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All Journal Jurnal Mahasiswa TEUB ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Jurnal Valuasi : Jurnal Ilmiah Ilmu Manajemen dan Kewirausahaan Journal of Artificial Intelligence and Digital Business Ranah Research : Journal of Multidisciplinary Research and Development Al-Bidayah : Jurnal Pendidikan Dasar Islam
Muhammad Aswin
Dept. of Mechanical Engineering, Brawijaya, University Malang
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Transportation Other

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SISTEM MONITORING UDARA HASIL PEMBAKARAN SAMPAH Fathonni, Mochammad Cyrilla; Maulana, Eka; Aswin, Muhammad
Jurnal Mahasiswa TEUB Vol. 12 No. 1 (2024)
Publisher : Jurnal Mahasiswa TEUB

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Abstract

Waste incineration is one of the solutions to reduce the amount of waste. This combustion can be useful for breaking down solid waste, but the process of burning waste can produce harmful residual gas emissions. So in this study, a trial was conducted using incinerator technology, an incinerator is a device that functions to burn garbage or waste in solid form and is operated by utilizing combustion technology at a certain temperature. This research was conducted to present a solution by measuring and filteringthe remnants of waste combustion gas emissions which are very dangerous for the human respiratory system. From the description of these problems, a tool is needed that can measure and filter the remnants of waste combustion emission gas. So one way that can be done is by monitoring how bad the levels of CO and CO2 gas contained in the remaining combustion and then binding or filtering these gases using precipitator technology so that the air that will come out of the remains of dangerous combustion that can disturb humans can be reduced. Keywords: Waste incineration, incinerators, precipitators, CO gas, and CO2 gas.
SISTEM IDENTIFIKASI PENYAKIT KATARAK MENGGUNAKAN SIAMESE CONVOLUTIONAL NEURAL NETWORK (SCNN) Imran, Azzam Zhafran; Rahmadwati, n/a; Aswin, Muhammad
Jurnal Mahasiswa TEUB Vol. 12 No. 3 (2024)
Publisher : Jurnal Mahasiswa TEUB

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Abstract

This study aims to detect cataract disease in retinal images obtained from retinal scans using a Siamese Convolutional Neural Network (SCNN) model. The Dataset used consists of retinal images captured directly from patients using an ophthalmoscope and collected from various sources. The Dataset includes images showing cataract disease as well as images from normal eyes. These images are then converted to grayscale to facilitate feature extraction, enhanced using Histogram equalization, then paired and labeled for use in the SCNN model. The data is divided into training, validation, and test sets for model training and testing. Training is conducted using the Tensorflow Keras framework with the SCNN model. Testing is performed in three stages: first, system performance testing with the use of Histogram equalization; second, learning parameter variations; and third, testing the identification of the SCNN model to detect cataracts. The best model is obtained using 100 epochs, RMSProp optimizer, and Binary Crossentropy loss function, achieving a test accuracy of 91.25% with a prediction time of 0.1113 seconds. Thus, an SCNN model has been successfully developed and implemented to detect cataract disease in the eye. Keywords— Cataract, Histogram equalization, Siamese Convolutional Neural Network (SCNN)
INTERNALIZATION OF HUMANISTIC VALUES FOR EARLY AGES CHILDREN IN FACING PANDEMIC COVID-19 Asfiati, Asfiati; Sutrisno, Sutrisno; Mahdi, Nur Imam; Aswin, Muhammad
Al-Bidayah : Jurnal Pendidikan Dasar Islam Vol. 12 No. 2 (2020): Al-Bidayah : jurnal pendidikan dasar Islam
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/al-bidayah.v12i2.578

