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All Journal EKSAKTA: Journal of Sciences and Data Analysis Jurnal Informatika Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control INSPIRAMATIKA Unisda Journal of Mathematics and Computer Science (UJMC) Limits: Journal of Mathematics and Its Applications International Journal of Computing Science and Applied Mathematics Contemporary Mathematics and Applications (ConMathA) Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) MATHunesa: Jurnal Ilmiah Matematika Jurnal Pengabdian Masyarakat: BAKTI KITA Limits: Journal of Mathematics and Its Applications
Siti Amiroch, Siti
Universitas Islam Darul 'Ulum Lamongan
Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Social Sciences Other

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XGB-Hybrid Fingerprint Classification Model for Virtual Screening of Meningitis Drug Compounds Candidate Mohammad Hamim Zajuli Al Faroby; Helisyah Nur Fadhilah; Siti Amiroch; Rahmat Sigit Hidayat
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 2, May 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i2.1424

Abstract

Meningitis is an infection of the lining of the brain caused by diffuse inflammation, and this condition is caused by viruses or bacteria that cause Meningitis. Prevention for this disease is still in the form of strengthening antibodies with vaccines. There is no significant compound to relieve or treat Meningitis patients. In previous studies, they got seven proteins vital to Meningitis. We continued to investigate the compounds associated with the seven proteins. We chose the in-silico process by utilizing data in an open database. We use several databases for the data collection process. After that, the compound data were extracted for bonding features and chemical elements using molecular fingerprints. We use two fingerprint methods, where both we combine with three types of combinations. The combined results produce three types of datasets with different matrix sizes. We establish the Extreme Gradient Boosting (XGB) method to form the classification model for the three datasets, select the best classification model, and compare it with other classification algorithms. The XGB model has better quality than the classification model of other algorithms. We used this model to predict and quantify compounds that strongly bind to seven vital meningitis proteins. The compound with the highest predictive score (we found more than 0.99) became a drug candidate to inhibit or neutralize Meningitis.
PENGENALAN PROGRAM STUDI MATEMATIKA DALAM KONDISI PANDEMI COVID-19 Novita Eka Chandra; Siti Alfiatur Rohmaniah; Mohammad Syaiful Pradana; Awawin Mustana Rohmah; Siti Amiroch
Jurnal Pengabdian Masyarakat : BAKTI KITA Vol 2 No 1 (2021): Jurnal Bakti Kita
Publisher : LPPM Universitas Islam Darul 'Ulum Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (615.058 KB)

Abstract

The increasingly high spread of Covid-19 pandemic cases has an impact on the field of education, especially new student admissions. In accordance with government policy, activities related to education were changed to online, so that the mathematics study program held promotional activities through online. This activity is focused on accepting new students online during the Covid-19 pandemic. Methods for implementing the activities include making materials for introducing mathematics courses through websites and social media, making flyers and banners, making profile videos, and conducting webinars. The results of the introduction of the mathematics study program in the context of socializing online new student admissions during the pandemic were very good, where more than 60% of the participants stated that the activities were very interesting and satisfying.
Classification of IGF1R ligand compounds for Identification of herbal extracts using extreme gradient boosting Mohammad Hamim Zajuli Al Faroby; Siti Amiroch; Bernadus Anggo Seno Aji; Avriono Aritonang
Jurnal Informatika Vol 16, No 3 (2022): September 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v16i3.a23286

Abstract

Diabetes Mellitus is a serious disease that requires serious treatment. The cause of this disease is due to malfunctions in insulin and insulin-producing organs. One of the proteins that become insulin signaling receptors is IGF1R, which has an important role in activating and maximizing insulin performance. In this study, we aimed to obtain herbal compounds that can activate the function of the IGF1R protein by utilizing compound data in an open database and modeling it using the ensemble method, namely extreme gradient boosting. We found that this method produces the best classification model than with other algorithms. We predicted 844 data for herbal compounds, but only 15 data met the threshold of 0.6. We got one plant from the fifteen herbal compounds, namely Zostera Marine, which was confirmed to have compounds that bind to IGF1R. These compounds have the highest probability value in the classification model that we formed compared to others.
KESULITAN SISWA DALAM MENYELESAIKAN MASALAH PENJUMLAHAN DAN PENGURANGAN DENGAN METODE JARIMATIKA DAN PEMBERIAN SCAFFOLDINGNYA Siti Daiyatul Hamidah; Ali Shodikin; Siti Amiroch
INSPIRAMATIKA Vol 5 No 2 (2019): Inspiramatika, December 2019
Publisher : Program Studi Pendidikan Matematika FKIP Universitas Islam Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/inspiramatika.v5i2.1752

