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All Journal Journal of Information Systems Engineering and Business Intelligence Science and Technology Indonesia Jurnal Pengabdian Masyarakat Tapis Berseri Abdi Akommedia : Jurnal Pengabdian Masyarakat Integra: Journal of Integrated Mathematics and Computer Science Nemui Nyimah
Wamiliana
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Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Education Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics Other

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LSTM-CNN Hybrid Model Performance Improvement with BioWordVec for Biomedical Report Big Data Classification Kurniasari, Dian; Warsono; Usman, Mustofa; Lumbanraja, Favorisen Rosyking; Wamiliana
Science and Technology Indonesia Vol. 9 No. 2 (2024): April
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2024.9.2.273-283

Abstract

The rise in mortality rates due to leukemia has fueled the swift expansion of publications concerning the disease. The increase in publications has dramatically affected the enhancement of biomedical literature, further complicating the manual extraction of pertinent material on leukemia. Text classification is an approach used to retrieve pertinent and top-notch information from the biomedical literature. This research suggests employing an LSTM-CNN hybrid model to tackle imbalanced data classification in a dataset of PubMed abstracts centred on leukemia. Random Undersampling and Random Oversampling techniques are merged to tackle the data imbalance problem. The classification model’s performance is improved by utilizing a pre trained word embedding created explicitly for the biomedical domain, BioWordVec. Model evaluation indicates that hybrid resampling techniques with domain-specific pre-trained word embeddings can enhance model performance in classification tasks, achieving accuracy, precision, recall, and f1-score of 99.55%, 99%, 100%, and 99%, respectively. The results suggest that this research could be an alternative technique to help obtain information about leukemia.
The Use of Probability and Edge Analysis to Solve the Multi-Period Degree Constrained Minimum Spanning Tree Problem Wamiliana; Junaidi, Akmal; Gamal, Mohammad Danil Hendry; Thamrin, Taqwan
Science and Technology Indonesia Vol. 9 No. 4 (2024): October
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2024.9.4.999-1008

Abstract

The goal of the Multiperiod Degree Constrained Minimum Spanning Tree (MPDCMST) problem is to determine the smallest weight-spanning tree that satisfies the vertex installation criterion for each period and maintains the degree requirement in each vertex. This issue emerges as a network connection problem. The degree requirement indicates the reliability of each vertex, and the vertex connection/installation requirement denotes the priority vertices that must be inserted in the network within a specific time frame. The installation is split up into multiple phases/stages. This is because of various considerations such as severe weather, budgetary limitations, etc. In this research, two algorithms for solving the MPDCMST using probability hybridized with Prim’s modification, and edge analysis are proposed. The algorithms are implemented on the undirected complete graph of orders 10 to 100. The solutions are compared with some heuristics which are already in the literature. The results show that the proposed algorithms perform better.
Konservasi Anggrek Dan Peningkatan Peringkat Greenmetric Melalui Kegiatan Penanaman Anggrek Di Kampus Widiarti; Usman, Mustofa; Wamiliana; Nurcahyani, Nuning; Master, Jani
Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) Vol. 2 No. 1 (2023): Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) (Edisi April)
Publisher : Pusat Studi Teknologi Informasi Fakultas Ilmu Komputer Universitas Bandar Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jpmtb.v2i1.39

Abstract

Upaya pelestarian anggrek, khususnya anggrek spesies merupakan salah satu kegiatan konservasi lingkungan hidup. Dalam rangka pelestarian lingkungan, lingkungan kampus sudah dipenuhi berbagai pohon-pohon rindang dan tinggi, yang sangat sesuai untuk habitat anggrek hutan. Adanya tanaman-tanaman ini merupakan salah satu upaya konservasi lingkungan, keindahan, dan pengurangan gas CO2. Untuk menambah keindahannya, pohon-pohon besar yang ada di lingkungan taman kampus dapat ditempel berbagai jenis anggrek yang sesuai dengan habitatnya seperti amabilis, retusa, bulbophyllum, aphyllum, dan dendrobium. Anggrek, selain indah dan cantik, juga akan mengurangi kadar CO2 di udara sehingga penanaman anggrek di lingkungan kampus akan berdampak baik terhadap peringkat greenmetric. Tujuan kegiatan pengabdian ini adalah untuk: (1) melestarikan anggrek spesies khususnya amabilis yang merupakan spesies asli Lampung, (2) mengurangi CO2 dan meningkatkan peringkat greenmetric. Kegiatan ini melibatkan tim dosen, mahasiswa, dan staff untuk membantu merawat tanaman anggrek. Tingkat keberhasilan hidup anggrek untuk beradaptasi di lingkungan kampus sangat baik (lebih dari 95%). Partisipasi dan antusiasme masyarakat dan civitas akademika di lingkungan kampus juga sangat baik. Hal ini ditandai dengan pertumbuhan anggrek yang baik dan masih utuhnya plant anggrek yang ditanam.
Pelatihan Penggunaan LaTeX Untuk Penulisan Skripsi Bagi Mahasiswa Program Studi Sarjana Matematika FMIPA Universitas Lampung Mega Sapitri, Nonik; Sawitri, Riza; Wamiliana; Abdurrahman, Ahmad Faruq
ABDI AKOMMEDIA : JURNAL PENGABDIAN MASYARAKAT Vol. 2 No. 4 (2024)
Publisher : ABDI AKOMMEDIA : JURNAL PENGABDIAN MASYARAKAT