Abstract

This research discusses the internalization of human values in children facing the COVID-19 pandemic in Padangsidimpuan. It was found that there were actions that were inappropriate for mothers, teachers and the community. Mothers understand the COVID-19 pandemic from a negative point of view. Mother forbids the children to see each other. The teacher advised the children not to leave the house. People advise children not to play outside of parental guidance. These are all inappropriate actions in understanding social distancing and staying at home as one of the government's appeals. However, it can follow play, study, and gather protocols. Therefore, it is necessary to conduct research on how the actions of mothers, teachers and society in children face the COVID-19 pandemic? How to internalize human values against the COVID-19 pandemic in Padangsidimpuan City? The results of the study found that mothers, teachers, and the community provided a more appropriate understanding of children and instilled the importance of being grateful to Allah SWT, feeling empathy for children whose parents were indicated to have COVID-19 and internalizing egalitarian, humanitarian attitudes, namely respect, care, share, strengthen hearts, and put forward identity so that life becomes useful.
Pengenalan Pola Dasar Angka berdasarkan Gerakan Tangan menggunakan Machine Learning NOR, SYAFRIYADI; MUSLIM, MUHAMMAD AZIZ; ASWIN, MUHAMMAD
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 10, No 3: Published July 2022
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v10i3.595

Abstract

ABSTRAKPengenalan gerakan tangan dianggap sebagai bagian penting dari interaksi manusia komputer, memungkinkan komputer untuk mengenali dan menafsirkan gerakan tangan dan menjalankan perintah. Penggunaan machine learning dimanfaatkan untuk mencari tren dan pola yang berbeda. Namun, tantangan untuk menerapkan machine learning menjadi bagaimana memilih di antara berbagai model berbeda digunakan untuk kumpulan data atau kasus berbeda. Tujuan dari penelitian ini adalah mengukur kinerja model machine learning yang diusulkan dengan pemilihan hyperparameter yang sesuai dalam mengenali 10 pola angka berdasarkan gerakan tangan di udara. Dalam makalah ini, model KNN, SVM, dan ANN-PSO diusulkan. Eksperimen dilakukan dengan mengumpulkan data gerakan yang berasal dari MPU-6050. Kinerja metode yang diusulkan dievaluasi menggunakan metrik standar seperti akurasi klasifikasi, presisi, recall, f1-score, dan AUC-ROC. Hasilnya menunjukkan bahwa akurasi rata-rata mencapai 87%.Kata kunci: HCI, hand gesture recognition, machine learning, MPU-6050, pola ABSTRACTHand gesture recognition is considered an essential part of human-computer interaction (HCI), enabling computers to recognize and interpret hand gesturesand execute  commands. The use of machine learning is utilized to look for different trends and patterns. However, the challenge for implementing machine learning becomes how to choose between different models used for different datasets or cases. This research aims to measure the performance of the proposed machine learning model by selecting the appropriate hyperparameters in recognizing 10 number patterns based on hand gestures in the air. In this paper, KNN, SVM, and ANN-PSO models are proposed. Experiments were carried by collecting gesture data from MPU-6050. The performance of the proposed method was evaluated using standard metrics such as classification accuracy, precision, recall, f1-score, and AUC-ROC. The results show that the average accuracy reaches 87%.Keywords: HCI, hand gesture recognition, machine learning, MPU-6050, pattern 
Identifikasi Penyakit Katarak berdasarkan Citra Fundus menggunakan Siamese Convolutional Neural Network RAHMADWATI, RAHMADWATI; IMRAN, AZZAM ZAHFRAN; ASWIN, MUHAMMAD; FERDIANA, KHAIRUNISA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 4: Published October 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i4.838