Abstract

This study aims to determine the difficulty and the provision of appropriate scaffolding used by students in solving addition and subtraction problems with the Jarimatic method. As for the difficulties of students analyzed in the form of fact errors, operational errors, and principle errors as well as the form of scaffolding conducted, namely explaining, reviewing, and restructuring. The subjects in this study were 32 first grade students at SDN Sumurber. The instruments in the study were written tests and interviews. The results of this study are (1) errors of fact students still have difficulty in operating fingers, (2) errors of operation where there are still many students who still have difficulty in calculating addition and subtraction operations, (3) and principle errors occur in some more students likes to count with chimera and haste. Scafolding provided includes explaining, reviewing, and restructuring.
ANALISIS KEMAMPUAN REPRESENTASI MATEMATIS PESERTA DIDIK DITINJAU DARI KARAKTERISTIK DOMINANCE, INFLUENCE, STEADINESS, COMPLIENCE (DISC) Ida Dwi Lestari; Siti Amiroch; Heny Ekawati Haryono
INSPIRAMATIKA Vol 7 No 2 (2021): Inspiramatika: Jurnal Inovasi Pendidikan dan Pembelajaran Matematika, December 20
Publisher : Program Studi Pendidikan Matematika FKIP Universitas Islam Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/inspiramatika.v7i2.2497

Abstract

Students' mathematical representation skills still need to be improved and developed. Because when faced with questions students experience difficulties and confusion to solve, where to start, which formulas to use and how to solve them. The ability of students in the aspect of mathematical representation is not optimal. Basically, each student also has the characteristics of different ways of thinking that influence the process of representing solving mathematical problems. This study aims to determine the mathematical representation ability of students in terms of Dominance, Influence, Steadiness, Complience (DISC) characteristics. The subjects of this study were students of class X MA Raudlatul Muta'allimin Babat. This research is a qualitative research. Qualitative research concludes the research data in the form of numbers. The data collection method uses a DISC characteristic questionnaire, representation ability test and interviews. The results showed that: (1) Subjects with Dominance characteristics were able to solve all aspects of mathematical representations, namely visual representations in the form of images, equations or mathematical expressions, and written words or texts. (2) Subjects with the characteristics of Influence are able to solve two aspects of mathematical representation, namely visual representations in the form of images and equations or mathematical expressions, whereas in the aspects of words or written texts students have not been able to solve them well. (3) Subjects with Steadiness characteristics are able to solve all aspects of mathematical representations, namely visual representations in the form of images, equations or mathematical expressions, and written words or texts. all questions and able to explain well. (4) Subjects with Compliance Characteristics are able to complete one aspect, namely the visual representation aspect in the form of images, while in the form of mathematical equations or expressions, and written words or texts, students have not been able to complete it properly.
PENGENALAN PROGRAM STUDI MATEMATIKA DALAM KONDISI PANDEMI COVID-19 Novita Eka Chandra; Siti Alfiatur Rohmaniah; Mohammad Syaiful Pradana; Awawin Mustana Rohmah; Siti Amiroch
Jurnal Pengabdian Masyarakat : BAKTI KITA Vol 2 No 1 (2021): Jurnal Bakti Kita
Publisher : LPPM Universitas Islam Darul 'Ulum Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/baktikita.v2i1.2494