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

Abstract

The purpose of this community service activity is to improve the ability of students of the Bachelor of Mathematics Study Program FMIPA University of Lampung to use LaTeX for thesis writing. LaTeX was chosen because it is able to produce documents with a professional format, especially in managing mathematical equations and document layout. The training was held on October 24, 2024 at the Computer Laboratory ofthe Mathematics Department with 19 fifth semester students participating. The methods used include providing training modules, using LaTeX-based thesis templates, and hands-on practice using the Overleaf platform. The training results showed that 95% of participants recognized theimportance of using LaTeX, with 93% feeling satisfied with the training implementation. However, time efficiency was evaluated with a score of 80%, indicating the need for further training. Participants showed high enthusiasm and were able to practice LaTeX features, including table creation and writing mathematical equations. Through this training, students are equipped with technical skills to produce a thesis that is not only content-quality but also meets academic standards. Thus, this activity supports the strengthening of student competencies while supporting the University of Lampung as a higher education institution that excels in academics and research.
Modeling Vector Error Correction with Exogeneous (VECMX) Variable for Analyzing Nonstationary Variable Energy Used and Gross Domestic Product (GDP) Usman, Mustofa; Wamiliana; Russel, Edwin; Kurniasari, Dian; Widiarti; Elfaki, Faiz A.M
Science and Technology Indonesia Vol. 10 No. 1 (2025): January
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2025.10.1.283-293

Abstract

Analysis of energy used, GDP and population has been carried out in many countries and has become a topic of interest for many researchers and governments. This is because energy used is an important factor for society and industry in a country. In this study, the modeling of the relationship between energy used, GDP and population as an exogenous variable for the cases of Indonesia from 1967-2023 will be discussed. The energy used and GDP data are nonstationary with order one, I(1), and there is cointegration between energy used and GDP. Therefore, the model which will be used is the Vector Error Correction Model with Exogenous variable (VECMX) with population as the exogenous variable. From the results of analysis, the best model is VECMX(3,1) with cointegration rank R=1. Based on this model, the pattern of the relationship among the three variables, Granger-causality between energy used and GDP, exogenous impact on energy used and GDP, and forecasting for the next 10 years will be discussed.
Pelatihan Pembuatan Infografis Desa dalam Rangka Mendukung Program Desa Cantik Widiarti; Kurniasari, Dian; Wamiliana; Asmiati
Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) Vol. 4 No. 1 (2025): Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) (Edisi April)
Publisher : Pusat Studi Teknologi Informasi Fakultas Ilmu Komputer Universitas Bandar Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jpmtb.v4i1.129

Abstract

The Desa Cantik program is one of the Central Statistics Agency (BPS) programs to realize sectoral statistical development at the village level in a sustainable and comprehensive manner. BPS Tanggamus Regency is one of the BPS that participates in developing Desa Cantik. In 2024, BPS Tanggamus will develop 4 villages spread across Tanggamus Regency. The four villages are Kampung Baru, Kagungan, Purwodadi and Banding Agung. The purpose of this development is to increase the capacity of the village or the ease in identifying data needs and potential owned by the village in order to eradicate poverty and increase statistical literacy in the village. In line with the responsibility carried out by BPS regarding this Desa Cantik program, the development is also a challenge for the staff of the Mathematics Department FMIPA Unila to participate in transferring knowledge and skills, especially related to Statistical Techniques. Through this program, human resources in the village are trained to process village monographic data and present it in the form of infographics with the help of the Tableu and Canva applications. The results of this training activity showed that 71% of participants had actively participated in preparing infographics.
The Relation of Noncrossing Partitioning of Odd and Even Numbers with Catalan Numbers Amansyah, Wahyu Dwi; Wamiliana; Hamzah, Nur
Integra: Journal of Integrated Mathematics and Computer Science Vol. 1 No. 1 (2024): March
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.2024114

Abstract

Catalan numbers, denoted by Cn, are generally defined by the equation Cn = 1/(n+1) (2nn) with n ≥ 0 and n ∈ ℤ. Catalan numbers have forms that can be determined through generaland recursive forms. Catalan numbers have several applications to various combinatorialproblems, such as in recursive analysis and the application of combinatorial theory topartitions that can form Catalan numbers. The odd numbers are defined as integers that arenot divisible by two, expressed in the form {2k + 1; k ∈ ℤ} . Meanwhile, even numbers aredefined as integers that are divisible by two, expressed in the form {2k; k ∈ ℤ} . In this studywe discuss the noncrossing partitions of positive odd numbers and positive even numbers.The results show those the noncrossing partitions have relationship with Catalan numbers.
Comparison of Support Vector Regression and Random Forest Regression Performance in Vehicle Fuel Consumption Prediction Nurdin, Muhaymi; Wamiliana; Junaidi, Akmal; Lumbanraja, Favorisen Rossyking
Integra: Journal of Integrated Mathematics and Computer Science Vol. 1 No. 2 (2024): July
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20241221

