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Lanthanum and Nickel Recovery from Spent Catalyst using Citric Acid: Quantitative Performance Assessment using Response Surface Method Petrus, Himawan Tri Bayu Murti; Wijaya, Ardyanto; Iskandar, Yusuf; Bratakusuma, Danu; Setiawan, Hendrik; Wiratni, Wiratni; Astuti, Widi
Metalurgi Vol 33, No 2 (2018): Metalurgi Vol. 33 No. 2 Agustus 2018
Publisher : Pusat Penelitian Metalurgi dan Material - LIPI

Heavy metals and Rare earth elements (REEs) are nowadays being used widely in many industries from electronics to petroleum industries as catalysts. However, their disposal caused serious problems to the environment. With the sharp growth in its usage, there is a better way to use and utilize valuable metals from secondary sources such as their disposal rather than using new raw materials. The aim of this work is to study the potential of citric acid as a leaching agent to extract lanthanum and nickel in various acid concentration and leaching temperature. The raw material used in this work is spent catalyst from Pertamina Refinery Unit VI, Balongan, Indonesia. The spent catalyst is decarbonized with a heat treatment at 725°C for 10 minutes before the leaching process. The leaching process used 0.1; 1; and 2 M of citric acid with a varied temperature of 30, 60, and 80°C. The lanthanum recovery was calculated by comparing the mass percentage of lanthanum before leaching process and after leaching process using Energy Dispersive X-Ray Spectroscopy (EDX). The results were analyzed by response surface methodology (RSM) and are proved to be a reliable method to depict and analyze the leaching characteristics. The molarity of the citric acid is the most significant independent variables used in the research for lanthanum recovery response. However, based on the Pareto analysis result there are no significant variables that affect the recovery of nickel. The second order polynomial fitting model is also proved to be compatible with the response of lanthanum recovery but is less compatible with nickel recovery.

Analisis Sentimen Twitter Kuliah Online Pasca Covid-19 Menggunakan Algoritma Support Vector Machine dan Naive Bayes Setiawan, Hendrik; Utami, Ema; Sudarmawan, Sudarmawan
Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 1 (2021)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v5i1.5189

The World Health Organization (WHO) COVID-19 is an infectious disease caused by the Coronavirus which originally came from an outbreak in the city of Wuhan, China in December 2019 which later became a pandemic that occurred in many countries around the world. This disease has caused the government to give a regional lockdown status to give students the status of "at home" for students to enforce online or online lectures, this has caused various sentiments given by students in responding to online lectures via social media twitter. For sentiment analysis, the researcher applies the nave Bayes algorithm and support vector machine (SVM) with the performance results obtained on the Bayes algorithm with an accuracy of 81.20%, time 9.00 seconds, recall 79.60% and precision 79.40% while for the SVM algorithm get an accuracy value of 85%, time 31.60 seconds, recall 84% and precision 83.60%, the performance results are obtained in the 1st iteration for nave Bayes and the 423th iteration for the SVM algorithm

PERSPEKTIF USHUL FIQIH ATAS ZAKAT PROFESI DALAM PEMIKIRAN FIQIH KONTEMPORER Rohmah, Yuni; Setiawan, Hendrik; Mubarriroh, Lailatul; Mamdukh, Muhammad; Latifah, Eny
JITAA : Journal Of International Taxation, Accounting And Auditing Vol 2 No 01 (2023): JITAA : Journal Of International Taxation, Accounting And Auditing
Publisher : Pusat Studi Ekonomi Publikasi Ilmiah dan Pengembangan SDM Azramedia indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62668/jitaa.v2i01.694

The purpose of this research is to find out the perspective of ushul fiqh scholars on professional zakat in contemporary fiqh thinking. The research method used is descriptive qualitative with the type of literature. The results of the study are that there are differences of opinion among contemporary scholars about the amount of professional zakat, namely 2.5% and 20%. Opinion of professional zakat with a level of 2.5%, this is because it is based on qiyas (analogous) to trade zakat. The reason is because professional workers are selling services, thus including tijarah (trade). Professional zakat is calculated based on hawl or not based on hawl. If it is based on hawl, what is subject to zakat is the accumulation (sum) of income for one year. If it is not based on hawl, then the obligation of zakat is carried out when the income reaches the nishab

Analisis Managemen Risiko dalam Produk Musyarakah Mutanaqishah Terhadap Pembiayaan KPR di Bank Syariah Indonesia (Studi Kasus Grha Syariah Indonesia Makassar) Setiawan, Hendrik; Lawang, Hasanna; Darmawangsa, Andi
El-Fata: Journal of Sharia Economics and Islamic Education Vol. 3 No. 2: OKTOBER 2024
Publisher : Fakultas Agama Islam Universitas Cokroaminoto Makassar