Abstract

The increasingly high spread of Covid-19 pandemic cases has an impact on the field of education, especially new student admissions. In accordance with government policy, activities related to education were changed to online, so that the mathematics study program held promotional activities through online. This activity is focused on accepting new students online during the Covid-19 pandemic. Methods for implementing the activities include making materials for introducing mathematics courses through websites and social media, making flyers and banners, making profile videos, and conducting webinars. The results of the introduction of the mathematics study program in the context of socializing online new student admissions during the pandemic were very good, where more than 60% of the participants stated that the activities were very interesting and satisfying.
Analisis Multiple Alignment Pada Penyebaran Epidemi Sars Cov E.G 5.1 Menggunakan Metode Neighbor - Joining Arta MS, Carly Marshanda; Amiroch, Siti; Rohmah, Awawin Mustana
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 9 No 2 (2023): Unisda Journal of Mathematics and Computer science
Publisher : Mathematics Department, Faculty of Mathematics and Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v9i2.6296

Abstract

SARS CoV-2 merupakan suatu virus yang masih menjadi topik hangat di media dan sangat menarik untuk dikaji. Apalagi SARS CoV-2 semakin bermutasi dari waktu ke waktu dan memunculkan varian jenis baru. Akhir-akhir ini dunia kembali dihebohkan dengan munculnya varian SARS CoV-2 jenis baru yang bernama varian E.G 5.1 atau biasa disebut Eris. Di Indonesia, varian E.G 5.1 pertama kali dilaporkan di Provinsi Jakarta pada 09/03/2023. Berdasarkan hal tersebut, penulis ingin mengetahui proses penyebaran Epidemi SARS CoV E.G 5.1 yang terjadi di Indonesia dengan analisis Multiple Alignment. Analisis ini memiliki beberapa tahap antara lain, melakukan analisis sistem jaringan topologi, sistem jaringan daerah mutasi dan sistem jaringan mode mutasi, sehingga diperoleh pohon filogenetik menggunakan algoritma Neighbor-Joining yang digunakan untuk menentukan awal mula penyebaran virus. Data yang digunakan adalah data 92 sekuen DNA yang diperoleh melalui GISAID. Hasil dari analisis tersebut diperoleh awal mula penyebaran SARS CoV E.G 5.1 di Indonesia yang secara singkat berawal dari Jakarta 09/03/2023, kemudian menyebar ke Bogor 20/04/23, Medan 11/05/23, Surabaya 03/07/23, Bandung 24/10/23, Riau 07/12/23, dan terakhir menyebar di Provinsi Bali (Denpasar) pada tanggal 10/12/23 dan 11/12/23.
Penerapan Fuzzy Interpolasi Spline Kubik Pada Data Pokok Lelang Di Pamekasan Nurmadhani, Nadya; Yulianto, Tony; Kuzairi, Kuzairi; Amiroch, Siti; Anekawati, Anik
Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) Vol 4 No 2 (2023): Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) Oktober 2023
Publisher : Fakultas Teknik Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31102/jatim.v4i2.2506

Abstract

Lelang sejak lama telah dikenal oleh masyarakat sebagai salah satu sarana untuk melakukan jual beli barang, Lelang merupakan mekanisme jual-beli yang diawali dengan adanya pengumuman atas penawaran barang kepada calon peserta lelang. KPKNL di Pamekasan memiliki peran yang cukup besar dalam rangka memenuhi kebutuhan masyarakat. Jual beli sistem lelang sangat membantu masyarakat untuk mempermudah melakukan transaksi jual beli dan tentu saja barang yang penulis miliki sudah terjamin dari berbagai sisi legalitasnya. Oleh karena itu, suatu perusahaan jasa harus mampu menawarkan berbagai produk untuk meningkatkan kepuasan dan memenuhi kebutuhan yang semakin beragam oleh masyarakat sebagai pemakai barang lelang. Maka dari itu, untuk mengetahui peningkatan dan penurunan jumlah lelang diperlukan suatu metode yang dapat digunakan untuk memprediksi jumlah lelang di Pamekasan, Metode yang peneliti gunakan dalam penelitian ini adalah metode fuzzy interpolasi Spline kubik. Berdasarkan hasil penelitian tersebut dapat terlihat bahwa hasil penerapan jumlah data pokok lelang di KPKNL Pamekasan dari bulan ke 50 sampai bulan ke 72 sangat mengalami peningkatan dibandingkan dari bulan ke 35 sampai bulan ke 49 yang sangat mengalami penurunan dengan nilai RMSE 0,2766 yang menghasilkan nilai eror sangat kecil.
Target Baru Pengobatan Meningitis berdasarkan Centrality Measure jaringan protein dan Self Oganizing Map. Amiroch, Siti; Hamim Zajuli al Faroby, Mohammad; Dzulfikar Fauzi, Mohammad
Limits: Journal of Mathematics and Its Applications Vol 21, No 3 (2024)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v21i3.21776

