Article Per Year (5 Year)
p-Index From 2021 - 2026
3.731
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Keteknikan Pertanian Tropis dan Biosistem Prosiding Seminar Matematika dan Pendidikan Matematik UNEJ e-Proceeding Jurnal Matematika: MANTIK Jurnal Ilmiah Soulmath : Jurnal Edukasi Pendidikan Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Indonesian Journal of Combinatorics CGANT JOURNAL OF MATHEMATICS AND APPLICATIONS Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Dedication : Jurnal Pengabdian Masyarakat
Ika Hesti Agustin, Ika Hesti
Department Of Mathematics, University Of Jember, Indonesia.
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 55 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 55 Documents
Search

 2   3   4   5   6 
Optimizing Data Classification in Support Vector Machines Using Metaheuristic Algorithms Awalin, Qonita Ilmi; Agustin, Ika Hesti; Hadi, Alfian Futuhul; Dafik, Dafik; Sunder, R.
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 9, No 2 (2024): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v9i2.29320

Abstract

To categorize patient diagnosis data related to Chronic Kidney Disease (CKD), this study compares the classification performance of Support Vector Machines (SVM) enhanced by Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). CKD is a severe illness in which the kidneys fail to adequately filter blood and perform their normal functions. This study utilized secondary data consisting of patient conditions and health information. Based on references from CKD-related journals, 15 independent variables and one dependent variable were selected from an initial set of 54 variables. To address the issue of unbalanced data, an oversampling technique was applied, and the data was subsequently split into 80% for training and 20% for testing. During the training phase, SVM-PSO and SVM-GA models were developed, and the gamma value was optimized using the RBF kernel function of SVM. The results indicated that in classifying CKD patient diagnosis data, the SVM-PSO model (97.54% accuracy) outperformed the SVM-GA model (97.37% accuracy). This finding suggests that PSO-based hyperparameter optimization yields a superior model for data classification
The Reflexive H-Strength on Some Graphs Sullystiawati, Lusia Herni; Marsidi, Marsidi; Putra, Eric Dwi; Agustin, Ika Hesti
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 9, No 1 (2024): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v9i1.23172

Abstract

Let G be a connected, simple, and undirected graph with a vertex set V(G) and an edge set E(G).  The irregular reflexive -labeling is defined by the function  and  such that  if  and  if , where  max . The irregular reflexive  labeling is called an -irregular reflexive -labeling of the graph  if every two different sub graphs  and  isomorphic to  it holds , where  for the sub graph . The minimum  for graph  which has an -irregular reflexive -labelling is called the reflexive  strength of the graph  and denoted by . In this paper we determine the lower bound of the reflexive  strength of some subgraphs,  on , the sub graph  on  the sub graph  on  and the sub graph  on .
On Local Antimagic b-Coloring and Its Application for STGNN Time Series Forecasting on Horizontal Farming R. Sunder; Ika Hesti Agustin; Dafik Dafik; Ika Nur Maylisa; N. Mohanapriya; Marsidi Marsidi
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i1.29968

Abstract

This article discusses a local antimagic coloring which is a combination between antimagic labeling and coloring. It is a new notion. We define a vertex weight of  as  where  is the set of edges incident to . The bijection  is said to be a local antimagic labeling if for any two adjacent vertices, their vertex weights must be distinct. Furthermore  a coloring of a graph is a proper coloring of the vertices of  such that in each color class there exists a vertex having neighbors in all other  color classes. If we assign color on each vertex by the vertex weight  such that it induces a graph coloring satisfying coloring property, then this concept falls into a local antimagic coloring of graph. A local antimagic chromatic number, denoted by , is the maximum number of colors chosen for any colorings generated by local antimagic coloring of . In this paper we initiate to explore some new lemmas or theorems regarding to . Furthermore, to see the robust application of local antimagic coloring, at the end of this paper we will analyse the implementation of local antimagic coloring on Graph Neural Networks (GNN) multi-step time series forecasting on for NPK (Nitrogen, Phosphorus, and Potassium) concentration of companion plantations.
Improving Teachers’ Competence in Designing Contextual STEM-Based Learning Activities through Training and Mentoring Ika Hesti Agustin; Dafik; Marsidi; Kiswara Agung Santoso; Kusbudiono
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 1 (2026): Juli 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i1.1311

