Article Per Year (5 Year)
p-Index From 2021 - 2026
2.923
P-Index
This Author published in this journals
All Journal ComEngApp : Computer Engineering and Applications Journal Jurnal Riset Kimia AL ISHLAH Jurnal Pendidikan Jurnal Kajian Bahasa, Sastra dan Pengajaran (KIBASP) TOTOBUANG Communications in Science and Technology JURNAL PHOTON SeBaSa: Jurnal Pendidikan Bahasa dan Sastra Indonesia Zonasi: Jurnal Sistem Informasi Jurnal Informatika Ekonomi Bisnis Bulletin of Computer Science Research Bulletin of Information Technology (BIT) Gunung Djati Conference Series Jurnal Informatika Ekonomi Bisnis Jurnal Pengabdian Masyarakat Mandira Cendikia (JPKM-MC) Jurnal Ilmiah Multidisiplin Keilmuan Mandira Cendikia (JIMK-MC)
Jasril Jasril
STKIP YDB Lubuk Alung Sumatera Barat
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Physics Social Sciences Other

Published : 21 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 21 Documents
Search

 1   2   3 
Penggunaan Convolutional Neural Network NASNetLarge Dalam Klasifikasi Citra Daging Babi dan Sapi Aqilah, M Alfandri; Jasril; Sanjaya, Suwanto; Insani, Fitri
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.666

Abstract

The adulteration of beef with pork is a serious issue in Indonesia, particularly for Muslim consumers who are required to consume halal products. According to a Kompas (2020) report, a case of meat adulteration involving 100 kilograms of mixed meat sold as beef was discovered in Tangerang City. This practice not only violates religious laws but also poses threats to public health and consumer trust. To address this challenge, this study adopts a deep learning approach using NASNetLarge for the classification of pork, beef, and mixed meat images. Unlike previous research that utilized EfficientNet-B2 and achieved an accuracy of 98.23%, this study’s NASNetLarge approach produced a comparably competitive accuracy of 98.03%. The dataset used consists of 1,932 images sourced from the Kaggle platform, which were processed through preprocessing and augmentation stages. The data were then split into two distribution scenarios: the entire dataset and a balanced class dataset with 90:10 and 80:20 ratios. Evaluation results show that the best parameter combination was achieved in the first scenario with a 90:10 ratio using augmented images, a learning rate of 0.001, 128 dense units, and the Adam optimizer. The model achieved the highest accuracy of 98.03%, with a precision of 98.63%, recall of 98.40%, and an F1-score of 98.50%. These results indicate that NASNetLarge is effective in accurately and consistently classifying meat images. Image augmentation significantly improved model performance, and the 90:10 data ratio yielded more optimal results compared to 80:20. These findings have the potential to support food surveillance efforts by enabling rapid and accurate detection of meat adulteration.
Pengembangan Aplikasi Pendeteksi Daging Sapi dan Babi Menggunakan Deep Learning Arsitektur EfficientNet-B6 Berbasis Android Pangestu, Yoga; Sanjaya, Suwanto; Jasril; Agustian, Surya; Safaat, Nazruddin
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 2 (June 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i2.1195

Abstract

The advancement of digital technology has generated a demand for applications that assist the public in ensuring the halal status of food products, particularly in distinguishing between beef and pork. This study aims to develop an Android-based application for detecting beef and pork using Deep Learning methods with the EfficientNet-B6 architecture, employing the eXtreme Programming software development approach. The image classification model utilizes a Convolutional Neural Network architecture integrated into a Python-based server, while the user interface is developed with Java in Android Studio. System testing was conducted using black-box methods on several Android devices, with varying room conditions and meat types. The results show that the application can classify meat with an accuracy of 66.7%, considering room conditions such as light and dark environments, and meat types including fatty and non-fatty. This application provides fast response times and a user-friendly interface. This application is expected to enable users to independently and efficiently verify the halal status of meat, thereby supporting the needs of Muslim consumers in the digital era.
Penerapan Algoritma K-Means Clustering pada Kinerja Mesin Screw press Kurnia Rahman, Fikri; Jasril; Sanjaya, Suwanto; Handayani, Lestari; Insani, Fitri
Bulletin of Information Technology (BIT) Vol 6 No 2: Juni 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i2.2002

