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All Journal Jurnal Teknologi dan Manajemen Informatika CommIT (Communication & Information Technology) Jurnal TIMES Sinkron : Jurnal dan Penelitian Teknik Informatika JIKO (Jurnal Informatika dan Komputer) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JOURNAL OF APPLIED INFORMATICS AND COMPUTING METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jiko (Jurnal Informatika dan komputer) JURIKOM (Jurnal Riset Komputer) JURTEKSI Building of Informatics, Technology and Science Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Ilmiah Smart Journal of Applied Computer Science and Technology (JACOST) Bulletin of Computer Science Research Journal of Artificial Intelligence and Engineering Applications (JAIEA) Majalah Ilmiah METHODA TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Journal of Computing Theories and Applications QOSIM: Jurnal Pendidikan, Sosial & Humaniora Jurnal Ilmiah Smart Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Robet Robet
STMIK TIME
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences

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Penerapan Metode Webqual 4.0 Dalam Pengukuran Kualitas Website Awicoffee Robet; Agus Maringan Siahaan; Satriya Miharja
Bulletin of Computer Science Research Vol. 4 No. 2 (2024): Februari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v4i2.339

Abstract

The measurement of Awicoffee’s website quality was conducted with the aim of enabling the website owner to develop aspects that have low value, so that they can continue to develop in line with the times. The data used for this research is the result of questionnaire distribution given to 100 respondents. Website quality measurement is carried out using the webqual 4.0 method with 3 aspects assessed, namely Usability, Information Quality, and Service Interaction Quality. The purpose of this research is to determine the satisfaction value of Awicoffee website users and to determine the most significant instrument in determining  user satisfaction. Based on the research results, it was found that these three variables have an influence of 76.59% on user satisfaction, while 23.41% is influenced by variables that were not examined. Also, the variable that has the most significant impact on user satisfaction is Information Quality with a value of 5.97, whereas the Usability variable has a value of 3.42 and the Service Interaction Quality variable has a value of 3.30.
PERANCANGAN WEBSITE E-COMMERCE MULTI CABANG PADA PT. PASAR SWALAYAN MAJU BERSAMA MENGGUNAKAN ALGORITMA JACCARD COEFFICIENT Andy, Andy; Agus Maringan Siahaan; Satriya Miharja; Robet, Robet; Didik Aryanto
Majalah Ilmiah METHODA Vol. 14 No. 1 (2024): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

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

Abstract

PT. Pasar Swalayan Maju Bersama is a company engaged in the supermarket sector and has 3 branches, namely Maju Bersama Glugur, Maju Bersama Merak Jingga, and Maju Bersama Marendal. But in practice, PT. Maju Bersama Supermarkets still have not utilized good marketing media, both internally and externally. On the internal side, the company has not been able to properly integrate the sales processes of its three branches. In addition, the main problem is related to the amount of transaction data stored in the company's storage. Transaction data recorded every day will certainly burden storage if it is not used properly to become useful knowledge for the company. From the description of the problem, it is necessary to develop a multi-branch based system that is implemented on an E-Commerce website. This research also implements the Jaccard Coefficient algorithm so that it can process company data which turns a lot of knowledge into product recommendations for customers. The results of the study show that the Jaccard Coefficient algorithm is proven capable of processing company data into knowledge in the form of product recommendations that are relevant to customers.
Implementation of Deep Learning Model for Classification of Household Trash Image Robet, Robet; Perangin Angin, Johanes Terang Kita; Pribadi, Octara
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14198

Abstract

The problem of household waste management is a very important issue today, where the rapid urbanization, consumptive culture, and the tendency to dispose of waste without sorting it first from home, makes the volume of waste in landfills increase. Therefore, household waste management needs to be managed quickly and appropriately, so as not to have a major impact on environmental, hygiene, and health problems. Although some environmental communities and local governments have made efforts to manage waste through recycling systems, the long-term use of human labor is inefficient, expensive, and harmful to workers' health. Therefore, utilizing artificial intelligence technology is the best solution to classify waste types quickly and accurately. This research tries to test several pre-trained convolutional neural network (CNN) models to perform classification. The results of testing pre-trained CNN models, such as AlexNet, VGG16, VGG19, ResNet50, and ResNeXt50, found that the pre-trained model ResNext50 is better with 100% accuracy, while the training loss and validation loss are 0.0414 and 0.0304, respectively. Then the second best model is the pre-trained ResNet50 model with 100% accuracy with training loss and validation loss of 0.0832 and 0.1077, respectively.
Pemanfaatan Dana Desa Untuk Meningkatkan Kesejahteraan Masyarakat Melalui Promosi Produk UMKM Menggunakan Collaborative Filtering Berbasis Android Siahaan, Agus Maringan; Robet; Jonathan Kevin Fernando; Donna Natalia
Bulletin of Computer Science Research Vol. 5 No. 1 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i1.377

