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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Teknika Jupiter Techno.Com: Jurnal Teknologi Informasi SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal CoreIT Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Nasional Komputasi dan Teknologi Informasi IJISTECH (International Journal Of Information System & Technology) JURIKOM (Jurnal Riset Komputer) Informatika : Jurnal Informatika, Manajemen dan Komputer JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) EDUMATIC: Jurnal Pendidikan Informatika Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Zonasi: Jurnal Sistem Informasi Jurnal Informatika Ekonomi Bisnis JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) JUKI : Jurnal Komputer dan Informatika Jurnal Ilmu Komputer IJISTECH Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Pendidikan dan Teknologi Indonesia Jurnal Informatika Terpadu Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Bulletin of Information Technology (BIT) Jurnal Informatika Ekonomi Bisnis SATIN - Sains dan Teknologi Informasi
Muhammad Affandes
Universitas Islam Negeri Sultan Syarif Kasim Riau
Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering 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 Library & Information Science Mathematics Neuroscience Social Sciences Transportation Other

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Implementasi Model Long Short Term Memory (LSTM) dalam Prediksi Harga Saham Kurniansyah, Juliandi; Siska Kurnia Gusti; Febi Yanto; Muhammad Affandes
Bulletin of Information Technology (BIT) Vol 6 No 2: Juni 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i2.2005

Abstract

Stock market investment is gaining popularity, although predicting stock price fluctuations remains challenging. Accurate stock prediction models can assist investors in decision-making. In this research, a Long Short-Term Memory (LSTM) model was employed to make predictions regarding the stock prices of BBCA based on daily historical data from January 1 2015 to January 1 2025. The data was gathered from the Yahoo Finance website, utilizing only the closing price ('close') variable. The research process included data pre-processing, Min-Max normalization, LSTM modeling with varying timesteps (30, 60, 90 days), and evaluation of prediction results. The LSTM model was built with two LSTM layers, a dropout layer, and a final dense layer, and its training involved the application of the mean_squared_error loss function and Adam optimizer. Evaluation results showed that the model configuration with 60 timesteps achieved optimal performance with a RMSE of 114.17, MAPE percentage of 0.96%, and an R-Squared of 0.98, indicating highly accurate and reliable predictions. This study demonstrated that LSTM is an effective model for stock price prediction based on time series data.
Sistem Tanya-Jawab Berbasis Chatbot Telegram Tentang Fiqih Kontemporer Menggunakan Langchain Dan LLM Mar'arif, Muhammad Mulky; Harahap, Nazruddin Safaat; Jasril, Jasril; Affandes, Muhammad
TEKNIKA Vol. 19 No. 2 (2025): Teknika Mei 2025
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15437200

Abstract

Informasi mengenai fiqih kontemporer sangat susah didapatkan, terkhusus berasal dari ustadz Syekh Al-Qardhawi. Perlunya sebuah layanan informasi yang bisa memberikan jawaban dari pertanyaan seputar fiqih kontemporer, salah satunya yaitu memanfaatkan teknologi saat ini seperti chatbot yang ada pada telegram. Dengan memanfaatkan chatbot pada telegram dapat menghasilkan sebuah sistem tanya-jawab mengenai fiqih kontemporer. Jadi, penelitian ini bertujuan untuk menerapkan sistem tanya-jawab berbasis chatbot Telegram mengenai fiqih kontemporer. Penelitian ini juga memanfaatkan metode langchain dan large language model (LLM) agar dapat menciptakan sistem tanya-jawab yang optimal. Penelitian ini berhasil menunjukkan keefektifan nya dalam memberikan jawaban mengenai fiqih kontemporer yang mana hasil pengujian User Acceptance Test (UAT) dan Black Box Testing menunjukkan bahwa sistem ini dapat memberikan informasi yang akurat dan juga berfungsi sebagaimana mestinya sebagai sistem tanya-jawab tentang fiqih kontemporer.
APLIKASI TANYA JAWAB TENTANG FIQIH BERSUCI BERBASIS WEB Elvina Afriani; H, Nazruddin Safaat; Fikry, Muhammad; Affandes, Muhammad
ZONAsi: Jurnal Sistem Informasi Vol. 6 No. 2 (2024): Publikasi Artikel ZONAsi: Periode Mei 2024
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v6i2.19970