Abstract

The screw press is one of the machines used in the process of separating oil from tanks containing Fresh Fruit Bunches (FFB). The machine consists of a twin-screw system that functions to extract oil from the pressing unit, with back pressure applied by a hydraulic double cone. The mixed fruit residue is compreWCSSd, causing the oil contained within the residue to be released due to the pressure exerted by the press machine. Maintenance and repair of machinery are eWCSSntial activities to support productive operations in any sector. Therefore, it is necessary to conduct analysis to identify patterns in machine conditions within the factory. One effective approach to discovering machine condition patterns is through clustering techniques. Clustering is a method of grouping data based on certain parameters to form clusters of objects that share similar characteristics. In this study, data were collected from PT. XYZ for the period of April 2024 to May 2024, with a total of 23,002 records. The analysis was conducted using the K-Means Clustering algorithm, with testing carried out on 3 to 15 clusters. Based on the evaluation using the Davies-Bouldin Index (DBI), the most optimal clustering result was obtained with 3 clusters, achieving the lowest DBI value of 0.386. Meanwhile, using the Elbow Method, the optimal number of clusters was determined to be 4, as indicated by the Elbow point on the WCSS graph, with a Sum of Square Error (WCSS) value of 270. Therefore, it can be concluded that the clustering results using the K-Means Clustering algorithm are relevant for identifying machine condition patterns and are expected to assist in monitoring and managing the condition of the screw press machine.
Turbofan Engine Remaining Useful Life Prediction Using 1-Dimentional Convolutional Neural Network Fauzan, Ahmad; Handayani, Lestari; Insani, Fitri; Jasril; Sanjaya, Suwanto
Computer Engineering and Applications Journal (ComEngApp) Vol. 13 No. 3 (2024)
Publisher : Universitas Sriwijaya

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

Abstract

Turbofan engines have been the dominant type of engine in aircraft for the last forty years. Ensuring the quality of these engines is crucial for flight safety, particularly for long-distance flights. However, their performance degrades over time, impacting flight safety. To address this issue, it is essential to predict potential engine failures by estimating the Remaining Useful Life (RUL) of the engines Deep learning, especially Convolutional Neural Networks (CNNs), has demonstrated exceptional proficiency in handling intricate, non-linear data, leading to improved RUL predictionsdue to their ability to process complex and non-linear data. In this project, a 1-D CNN is used to predict RUL using the NASA C-MAPSS FD001 dataset, which consists of 3 settings and 21 sensors, though sensors with stagnant readings are excluded. The dataset is normalized using min-max and z-score methods, and then segmented into sequences for input into the 1-D CNN model. Various training scenarios were evaluated, with the best RMSE of 3.26 achieved using 10 epochs, a learning rate of 0.0001, and z-score normalization. The results indicate that feature selection can produce a lower RMSE compared to scenarios without feature selection.
Pelatihan Penerapan Model Connected Untuk Meningkatkan Kemampuan Berbahasa Siswa Sekolah Dasar Jasril; Asmawati; Laspida Harti; Julian Chandra; Desi Fitria; Efrianto; Winda Azmi
Jurnal Pengabdian Masyarakat Mandira Cendikia Vol. 4 No. 7 (2025)
Publisher : YAYASAN PENDIDIKAN MANDIRA CENDIKIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70570/jpkmmc.v4i7.1816

Abstract

Pengabdian kepada masyarakat ini bertujuan meningkatkan kompetensi guru dalam merancang dan melaksanakan pembelajaran menggunakan model connected dalam rangka meningkatkan keterampilan berbahasa siswa. Kegiatan ini dilakukan melalui tiga tahap utama: (1) persiapan, meliputi koordinasi dengan sekolah mitra, observasi awal, dan penyusunan modul pelatihan; (2) pelaksanaan, yang mencakup pelatihan guru, pendampingan implementasi di kelas, serta penggunaan media pembelajaran kontekstual; dan (3) evaluasi, melalui observasi, analisis hasil karya siswa, serta diskusi reflektif bersama guru. Metode yang digunakan adalah metode partisipatif dan kolaboratif. Hasil pelatihan menunjukkan bahwa kegiatan ini berhasil meningkatkan kapasitas guru baik secara konseptual maupun praktikal. Guru tidak hanya mendapatkan pemahaman baru tentang model connected, tetapi juga mampu merancang pembelajaran yang konkret dan relevan dengan pengembangan keterampilan berbahasa siswa sekolah dasar. Penerapan model ini selain mampu meningkatkan kemampuan berbahasa siswa secara signifikan, sekaligus menjadikan siswa lebih aktif, komunikatif, dan mampu mengungkapkan gagasan secara lisan maupun tertulis dalam pembelajaran
Biosynthesis of sulfur and selenium co-doped ZnO nanoparticles for the enhanced photocatalytic treatment of industrial wastewater Sulistyo Rini, Ari; Sitorus, Afrida Helena; Rati, Yolanda; Taer, Erman; Usman, Zulkarnain; Jasril; Umar, Akrajas Ali
Communications in Science and Technology Vol 10 No 1 (2025)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.10.1.2025.1539

