Kendali Optimal Produksi Lipid pada Mikroalga dengan Keterbatasan Nutrisi dan Karbondioksida Menggunakan Metode Linear Quadratik Regulator

Mikroalga memiliki kemampuan yang tinggi untuk memproduksi lipid. Semakin cepat proses pembentukan lipid oleh mikroalga, semakin cepat juga minyak yang dihasilkan. Produksi lipid pada mikroalga dipengaruhi oleh nutrisi, karbon dioksida dan proses fotosintesis. Dalam penelitian ini akan ditunjukkan verifikasi model produksi lipid pada mikroalga, agar didapatkan nilai yang optimal pada variabel state. Dengan kendali optimal produksi lipid pada mikroalga dengan faktor pengendalinya adalah substrat nutrisi dan karbon dioksida. Verifikasi model menunjukkan bahwa model produksi lipid pada mikroalga bersifat safe dengan spesifikasi yang telah ditentukan. Metode Linear Quadratic Regulator menghasilkan konsentrasi mikroalga sebesar X=33,8 mg/CL dan Ql=78,5 mg/CL ================================================================================================= The greater produced of lipids by microalgae, will increasing biomass production. The lipids produced in the microalgae with influenced by nutrients, carbon dioxide and photosynthetic process. In this research, will be proposed using model verification to get a value from the state space, thats influence in the optimal control problem. The optimal control problem of the lipids production in the microalgae will be proposed using the optimal control method. The objective function is to maximize the lipids production while the control is substrate of nutrients and carbon dioxide. The model verification can be present, its was safety system using specification before. Furthermore, the results from the Linear Quadratic Method was the microalgae can produced X=33,8 mg/CL and Ql=78,5 mg/CL

Restorasi Citra Pada Kompresi Spiht (Set Partitioning In Hierarchical Trees) Menggunakan Metode Iteratif Lanczos-Hybrid Regularization

Restorasi citra merupakan proses merekonstruksi atau mendapatkan kembali citra asli dari sebuah citra yang terdegradasi agar dapat menyerupai citra asli. Kompresi citra merupakan salah satu proses pemampatan citra yang menyebabkan citra mengalami degradasi atau penurunan kualitas. Penurunan kualitas citra terjadi pada proses kompresi loosy, salah satu contoh kompresi loosy adalah dengan metode Set Partitioning In Hierarchical Tress (SPIHT). Oleh karena itu, untuk meningkatkan kembali kualitas citra agar menyerupai citra asli maka digunakan restorasi citra dengan metode Iterative Lanczos Hybrid Regularization. Pada tugas akhir ini menggunakan citra grayscale dengan beberapa variasi resolusi citra untuk data uji coba kompresi SPIHT dan restorasi citra. Pengujian restorasi citra dengan data uji coba nilai PSNR sebesar 25 dB mengalami kenaikan nilai PSNR rata-rata sebesar 0,91 dB dan waktu komputasi 187,058 detik lebih lambat dari proses kompresi. Pada data uji coba nilai PSNR sebesar 35 dB mengalami kenaikan nilai PSNR rata rata sebesar 0,57 dB dan waktu komputasi 127,418 detik lebih cepat dari proses kompresi. Hal ini menunjukkan bahwa citra hasil restorasi dengan menggunakan metode iteratif lanczos hybrid regularization dapat meningkatkan kualitas citra ========================================================================= Image restoration is reconstructing original image from image degradation so that can be similar with original image. Image compression is one of image processing which causes image degradation or loss of quality. A decrease image quality occurs in loosy compression, an example using Set Partitioning In Hierarchical Trees. Therefore, to improve the image quality, back to resemble the original image used image restoration with iterative lanczos-hybrid regularization method. In this research using grayscale image with some variation of the image resolution for trial data compression and image restoration. Image restoration program with PSNR value by 25 dB can increased by an average of 0,91 dB and have total time elapsed about 187,058 second slowest than the compression process. At trial data PSNR value by 35 dB can increased by an average of 0,57 dB and have total time elapsed about 127,418 second fastest than the compression process. Than, this research can showed that the image restoration using iterative lanczos hybrid regularization method can increased image qualit