Abstract

ABSTRAKKatarak merupakan penyakit yang dipengaruhi oleh faktor-faktor tertentu seperti usia, aktivitas dan penderita penyakit genetik seperti diabetes, hipertensi, asam urat serta riwayat keluarga katarak. Diagnosis penyakit katarak ini dapat dipengaruhi oleh faktor subyektif seperti pengalaman dan keahlian dokter. Untuk mengatasi hal tersebut dan menurunkan tingkat subyektivitas diperlukan pendekatan yang akurat dan konsisten yaitu sistem identifikasi penyakit katarak terbantukan komputer. Penelitian ini bertujuan sebagai deteksi dini katarak. Metode SCNN digunakan untuk mengidentifikasi citra fundus mata katarak. Fine tuning parameter SCNN memberikan performa yang baik pada proses pelatihan dan pengujian yaitu 100 epoch, optimizer : RMS Prop dan loss function Binary Crossentropy. Performansi yang diberikan yaitu akurasi 91,25%, kepresisian 91%.Kata kunci: penyakit katarak, siamese convolutional neural network, citra fundus. ABSTRACTThe cataract is a disease that influenced by certain factors such as age, activity and people with genetic disease such as diabetes, hypertension, uric acid and family history of cataract. The diagnosis of cataracts based on opthamologist experience and expertise which signifies a level of a diagnostic subjectivities. In order to overcome that problem and reduce the level of subjectivity, the need for an accurate and consistent computer aided identification for cataract disease is inevitable. This research aims to as an early detection of cataracts. The SCNN is applied for identify the cataract disease based on eye fundus image. Fine tuning SCNN parameters which provide good performances in the training and testing process with 100 epochs, RMSProp optimizer, Binary Crossentropy Loss function.This system gives promising result with the accuracy 91,25% , precision level is 91%.Keywords: cataract disease, siamese convolutional neural network, fundus images
ANALISIS EFEKTIVITAS PROGRAM PENGOLAHAN WIRAUSAHA PESANTREN AL FATH KENDARI DALAM MENINGKATKAN KETERAMPILAN DAN JIWA WIRAUSAHA SANTRI Wahidin, La Ode; Husriadi, Muh.; Hasan, Hasni; Aswin, Muhammad
Jurnal Valuasi: Jurnal Ilmiah Ilmu Manajemen dan Kewirausahaan Vol. 5 No. 1 (2025): Jurnal Valuasi : Jurnal Ilmiah Ilmu Manajemen dan Kewirausahaan
Publisher : LP2M Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/vls.v5i1.302

Abstract

Al Fath Kendari Islamic Boarding School has an entrepreneurial processing program that aims to improve the skills and entrepreneurial spirit of students. This study aims to analyze the effectiveness of the program in achieving its goals. The research method used is qualitative with a descriptive approach. Data was collected through interviews, observations, and documentation. Interviews were conducted with related parties, such as Islamic boarding school caregivers, entrepreneurial program administrators, and students participating in the program. Observations were carried out at the location of entrepreneurial programs and student entrepreneurial activities. The documentation collected is in the form of entrepreneurial program materials, program activity reports, and student entrepreneurial products. The results of the study show that the entrepreneurial processing program of the Al Fath Kendari Islamic Boarding School is quite effective in improving the skills and entrepreneurial spirit of students. This is evidenced by the increase in knowledge, attitudes, and skills of students in entrepreneurship. Students' knowledge about entrepreneurship has increased significantly after participating in the program. Students become more aware of the concept of entrepreneurship, types of businesses, and strategies for starting and running a business. The attitude of students towards entrepreneurship has also undergone positive changes. Students become braver to take risks, creative in looking for business opportunities, and never give up in facing challenges. The skills of students in entrepreneurship have also improved. Students are able to make business plans, conduct market analysis, and manage their business finances. The entrepreneurial processing program of the Al Fath Kendari Islamic Boarding School is quite effective in improving the skills and entrepreneurial spirit of students. This program can be a model for other Islamic boarding schools in developing entrepreneurial programs for students
Tinjauan Kuat Tekan dan Microstructure pada Mortar ECC (Engineered Cementitious Composites) dan CR (Crumb Rubber) -ECC Simbolon, Eka Silvy Maranatha; Aswin, Muhammad; Syam, Bustami
Ranah Research : Journal of Multidisciplinary Research and Development Vol. 7 No. 4 (2025): Ranah Research : Journal Of Multidisciplinary Research and Development
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/rrj.v7i4.1547