Abstract

Although ZnO photocatalysts show potential for wastewater treatment, their low efficiency limits the commercialization. To address this problem, we investigated the effect of co-doping ZnO with selenium (4%, fixed) and sulfur (0.5, 1, and 1.5 wt%). The catalysts were synthesized using Matoa leaf extract and zinc nitrate hexahydrate while being subjected to 540 W microwave irradiation. UV-Vis analysis revealed absorption peaks at 340-398 nm with sulfur doping increasing the band gap. XRD confirmed the preservation of the hexagonal wurtzite structure, while FESEM images showed a morphological transformation from nanoflowers to petal flakes with increasing sulfur content. EDX analysis confirmed the presence of S, Se, Zn, and O, while FTIR analysis identified OH groups from the extract in the nanoparticles. BET surface area was found to progressively reduced from 24.58 to 16.86 m²/g with sulfur doping. The co-doped catalyst with 0.5 wt% sulfur (0.5S(4Se-ZnO)) demonstrated the highest degradation of 4-nitrophenol at 99.69%, indicating its applicability in industrial wastewater treatment. These findings indicate that the Se/S co-doped ZnO, prepared via a green synthesis route, holds a strong promise as an efficient and practical photocatalyst for addressing environmental pollution in a sustainable and economical manner.
Synthesis of Pyridazinone Derivatives Substituted with Methoxy with Phenyl Hydrazine and In Silico Test of Anticancer Activity Zulmy, Winda Permata; Sholihah, Putri Mar Atus; Yuda Teruna, Hilwan; Jasril
Jurnal Riset Kimia Vol. 16 No. 2 (2025): September
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jrk.v16i2.809

Abstract

The synthesis of pyridazinone derivatives has gained increasing attention due to their diverse biological activities, particularly as anticancer agents. In this study, novel pyridazinone derivatives substituted with methoxy groups and phenyl hydrazine were synthesized through a multi-step reaction pathway, starting from methoxyacetophenone and glyoxylic acid, followed by cyclization and substitution reactions to yield the target compound 7-(2-methoxyphenyl)-2H-pyridazino[6,1-c][1,2,4]triazine-3(4H)-one. The synthesized compounds were characterized by melting point, TLC, HPLC, UV-Vis, FTIR, NMR, and MS analyses, confirming the expected structures. In silico evaluation was performed using molecular docking against estrogen receptor α (ERα) kinase domain (PDB ID: 1T46), a key protein in breast cancer progression. The docking results showed that the synthesized compounds exhibited strong binding affinities, with compound 8 displaying a binding free energy of –9.1971 kcal/mol and stable interactions with residues Cys673, Leu799, and Phe811. These values were superior compared to the natural ligand and comparable to the reference drug doxorubicin, indicating significant anticancer potential. The results suggest that structural modification of pyridazinone with methoxy and phenyl hydrazine substituents enhances its cytotoxic activity, making it a promising candidate for further development as an anticancer agent.
AUGMENTASI DATA PADA IMPLEMENTASI CONVOLUTIONAL NEURAL NETWORK ARSITEKTUR EFFICIENTNET-B3 UNTUK KLASIFIKASI PENYAKIT DAUN PADI Putri Ayuni, Desy; Jasril; Irsyad, Muhammad; Yanto, Febi; Sanjaya, Suwanto
ZONAsi: Jurnal Sistem Informasi Vol. 5 No. 2 (2023): Publication Periodic ZONAsi: Jurnal Sistem Informasi.
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v5i2.13874

Abstract

Padi adalah salah satu jenis biji-bijian dengan urutan ketiga sebagai bahan pokok makanan setelah gandum dan jagung. Jenis penyakit yang menyerang daun tanaman terdiri atas blast, brownspot, leaf smut. Pada penelitian ini metode Convolutional Neural Network dengan Arsitektur Efficientnet-B3 digunakan untuk mengklasifikasikan penyakit daun pada tanaman padi. Tujuan penelitian ini membandingkan tingkat akurasi menggunakan data tanpa augmentasi (asli) dan data yang telah di augmentasi. Augmentasi data yang digunakan brightness, rotation, dan vertical_flip. Selain itu dilakukan juga pengujian menggunakan optimizer yang berbeda yaitu optimizer RMSprop dan optimizer SGD (Stochastic Gradient Descent). Pengujian dilakukan dengan tiga model perbandingan data yaitu 90:10, 80;20 dan 70:30. Hasil pengujian memperlihatkan akurasi tertinggi menggunakan data asli pada rasio 70:30 yaitu sebesar 92.39% dengan optimizer RMSprop. Sedangkan untuk akurasi tertinggi menggunakan data augmentasi terdapat pada rasio 90:10 yaitu sebesar 98.91% dengan optimizer RMSprop.
Implementasi Pemanfaatan Permainan Dalam Pembelajaran Membaca Di Sekolah Dasar Jasril; Asmawati; Laspida Harti
Jurnal Pengabdian Masyarakat Mandira Cendikia Vol. 3 No. 1 (2024)
Publisher : YAYASAN PENDIDIKAN MANDIRA CENDIKIA

