Article Per Year (5 Year)
p-Index From 2021 - 2026
2.986
P-Index
This Author published in this journals
All Journal ComEngApp : Computer Engineering and Applications Journal Jupiter Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Sriwijaya Journal of Informatics and Applications Jurnal Generic Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS
Alvi Syahrini Utami
Teknik Informatika, Fakultas Ilmu Komputer, Universitas Sriwijaya
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Social Sciences Other

Published : 19 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 19 Documents
Search

 1   2 
Comparison Of Dempster Shafer AND Certainty Factor Methods In Expert System For Early Diagnosis Of Stroke Disease Arsalan, Osvari; Febrivia, Pretty Fujianti; Utami, Alvi Syahrini; Rodiah, Desty
Sriwijaya Journal of Informatics and Applications Vol 5, No 1 (2024)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v5i1.79

Abstract

Stroke is one of endangering disease if not treated properly and could lean to death. Most people unwilling to check their health because of high cost, lack of medical service, medical staff of neurologist and their limited working time. Therefore, we need an expert system that can help in early diagnosis of stroke. The Dempster Shafer and Certainty Factor methods are expert systems methods used in many cases to support uncertainty from the expert. The aim of this study is to compare two methods to determine the best method in the expert system for diagnosing stroke, by calculating symptoms so as to produce CF values in the Certainty Factor method and density values in the Dempster Shafer method. The data used in the study to diagnose stroke consisted of data on eighteen disease symptoms and two types of stroke identified. Based on the results of testing on 105 test data, the accuracy value of the expert system for diagnosing stroke using the Dempster Shafer method is 95.2% and the accuracy value of the expert system for diagnosing stroke with the Certainty factor method is 98.1%.
Bully Comments Classification on TikTok Using Support Vector Machine and Chi-Square Feature Selection Putri, Amelia; Abdiansyah, Abdiansyah; Utami, Alvi Syahrini
Sriwijaya Journal of Informatics and Applications Vol 5, No 1 (2024)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v5i1.71

Abstract

TikTok has been named the world’s most popular social media platform. The high level of TikTok use makes it easier for an irresponsible user to do unethical things such as spreading hateful comments on someone’s account. TikTok developers can prevent bullying by using policies such as word detection and filtering features that indicate comments fall under the category of bullying or non-bullying comments. Therefore, we conducted this study to classify bullying comments using Machine Learning methods for convenience purposes on TikTok usage, a method that we used in this research is the SVM method to classify the data and Chi-Square as the feature selection. Tests were carried out using the Linear, Polynomial, and RBF kernel functions with the C parameter, namely 0,1, 1, and 10 for each kernel. The results of this research show that the Support Vector Machine method with Chi-Square Feature Selection has a better performance.  This was proven by the increased accuracy in RBF kernel C=0,1 which was 0,20
Perbandingan Metode Mapreduce Berbasis Single Node Hadoop Pada Aplikasi Word Count Marieska, Mastura Diana; Utami, Alvi Syahrini; Oktaviani, Elvira
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 1 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.11097045

Abstract

In the context of Big Data processing, Hadoop MapReduce serves as a framework used to develop software and process large-scale data in parallel. Word Count is a type of task used to count the occurrences of unique words in a text file. Considering processing time is crusial in adhering to standards of Big Data Processing. The conducted research involved the processing of text files using the MapReduce method on the Hadoop Distributed File System (HDFS) using a single node, comparing the results of Word Count processing with and without the use of MapReduce. The research findings indicate that the implementation of Word Count without using MapReduce offers better speed in processing Indonesian language text data on a Hadoop single node. Additionally, the comparison of processing time between the Word Count program with Hadoop MapReduce and the Word Count program without MapReduce shows that the latter has faster processing time. A significant reduction in processing time, up to 95% for a 5 MB file size, can be achieved by using the Word Count method without MapReduce. However, the level of reduction decreases with increasing file size.
Fisheries Harvest Prediction using Genetic Algorithm Optimized of Gated Recurrent Unit Herman, Adelwin; Utami, Alvi Syahrini; Darmawahyuni, Annisa
Sriwijaya Journal of Informatics and Applications Vol 5, No 2 (2024)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v5i2.109

