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All Journal International Journal of Electrical and Computer Engineering Tekno : Jurnal Teknologi Elektro dan Kejuruan JURNAL ECONOMIA CommIT (Communication & Information Technology) Jurnal Informatika dan Teknik Elektro Terapan Jurnal Informatika Upgris Journal of Information Technology and Computer Science JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Journal of Information System, Applied, Management, Accounting and Research Jurnal Mantik bit-Tech ILKOMNIKA: Journal of Computer Science and Applied Informatics CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Jifosi Nusantara Science and Technology Proceedings Jurnal Ilmiah Teknologi Informasi dan Robotika International Journal of Data Science, Engineering, and Analytics (IJDASEA) ALINIER: Journal of Artificial Intelligence & Applications Abdimas Altruis: Jurnal Pengabdian Kepada Masyarakat JUSIFOR : Jurnal Sistem Informasi dan Informatika JEECS (Journal of Electrical Engineering and Computer Sciences) Jurnal Inovatif Wira Wacana Inspiration: Jurnal Teknologi Informasi dan Komunikasi STATISTIKA Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Journal of Technology and System Information Informasi interaktif : jurnal informatika dan teknologi informasi Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK)
Andreas Nugroho Sihananto
Department Of Informatics, Universitas Pembangunan Nasional “Veteran” Jawa Timur, Surabaya 60294, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Social Sciences Other

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ANALISIS SENTIMEN PADA MEDIA SOSIAL X TERHADAP IMPLEMENTASI KURIKULUM MERDEKA MENGGUNAKAN METODE FASTTEXT DAN LONG SHORT-TERM MEMORY (LSTM) Pangestu, Arif Fajar; Rahmat, Basuki; Sihananto, Andreas Nugroho
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 4 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i4.5665

Abstract

Perubahan kurikulum adalah keharusan untuk mengikuti perkembangan zaman dan memastikan standar pendidikan terpenuhi. Namun, perubahan ini sering kali menyebabkan kebingungan di kalangan pendidik dan orang tua, yang mengganggu proses pendidikan. Kurikulum Merdeka, yang diperkenalkan sebagai inovasi penting dalam pendidikan Indonesia, menawarkan kerangka kerja yang lebih baik dan sesuai dengan kebutuhan. Meskipun demikian, dengan meningkatnya jumlah peserta didik, tantangan yang dihadapi oleh sistem pendidikan Indonesia juga bertambah. Penelitian ini bertujuan untuk menganalisis opini yang muncul di media sosial X tentang implementasi Kurikulum Merdeka, menggunakan metode word embedding FastText dan model klasifikasi Long Short-Term Memory. Dua dataset uji coba digunakan dalam penelitian ini, yang pertama berisi 7.500 entri dan yang kedua 3.000 entri. Penelitian ini juga menguji delapan skenario yang berbeda, dengan kombinasi metode ekstraksi fitur Continuous Bag of Words dan Skip-Gram, serta variasi pemisahan data 80:20 dan 85:15. Hasilnya menunjukkan tingkat akurasi yang tinggi di semua skenario, di atas 85%. Temuan ini mengungkap dominasi sentimen negatif dalam setiap kategori yang diamati selama implementasi Kurikulum Merdeka, menunjukkan adanya beberapa tantangan atau hambatan dalam penerimaan dan penerapan kurikulum tersebut di berbagai lingkungan pendidikan
Implementation of Least Square Algorithm to Predict Monthly Revenue (Case Study: Djuju’s Grocery Store) Aditya Rizqi Ardhana; Chrystia Aji Putra; Andreas Nugroho Sihananto
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 8 No. 1 (2023): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v8i1.3

Abstract

Business owners need to estimate their revenue, which is crucial for the sustainability of their operations. Thus, entrepreneurs such as micro, small, and medium-sized business owners, as well as owners of grocery stores, leverage technological advancements to maximize their sales operations. However, manual sales activities can pose challenges for managing sales data, such as disorganized sales record keeping, failure to record sales of high-volume customers, and time-consuming manual reporting for revenue predictions. To address these issues, researchers have developed a revenue prediction information system. In this study, revenue and profit predictions for the following period were calculated using the Least Square algorithm with the Mean Absolute Percentage Error (MAPE). An example calculation for a 12-month period resulted in a revenue forecast of Rp. 2,837,687.76 for the month of June 2023 with a MAPE of 12.71%.
History Learning Game of the Three-Day Battle Surabaya with Branching Narrative Rantau Himawan; Chrystia Aji Putra; Andreas Nugroho Sihananto
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3346

