Article Per Year (5 Year)
p-Index From 2021 - 2026
1.203
P-Index
This Author published in this journals
All Journal PROSIDING SEMINAR KIMIA Sinkron : Jurnal dan Penelitian Teknik Informatika Prima Abdika: Jurnal Pengabdian Masyarakat CHEDS: Journal of Chemistry, Education, and Science Jurnal Ilmiah Teknik dan Sains (JITS) Journal of Information Technology, Software Engineering and Computer Science
Maulidna, Maulidna
Politeknik Teknologi Kimia Industri
Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Education Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 6 Documents
Search

 1 
ANTIOXIDANT ACTIVITY OF BLUMEA BALSAMIFERA L. LEAVES EXTRACTS Binawati Ginting; Maulidna Maulidna; Nurdin Nurdin; Aida Lisma
PROSIDING SEMINAR KIMIA Prosiding SNKT Himpunan Mahasiswa Kimia FMIPA UNMUL 2021
Publisher : PROSIDING SEMINAR KIMIA

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

Abstract

Blumea balsamifera L leaves were isolated and tested for antioxidant activity using the 1,1-diphenyl-2-picrylhydrazyl(DPPH) method. B. balsamifera leaves were macerated as much as 1300 gram using a methanol solvent thenpartitioned with petroleum ether, n-hexane, and extracted with ethyl acetate and acetone to obtain petroleum ether, nhexane, ethyl acetate, acetone and methanol extracts by weight and% yield respectively, namely 6.34 g (5.43%), 4.97 g(4.25%), 7.34 g (6.28%), 14.14 g (12.11%) dan 5.66 (4.85%). Phytochemical tests of petroleum ether and n-hexaneextracts showed the presence of steroid compounds, while ethyl acetate, acetone, and methanol extracts showed thepresence of alkaloids, saponins, flavonoids, terpenoids, and phenolic compounds. The antioxidant activity test ofpetroleum ether, n-hexane, ethyl acetate, acetone, and methanol extracts obtained IC50 values respectively 177.47 ppm,192.66 ppm, 4.28 ppm, 7.33 ppm and 8.61 ppm. Acetone extract of B. balsamifera (BBA) is separated by chemicalcomponents using chromatography of gravity column so that the combined fraction of acetone B. balsamifera extract(BBA1-BBA11) is obtained. Antioxidant activity test of BBA1, BBA2, BBA3, BBA4, BBA5, BBA6, BBA7, BBA8, BBA9,BBA10 and BBA 11 fractions IC50 values obtained were 147.17 ppm, 81.36 ppm, 10.31 ppm, 3.84 ppm, 1.18 ppm, 3.37ppm, 6.76 ppm, 9.32 ppm, 19.26 ppm, 16.82 ppm, and 30.71 ppm. The BBA extract is characterized by its structureusing Gas Chromatography-Mass Spectrometry (GC-MS).Keywords: Blumea balsamifera L leaves, acetone extract, Antioxidant activity, 1-diphenyl-2-Pikrilhidrazil (DPPH)
Comparison of Activation Functions on Convolutional Neural Networks (CNN) to Identify Mung Bean Quality Karo Karo, Ichwanul Muslim; Karo Karo, Justaman Arifin; Ginting, Manan; Yunianto, Yunianto; Hariyanto, Hariyanto; Nelza, Novia; Maulidna, Maulidna
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.13107

Abstract

Mung bean production levels by farmers in Indonesia are not stable. When there is a surplus, the stock of mung beans in the warehouse will accumulate, the storage factor affects the quality of mung beans. Indicators of quality mung beans can be seen from the color and size through direct observation. However, the aspect of view and assessment and the level of health of each observer is a human error in the classification of mung bean quality so that the results are less than optimal. One alternative way to identify object quality is to use deep learning algorithms. One of the popular deep learning algorithms is convolution neural network (CNN). This study aims to build a model to classify the feasibility of mung beans. The process of building the model also goes through the image preprocessing stage. In the process of building the model, there are ten setup parameters and four setup data used to produce the best model. As a result, the best CNN algorithm model performance is obtained from data setup I, with accuracy, precision, recall and F1 score above 75%. In addition, this study also analyzes Rel U and Adam activation functions on CNN algorithm on model performance in identifying mung bean quality. CNN algorithm with Adam activation function has 92% accuracy, 92.53% precision, 91.9% recall, and 92.19% F1 score. In addition, the performance of CNN algorithm with Adam activation function is superior compared to CNN algorithm with Adam activation function and previous study
ANALISIS KADAR NaCl PADA PROSES REGENERASI RESIN DALAM PENURUNAN KESADAHAN Ca2+ DAN Mg2+ PADA PROSES WATER TREATMENT DI PT. ANY Nelza, Novia; Maulidna, Maulidna; Rachmiadji, Irwan; Barus, Adil; Donda, Donda; Darmadi, Herry
CHEDS: Journal of Chemistry, Education, and Science Vol 8, No 2 (2024)
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/cheds.v8i2.10127