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

Tujuan penelitian ini adalah untuk mengetahui penerapan manajemen risiko Dalam Produk Musyarakah Mutanaqishah Pembiyaan KPR dan apa saja resiko yang timbul dalam Dalam Pembiyaan KPR menggunakan akad Musyarakah Mutanaqishah. Jenis penelitian yang di gunakan dalam penelitian ini adalah jenis penelitan studi kasus degan metode kuaitatif pendekatan deskriptif. Sumber data yang di peroleh sumber data primer dan sumber data sekunder yang dimana mengumpulkan data-data menggukan metode observasi, wawancara, dan juga dokumentasi. Hasil penelitian ini menujukkan bahwasanya akad musyarakah mutanaqisah dalam pembiayaan KPR di Bank GRHA syriah Indonesia dalam proses menagemen resiko menggunkan prisip kehati-hatian degan sesuai SOP yang ada di Bank tersebut untuk menilai kerja sama degan nasaba dalam proses pembiayaan musyarakah mutanaqisah mengguakan system 5C (character, capacity, collateral, capital dan conditional). Resiko yang sering terjadi dalam pembiayaan Musyarakah mutanaqisah adalah resiko proses pembiayaan top up, yang di mana sebelumya dalam bentuk Mudarabah.

Advanced Long Short-Term Memory (LSTM) Models for Forecasting Indonesian Stock Prices Santosa, Firman; Oktafanda, Ego; Setiawan, Hendrik; Latif, Abdul
Jurnal Galaksi Vol. 1 No. 3 (2024): Galaksi - Desember 2024
Publisher : Yayasan Sraddha Panca Widya Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70103/galaksi.v1i3.42

The Indonesian stock market is a key indicator of national economic dynamics. Blue-chip stocks, including Bank Central Asia (BBCA), Bank Rakyat Indonesia (BBRI), and Bank Mandiri (BMRI), hold significant influence due to their liquidity and impact on the market index. However, their price volatility, driven by global economic conditions, monetary policies, and market sentiment, poses challenges for accurate forecasting. This study employs the Long Short-Term Memory (LSTM) model to address these challenges. LSTM, a deep learning technique, effectively handles time series data by capturing long-term dependencies and complex price patterns. Using historical stock data from 2019 to 2024, the model was trained and optimized. Evaluation metrics, including Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE), were used to assess performance. BBCA stocks achieved the best results, with a MAPE of 0.0099 and RMSE of 128.02.The findings demonstrate LSTM's robustness in forecasting stock price trends, providing investors with valuable tools for informed decision-making. This research advances predictive analytics in financial markets, particularly in emerging economies like Indonesia, and highlights LSTM’s potential to improve accuracy in volatile environments.

PERSPEKTIF USHUL FIQIH ATAS ZAKAT PROFESI DALAM PEMIKIRAN FIQIH KONTEMPORER Rohmah, Yuni; Setiawan, Hendrik; Mubarriroh, Lailatul; Mamdukh, Muhammad; Latifah, Eny
JITAA : Journal Of International Taxation, Accounting And Auditing Vol 2 No 01 (2023): JITAA : Journal Of International Taxation, Accounting And Auditing
Publisher : Pusat Studi Ekonomi Publikasi Ilmiah dan Pengembangan SDM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62668/jitaa.v2i01.694

The purpose of this research is to find out the perspective of ushul fiqh scholars on professional zakat in contemporary fiqh thinking. The research method used is descriptive qualitative with the type of literature. The results of the study are that there are differences of opinion among contemporary scholars about the amount of professional zakat, namely 2.5% and 20%. Opinion of professional zakat with a level of 2.5%, this is because it is based on qiyas (analogous) to trade zakat. The reason is because professional workers are selling services, thus including tijarah (trade). Professional zakat is calculated based on hawl or not based on hawl. If it is based on hawl, what is subject to zakat is the accumulation (sum) of income for one year. If it is not based on hawl, then the obligation of zakat is carried out when the income reaches the nishab

Performance Analysis of SVM In Emotion Classification: A Comparative Study Of TF-IDF and Countvectorizer Fitriana, Frizka; Setiawan, Hendrik
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 2 (2025): June 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i2.8396

In today’s digital era, emotion analysis of social media comments plays a critical role in gaining deeper insights into user sentiment. This study aims to compare two text representation methods TF-IDF and CountVectorizer in enhancing the performance of the Support Vector Machine (SVM) algorithm for emotion classification. The dataset employed in this research is a subset of GoEmotions, consisting of 1,000 YouTube comments labeled with 27 distinct emotion categories. The dataset was split into training and testing sets with an 80:20 ratio. Both text representation methods were tested separately using a linear kernel in the SVM algorithm. The models were evaluated based on accuracy, precision, recall, and F1-score. The classification results show that TF-IDF slightly outperformed CountVectorizer in terms of accuracy (35% vs. 32%). However, CountVectorizer exhibited marginally better performance in precision and F1-score. These findings suggest that the choice of text representation significantly impacts emotion classification outcomes. This research contributes to the development of text-based emotion analysis systems for social media platforms.

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