Abstract

Dalam konteks perkembangan masyarakat yang semakin antusias terhadap teknologi dan keilmuan keagamaan, terdapat tantangan signifikan terkait akses terhadap informasi fiqih bersuci. Kesulitan mengakses dan mengorganisir data terstruktur dari berbagai sumber web seringkali menimbulkan kebingungan. Penelitian ini mengeksplorasi potensi penerapan Artificial Intelligence (AI), khususnya Question Answering System (QAS), sebagai solusi untuk meningkatkan akses dan pemahaman terhadap fiqih bersuci. QAS memungkinkan komputer memahami pertanyaan dengan bahasa alami dan memberikan respons berdasarkan informasi yang tersedia. Implementasi multimedia dalam pembelajaran dan pemanfaatan metode Natural Language Processing (NLP) juga diintegrasikan untuk meningkatkan efisiensi dan akurasi. QAS dibangun dengan frame work chatbot yang sudah ada yaitu streamlit dengan aplikasi Web sebagai antarmuka, Dengan memanfaatkan teknologi AI dan NLP, penelitian ini bertujuan mengembangkan platform pembelajaran yang menyajikan informasi fiqih bersuci secara mudah, cepat, dan terkini. Diharapkan, implementasi ini dapat memberikan kontribusi positif terhadap kemudahan akses dan pemahaman masyarakat terhadap aspek hukum Islam, khususnya mengenai kebersihan dan kesucian. Pengujian terhadap aplikasi menunjukkan kinerja yang relatif tinggi dalam memahami dan memproses bahasa manusia. Akurasi jawaban dengan BERTScore didapati precision sebesar 69%, recall sebesar 56% dan F1-score sebesar 83%.
Penerapan Chatbot pada Aplikasi Web Tanya Jawab Tentang Fiqih Jual Beli Islam Menggunakan LangChain Nurhapiza, Nurhapiza; Harahap, Nazaruddin Safaat; Fikry, Muhammad; Affandes, Muhammad
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5148

Abstract

Fiqh is the field that studies Islamic rules on how humans behave, both in speech and action. Islamic Fiqh of buying and selling is a branch of fiqh that concentrates on the laws and rules relating to transactions and social interactions that occur in the daily lives of Muslims. There are many sources of learning about the fiqh of buying and selling, including books and the internet. However, manual searches can take a long time and make it difficult for some people to gain in-depth understanding. The application of a chatbot to a question and answer web application can provide a solution to provide easier access. This research aims to provide an effective and efficient solution in understanding fiqh muamalah (Islamic buying and selling). This research develops a question and answer system about the fiqh of Islamic buying and selling to make it easier for users to understand, by utilizing a deep learning approach through technologies such as LangChain, OpenAI, Large Language Model, and ChatGPT 3.5 turbo. Implementation is done through a chatbot web application that provides an initial display and menu, allowing users to ask questions about the fiqh of Islamic buying and selling and see the answers and references. Testing was conducted by students of UIN Sultan Syarif Kasim Riau and an ustaz who has a good understanding of fiqh muamalah using ten questions that were tested through the question and answer web application as a guide. The test results showed an answer evaluation of 88.8% with a very suitable category regarding the correctness of the responses given.
Penerapan Merger Retriever pada Question Answering System Hadits Saputra, Rozi; Harahap, Nazaruddin Safaat; Novriyanto; Affandes, Muhammad
SATIN - Sains dan Teknologi Informasi Vol 10 No 1 (2024): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/stn.v10i1.1117