Abstract

Resin merupakan bahan yang mengandung ion-ion yang dapat ditukar dengan ion-ion yang ada di dalam air. Resin sebagai media penukar ion memiliki kemampuan terbatas dalam menukar ion hingga resin jenuh. Resin yang telah mengalami kejenuhan akan diregenerasi menggunakan larutan NaCl sehingga kemampuan resin dalam menukar ion kembali efisien. Dari perhitungan yang telah dilakukan diketahui bahwa jumlah NaCl yang digunakan untuk proses regenerasi dapat ditentukan dengan menghitung jumlah zat reaktif yang ditukar resin dengan kesadahan yang terkandung dalam air. Cara penentuan tingkat kesadahan dalam air menggunakan metode titrasi kompleksometri. Dari hasil penelitian yang telah dilakukan diketahui besarnya kekerasan yang terserap sebesar 18,9387 mg/L untuk logam Ca2+ dan 9,324 mg/L untuk logam Mg2+, jumlah zat reaktif Na+ yang ditukar sebesar 14,4763 mg/L untuk Ca2+ dan 7,0462 mg/L. mg/L untuk logam Mg2+ dan jumlah NaCl yang dibutuhkan sebesar 21,1504 mg/L untuk regenerasi resin.
Sosialisasi Dasar Keselamatan dan Kesehatan Kerja Pengelasan untuk Pegawai PMT PTPN IV Dolok Ilir Sitepu, Evi Christiani; Purba, Switamy Angnitha; Sitinjak, Anna Angela; Lumbantoruan, Sorta; Kurnia, Dian; Saragih, Koko Pratama; Tarigan, Nurlianna; Manik, Toba Sastrawan; Maulidna, Maulidna; Nelza, Novia; Samiriadi, Samiriadi; Tambunan, Diman Raymond S
Prima Abdika: Jurnal Pengabdian Masyarakat Vol. 3 No. 3 (2023): Volume 3 Nomor 3 Tahun 2023
Publisher : Program Studi Pendidikan Guru Sekolah Dasar Universitas Flores Ende

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37478/abdika.v3i3.3052

Abstract

The application of Occupational Safety and health (K3) is very important in the work environment because it is closely related to the risk of accidents, safety and health when carrying out work. Various efforts have been made by the Tenera machinery factory (PMT) PTPN IV to minimize work accidents and diseases caused by work by installing warning signs, the use of complete personal protective equipment (PPE), providing good nutrition and regular health checks. However, the lack of awareness of K3 is still found in PMT PTPN IV Dolok Ilir workers. This can be seen from the still finding of minor work accidents and occupational health effects shown from the results of employee health reports. The methods used in this service activity are socialization, training, discussion on the basics of K3 welding for employees of PMT PTPN IV, so that factory employees are able to identify potential hazards that can occur in the workplace and accident prevention measures. The results of the socialization and training of welding K3 activities that have been carried out are expected to increase employee awareness of the importance of K3. So that the company is able to maintain the zero accident predicate.
Digitalisasi Perekaman Data Alat Uji Tensil Berbasis Pengukur Regangan dan Mikrokontroler Manan Ginting; Ulfani Ikhwana Purba; Ratih Paramitha; Herry Darmadi; Darry Christine Silowaty Purba; Maulidna Maulidna; Naqasya Asyrori Sidabutar; Sindi Wahyuni; Iqbal Huseini; Muhammad Vandi
Jurnal Ilmiah Teknik dan Sains (JITS) Vol. 4 No. 1 (2026): Agustus: Jurnal Ilmiah Teknik dan Sains (JITS)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat AKIPBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62278/jits.v4i1.151