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

Abstract

Membaca permulaan merupakan tahapan proses belajar membaca bagi siswa sekolah dasar kelas awal. Siswa belajar untuk memperoleh kemampuan, menguasai teknik-teknik membaca dan menangkap isi bacaan dengan baik. Oleh karena itu, guru perlu merancang pembelajaran membaca dengan baik sehingga mampu menumbuhkan kebiasan membaca sebagai suatu yang menyenangkan. Suasana belajar harus dapat diciptakan melalui kegiatan permainan bahasa dalam pembelajaran membaca. Hal itu sesuai dengan karakteristik anak yang masih senang bermain. Permainan memiliki peran penting dalam perkembangan kognitif dan sosial anak. Oleh sebab itu, strategi permainan dapat dijadikan sebagai salah satu strategi dalam pembelajaran membaca di kelas pemula. Pengabdian ini menggunakan metode permainan dengan informan siswa kelas 2 SD Negeri 16 Enam Lingkung, Kecamatan Enam Lingkung, Kabupaten Padang Pariaman, Sumatera Barat. Hasil pengabdian ini adalah pemanfaatan permainan dalam pembelajaran bahasa di sekolah dasar membuat siswa merasa senang dan riang dalam pembelajaran membaca. Dengan adanya pengabdian ini diharapkan dapat meningkatkan keterampilan membaca siswa melalui pemanfaatan permainan.
Pertarungan Jiwa Tokoh Utama Dalam Novel Kubah Karya Ahmad Tohari Jasril; Laspida Harti; Desi Fitria
Jurnal Ilmiah Multidisiplin Keilmuan Mandira Cendikia Vol. 2 No. 7 (2024)
Publisher : Yayasan Pendidikan Mandira Cendikia

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

Abstract

Penciptaan novel tidak terlepas dari konflik baik fisik maupun batin tokoh cerita (konflik batin selanjutnya ditulis pertarungan jiwa). Konflik merupakan jiwa cerita yang menggiring pembaca sampai akhir cerita. Tanpa ada konflik cerita akan datar, hambar, dan tidak menarik bagi pembaca. Penelitian ini mencoba mendeskripsikan bentuk pertarungan jiwa tokoh utama, penyebab pertarungan jiwa tokoh utama, dan penyelesaian pertarungan jiwa tokoh utama. Teori yang mendasari penelitian ini adalah teori psikoanalisis. Jenis penelitian ini adalah kualitatif deskripstif. Pengumpulan dan penganalisisan data dilakukan secara bersamaan dengan teknik baca-catat-analisis, menggunakan teknik analisis isi dan metode pembacaan heuristik dan hermeneutik. Data berbentuk kata, kalimat, dan pragraf yang mengandung pertarungan jiwa yang bersumber dari novel Kubah karya Ahmad Tohari. Hasil penelitian menyimpulkan bahwa dalam novel kubah terdapat pertarungan jiwa dalam diri Karman sebagai tokoh utama yang pengaruhi oleh id yaitu keinginan membalas sakit hati kepada H.Bakir, ego menikahi Marni setelah bekerja dan lamaran di tolak H. Bakir, dan super ego keluar dari penjara dan menyadari semua kesalahannya. Pertarungan jiwa Karman disebabkan oleh perasaan marah dan kecewa, beban masa kecil, dan perasaan ditinggalkan. Penyelesaian pertarungan jiwa tokoh utama melalui membalas sakit hati, mencari pelarian, menerima dengan sabar dan ikhlas, bertobat, dan kembali ke masyarakat.
Co-Authors Ahmad Fauzan Akrajas Ali Umar Aqilah, M Alfandri Asmawati Asmawati Asmawati Dadang Sunendar Desi Fitria Efrianto Erman Taer Febi Yanto Fitri Insani Hendra, Rudi Julian Chandra Kurnia Rahman, Fikri Laspida Hartati Laspida Harti Lestari Handayani Lira Hayu Afdetis Mana M. Aries Taufiq Mega Silfina Mimi Jamilah Muhammad Irsyad Nazruddin Safaat Novriyanto Pangestu, Yoga Putri Ayuni, Desy Rahmi Eka Putri Rati, Yolanda Saputra, M Ridho shalihah, putri Sholihah, Putri Mar Atus Sitorus, Afrida Helena Sulistyo Rini, Ari Sumiyadi Sumiyadi Surya Agustian Suwanto Sanjaya Winda Azmi Yasnur Asri Yuda Teruna, Hilwan Zulkarnain Usman Zulmy, Winda Permata