Article Per Year (5 Year)
p-Index From 2021 - 2026
0.659
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Kelautan Spermonde International Journal of Science and Society (IJSOC) Indonesian Journal of Statistics and Its Applications
Kuswanto, Hedi
Unknown Affiliation
Computer Science & IT Earth & Planetary Sciences Materials Science & Nanotechnology Mathematics Social Sciences Other

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Nutrient Enrichment of Artemia salina Using the Bioencapsulation Method with Single Cell Protein Extract from Chlorella Vulgaris Saputra, Anugerah; Karim, Yusri; Zainuddin; Kuswanto, Hedi
International Journal of Science and Society Vol 7 No 1 (2025): International Journal of Science and Society (IJSOC)
Publisher : GoAcademica Research & Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54783/ijsoc.v7i1.1406

Abstract

Single Cell Protein (SCP) is a biotechnological product designed to enhance biomass or extract proteins and lipids from a given material. One of the methods to utilize single-cell protein is bioencapsulation. Bioencapsulation is a nutrient enrichment technique that involves adding specific substances to natural feed to improve its quality and quantity, thus enhancing its overall nutritional value. The single-cell protein used in this study is Chlorella vulgaris (C. vulgaris), while the bioencapsulation material or observed subject is Artemia salina (A. salina). This study aims to analyze the nutritional content based on the retention or absorption capacity of A. salina using the SCP bioencapsulation method from C. vulgaris and to determine the optimal SCP dosage for bioencapsulation in A. salina. The tested dosages in this study were 100 mg/L, 200 mg/L, 300 mg/L, and 0 mg/L (without SCP administration as a control). The results showed that the SCP retention value in A. salina was significantly different (P<0.05) across the tested dosage treatments. The highest retention value was observed at a dosage of 300 mg/L, with the highest retention of soluble protein and fat recorded at 85.65% and 0.27%, respectively. However, the overall results indicate that as the administered SCP dosage increases, the retention or absorption of SCP nutrients in A. salina also increases.
PRELIMINARY STUDY OF MICRODEBRIS CONTAMINATION IN SEDIMENT FROM THREE ESTUARIES ON THE PANGKAJENE RIVER Sukri, Nurul Magfirah; Ambeng, Ambeng; Ilham, Ilham; Tanjung, Jennyta Dhewi Darmansyah; Anshari, Muhammad Al; Kuswanto, Hedi; Zainuddin, Zarlina
Jurnal Ilmu Kelautan SPERMONDE VOLUME 8 NUMBER 2, 2022
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/jiks.v8i2.21805

Abstract

Studies on microdebris contamination in sediments at the estuary of the Pangkajene River were carried out at three stations. This study aims to observe the abundance and characteristics of microdebris in the estuary sediments of the Pangkajene River. The samples of sediment were collected using a core sampler with a diameter of 8 cm. Microdebris was extracted using the flotation method and vacuum filtration system. The particles were observed with a stereomicroscope then classified based on shape (form), size, and color. The number of particles found ranged from 2.83±2.04-4.00±1.87 item/100gr. The analysis of variance (ANOVA) showed p>0.05, therefore the abundance of microdebris between the three stations did not show a significant difference. Microdebris in Fragment form had the highest percentage compared to fibers and granules. Blue and black particles of microdebris were the most common colors. The dominant size of particles was found in the size class <100µm and 100µm-500µm. This preliminary study revealed that the microdebris occurs in the Pangkajene estuary sediments. Currently, we have not classified the types of microdebris found as microplastic, semi-synthetic debris, or natural origin. Therefore, further research is needed to verify particles using an FT-IR Microscope to determine the type of microdebris polymer.
KLASIFIKASI FAKTOR-FAKTOR PENYEBAB PENYAKIT DIABETES MELITUS DI RUMAH SAKIT UNHAS MENGGUNAKAN ALGORITMA C4.5 Ente, Dewi Rahma; Thamrin, Sri Astuti; Arifin, Samsul; Kuswanto, Hedi; Andreza, Andreza
Indonesian Journal of Statistics and Applications Vol 4 No 1 (2020)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v4i1.330

Abstract

Diabetes mellitus (DM) is one of the chronic and deadly diseases that are widely observed in various countries today. This disease continues and is increasing to a very alarming stage. This study aims to identify and see the relationship between factors that influence DM disease. The method used in this research is C4.5 algorithm which is one of the algorithms used to make predictive classifications. Classification is one of the processes in data mining that aims to find patterns in relatively large data that use the representations in the form of decision trees. This method is applied to data from medical records of patients with DM in 2014-2018 taken from the Hasanuddin University Teaching Hospital. The results obtained indicate that there are four factors that influence the prediction of a patient's DM status namely; Fasting Blood Glucose (GDP), LDL Cholesterol, Triglycerides, and Body Weight.
Exploration of Obesity Status of Indonesia Basic Health Research 2013 With Synthetic Minority Over-Sampling Techniques: Eksplorasi Status Obesitas Riset Kesehatan Dasar 2013 Indonesia dengan Teknik Synthetic Minority Over-Sampling Thamrin, Sri Astuti; Sidik, Dian; Kuswanto, Hedi; Lawi, Armin; Ansariadi, Ansariadi
Indonesian Journal of Statistics and Applications Vol 5 No 1 (2021)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i1p75-91

Abstract

The accuracy of the data class is very important in classification with a machine learning approach. The more accurate the existing data sets and classes, the better the output generated by machine learning. In fact, classification can experience imbalance class data in which each class does not have the same portion of the data set it has. The existence of data imbalance will affect the classification accuracy. One of the easiest ways to correct imbalanced data classes is to balance it. This study aims to explore the problem of data class imbalance in the medium case dataset and to address the imbalance of data classes as well. The Synthetic Minority Over-Sampling Technique (SMOTE) method is used to overcome the problem of class imbalance in obesity status in Indonesia 2013 Basic Health Research (RISKESDAS). The results show that the number of obese class (13.9%) and non-obese class (84.6%). This means that there is an imbalance in the data class with moderate criteria. Moreover, SMOTE with over-sampling 600% can improve the level of minor classes (obesity). As consequence, the classes of obesity status balanced. Therefore, SMOTE technique was better compared to without SMOTE in exploring the obesity status of Indonesia RISKESDAS 2013.
Co-Authors Ambeng Ambeng, Ambeng Andreza, Andreza Ansariadi Ansariadi Anshari, Muhammad Al Armin Lawi Dian Sidik Ente, Dewi Rahma Ilham Ilham Karim, Yusri Samsul Arifin Saputra, Anugerah Sri Astuti Thamrin Sukri, Nurul Magfirah Tanjung, Jennyta Dhewi Darmansyah Zainuddin Zainuddin, Zarlina