Article Per Year (5 Year)
p-Index From 2021 - 2026
3.761
P-Index
This Author published in this journals
All Journal International Conference on Engineering and Technology Development (ICETD) KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal Komputasi Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Teknoinfo Kurawal - Jurnal Teknologi, Informasi dan Industri Jurnal Pengabdian Kepada Masyarakat (JPKM) Tabikpun Journal Social Science And Technology For Community Service Jurnal Pengabdian Dharma Wacana International Journal of Electronics and Communications Systems Jurnal Pepadun Journal of Central Banking Law and Institutions Probono and Community Service Journal Jurnal Komputasi
Tristiyanto Tristiyanto
Jurusan Ilmu Komputer, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Lampung
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Social Sciences Other

Published : 53 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 53 Documents
Search

 2   3   4   5   6 
Perancangan Sistem Manajemen Mutu untuk Penilaian Mata Kuliah di Ilmu Komputer weike Sandy; Tristiyanto Tristiyanto; Anie Rose Irawati; Didik Kurniawan
Jurnal Komputasi Vol. 12 No. 2 (2024): Jurnal Komputasi
Publisher : Jurusan Ilmu Komputer Fakultas MIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v12i2.274

Abstract

Penelitian ini berfokus pada pengembangan Sistem Penilaian Kualitas Mata Kuliah di Jurusan IlmuKomputer Universitas Lampung, dengan memanfaatkan platform berbasis web yang menggunakan frameworkLaravel. Sistem ini bertujuan untuk memfasilitasi manajemen data mahasiswa dan pemantauan kemajuanpembelajaran mereka dengan lebih efisien. Sistem ini mencakup fungsionalitas seperti pembuatan Templatepenilaian untuk evaluasi mahasiswa, memungkinkan unggahan file untuk integrasi basis data, dan menyediakanplatform bagi anggota fakultas untuk memasukkan dan meninjau data kinerja mahasiswa. Studi ini menanganikebutuhan kritis akan sistem penilaian yang terstruktur untuk mengevaluasi kompetensi mahasiswa secaramenyeluruh, sehingga meningkatkan kualitas pendidikan dan mendukung intervensi yang ditargetkan untukpengembangan mahasiswa.
Pengembangan Aplikasi Penilaian Angka Kredit Dosen (Studi kasus: FMIPA Universitas Lampung) Alifia Intan Andrean Nunyai; Tristiyanto Tristiyanto
Jurnal Pepadun Vol. 4 No. 2 (2023): August
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v4i2.168

Abstract

According to Law Number 14 of 2005 on Teachers and Lecturers, lecturers are defined as professional educators and scholars whose primary responsibility is to transform, advance, and disseminate knowledge, technology, and the arts through education, research, and community service, often referred to as the Tri Dharma of Higher Education (Chapter 1, Article 1, paragraph 2). The assessment of lecturers' performance is deemed essential in the context of implementing the Tri Dharma of Higher Education to gauge the degree to which it is executed. In practice, lecturers are required to accrue credit points in line with the established standards specified in the operational guidelines for credit point assessment. Nevertheless, lecturers often encounter delays in the collection of these credit points, primarily due to the substantial amount of data used as assessment criteria and the manual creation of reports using Microsoft Excel. Consequently, this protracted process is responsible for the extensive time required for the preparation of Academic Qualification Credit Points (DUPAK) reports. To tackle this issue, the development of an Information System has been proposed to expedite and enhance the accuracy of data collection. The Information System is constructed using the prototype methodology, which encompasses three core phases: "Listening to Customer" to identify user requirements, "Building/Revising the Mock-Up" to develop the prototype, and "Testing the Mock-Up" to assess its compliance with user expectations. The system is coded using the PHP programming language, and the Laravel framework is employed to simplify the coding process. The system's functionality is rigorously tested using the Black Box Testing method with Equivalence Partitioning to ensure its reliability and accuracy. The outcome of this research is a Web-Based Lecturer Performance Evaluation Information System designed to streamline the DUPAK report creation process for lecturers, making it more efficient and precise.
Analisis Komparatif Kinerja LSTM, BiLSTM, dan LSTM-AM dalam Prediksi Harga Saham Syariah Muhamad Ramadhan Kamal; Rahman Taufik; Ridho Sholehurrahman; Tristiyanto .; Bita Parga Zen
Kurawal - Jurnal Teknologi, Informasi dan Industri Vol 9 No 1 (2026): Vol 9 No 1 (2026): Jurnal Kurawal Volume 9, Nomor 1, Maret 2026
Publisher : Universitas Ma Chung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33479/kurawal.v9i1.1470