Abstract

The development of twenty-first-century competencies requires teachers to design contextual and problem-oriented learning activities. However, many teachers still face difficulties in translating STEM concepts into practical classroom activities. This community service program aimed to improve teachers’ competence in designing contextual STEM-based learning activities through training and mentoring. The program was conducted at CDAST, University of Jember, from February to March 2026, involving 25 teachers from various subject areas. The activities included needs identification, preparation of materials and templates, delivery of STEM concepts, demonstration of simple STEM activities, group workshops, mentoring, presentation, and evaluation. Data were collected through observation, questionnaires, and product assessment using a rubric. The results showed that participants produced five STEM Learning Activity designs. Participant responses were highly positive, with all indicators exceeding 90%, while product assessment scores ranged from 2.60 to 2.80 on a three-point scale. These findings indicate that practice-based training and mentoring effectively support teachers in developing applicable STEM learning designs.
Deep Neural Network-Based Estimation of Irrigation Water Requirements for Verticulture and Its Application in Irrigation Management Suhardi; Dafik; Agustin, Ika Hesti; Marhaenanto, Bambang
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 14 No. 2 (2026): August 2026
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/

Abstract

Vertical farming is a crop cultivation system with a tiered planting medium configuration designed to optimize accessibility, maintenance, and harvesting efficiency. The implementation of modern technology based on environmental sensors allows real-time monitoring of microclimate parameters to support precise irrigation management through estimation of evapotranspiration rates (ETo). This study aims to evaluate and estimate ETo values in vertical farming systems using a DNN architecture. Estimation is carried out through Python programming language simulations on the Google Colaboratory platform using a pre-trained DNN model (4 hidden layers) based on input data of average temperature (Tmean) and average relative humidity (RHmean) over a 4-hours duration. The implemented DNN model was validated against actual ETo data in previous studies to ensure the reliability of predictions. The results show that DNN-based evapotranspiration values are significantly influenced by temperature and relative humidity factors. Furthermore, evapotranspiration values, plant growth phases, and planting area are variables needed to calculate irrigation water requirements in the vegetative, generative, and final phases, which require 6.41 liters, 22.85 liters, and 21.73 liters, respectively. Thus, the use of the validated DNN model is proven to be a reliable predictive instrument for precisely determining crop water requirements to achieve more efficient irrigation management.
Co-Authors A. Y. Harsya Agustina Muharromah, Agustina Alfian Futuhul Hadi Alfian Yulia Harsya, Alfian Yulia Antonius Cahya Prihandoko Arika Indah Kriatiana Awalin, Qonita Ilmi Bambang Marhaenanto Cangul, Ismail Naci D. Dafik Dafik Dafik Dafik Dafik Dwi Agustin Retnowardani Dwi Noviani Sulisawati Firdaus Ubaidillah, Firdaus Firdausiyah, Iftitahul Gembong A. W. Hani'ah Zakin Herninda Lucky Oktaviana Ida Ariska Ika Nur Maylisa Imro’atun Rofikah Ismail Naci Cangul Jannah, Excelsa Suli Wildhatul Karinda Rizqy Aprilia, Karinda Rizqy Kiki Kurdianto Kiswara Agung Santoso Kosala Dwidja Purnomo Kurniawati, Elsa Yuli Kusbudiono Kusbudiono Kusbudiono, Kusbudiono Larasati, Indry Mardiyah, Fitriyatul Marsidi Marsidi Marsidi Marsidi Mohanapriya, N. Mursyidah, Indah Lutfiyatul N. Mohanapriya N. Mohanapriya Novian Nur Fatihah Nur Asia Jamil, Nur Asia Nuraeni Mauliddatul Fikria Prihandini, Rafiantika Megahnia Putra, Eric Dwi Putri Rizky H.P, Putri Rizky R. Sunder Rafiantika Megahnia Prihandini Rahman, Md. Saidur Reyka Bella Desvandai Ridho Alfarisi, Ridho Riza Nurfadila Robiatul Adawiyah Rosita, Merlinda S Slamin Sherly Citra Wuni, Sherly Citra Sih Muhni Yunika, Sih Muhni Siswono, Hendrik Siti Aminatus Solehah Siti Latifah Suhardi Sullystiawati, Lusia Herni Sunder, R. Ukas Alif Fuadi Viqedina Rizky Noviyanti Yessy Eki Fajar Reksi