Abstract

Utilizing village funds through Badan Usaha Milik Desa (BUMDes) is a strategic effort to improve the welfare of rural communities. However, its implementation often faces challenges such as suboptimal management of local economic potential and limited promotion of Micro, Small, and Medium Enterprises (MSMEs) products. This study aims to develop an Android-based application utilizing the Collaborative Filtering method as an innovative solution to support the promotion of village MSME products, enhance the effective use of village funds, and drive economic growth in rural areas. The application is designed to provide MSME product recommendations based on user preferences. Integrating the Collaborative Filtering method, the application analyzes user interaction data to offer relevant product suggestions. Its key features include product search, personalized recommendations, and a user-friendly interface that is easy for rural communities to operate. The black-box method testing results show that this application works according to the designed specifications with a system interface functional success rate of 100% of 31 functional interfaces. increased the promotion and sales of local MSME products.
Akurasi K-Means dengan Menggunakan Cluster dan Titik Grid Terbaik pada Pemetaan Grid Interatif K-Means Perangin Angin, Johanes Terang Kita; Rizkita, Ari; Robet, Robet; Pribadi, Octara
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp127-129

Abstract

Traditional K-Means face 2 (two) main problems, namely: Determination of Initial Centroid and poor initial cluster. Determining the initial centroid using random numbers is one of the main problems in classical K-Means which results in low accuracy and long computation time. Likewise, determining the good centroid of each cluster without being accompanied by a process of paying attention to the performance of each cluster can also cause the accuracy value obtained is not good. This study will contribute to how the performance obtained by determining a good initial centroid is combined with the use of a good cluster. Determination of a good initial centroid is done by using the K-Means Grid Mapping which divides the determination of the centroid into several Grid Points. The result of this research is a combination of Iterative K-Means with Grid Mapping K-Means to become Iterative Grid Mapping K-Means which will get a good initial centroid and also a good cluster shown in the table of iris and abalone, comparison of the variables in the iris and abalone affecting the best cluster as a result.
IMPLEMENTASI METODE PROTOTYPING DALAM PERANCANGAN UI/UX DESIGN PADA MEDIA DIGITAL TERANG KITA Rizkita, Ari; Perangin Angin, Johanes; Robet; Pribadi, Octara
Jurnal TIMES Vol 14 No 1 (2025): Jurnal TIMES
Publisher : STMIK TIME

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51351/jtm.14.1.2025834

Abstract

Perkembangan teknologi informasi pada era saat ini bergerak sangat pesat dan mencakup seluruh aspek kehidupan manusia, termasuk pada bidang media. Media digital terangkita.com, sebuah platform yang bergerak di bidang edukasi dan penyebaran konten positif berbasis nilai-nilai sosial. Proses perancangan dilakukan melalui tahapan metode prototyping, mulai dari pengumpulan kebutuhan pengguna, pembuatan sketsa awal, hingga pengujian desain interaktif. Pendekatan ini memungkinkan kolaborasi yang dinamis antara desainer dan pengguna, serta memberikan fleksibilitas untuk melakukan revisi berdasarkan umpan balik secara iteratif. Hasil penelitian menunjukkan bahwa metode prototyping mampu meningkatkan kualitas desain UI/UX secara signifikan, ditinjau dari aspek keterpahaman, kemudahan navigasi, dan kepuasan pengguna terhadap antarmuka. Temuan ini memberikan kontribusi terhadap pengembangan desain media digital yang lebih human-centered, serta menjadi acuan dalam proses desain interaktif berbasis kebutuhan pengguna. Kata kunci: UI/UX Design, Prototyping, Media Digital, Desain Interaktif, Terang Kita
Aplikasi Pencarian Bengkel Tambal Ban Dan Spbu Terdekat Di Kota Medan Menggunakan Metode Dijkstra Dan Haversine Berbasis Android Robet, Robet
Jurnal TIMES Vol 10 No 1 (2021): Jurnal TIMES
Publisher : STMIK TIME