Abstract

The continuously evolving Sharia stock market necessitates more accurate price modeling due to high volatility, regime shifts, and outliers that frequently disrupt investment decision-making processes. This study aims to comparatively evaluate the performance of three deep learning algorithms—LSTM (Long Short-Term Memory), BiLSTM (Bidirectional LSTM), and LSTM-AM (LSTM with Attention Mechanism)—in predicting Sharia stock prices. The research method utilizes daily closing price data from five Indonesian Sharia-compliant issuers (ANTM, ERAA, KLBF, SMGR, and WIKA) spanning the period of December 2016 to December 2021. The data underwent preprocessing using Robust Scaling and was structured into time series with a 60-day window. Model evaluation was conducted via window-based cross-validation with the results show that BiLSTM delivered the best performance with an average MAPE of 9.41% and RMSE of 249.956. This performance was followed by LSTM (MAPE 11.87%) and LSTM-AM as the lowest (MAPE 19.58%). These findings provide a clear understanding of the effectiveness of each architecture in predicting dynamic Sharia stock prices, indicating that increasing model complexity (LSTM-AM) does not always guarantee better accuracy in this domain. Consequently, BiLSTM can be considered the superior model for more stable prediction.
Co-Authors Abdul Muthalib Tahar Adelliani Adelliani Afridho Rachmadi Kartawiria Alifia Intan Andrean Nunyai Almira Fardani Lahay Alvi Yani Andrian, Rico Anggie Tamara Annisa Meyliana Ardian Hermawansyah Ardiansyah Ardiansyah arien ferlina putri arien ferlina putri Aristoteles, Aristoteles Bambang Hermanto Bita Parga Zen Dana Febri Setiawan Desrizal Dwi Ayu Deviana Saputri Dorothy Rouli Pandjaitan Dwi Sakethi Dwi Sakethi, Dwi Emir Sasmita Eva Yunita Fadhli Munadi Iman Febi Eka Febriansyah Febryani Sabatira Feri Krisnanto Gabriela Minang Sari Gofariyanti Dharmaningtyas Hanan Risnawati Heningtyas, Yunda Henky Mayaguezz Hernani, Livia Ayu Istoria Hijriani, Astria Iman, Fadhli Munadi Irawati, Anie Rose Kalista Setiawan Kurnia Muludi Lilis Oktaviani Sirait Lumbanraja, Favorisen R Melya Riniarti Muhamad Ramadhan Kamal Muhammad Iqbal Muhammad Iqbal Muhammad Yusuf Amran Noviyanti Noviyanti orima davey parabi, M.Iqbal Patrice Kevin Marcus Prabowo, Rizky Prabowo, Rizky Prabowo, Rizky Priyambodo Priyambodo Putri Ayu Febrina Rafi Amalia Rahmanda Rahmadila Nurjannah Rahman Taufik Rahmat Safe'i Ratih Indah Wardani Ria Wierma Putri Ridho Sholehurrahman Ridzana Wulantika Rifki Aflaza Arba Rifqi Adiyatma Rizky Prabowo Sari, Gabriela Minang Sasqia Yovita Dewi Syintia Dwi Nurrahmi Tamara, Anggie Tantut Wahyu Setyoko Ulfah Septiani Ully Novianti S Vynda Levy Cahyani weike Sandy Winda Rahmawati Yunita Maya Putri