Abstract

In today's digital world, information technology has had a significant impact on various aspects of life, including the study and exploration of Hadiths. This research aims to develop a Hadith question answering system that enables users to obtain quick and accurate answers to Hadith-related questions. By utilizing LangChain and Gemini-pro models, and implementing the merger retriever method, this system provides an innovative solution for searching Hadiths from the nine main books (kutubut tis’ah). LangChain and Gemini-pro ensure that the generated answers are not only relevant but also accurate, utilizing Large Language Model (LLM) technology. Additionally, the implementation of the merger retriever enhances the system's performance in finding the most suitable answers from various Hadith sources simultaneously. This research involves a series of stages ranging from collecting Hadith data, system analysis and design, implementation, to system testing. The test results show that the Hadith question answering system can produce relevant and accurate answers, with expert Hadith respondents evaluating the quality of answers averaging 88.5% satisfaction with the "Strongly Agree" rating interval, and LangChain evaluator scoring averaging 91% within the "Strongly Agree" category interval. This emphasizes the significant potential of applying information technology in the study of Hadiths, and opens opportunities for further development in this field. This research is expected to make a significant contribution to the ease of access to accurate and fast Hadith information for the Muslim community.
Intrusion Detection System (IDS) Pada Snort Dengan Bot Telegram Sebagai Sistem Notifikasi Terhadap Serangan Syn Flood dan Ping Of Death Zuriati Ardila Safitri; Elin Haerani; Rometdo Muzawi; Muhammad Affandes; Pizaini
SATIN - Sains dan Teknologi Informasi Vol 10 No 1 (2024): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/stn.v10i1.1138

Abstract

Keamanan jaringan menjadi prioritas penting dalam era digital. Penelitian ini mengembangkan sistem Intrusion Detection System (IDS) berbasis Snort yang terintegrasi dengan bot Telegram untuk notifikasi real-time dan menggunakan kecerdasan buatan (AI) untuk mendeteksi serta mengelompokkan jenis serangan Syn Flood dan Ping of Death. Snort dikonfigurasi dengan aturan khusus untuk mendeteksi kedua jenis serangan ini. Bot Telegram digunakan untuk mengirimkan notifikasi langsung kepada administrator jaringan saat serangan terdeteksi. Hasil penelitian menunjukkan bahwa sistem ini mampu mendeteksi serangan dengan cepat, memberikan notifikasi real-time, dan mengelompokkan jenis serangan dengan akurasi tinggi. Integrasi ini meningkatkan efektivitas deteksi dan respons terhadap serangan jaringan, menawarkan solusi yang lebih aman dan efisien bagi organisasi.
Co-Authors Abdul Aziz Ahmad Efendi Al Fajri Albis Ya Albi Aldri Permana, Lutfi Alwis Nazir Alwis Nazir Alwis Nazir Amany Akhyar Amany Akhyar Amany Akhyar Andrian Wahyu Ardelia, Adinda Abidah Asmarita Asmarita Badri Yusuf Chandra, Reski Mai citra ainul mardhia putri Destri Putri Yani Dhymas Julyan Riyanto Eka Pandu Cynthia Elin Haerani Elin Haerani Elin Haerani Elvia Budianita Elvina Afriani Fadhilah Syafria Fatmawati Fatmawati Febi Yanto Fikry, Muhammad Fitri Insani Fitri Insani Fitri Wulandari Fitri Wulandari Gunawan Setia Wiguna Harahap, Nazaruddin Safaat hariansyah, Aldi imelda amuis Iqbal Salim Thalib Iwan Iskandar Iwan Iskandar Iwan Iskandar Jasril Jasril Jasril Jasril Kana Saputra S Khairul Amri Khonofi, Khoidir Kurniansyah, Juliandi Lola Oktavia Mar'arif, Muhammad Mulky Marlina, Resti Muhammad Fikry Muhammad Irsyad Muhammad Irsyad Muhammad Ridha Muhammad Rizky Ramadhan Nazruddin Safaat Nazruddin Safaat H Nazruddin Safaat H Nazruddin Safaat H Novi Yanti Novialdi T Novri Rahman Novri Yanto Novriyanto Novriyanto Novriyanto Nurhapiza, Nurhapiza Oktavia, Lola Pizaini Pizaini Prameswari, Putri Rahmad Kurniawan Raja Sultan Firsky Ramu Will Sandra Reski Mai Candra Reski Mai Candra Reski Mai Candra Reski Mai Candra Reski Mai Candra Reski Mai Candra Rindi Yani Rometdo Muzawi, Rometdo Roni Setyawan Saputra, Rozi Sarah Lasniari Sarah Lasniari Siska Kurnia Gusti Siska Kurnia Gusti Surya Andika Suwanto Sanjaya Syarifuddin Syarifuddin Tania, Windy Teddie Darmizal Teddie Darmizal Thomas Alva Edison Tri Prastio Nugroho Wedi Kurniawan Wirasatria Putra Yazid, Fathuddin Yelfi Vitriani Yelfi Vitriani Zuriati Ardila Safitri