Abstract

Indonesia is a maritime country with most of the population living near water areas. Water products are a common commodity often consumed cheaply, and food is therefore one of the primary human needs. Fishery harvest predictions are needed to control prices, prepare seeds, and ensure stable sales and consumption. The reason for choosing GRU for this prediction is that classical methods, commonly used in econometrics or time series analysis, were previously prevalent. GRU requires fewer operations than LSTM. Instead of training with an optimization algorithm relying on backpropagation and gradients, metaheuristic optimization in the form of a GA is used. GA does not require gradient information and is expected to avoid local optima. The total average MSE obtained is 9.55%.
Diagnosing Disease Of Betta Fish Using Fuzzy Logic Sugeno And Forward Chaining Method Pratama, M Wahyu; Utami, Alvi Syahrini; Kurniati, Rizki
Sriwijaya Journal of Informatics and Applications Vol 5, No 2 (2024)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v5i2.87

Abstract

Betta fish are very popular with people of all ages who make betta fish as small and medium businesses who consider betta fish as a business, but betta fish maintenance is quite the opposite. The ease of breeding betta fish and ignorance in caring for good fish can cause death in betta fish caused by various diseases. Therefore, an expert system for diagnosing disease in betta fish was created. In this study the Forward Chaining method was used to diagnose fish disease, while the Fuzzy Sugeno method determined the severity of the disease. The accuracy generated by the system based on tests carried out using 100 data was 93%.
PENINGKATAN MOTIVASI BELAJAR SISWA SMA MELALUI PENDEKATAN PEMROGRAMAN KOMPUTER Abdiansah, Abdiansah; Utami, Alvi Syahrini; Yusliani, Novi; Miraswan, Kanda Januar; Wedhasmara, Ari
Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Vol. 1 No. 4 (2023): Agustus
Publisher : CV. Alina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jpki2.v1i4.56

Abstract

PISA adalah penilaian tingkat internasional yang diselenggarakan setiap tiga sekali untuk menguji kemampuan akademis siswa yang berusia 15 tahun. Tujuan PISA adalah untuk menguji dan membandingkan prestasi anak-anak sekolah di seluruh dunia. Nilai PISA Indonesia di tahun 2018 masih rendah untuk ketiga bidang yang dinilai, yaitu: Matematika, Sains, dan Membaca. Untuk mengatasi hal tersebut dibutuhkan metode pembelajaran yang mampu memotivasi belajar siswa, terutama di bidang STEM (Science, Technology, Engineering, Math). Salah satu metode kegiatan yang dapat meningkatkan motivasi siswa adalah dengan memberikan pengenalan konsep dan praktik pemrograman komputer untuk diterapkan di bidang matematika, fisika, dan kimia. Hasil evaluasi menunjukkan bahwa terjadi peningkatan kemampuan belajar siswa sebesar 15.00% (N-Gain) meskipun secara keseluruhan hasilnya masih belum signifikan. Meskipun demikian hasil evaluasi kegiatan pelatihan cukup memuaskan dengan nilai sebesar 84.91% (Skala Likert). Hasil tersebut membuktikan bahwa pendekatan pemrograman komputer untuk meningkatkan motivasi belajar siswa di bidang STEM cukup menjanjikan. Kata Kunci: PISA, STEM, Pemrograman Komputer
Aplikasi QR-code untuk sistem daftar hadir: Solusi digitalisasi administrasi di SMA dan SMK Rodiah, Desty; Yusliani, Novi; Abdiansah; Utami, Alvi Syahrini; Miraswan, Kanda Januar; Marieska, Mastura Diana; Yunita; Rini, Dian Palupi
Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Vol 8 No 2 (2025)
Publisher : University of Islam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33474/jipemas.v8i2.22696