Abstract

Pengukuran kekuatan tarik material merupakan bagian penting dalam rekayasa teknik untuk mengetahui sifat mekanik bahan, namun banyak mesin uji tarik skala laboratorium masih menggunakan pembacaan analog yang rawan kesalahan pembacaan (human error) dan tidak menyediakan rekam data digital secara otomatis. Penelitian ini bertujuan merancang dan menguji coba kinerja sistem perekaman data digital pada alat uji tarik menggunakan sensor strain gauge sebagai transduser gaya dan mikrokontroler sebagai unit akuisisi data. Metode penelitian meliputi perancangan sistem akuisisi data berbasis jembatan Wheatstone, modul penguat sinyal HX711, dan mikrokontroler, yang kemudian diuji coba pada lima kondisi spesimen baja karbon (satu spesimen per kondisi), yaitu tanpa perlakuan panas (original), quenching, normalizing, annealing, dan tempering. Hasil penelitian menunjukkan bahwa sistem mampu merekam seluruh proses pembebanan secara otomatis dan real time, mulai dari awal pembebanan hingga spesimen patah, serta menghasilkan pola respons sinyal yang berbeda dan konsisten antar kondisi spesimen, dengan nilai puncak bacaan sensor tertinggi pada spesimen quenching (5.122 ADC count), diikuti normalizing (3.211), tempering (2.855), original (2.794), dan terendah pada annealing (2.236). Urutan nilai puncak tersebut secara kualitatif sejalan dengan teori metalurgi mengenai pengaruh perlakuan panas terhadap kekuatan baja karbon. Kalibrasi sensor yang dilakukan pada tahap ini masih berupa kalibrasi dua titik (zero dan satu beban acuan) tanpa kurva regresi multi-titik, dan pengujian belum direplikasi dengan beberapa spesimen per kondisi, sehingga hasil penelitian ini bersifat kualitatif-komparatif sebagai pembuktian konsep (proof of concept), sedangkan validasi kuantitatif sistem sebagai instrumen pengukuran memerlukan kalibrasi multi-titik dan pembandingan terhadap instrumen acuan pada penelitian lanjutan.
Optimasi Klasifikasi Pola Detak Jantung Menggunakan Particle Swarm Optimization (PSO) dan Algoritma XGBoost Ichwanul Muslim Karo Karo; Justaman Arifin Karo Karo; Manan Ginting; Darni Paranita; Ratna Kristina Tarigan; Maulidna Maulidna
Journal of Information Technology, Software Engineering and Computer Science (ITSECS) Vol. 4 No. 4 (2026): Volume 4 Number 4 October 2026 (Issue in Progress)
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/itsecs.v4i4.372

Abstract

Pemantauan detak jantung merupakan salah satu pendekatan penting dalam mendukung deteksi dini gangguan kardiovaskular. Perkembangan Internet of Things (IoT) memungkinkan proses akuisisi data fisiologis dilakukan secara real-time melalui perangkat wearable, namun pemanfaatan data tersebut masih menghadapi tantangan dalam menghasilkan model klasifikasi yang akurat. Penelitian ini bertujuan mengoptimalkan proses klasifikasi pola detak jantung normal dan abnormal menggunakan algoritma Extreme Gradient Boosting (XGBoost) yang dipadukan dengan Particle Swarm Optimization (PSO) sebagai metode hyperparameter tuning. Dataset penelitian diperoleh dari hasil pengukuran detak jantung mahasiswa Program Studi Ilmu Komputer Universitas Negeri Medan menggunakan sensor MAX30102 yang terintegrasi pada perangkat IoT berbasis ESP32-C3 Mini. Tahapan penelitian meliputi akuisisi data, preprocessing, ekstraksi fitur statistik, pembangunan model baseline XGBoost, optimasi threshold klasifikasi menggunakan PSO, serta evaluasi performa model berdasarkan metrik accuracy, precision, recall, dan F1-score. Hasil penelitian menunjukkan bahwa optimasi PSO mampu meningkatkan performa model dari akurasi 90% (baseline) menjadi 100%, dengan threshold optimal pada rentang 68,44–97,82 BPM yang memberikan proses inferensi sederhana dan cepat. Temuan ini menunjukkan bahwa integrasi PSO dengan XGBoost efektif dan efisien untuk diterapkan pada sistem klasifikasi detak jantung berbasis IoT secara real-time
Co-Authors Aida Lisma Barus, Adil Binawati Ginting Darmadi, Herry Darni Paranita Darry Christine Silowaty Purba Donda, Donda Ginting, Manan HARIYANTO HARIYANTO Herry Darmadi Ichwanul Muslim Karo Karo Iqbal Huseini Justaman Arifin Karo Karo Karo karo, Justaman Arifin Kurnia, Dian Lumbantoruan, Sorta Manan Ginting Manik, Toba Sastrawan Muhammad Vandi Naqasya Asyrori Sidabutar Nelza, Novia Nurdin Nurdin Purba, Switamy Angnitha Rachmiadji, Irwan Ratih Paramitha Ratna Kristina Tarigan Samiriadi, Samiriadi Saragih, Koko Pratama Sindi Wahyuni Sitepu, Evi Christiani Tambunan, Diman Raymond S Tarigan, Nurlianna Ulfani Ikhwana Purba Yunianto Yunianto