Abstract

The construction industry continues to develop, which of course has a great influence on the environment. One of the reliable products is engineered cementitious composites (ECC). Usually, ECC products produce green products that are environmentally friendly. The cementitious material of ECC always generated from waste materials and by-products. Meanwhile, the amount of cement used can be less than 500 kg/m3. In this study, palm shell ash (ACS) is used as a cementitious material, and crumb rubber is used as a substitute for fiber. Meanwhile, the amount of cement used is less than 265 kg/m3. In addition to green products, ECC also has superior mechanical properties. Based on the results of the compressive test at the age of 3 days for three types of ECC mortar variations (those are AME, EM and TEM), the average compressive strength was obtained in the range of 19.70-42.67 MPa. As for each type of ECC mortar that is varied with crumb rubber (2.5-12.5%), namely for FCR, CRE and TCRE variations, the average compressive strength is obtained between 17.70-37.28 MPa, there has been a decrease in strength. The addition of ACS to a certain percentage can increase the compressive strength of the ECC, where SiO2 can produce Calcium Silicate Hydrate (CSH) which is a strength contributor to the ECC. Meanwhile, crumb rubber can cause a decrease in compressive strength because it is quite compressible. If viewed from the aspect of microstructure (based on the SEM observations on EM and CRE samples only), the results of the scanning electron microscope - energy dispersive x-ray spectroscopy (SEM-EDX) Mapping test on the samples from the compression test on the ECC mortar show that the ECC mortar matrix has tighter pores and fewer microcracks compared to the crumb rubber ECC (CR-ECC) samples. However, ECC mortar is denser than CR-ECC, so the results of the microstructure have strengthened the results of the mechanical properties tests that have been carried out.
PERANCANGAN GATE SISTEM PARKIR ARMADA TRUK MENGGUNAKAN METODE OCR UNTUK DETEKSI NOMOR KENDARAAN PADA PT. GALENA PERKASA BERBASIS RASPBERRY PI Khairullah, Naufal Raihan; Maulana, Eka; Aswin, Muhammad
Jurnal Mahasiswa TEUB Vol. 13 No. 2 (2025)
Publisher : Jurnal Mahasiswa TEUB

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Abstract

Perkembangan teknologi informasi dan komunikasi telah memberikan dampak yang signifikan pada industri transportasi. Dampak dari teknologi  tersebut berperan besar dalam manajemen operasional yang salah  satunya adalah pengelolaan armada kendaraan dalam suatu perusahaan. Penggunaan IoT dalam pengelolaan autentikasi kendaraan perusahaan  dapat meningkatkan efisiensi dengan memanfaatkan data secara real-time yang dapat mengurangi waktu yang tidak produktif dan biaya operasional.  Autentikasi kendaraan perusahaan yang kurang efektif telah menjadi hambatan utama pada PT Galena Perkasa dalam memastikan ketersediaan tempat pemberentian yang memadai ketika unit antar cabang  membutuhkan tempat parkir untuk armada mereka. Oleh karena itu  penelitian ini bertujuan mengembangkan sistem parkir armada berbasis  IoT yang tidak hanya mampu memantau lokasi parkir yang tersedia secara  real-time, tetapi juga dapat mengelola alokasi parkir armada secara otomatis. Sistem ini dilengkapi kamera berbasis Optical Character  Recognition (OCR) menggunakan Rasberry Pi yang dapat mendeteksi  nomor plat kendaraan yang seusai. Berdasarkan hasil pengujian sistem  parkir armada truk yang telah dirancang dapat meningkatkan efisiensi dan  akurasi parkir, hal ini dibuktikan dengan kombinasi sudut 30° dan jarak 20  cm dalam mendeteksi 10 gambar, dimana pada sudut sudut 30°  menghasilkan akurasi 90% dan rata-rata waktu respons 1,24 detik.  Sementara itu, pada jarak 20 cm menghasilkan akurasi deteksi yang sama  optimalnya, yaitu 90%, dengan waktu respons tercepat, yakni 1,87 detik, sehingga dapat diartikan sistem dapat melakukan melakukan verifikasi cepat terhadap kendaraan yang memiliki izin parkir dan dapat  meningkatkan efisiensi waktu serta dapat memperkecil potensi terjadinya  kesalahan oleh manusia. Kata Kunci—Internet of Things (IoT), Autentikasi, Optical Character  Recognition (OCR), Raspberry Pi
Optimasi Hyperparameter Metode Convolutional Neural Network (CNN) dengan Algoritma Genetika pada Klasifikasi Kanker Melanoma Kusuma, Yobel Fernando Ilianto; Rahmadwati, n/a; Aswin, Muhammad
Jurnal Mahasiswa TEUB Vol. 13 No. 2 (2025)
Publisher : Jurnal Mahasiswa TEUB