Abstract

Meningitis is a serious threat to health with potentially fatal consequences. Understanding protein interactions related to chronic conditions is crucial for the development of effective treatments. In silico analysis is considered to have greater effectiveness because it simulates through computation and tries various possibilities at a lower cost. This study aims to analyze protein-protein interactions related to Meningitis with cluster analysis techniques on undirected graphs. The proposed method is the Self Organizing Map (SOM) algorithm as a cluster. This algorithm can cluster undirected graph-based protein interaction data. Protein data involved in Meningitis disease comes from OMIM. From this data, proteins belonging to the gene locus are explored for their interactions, resulting in interaction data in the form of an undirected graph. The combination of centrality measure is used for feature engineering on undirected graph data. The main protein candidates are potentially located in the Cluster 1 model with the largest silhouette score (0.359) and Davies-Bouldin Index (1.667). The cluster has 18 proteins with the highest significance to Meningitis. From the overall centrality ranking results, the three highest significance proteins are CISH (3.921222), TNFSF10 (3.403541), and ICAM3 (2.623702) which have the potential to become Meningitis target proteins. CISH protein has the highest overall centrality score value compared to the others, so CISH protein may be a new alternative in the treatment of Meningitis.
Pattern-Based Identification of Priority Sectors for Greenhouse Gas Emission Control in Indonesia Using Self-Organizing Map Nurdini, Aisyah Tur Rif’atin; Amiroch, Siti
Contemporary Mathematics and Applications (ConMathA) Vol. 7 No. 2 (2025)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v7i2.74176

Abstract

Indonesia is one of the countries that ratified the Paris Agreement, a legally binding international treaty under the United Nations Framework Convention on Climate Change (UNFCCC) regarding greenhouse gas emissions. In line with this commitment, Indonesia is expected to prioritize emission control in sectors that contribute significantly to national emission levels. This study applies the Self-Organizing Map (SOM), a type of neural network, to cluster emission data by sector based on similarity patterns, aiming to identify priority sectors for emission control in Indonesia. The results indicate that the highest-emitting sectors are: Processes for Carbon Dioxide (CO₂), Transport for Methane (CH₄), Processes for F-Gases, and Agriculture for Nitrous Oxide (N₂O). These findings can inform government efforts to prioritize emission control policies in the Processes, Transport, and Agriculture sectors, tailored to each dominant gas type. Such recommendations are essential to support data-driven decision-making, improve national emission control strategies, and strengthen Indonesia’s position in meeting its Nationally Determined Contributions (NDCs) under the Paris Agreement. Model validation using Quantization Error (QE) produced values of 0.0218 for CO₂, 0.0207 for CH₄, 0.0040 for F-Gases, and 0.0171 for N₂O. These low values indicate high mapping accuracy and confirm that SOM is effective in capturing the distribution patterns of emission data, thus providing a scientific basis for designing more targeted mitigation strategies.  
Co-Authors Aisyah Tur Rif’atin Nurdini Ali Shodikin Anekawati, Anik Arta MS, Carly Marshanda Avriono Aritonang Awawin Mustana Rohmah Bernadus Anggo Seno AjiAji Dzulfikar Fauzi, Mohammad Eva Wahyu Listyawati Evi Eka Andini Fauzi, Muhammad Dzulfikar Fifin Nur Aini Helisyah Nur Fadhilah Heny Ekawati Haryono Ida Dwi Lestari Kiratama, Danang Kuzairi Mohammad Hamim Zajuli Al Faroby Mohammad Hamim Zajuli Al Faroby Mohammad Syaiful Pradana, Mohammad Syaiful Mu’tasim Billah Novita Eka Chandra, Novita Eka Nurdini, Aisyah Tur Rif’atin Nurmadhani, Nadya Rahmat Sigit Hidayat Siti Alfiatur Rohmaniah Siti Alfiatur Rohmaniah Siti Daiyatul Hamidah Tony Yulianto Umi Maftukhah