaluates LSTM, CNN-LSTM, LSTM-GRU, and CNN-LSTM-GRU architectures for forecasting Indonesian gold prices using 1,269 daily observations (2022–2025). Models utilized Bayesian-optimized hyperparameters and were benchmarked against ARIMA-GARCH and Random Forest baselines across 30-day and 365-day horizons. Performance was assessed via MAE, RMSE, R², and MAPE, confirming deep learning’s superiority in capturing non-linear dynamics over classical methods. The LSTM-GRU achieved the best nu...
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Corrosion Inhibition of Mild Steel by Ethanolic Terminalia microcarpa Decne Leaf Extracts in 3.5% NaCl Solution: A Gravimetric and Surface Analysis Studies
Mild steel is widely used but vulnerable to corrosion, with conventional inhibitors posing toxicity risks. This study evaluated the leaf extracts of Terminalia microcarpa Decne, also locally known as kalumpit, as a green corrosion inhibitor for mild steel in a 3.5% NaCl solution. The prepared extracts, characterized by FTIR, were found to contain phytochemicals with inhibition potential. Weight loss measurements showed that inhibition efficiency was concentration-dependent, but was not influence...
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Digital Lean-Process Framework for Creative-Industry Efficiency (Case: Sipirok, Indonesia)
This study develops a community empowerment model for the creative economy by integrating local wisdom, education, institutional support, and technology while applying Value Stream Mapping (VSM) to reduce process inefficiencies affecting sustainable tourism. The research introduces Lean-based process optimization using engineering metrics such as cycle time, uptime, and defect ratio. Results indicate that Lean interventions reduced cycle time by 25.3%, increased uptime by 6.8%, and decreased wai...
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Comparative Evaluation of Automatic Labeling and Modeling Strategies for Indonesian Sentiment Analysis: Methodology and Performance Evaluation
Latifa, Khoiriya
; Agung Handayanto
; Nur Latifah Dwi M.S
; Rahul Bhandari
; Ton Nguyen Trong Hien
; Doston Pirnazarov
Sentiment analysis is vital for understanding consumer perception, yet Indonesian sentiment classification faces challenges due to labeled data scarcity and computational constraints. This study advances automatic labeling techniques and establishes performance benchmarks for Indonesian text. The research compares two labeling approaches InSet Lexicon and IndoBERT based Hugging Face pipeline on 8,447 Tapera-related opinions. Results show InSet Lexicon produced a highly skewed distribution (89.66...
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Implementation of Project-Based Learning (PjBL) Assisted by Geogebra Application to Improve Students’ Spatial Abilities
The purpose of this study was to determine whether the implementation of the Geogebra-assisted Project Based Learning (PjBL) model has an impact on improving students' spatial abilities or not. Quantitative method with experiments was used in this study. The sample used was class B and C students of Mathematics Education IAIN Kudus class of 2022/2023 who were selected through cluster random sampling techniques. To determine the level of effectiveness, pretest and posttest instruments were given...
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The Development of Student Worksheets (LKPD) Based on Higher Order Thinking Skill (HOTS) with Nuance of Numeracy Literacy in Mathematics Subjects for Elementary School Class V Students
This study is motivated by the low level of students’ numeracy literacy skills and the suboptimal use of instructional materials that facilitate higher-order thinking skills in elementary mathematics learning. Teacher-centered learning practices tend to limit students’ active participation and hinder their ability to solve contextual problems. This study aims to develop a Student Worksheet (LKPD) based on Higher Order Thinking Skills (HOTS) with a numeracy literacy orientation on p...
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Problem-Solving Ability In Arithmetic Sequences And Series Using Problem-Based Learning
This study aims to describe the learning process on the topic of sequences and series using the Problem-Based Learning (PBL) approach, and to describe students' mathematical problem-solving abilities on the topic of arithmetic sequences and series using the Problem-Based Learning (PBL) approach. The study was conducted at SMA Negeri 1 Adonara Tengah in February 2026. The subjects of this study were 16 students in Grade XI. The data collection techniques used were learning process, written tests,...
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Design and Implementation of a Web-Based QR Code Employee Attendance System for Optimizing Attendance Management: A Case Study at Bento and Es Teh Luwes Ungaran
Nufninu, Novinda Grezen
; Rudjiono, Rudjiono
; Panjaitan, Cherlina Helena Purnamasari
; Nufninu, Novinda Grezen
; Rudjiono, Rudjiono
; Panjaitan, Cherlina Helena Purnamasari
Penelitian ini dilatarbelakangi oleh proses absensi karyawan pada Stand Bento dan Stand Es Teh Luwes Ungaran yang masih dilakukan secara manual menggunakan buku absensi. Kondisi tersebut menimbulkan beberapa kendala, seperti kesalahan pencatatan jam masuk dan pulang, risiko kehilangan atau kerusakan data, serta lambatnya proses rekapitulasi laporan kehadiran. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem absensi karyawan berbasis web menggunakan teknologi QR Code guna m...
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Deteksi Aktivitas Vape Berbasis Yolov8 pada Citra dan Video dengan Pendekatan Deep Learning
Lahuddin, Lahuddin
; Larasati, Pamela
; Hasbi, Abdilah
; Lahuddin, Lahuddin
; Larasati, Pamela
; Hasbi, Abdilah
Perkembangan teknologi artificial intelligence, khususnya dalam bidang computer vision dan deep learning, telah mendorong lahirnya berbagai sistem otomatis dalam analisis citra dan video. Salah satu implementasi yang banyak digunakan adalah deteksi objek secara real-time menggunakan algoritma YOLO (You Only Look Once). Di sisi lain, penggunaan rokok elektronik atau vape semakin meningkat, terutama di lingkungan pendidikan, sehingga diperlukan sistem pengawasan otomatis yang mampu mendeteksi akti...
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Grouping of Student Attendance Discipline Levels Based on Daily Attendance Data Using the K-Means Algorithm
Putri, Syahwa Mutiara
; Rahmawati, Anita
; Bella, Alfina Chintya
; Gurowo, Damar Aji
; Arifin, Muhammad
; Putri, Syahwa Mutiara
; Rahmawati, Anita
; Bella, Alfina Chintya
; Gurowo, Damar Aji
; Arifin, Muhammad
Kedisiplinan kehadiran siswa merupakan aspek penting dalam proses pembelajaran karena mencerminkan partisipasi, tanggung jawab, dan kepatuhan terhadap aturan sekolah. Namun, data absensi sering kali hanya diperlakukan sebagai catatan administratif dan jarang dianalisis untuk mengidentifikasi pola keterlambatan yang berulang. Penelitian ini bertujuan untuk mengelompokkan pola keterlambatan siswa berdasarkan data absensi harian menggunakan algoritma K-Means guna memberikan gambaran yang lebih ters...
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