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (659.225 KB) | DOI: 10.51351/jtm.10.1.2021633

Abstract

Sarana transportasi yang paling banyak dimiliki dan digunakan oleh masyarakat kota Medan pada saat ini adalah sepeda motor. Walaupun saat ini peningkatan jumlah sepeda motor yang pesat menimbulkan berbagai permasalahan dari sisi ekonomi, sosial dan lingkungan. Namun di sisi lain, sepeda motor memiliki harga yang mudah dijangkau oleh masyarakat dalam menunjang berbagai aktivitas bisnis, pekerjaan, pendidikan untuk berpergian dari satu tempat ke tempat yang lain. Dengan kemudahan mobilitas yang tinggi dan jangkauan akses ke suatu tempat, namun ada kekurangan dari sepeda motor yaitu mudahnya terjadi kebocoran ban serta mudahnya kehabisan bahan bakar minyak dikarenakan umumnya tangki minyak sepeda motor yang kapasitasnya kecil, sehingga pengendara sepeda motor terpaksa harus berhenti dan mendorong motornya. Fakta di lapangan para pengendara sepeda motor yang mengalami kebocoran ban dan kehabisan bahan bakar minyak, untuk mencari lokasi tambal ban ataupun SPBU seringkali dilakukan secara konvensional. Namun yang menjadi permasalahan, karena luasnya kota Medan membuat kesulitan bagi pengendara sepeda motor untuk menelusuri satu per satu lokasi bengkel tambal ban ataupun SPBU apalagi ketika malam hari tidak banyak kedua tempat tersebut buka. Memang saat ini pencarian tempat tambal ban dan SPBU sudah bisa dilakukan melalui aplikasi Google Map, namun kekurangannya adalah aplikasi Google Map belum dapat memberikan rekomendasi bengkel tambal ban dan SPBU terdekat dari posisi pengendara sepeda motor. Oleh sebab itu maka perlu dilakukan penelitian untuk membangun aplikasi pencarian bengkel tambal ban dan SPBU berbasis Android dengan penerapan metode Dijkstra dan Haversine dalam memberikan rekomendasi lokasi terdekat bengkel tambal ban dan SPBU di kota Medan.
Attention Augmented Deep Learning Model for Enhanced Feature Extraction in Cacao Disease Recognition Robet, Robet; Perangin Angin, Johanes Terang Kita; Siregar, Tarq Hilmar
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 4 (2025): Articles Research October 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i4.15249

Abstract

Accurate cacao disease recognition is critical for safeguarding yields and reducing losses. Prior cacao studies primarily rely on handcrafted descriptors (eg, Color Histogram, LBP, GLCM) or standard CNN/transfer-learning pipelines, often limited to ≤ 3 classes and a single plant organ; explicit channel-spatial attention and comprehensive multiclass evaluation remain uncommon. To the best of our knowledge, no prior work integrates Squeeze-and-Excitation (SE) and the Convolutional Block Attention Module (CBAM) on a ResNeXt50 backbone for six-class cacao disease classification, accompanied by a standardized ablation study and t-SNE-based interpretability. We propose a six-class classifier (five diseases + healthy) built on ResNeXt-50 enhanced with SE (channel recalibration) and CBAM (channel-spatial emphasis) to highlight lesion-relevant cues. The dataset comprises labeled leaf and pod images from public sources collected under field-like conditions; preprocessing includes resizing to 224x224, normalization, and augmentation (flips, small rotations, color jitter, random resized crops). Trained with Adam and early stopping, ResNeXt50+SE+CBAM attains 97% test accuracy and 0.97 macro-F1, surpassing a ResNeXt50 baseline of 94% and 0.95 and SE-only/CBAM-only variants. Confusion matrix and t-SNE analyses show fewer mix-ups among visual classes and clearer separability, while the ablation validates complementary benefits of SE and CBAM. On a desktop-hosted, web-based setup, batch-1 inference at 224x224 is 7.46 ms/image (134 FPS), demonstrating real-time capability. The findings support deployment as browser-based decision-support tools for farmers and integration into continuous field-monitoring systems.
Comparative Analysis of DNA Sequence Alignment Algorithms in SARS-CoV-2 Edi, Edi; Robet, Robet; Harahap, Nurhayati
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 4 (2025): Articles Research October 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i4.15323