OPTIMAL CONTROL OF NEUTRAL LIPIDS IN MICROALGAE PRODUCTION WITH NUTRIENT LIMITATION

Consumer demand for fuel was increasing, while the supply of fuel has began dwindling. Therefore, it is necessary to undertake an effort to develop a renewable alternative energy such as usage of microalgae. Microalgae have four main components of substance i.e carbohydrates, proteins, nucleic acid and lipids. The relatively high lipid levels can be used as a source of biomass with using light, glucose, nutrients, carbon dioxide and water. Nutrient concentration is modified to keep the concentration of biomass through the dilution rate. In addition, carbon dioxide regulated also influence of microalage production in photobioreactor. Thereby, we used dilution rate and carbon dioxide mobilization as optimal control using Pontryagin Maximum Principle method to increased biomass and quota lipid production. Hence, the result is biomass increased as 4,5678% and quota lipid increased 44, 9727%

Multi-label Classification Using Vector Generalized Additive Model via Cross-Validation

Multi-label classification is a unique challenge in machine learning designed for two targets with each containing one or multiple classes. This problem can be resolved using several methods, including the classification of the targets individually or simultaneously. However, most models cannot classify the target simultaneously, and this is not expected to happen in the modeling rule. This study was conducted to propose a novel solution in the form of a Vector Generalized Additive Model Using Cross-Validation (VGAMCV) to address these problems. The proposed method leverages the Vector Generalized Additive Model (VGAM), which is a semi-parametric model combining both parametric and non-parametric components as the underlying base model. Cross-validation was also applied to tune the parameters to optimize the performance of the method. Moreover, the methodology of VGAMCV was compared with a tree-based model, Random Forest, commonly used in multi-label classification to evaluate its effectiveness based on fourteen metric scores. The results showed positive outcomes as indicated by 0.703 average accuracy and 0.601 Area Under Curve (AUC) recorded, but these improvements were not statistically significant. Meanwhile, the method offered a viable alternative for multi-label classification tasks, and its introduction served as a contribution to the expanding repertoire of methods available for this purpose

Implementation of Web Scraping on Google Search Engine for Text Collection Into Structured 2D List

Purpose: This research proposes the implementation of web scraping on Google Search Engine to collect text into a structured 2D list.Design/methodology/approach: Implementing two important stages in the process of collecting data through web scraping, namely the HTML parsing process to extract links (URL) on Google Search Engine pages, and HTML parsing process to extract the body text from website pages on each link that has been collected.Findings/result: The inputted query is adjusted to the latest issues and news in Indonesia, for example the President's important figures, the month of Ramadan and Idul Fitri, riots tragedy (stadium) and natural disasters, rising prices of basic commodities, oil and gold, as well as other news. The least number of links obtained was 56 links and the most was 151 links, while the processing time to obtain links for each of the fastest queries was 1 minute 6.3 seconds and the longest was 2 minutes 49.1 seconds. The results of scraping links from these queries were obtained from Wikipedia, Detik, Kompas, the Election Supervisory Body (Bawaslu), CNN Indonesia, the General Election Commission (KPU), Pikiran Rakyat, and others.Originality/value/state of the art: Based on previous research, this study provides an alternative to produce optimal collection of links and text from web scraping results in the form of a 2D list structure. Lists in the Python programming language can store character sequences in the form of strings and can be accessed using index keys, and manipulate text efficiently

ANALISIS PREDIKSI HARGA SAHAM SEKTOR PERBANKAN MENGGUNAKAN ALGORITMA LONG-SHORT TERMS MEMORY (LSTM)

AbstractInvesting, buying or selling activity on the stock exchange requires knowledge and skill in the field of data analysis. The movement of the curve in the stock market place is very dynamic, hence it requires data modelling to predict stock prices in order to get a price with a high degree of accuracy. Currently, machine learning has a good level of accuracy in processing and predicting data. In this work, we proposed the data modelling using the Long-Short Term Memory (LSTM) algorithm to predict stock prices. The main purpose for this research is to analyze the accuracy of the machine learning algorithm in predicting stock price data and analyzing the number of epochs in the optimal model formation. The results of our study indicate that the LSTM algorithm has an accurate level of prediction as indicated by the RMSE value and the data model obtained the variation of the epochs value.Keywords : LSTM Algorithm, Stock Price, Analysis Prediction, Machine LearningUntuk melakukan investasi atau jual beli di bursa saham memerlukan pemahaman dibidang analisis data. Pergerakan kurva pada pasar saham sangat dinamis, sehingga memerlukan pemodelan data untuk melakukan prediksi harga saham agar mendapatkan harga dengan tingkat akurasi yang tinggi. Machine Learning pada saat ini memiliki tingkat keakuratan yang baik dalam mengolah dan memprediksi data. Pada penelitian ini kami melakukan pemodelan data menggunakan algoritma Long-Short Term Memory (LSTM) untuk memprediksi harga saham. Tujuan utama pada jurnal ini adalah untuk menganalisis tingkat keakuratan algoritma Machine Learning dalam melakukan prediksi data harga saham serta melakukan analisis pada banyaknya epochs dalam pembentukan model yang optimal. Hasil penelitian kami menunjukkan bahwa algoritma LSTM memiliki tingkat prediksi yangg akurat dengan ditunjukkan pada nilai RMSE serta model data yang di dapatkan pada variasi nilai epochs.Kata Kunci : Algoritma LSTM, Harga Saham, Analisis Prediksi, Machine Learnin

