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All Journal Jurnal Ilmiah KOMPUTASI JITK (Jurnal Ilmu Pengetahuan dan Komputer) International Journal of Supply Chain Management Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat International Journal of Business, Economics, and Social Development International Journal of Electronics and Communications Systems JSEP (Journal of Science Education and Practice) Journal of Engineering and Information Technology for Community Service Jurnal Pemberdayaan Masyarakat Kenduri: Jurnal Pengabdian Dan Pemberdayaan Masyarakat ABDIMAS Iqtishadia Indonesian Journal of Statistics and Its Applications Jurnal Pengabdian Masyarakat Inovatif Jurnal Pengabdian Masyarakat Inovatif
Asep Saepulrohman
Universitas Pakuan
Religion Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Journal : International Journal of Electronics and Communications Systems

 1 
The Effect of Cerium Doping on LiTaO3 Thin Film on Band Gap Energy Ismangil, Agus; Subiyanto, Subiyanto; Sudradjat, Sudradjat; Prakoso, Wahyu Gendam; Saepulrohman, Asep
International Journal of Electronics and Communications Systems Vol. 1 No. 2 (2021): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v1i2.7906

Abstract

Lithium tantalite LiTaO3 was grown on a Si Type-P (100) substrate by chemical solution deposition and spin coating methods at a speed of 3000 rpm for 30 seconds with an annealing temperature of 800 ° C, 900 ° C. This study aims to determine the effect of temperature variations on the band gap energy. The results show that the energy band gap value of the thin film has a significant impact on the interpretation of annealing temperature. It can be seen that a high energy band gap peak occurs at an annealing temperature of 900 ° C and a time of 15 hours of the energy band gap of 1,49 eV. This shows the effect of temperature variations on the energy band gap to move from the valence band to the conduction band, which will produce current.
Data integrity and security of digital signatures on electronic systems using the digital signature algorithm (DSA) Saepulrohman, Asep; Ismangil, Agus
International Journal of Electronics and Communications Systems Vol. 1 No. 1 (2021): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v1i1.7923

Abstract

The digital signature generation process begins with the creation of a public key and a private key. A public key is generated and published to verify the signature and calculate the hash value of the received document. At present, in the very fast development of information technology, quantum computers have emerged the ability to solve very large and complex amounts of data calculated by qubits, which when compared to quantum computers can work 10 minutes to work on a process that takes 1025 years on a computer. Therefore, the research focuses on how electronic signatures on documents have a reliable security system. The Digital Signature Algorithm (DSA) is a key algorithm used for digital signatures, which uses the Secure Hash Algorithm (SHA-1) to convert messages into message digest and parameters based on the ElGamal signature algorithm. The author also shows an example of digital signature encryption and decryption process by taking any numbers p = 59419 and q = 3301 to prove that the message can be formed and verified its authenticity.
Optimization of Stock Price Prediction Using Long Short-Term Memory (LSTM) Algorithm and Cross-Industry Standard Process Approach for Data Mining (CRISP-DM) Saepulrohman, Asep; Chairunnas, Andi; Denih, Asep; Safitri Yasibang, Nurdiana Dini
International Journal of Electronics and Communications Systems Vol. 5 No. 1 (2025): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v5i1.26727

Abstract

Predicting stock prices accurately is an integral part of investment analysis as it permits forecasting movements in the financial markets and tailoring strategies accordingly. In this study, the LSTM (Long Short-Term Memory) algorithm is used with the aim of improving predictive accuracy, particularly the forecasting of stock price movements. This research follows the CRISP-DM framework or Cross-Industry Standard Process for Data Mining, which incorporates six defined steps including: understanding the business context, data understanding, data preparation, model building, evaluation, and implementation. Stock price data for the ticker symbol “ANTM.JK” was sourced from Yahoo Finance for the date range of October 29, 2005 to July 11, 2024. Along with the consistency, several model accuracy enhancing preprocessing steps such as data cleaning, feature selection, and normalization with Python were performed before modeling. Hyperparameter tuning to reduce the error margins on predictions was conducted after training the LSTM model. Testing the hypotheses showed that the LSTM model demonstrated a low Root Mean Square Error (RMSE) on the test dataset indicating outstanding forecasting accuracy. The ability of the model to outperform conventional time series forecasting techniques is attributed to its ability to effectively retain nonlinear time-series relationships and long-term dependencies. These findings suggest that the LSTM algorithm can serve as a reliable tool for stock price forecasting in emerging markets. This study provides practical insights for investors and lays the groundwork for future research on hybrid or ensemble models to further improve prediction robustness and accuracy
Co-Authors Adriana Sari Aryani Agita Tiara Putri Agung Prajuhana Putra Agung, Moch Panji Agus Ismangil Andi Chairunnas Arie Qur’ania Arief Rachman Hakim Asep Denih Asep Denih Azha, Arrazy Deden Ardiansyah Drajar, Muhamamd Bintang Eka Suhardi Endang Soeryana Hasbullah Erna Selviyanti Febri Febriansyah Gandhy, Abel Gesa Rizky N Gustian Rama Putra Gustian Rama Putra Gustian Rama Putra Hermawan Hermawan Hidayatulah, Syarif I Wayan Sriyasa I Wayan Sriyasa Kotim Subandi Lathifah, Suci Siti Layung Paramesti Martha Leny Heliawati Leny Heliawati Lita Karlitasari Lusi Agus Setiani Muhammad Taufiq Negara, Teguh Puja Oktavian Nursetiaji Olandina Cahyani P Prastio, Agung Dwi Puspa Citra Putra, Gustian Rama Putri Nabila Adinda Adriansyah Putri Nabila Adinda Adriansyah Putri Nabila Adinda Adriansyah Safitri Yasibang, Nurdiana Dini Sandi Budiana Sri Setyaningsih Stella Talitha Subiyanto Subiyanto Sudradjat Sudradjat Sudradjat Sudradjat Sukono . Surti Kurniasih Suyudi, Mochammad Syarif Hidayatullah Taruma Leo Wijaya Tjut Awaliyah Zuraiyah Tri Aminingsih Tri Aminingsih Victor Ilyas Sugara Wahyu Gendam Prakoso Wahyu Gendam Prakoso, Wahyu Gendam Wahyu Sardjono Wahyu Sardjono Yusma Yanti Zulfa, Rulla Aliyah