Abstract

Sequence alignment is fundamental in bioinformatics, with Smith-Waterman (local) and Needleman-Wunsch (global) algorithms widely applied. However, comparative analyses on highly similar viral genomes such as SARS-CoV-2 remain scarce. This study systematically evaluated both algorithms using the first 5,000 nucleotides of two SARS-CoV-2 genomes (29,903 and 29,684 nt) under four parameter configurations: standard, low gap penalty, high gap penalty, and high match reward. Performance was assessed through alignment score, sequence identity, gap distribution, execution time, and parameter sensitivity. Both algorithms produced identical sequence identity (97.80%), with 4,943 matches out of 5,054 positions. Smith-Waterman consistently yielded higher alignment scores (12.6-112 points advantage), while Needleman-Wunsch was substantially faster (0.7752 vs 3.9014 s), showing 5.03 times greater computational efficiency. These findings indicate that both methods are reliable for highly similar viral sequences, with a trade-off between scoring precision and computational speed. This study provides the first parameter-sensitive comparison for full SARS-CoV02 genomes, emphasizing how parameter tuning can influence performance outcomes. A key limitation is that the analysis was restricted to the first 5,000 nucleotides, which may not capture variability across the complete genome.
A Comparative Study of Machine Learning and Deep Learning Models for Heart Disease Classification Simanjuntak, Martina Sances; Robet, Robet; Hoki, Leony
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11546

Abstract

Heart disease remains one of the leading causes of mortality worldwide, necessitating accurate early detection. This study aims to compare the performance of several Machine Learning (ML) and Deep Learning (DL) algorithms in heart disease classification using the Heart Disease dataset with 918 samples. The methods tested included Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine (SVM), Logistic Regression, K-Nearest Neighbor (KNN), and Deep Neural Network (DNN). Preprocessing included feature normalization, data splitting (80:20), and simple hyperparameter tuning for parameter-sensitive models. Evaluations were conducted using accuracy, precision, recall, F1-score, AUC, and confusion matrix analysis to identify error patterns. The results showed that SVM and DNN achieved the highest accuracies of 91.3% and 92.1%, respectively. However, DNN has higher computational costs and risks of overfitting on small datasets. These findings confirm that traditional ML models such as SVM remain highly competitive on tabular medical data.
Co-Authors Agus Maringan Siahaan Agus Maringan Siahaan Alvin Alvin Alvin Alvin, Alvin Andi Andi Andy Andy Andy Andy Ari Rizkita Ari Rizkita Arnold Adimabua Ojugo Barus, Hanisa putri Bayu Teta Bimo Haryo Setyoko Br Tarigan, Widia CANDRA GUNAWAN Carles Juliandy Chandra Chandra De Rosal Ignatius Moses Setiadi Didik Aryanto Didik Aryanto Donna Natalia edi edi Edi Wijaya Edi Wijaya Eferhire Valentine Ugbotu Etika Kartikadarma Feriani Astuti Tarigan Feriani Astuti Tarigan Feriani, Feriani Astuti Tarigan Haria Wirawan Hendri Hendri Hendri Hendri Hoki, Leony Hose, Fernando Iqbal Giffari Ritonga Jackri Hendrik Jenime Darwin Jerico Setiawan Johanes Terang Kita Perangin Angin Jonathan Kevin Fernando Juan Charles Kelvin Leonardi Kohsasih Lase, Wisriani Liecero, Marcus Md Kamruzzaman Sarker Michael Angelo Nicholas Tio Nurhayati Harahap Octara Pribadi Panjaitan, Tabitha Martha Agustine Perangin Angin, Johanes Poppy Amalia Putri, Jihan Hidayah Randy Wilson Rizkita, Ari Robin Robin Robin Robin, Robin Robin Zheng Satriya Miharja Satriya Miharja Siahaan, Agus Maringan Simanjuntak, Martina Sances Sinaga, Asra Gretya Siregar, Tarq Hilmar Suyud Widiono Suyud Widiono Tabitha Chukwudi Aghaunor Vic Devlin Yehezkiel E.A Parapak Yessica Yamin Yuliana Yuliana