Abstract

Predicting vehicle fuel consumption is an important aspect in improving energy efficiency and supporting sustainable transportation. This study aims to compare the performance of Support Vector Regression (SVR) and Random Forest Regression (RFR) algorithms in predicting combined vehicle fuel consumption (COMBINED, a combination of 55% urban and 45% highway). The Canadian government's Fuel Consumption Ratings dataset was used, with 2015-2023 data (9,185 entries) for training and testing, and 2024 data (764 entries) for further testing. Pre-processing involved StandardScaler for numerical features and OneHotEncoder for categorical features, followed by hyperparameter optimization using Grid Search, resulting in optimal parameters: SVR (C=100, epsilon=0.5, gamma=1) and RFR (n_estimators=200, max_depth=None, min_samples_split=2). Results show RFR is superior with R2 0.8845, RMSE 0.9671, and MAE 0.6566, compared to SVR with R2 0.8648, RMSE 1.0462, and MAE 0.7150. Evaluation on 2024 data and visualization of error distribution corroborate the superiority of RFR. This study concludes RFR is more effective for COMBINED prediction, although SVR is competitive post-optimization, and contributes to the selection of machine learning models for green vehicle technology.
Comparative Analysis of CIH and Christofides Algorithms for Optimal Tourist Route Planning in West Java Hadi, Nur Wafiqoh; Nurfabella, Rehsya; Wamiliana; Mustika, Mira
Integra: Journal of Integrated Mathematics and Computer Science Vol. 2 No. 2 (2025): July
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20252231

Abstract

Efficient route planning plays a crucial role in supporting tourism development, particularly in regions with numerous scattered attractions such as West Java, Indonesia. This study addresses the Traveling Salesman Problem (TSP) by comparing two algorithmic approaches: the Cheapest Insertion Heuristic (CIH) and the Christofides algorithm, to determine the shortest tour among 20 selected tourist sites. Using travel time data obtained from Google Maps, both algorithms were implemented manually and using Python language programming. The manual application of the CIH algorithm resulted in a total travel time of 813 minutes, which was later optimized to 764 minutes after adjustments to eliminate intersecting paths. Meanwhile, the CIH algorithm implemented in Python provided a final route of 717 minutes. In contrast, the Christofides algorithm yielded consistent results for both manual and Python-based calculations, producing a tour with a total travel time of 746 minutes. The findings suggest that the CIH algorithm using Python language offers the most efficient route in this case study. This research contributes to the development of intelligent tour planning systems and can be a valuable reference for optimizing regional tourism logistics.
Dynamic Modeling of Energy Data: World Crude Oil and Coal Prices 2017-2023 (A State-Space Model Analysis of Multivariate Time Series) Russel, Edwin; Wamiliana; Usman, Mustofa; Elfaki, Faiz AM; Adnan, Arisman; Lindrianasari
Science and Technology Indonesia Vol. 10 No. 4 (2025): October
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2025.10.4.1301-1311

Abstract

The analysis of global crude oil and coal prices has attracted considerable research interest, as these prices significantly affect both society and industry, making the topic highly relevant for governments and policy makers. This study examines the correlation between global coal and crude oil prices from 2017 to 2023. It analyzes the behavior of these price series using a unit root test and develops an optimal model for conducting a Granger-causality analysis. To forecast crude oil and coal prices for the next 30 periods, a state-space modeling approach is applied. The unit root test results reveal that these prices are non-stationary, suggesting that any shocks to prices will have persistent effects. The best-fitting model for the association between coal and crude oil prices is a vector autoregressive model of order two (VAR(2)). The Granger-causality results reveal that current crude oil prices are influenced by both their own past values and previous coal prices, and vice versa. Forecasts using the state-space model suggest a modest upward trend for crude oil prices over the next 30 periods, while coal prices are projected to rise more strongly.
Co-Authors Abdurrahman, Ahmad Faruq Akmal Junaidi Amansyah, Wahyu Dwi Arisman Adnan Asmiati Dian Kurniasari Elfaki, Faiz A.M Elfaki, Faiz AM Favorisen R. Lumbanraja Gamal, Mohammad Danil Hendry Hadi, Nur Wafiqoh Jani Master, Jani Lindrianasari Lumbanraja, Favorisen Rossyking Mega Sapitri, Nonik Mustika, Mira Mustofa Usman Notiragayu Nuning Nurcahyani Nur Hamzah Nurdin, Muhaymi Nurfabella, Rehsya Russel, Edwin Sawitri, Riza Taqwan Thamrin Warsono Widiarti Zaenal Abidin