Abstract

This study presents the development of an educational history game about the Three-Day Battle in Surabaya, designed using a branching narrative approach to enhance students’ engagement and historical understanding. Traditional history learning in Indonesia often relies on memorization and lacks interactive media, leading to low student motivation. To address this issue, the game integrates a decision-based narrative structure that allows players to explore consequences, experience alternative paths, and engage with historical events through meaningful choices. The game was developed using the Unity Engine with iterative refinement involving playtesting and feedback-based adjustments to dialogue flow, minigame mechanics, and visual presentation. The evaluation involved 15 participants and employed the GUESS-18 instrument. The results indicate strong user reception, with high scores in Narrative Understanding and Game Engagement, while Playability and Aesthetics received moderate ratings, highlighting areas for visual and interaction improvements. Despite the short testing duration, the game demonstrated potential to support historical learning by increasing immersion and reinforcing students’ understanding of key events and cause–effect relationships during the Surabaya conflict. This study contributes to the field of educational game development by demonstrating the pedagogical value of branching narratives and providing a practical model that can be adapted to other historical topics in future research.
A Branching Narrative 2D Action RPG Game to Enhance Learning About the Ambarawa Battle Laudy Nurdibya Nandaru; Chrystia Aji Putra; Andreas Nugroho Sihananto
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3420

Abstract

This study develops a historical educational game titled Pertempuran Ambarawa to address the persistent challenge of low student engagement and limited contextual understanding in history classrooms, where learning is often dominated by memorization-based instruction. To provide a more interactive and reflective learning experience, the game integrates a branching narrative structure, 2D action RPG mechanics, and stealth–strategy minigames within the Interactive Digital Narrative (IDN) framework. This approach is intended to enhance learners’ historical reasoning by situating them in decision-based scenarios that mirror the complexities of the Ambarawa Battle. The game was implemented in Unity with 2D pixel-art aesthetics and evaluated through a pre-test–post-test design involving 25 junior high school students. Results show a significant improvement in historical comprehension, with mean scores increasing from 59.2 to 79.2 and the Wilcoxon Signed-Rank test yielding p = 0.00077 (p < 0.05). User experience was assessed using the GUESS-18 instrument, achieving an overall rating of 4.29 (Very Good), with the Education and Branching Narrative dimensions receiving the highest scores. These findings indicate that narrative interactivity and contextualized gameplay meaningfully contribute to learning effectiveness. Overall, the study demonstrates that combining branching narratives with RPG-based exploration provides a compelling alternative learning medium, offering both pedagogical value and strong user acceptance in history education.
Hyperparameter Optimization of Hybrid LSTM-GRU using Genetic Algorithm for Stock Price Prediction Mordekhai Gerin Lumangkun; Made Hanindia Prami Swari; Andreas Nugroho Sihananto
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3656

Abstract

Predicting stock prices in the banking sector, particularly for high-capitalisation stocks such as Bank Rakyat Indonesia (BBRI), remains challenging amid market volatility. While Hybrid LSTM-GRU models have demonstrated capability in capturing temporal dependencies in time-series data, prior studies have predominantly focused on manual tuning or optimization of single recurrent architectures, with limited application of Genetic Algorithms for optimizing hybrid recurrent networks in emerging stock markets (R1). This research aims to address this gap by implementing an evolutionary optimization framework using a Genetic Algorithm (GA) to automatically tune the hyperparameters of a Hybrid LSTM-GRU model for enhanced stock price forecasting accuracy. Historical BBRI data from November 2020 to June 2025 were preprocessed through normalization and transformed into supervised time-series sequences before being divided into training, validation, and testing sets. The GA was configured with a population size of 20, 80 generations, and a crossover rate of 0.8 to search for optimal learning rates, batch sizes, and hidden units. The optimized configuration identified 64 units for LSTM and GRU layers, a learning rate of 0.002, and a batch size of 16. The resulting model achieved an RMSE of 82.11 and an MAPE of 1.51%, representing a 20% error reduction compared to baseline hybrid models and outperforming benchmark approaches reported in prior studies (R1). Achieving a 1.51% MAPE indicates reliability for financial forecasting, supporting risk-sensitive investment decision-making (A). Overall, this study demonstrates that evolutionary hyperparameter optimization enhances hybrid deep learning architectures.
Optimization of Sauvola Thresholding Parameters for Braille Dot Detection: A Comparative Study with Niblack Method Prihantono, Silvanus; Anggraeny, Fetty Tri; Sihananto, Andreas Nugroho
ILKOMNIKA Vol 8 No 2 (2026): Volume 8, Number 2, August 2026
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/ilkomnika.v8i2.887