Antithesis of Human Rater: Psychometric Responding to Shifts Competency Test Assessment Using Automation (AES System)

This research is part of proof tests to a combination of statistical processing methods, collecting assessment rubrics in vocational education by comparing two systems, automated essay scoring and human rater. It aims to analyze the final assessment score of essays in Akademi Komunitas Negeri (AKN) Pacitan (Pacitan’s State Community College) and Akademi Komunitas Negeri (AKN) Blitar (Blitar’s State Community College) in East Java, Indonesia. The provisional assumption is that the results show an antithesis to the assessment of human feedback with an automated system due to the conversion of scores between the rubric and the algorithm design. As the hypothesis, algorithm-based score conversion affects automated essay scoring and human rater methods, which led to antithesis feedback. The validity and reliability of the measurement maintain the scoring consistency between the two methods and the accuracy of the answers. The novelty of this article is comparing between AES system and Human Rater using statistical methods. The research shows that there is a similar result using the psychometrics approach, which indicates different metaphor expressions and language systems. Thus, the objective of this study is to provide assistance in the advancement of an information technology system that utilizes a scoring mechanism merging computer and human evaluations, employing a psychological approach known as psychometric leads

PEMANFATAAN APLIKASI CANVA SEBAGAI MEDIA PEMASARAN DI KAMPUNG KUE SURABAYA

The evolution of information technology in Industrial 4.0 and Society 5.0 makes people have to divert buying and selling activities using digital media. A cake cluster (kampung kue) in Surabaya needs a media or application based on information technology for making catalogs that can be published through social media. We offer a solution to make it easier for the sellers by using the Canva Application as a medium for cataloging and marketing the cake through many social media to attract buyers and customers. In carrying out the promotion, it is necessary to prepare the best promote the Indonesian Language, hence we also give the participant to improve the promotion skills. The other result of our training and mentoring approach during community service is a training module publication. This module provides participants with how to use the Canva Application and promotional language. Therefore, marketing and selecting strategies are the main keys in the business of the digital era. Utilizing information technology and social media has proven to have a very positive impact on increasing sales effects. Keywords: Catalog, Canva, Kampung Kue, Promotion Language Abstrak Perkembangan teknologi informasi di era Industri 4.0 dan Society 5.0 menjadikan masyarakat harus mengalihkan kegiatan jual beli melalui media digital. Salah satu komunitas di Kota Surabaya yaitu Kampung Kue membutuhkan media pembuatan katalog yang bisa dipublikasikan melalui media sosial. Solusi yang bisa kami tawarkan untuk memudahkan Ibu-Ibu penjual kue adalah dengan memanfaatkan aplikasi canva sebagai media pembuatan katalog dan memasarkan hasil katalognya melalui banyak media sosial untuk menarik pembeli dan pelanggan. Dalam melakuakan promosi dibutuhkan penyusunan Bahasa Indonesia yang baik, benar dan tepat, agar kualitas promosinya lebih baik, sehingga kami juga melatih keterampilan Ibu-Ibu di Kampung Kue dengan memberikan keterampilan promosi. Kegiatan ini menghasilkan ketertarikan Ibu-Ibu untuk memanfaatkan aplikasi canva sebesar 80% dari total jumlah peserta yang hadir selama dua hari. Salah satu hasil yang diberikan dari pelatihan dan pendampingan ini adalah modul pelatihan. Modul ini memberikan tata cara penggunaan aplikasi canva dan Bahasa promosi kepada pengusaha kue. Oleh karena itu, memasarkan dan pemilihan strategi serta media sosial menjadi kunci utama dalam usaha di era digital ini. Dengan memanfaatkan teknologi informasi dan media sosial terbukti sangat berdampak positif dalam meningkatkan hasil penjualan. Kata kunci: Katalog, Canva, Kampung Kue, Bahasa Promosi