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Abstract

Kanker melanoma merupakan kanker kulit yang mematikan, maka dari itu  diperlukan diagnosa awal yang akurat dan cepat. Salah satu metode untuk  mengatasi hal tersebut adalah dengan menggunakan metode  pembelajaran mesin yang sering digunakan dalam klasifikasi gambar yaitu convolutional neural network (CNN). Tetapi penentuan hyperparameter  dari model CNN yang optimal masih menjadi tantangan karena banyaknya  kombinasi hyperparameter yang dapat memberikan pengaruh kepada  peforma model. Pada penelitian ini memiliki tujuan untuk mengoptimasi  kombinasi hyperparameter model CNN menggunakan algoritma optimasi,  yaitu genetic algorithm (GA) untuk meningkatkan akurasi klasifikasi. Hyperparameter yang dioptimasi terdiri dari jumlah filter dan ukuran  kernel pada tiap lapisan konvolusi. Dataset yang digunakan dalam  penelitian ini terdiri dari data pelatihan sebanyak 9605 gambar dan data uji sebanyak 1000 yang dibagi menjadi 2 kategori yaitu benign dan malignant.  Hasil penelitian menunjukkan bahwa model CNN yang tidak dioptimasi hyperparameternya memiliki akurasi data pelatihan 91,32% dan akurasi  data uji 88,9%. Sedangkan pada model CNN yang dioptimasi didapatkan  akurasi pelatihan terbaik pada 92,55% dan akurasi data uji 90,7%. Kata Kunci—Kanker melanoma, Pembelajaran mesin, Convolution neural network, Algoritma Genetika.
ANALISIS PERFORMANSI ALGORITMA RANDOM FOREST, LOGISTIC REGRESSION, DAN DECISION TREE UNTUK MELAKUKAN KLASIFIKASI SERANGAN SIBER Kuswardana, Ega Ferdian; Setyawan, Raden Arief; Aswin, Muhammad
Jurnal Mahasiswa TEUB Vol. 13 No. 4 (2025)
Publisher : Jurnal Mahasiswa TEUB

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Abstract

Intrusion Detection System (IDS) berperanpenting dalam mendeteksi serangan siber, termasukAdvanced Persistent Threat (APT) yang bersifatkompleks dan tersembunyi. Penelitian ini mengusulkanpendekatan klasifikasi berlapis (multilayer classification)yang terdiri dari dua tahap: klasifikasi awal untukmembedakan trafik APT, Non-APT, dan Normal, sertaklasifikasi utama untuk mengidentifikasi jenis serangansecara lebih spesifik. Model dibangun menggunakankombinasi algoritma Random Forest, Decision Tree, danLogistic Regression. Hasil menunjukkan bahwakombinasi Decision Tree dan Random Forest (DT+RF)menghasilkan akurasi terbaik, yaitu 97% untuk dataserangan dan 99% secara keseluruhan. Dibandingkanpenelitian sebelumnya, pendekatan ini menunjukkanpeningkatan nilai precision dan recall pada sebagian besarkategori serangan. Namun, pengujian terhadap data realworld menunjukkan tantangan dalam generalisasi model,menandakan perlunya pengembangan lebih lanjut agarlebih adaptif terhadap kondisi lalu lintas nyata.Kata Kunci— IDS, Advanced Persistent Threat,Multilayer klasifikasi, Random Forest, Decision Tree,real-world data.
Co-Authors Adharul Muttaqin Al-Mukhlasin, Sultan Ainnur Ridwan Alaydrus Amsal Sahban, Muhammad Angger Abdul Razak Asfiati, Asfiati Bustami Syam Citta, Andi Batary Fathonni, Mochammad Cyrilla FERDIANA, KHAIRUNISA Harry Soekotjo Dachlan Hasan, Hasni Hendra Suprayogi IMRAN, AZZAM ZAHFRAN Imran, Azzam Zhafran Khairullah, Naufal Raihan Kusnadi, Vanny Kusuma, Yobel Fernando Ilianto Kuswardana, Ega Ferdian La Ode Wahidin Luthfia, Sarah Aqila Mahdi, Nur Imam Maulana, Eka Mediyanto, Ralfie Mirza Merinda Lestandy Muh. Husriadi Muhammad Aziz Muslim Nor, Syafriyadi Pambudi, Muhammad Farrel Putra Raden Arief Setyawan Rahmadwati Rahmadwati Rahmadwati, n/a Simbolon, Eka Silvy Maranatha Sutrisno, Sutrisno Zainul Abidin