Abstract

Braille is a tactile writing system used to assist individuals with visual impairments. While Braille paper is a common medium, it is highly vulnerable to physical degradation, making automated optical recognition challenging. Despite effectiveness of local thresholding for degraded documents, grid search parameter analysis and configurations for Braille dot detection remain largely unexplored, leading to suboptimal detection performance. This study aims to systematically grid search Sauvola parameter analysis binarization parameters for Braille dot detection prior to Circle Hough Transform, encompassing a comparative evaluation against Niblack and Otsu baseline methods. To eliminate evaluation bias, dataset of 38 manually annotated 640x640 pixel images was strictly partitioned into a 10-image tuning set and a 28-image test set. Parameter grid search identified an optimal spatial boundary at window size=13. Mathematically aligning with maximum topographical footprint of a Braille cell and sensitivity parameter of k=0.050. In isolated test set, Sauvola achieved a superior Mean F1-Score of 0.7916, significantly outperforming Niblack of 0.7088, global Otsu thresholding of 0.4513, and CHT-only baseline of 0.7392. Our results suggest that normalization factor may contribute to observed performance differences. However, its individual effect was not isolated in present experiments.
Optimasi Data Sensor Partikulat Low-Cost Menggunakan Hybrid Filtering pada Sistem Monitoring Udara Berbasis IoT MOHAMMAD HAFIZ AR RAFI; Agussalim Agussalim; Andreas Nugroho Sihananto
Jurnal Inovatif Vol. 5 No. Special (2026): Volume 05 Edisi Khusus Agustus 2026
Publisher : Universitas Kristen Wira Wacana Sumba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58300/dn3dw695

Abstract

Sensor partikulat low-cost banyak digunakan pada sistem monitoring udara berbasis Internet of Things (IoT), namun pembacaan data yang dilakukan sensor tersebut sering dipengaruhi oleh noise, fluktuasi sinyal, dan lonjakan nilai sesaat (spike). Penelitian ini bertujuan meningkatkan kualitas data sensor partikulat melalui penerapan hybrid filtering yang mengombinasikan Median Filter dan Exponential Moving Average (EMA). Sistem monitoring dikembangkan menggunakan sensor GP2Y1010AU0F, ESP32, DHT22, Firebase Realtime Database, dan dashboard pada platform Blynk. Sebanyak 4.019 data pengamatan dikumpulkan dan diproses menggunakan Median Filter dan EMA. Evaluasi dilakukan menggunakan parameter statistik berupa standard deviation (SD), variance (V), coefficient of variation (CV), dan interquartile range (IQR). Hasil penelitian menunjukkan bahwa penerapan hybrid filtering mampu menurunkan SD sebesar 52,85%, variance sebesar 77,77%, CV sebesar 46,66%, dan IQR sebesar 29,58%, sehingga meningkatkan stabilitas serta mengurangi variabilitas sinyal sensor. Kombinasi Median Filter dan EMA efektif mereduksi pengaruh noise dan spike tanpa menghilangkan tren utama data. Dengan demikian, pendekatan yang diusulkan dapat meningkatkan reliabilitas sistem monitoring udara berbasis IoT yang menggunakan sensor partikulat low-cost.
Analisis Sentimen Pada Pembatalan Tuan Rumah Indonesia Di Piala Dunia U-20 Menggunakan Fasttext Embeddings Dan Algoritma Recurrent Neural Network Aan Evian Nanda; Andreas Nugroho Sihananto; Agung Mustika Rizki
SABER : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Vol. 2 No. 2 (2024): April : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi
Publisher : STIKes Ibnu Sina Ajibarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59841/saber.v2i2.1000