Abstract

Kebijakan Merdeka Belajar dari Kemendikbud RI mendorong guru untuk menerapkan pendekatan pengajaran yang fleksibel dan adaptif melalui integrasi teknologi dalam kegiatan pembelajaran. Dalam konteks ini, program pengabdian kepada masyarakat memberikan pelatihan untuk mengembangkan sebuah aplikasi daftar hadir berbasis QR-Code menggunakan Python untuk guru SMA dan SMK. Aplikasi ini dirancang untuk mencatat kehadiran siswa secara cepat, tepat, dan efisien, serta mendukung kemudahan administrasi dan memberikan pengalaman langsung dalam penggunaan teknologi pemrograman. Kegiatan pengabdian ini menerapkan metode Participatory Action Research (PAR), yang meliputi lima tahap: To Know (menggali kebutuhan mitra melalui survei), To Understand (mengevaluasi pelatihan sebelumnya), To Plan (menyusun materi dan instrumen evaluasi), To Act (melaksanakan pelatihan melalui presentasi dan praktikum), dan To Change (melakukan evaluasi). Evaluasi dilakukan dengan pendekatan N-Gain dan skala Likert. Hasil N-Gain sebesar 20,90% menunjukkan efektivitas pelatihan yang kurang meskipun terdapat peningkatan nilai rata-rata sebesar 7,37 poin. Hal ini dipengaruhi oleh latar belakang peserta yang sudah berpengalaman, sehingga materi dan soal perlu dikembangkan lebih lanjut. Di sisi lain, hasil Likert menunjukkan persepsi peserta yang sangat positif. Kendala koneksi internet sempat memengaruhi praktikum, namun narasumber dan mahasiswa aktif membantu peserta yang mengalami hambatan tersebut.
Performance Comparison of Monolithic and Microservices Architectures in Handling High-Volume Transactions Marieska, Mastura Diana; Arya Yunanta; Harisatul Aulia; Alvi Syahrini Utami; Muhammad Qurhanul Rizqie
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 3 (2025): June 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i3.6183

Abstract

Monolithic and microservices are two distinct approaches for designing and developing applications. However, these architectures exhibit contrasting characteristics. In monolithic architecture, all components of an application form a unified entity with closely interconnected parts, whereas microservices decompose an application into independent, lightweight services that can be developed, deployed, and updated separately. Microservices are often regarded as superior to monolithic architectures in terms of their performance. This study aims to compare the performance of monolithic and microservices architectures in handling a high volume of transactions. It is important to observe how the two architectures behave when handling transactions from a large number of concurrent users. A prototype of an online ticketing system was implemented for both architectures to enable comparative analysis. The selected performance metrics were response time and error rate. The experimental results reveal that under high-load conditions, microservices outperform monolithic architectures, demonstrating 36% faster response times and 71% fewer errors. However, under overload conditions—when CPU usage exceeds 90%—the performance of microservices degrades significantly. This does not imply that microservices cannot handle a large number of concurrent users but highlights the necessity for enhanced resource management.
Query Reformulation for Indonesian Question Answering System Using Word Embedding of Word2Vec Utami, Alvi Syahrini; Yusliani, Novi; Marieska, Mastura Diana; Abdiansyah
Computer Engineering and Applications Journal (ComEngApp) Vol. 11 No. 1 (2022)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Query reformulation is one of the tasks in Information Retrieval (IR), which automatically creates new queries based on previous queries. The main challenge of query reformulation is to create a new query whose meaning or context is similar to the old query. Query reformulation can improve the search for relevant documents for Open-domain Question Answering (OpenQA). The more queries are given to the search system, and the more documents will be generated. We propose a Word Predicted and Substituted (WPS) method for query reformulation using a word embedding word2vec. We tested this method on the Indonesian Question Answering System (IQAS). The test results obtained an E-1 value of 81% and an E-2 value of 274%. These results prove that the query reformulation method with WPS and word-embedding can improve the search for potential IQAS answers.
Co-Authors Abdiansah Abdiansah, Abdiansah Abdiansyah Abdiansyah, Abdiansyah Adi Kurniawan Ahmad Fali Oklilas Aisyah Filza Aliyah Ari Wedhasmara Armenia Yuhafiz Arya Yunanta Darmawahyuni, Annisa Desty Rodiah Dian Palupi Rini Dian Palupi Rini Endang Lestari Ruskan Febrivia, Pretty Fujianti Harisatul Aulia Herman, Adelwin Kanda Januar Miraswan Mastura Diana Marieska Mudinillah, Adam Muhammad Fachrurrozi Muhammad Qurhanul Rizqie Naura Qatrunnada Novi Yusliani Oktadini, Nabila Rizky Oktaviani, Elvira Osvari Arsalan Pratama, M Wahyu Putri, Amelia Rizki Kurniati Wiwik Anum Puspita YUNITA