Abstract

Indonesia's golden opportunity to take part in a world-class soccer competition at the U-20 World Cup competition was wiped out, as FIFA gave the decision to revoke Indonesia's status as host of the U-20 World Cup. Indonesian netizens who felt disappointed expressed their opinions and trended on social media Twitter. This research focuses on sentiment analysis of tweets using a combination of FastText embeddings method for word vectorization and using LSTM type RNN algorithm for sentiment classification. The dataset used totals 9,645 data consisting of 4,141 positive data and 5,504 negative data taken from March 29, 2023 to April 05, 2023. The test results on the LSTM model provide the best performance with an accuracy value of 74.92%, precision 74.74%, recall 74.92%, and f1-score 74.78%. The conclusion of this research is that the majority of datasets have negative sentiments, which means that people are more likely to give negative opinions than to provide support to Indonesian football which is experiencing problems. It is hoped that with this conclusion in the future people will better control their opinions and provide positive opinions when Indonesia is experiencing problems.
Co-Authors Aan Evian Nanda Abdul Rezha Efrat Najaf Abdurrahman, Nizar Achmad Junaidi Aditya Primayudha Aditya Rizqi Ardhana Afifudin, Muhammad Afriani, Regita Agung Mustika Rizki, Agung Mustika Agussalim Agussalim Agussalim, Agussalim Agussalim, Agussalim Alif Wisam Desanta Fitrianto Alifah, Nurul Aini Amalia, Nadhia Rizqy Amri Muhaimin Anggraini PS Anggraini Puspita Sari Ani Dijah Rahajoe Ar Romandhon, Mitzaqon Gholizhan Ardiansyah, Muhammad Dafa Arif Widiasan Subagio Basuki Rahmat Masdi Siduppa Bisma Putra Sulung Christianty, Theressa Marry Dwi Arman Prasetya Edi Sugiyanto Edi Sugiyanto Fakhruddin, Fikri Farkhan Fauzi, Zaky Ahmad Fetty Tri Anggraeny Gusti Ahmad Fanshuri Alfarisy, Gusti Ahmad Fanshuri Henni Endah Wahanani Izzatul Fithriyah Kartini Kartini Kartini Laudy Nurdibya Nandaru Lesmana, Benedictus Rafael M Shochibul Burhan, M Shochibul M. Arif Mardhavi M. Shochibul Burhan Made Hanindia Prami Swari Mardhavi, Arif Marselina, Anif Fitria Dewi Maulana Fauzan Maulana, Hendra Maulana, Yoga MOHAMMAD HAFIZ AR RAFI Mohammad, Farrel Adel Mordekhai Gerin Lumangkun Muhammad Afifudin Muhammad Dafa Ardiansyah Muhammad Muharrom Al Haromainy Naila, Amelia Maslaqun Nurhaliza, Risma Nurlaili, Afina Lina Octaviani, Vincentia Indri Pangestu, Arif Fajar Parlika, Rizky Pradana, Ilham Akbar Prami, Made Hanindia Prihantono, Silvanus Putra, Chrystia Aji Putra, Gredy Christian Hendrawan Putra, Raditya Lungguk Satya Ramadhan, Dimas Dharu Rantau Himawan Rasjid, Azka Avicenna Ratna Yulistiani Retno Mumpuni Reza, Reno Alfa Rizki, Agung Mustika Safitri, Erista Maya Safitri, Eristya Maya Santosa, Mochammad Kevin Saputra, Dewa Raka Krisna Saputri, Asih Sebrina, Aida Fitriya Shahab, Muhammad Syaugi Suryandari, Sabrina Heryanti Taufiqurrahman, Rahmadany Fahreza Tirana Noor Fatyanosa, Tirana Noor Trianingsih, Arini Trimono, Trimono Wayan Firdaus Mahmudy Wiwik Handayani Yisti Vita Via Yudistira, Mochammad Ervinda Yulianto, Rusman