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The Best Smartphone Brand using The Preference Selection Index Method Angriawan, Sherkhing; Dewi Nasien; M. Hasmil Adiya; Roni Sanjaya; Yenny Desnelita; Feri Candra
International Journal of Electrical, Energy and Power System Engineering Vol. 5 No. 2 (2022): International Journal of Electrical, Energy and Power System Engineering (IJEEP
Publisher : Electrical Engineering Department, Faculty of Engineering, Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/ijeepse.5.2.37-44

The existence of the Covid-19 pandemic has had a tremendous impact in all aspects, including the educational aspect. Before the pandemic, education generally is done by face-to-face learning, but after the pandemic hit, it changed to online learning. Several problems often occur during online learning education, especially for college students, such as a mobile phone that does less support for online learning activities. Hence, the author wants to build an application that has the function of helping users to choose a mobile phone which supports online learning activities. The selection decision used by the author is the Preference Selection Index method since it can determine the value for each attribute and continue with a ranking that is able to select each attribute from the best alternative from several existing alternatives, with the help of a decision support system and application of the PSI (Preference Selection Index) method. The result indicates that the highest value obtained from smartphone selection with an average price under 3 million rupiah is infinix by 90.88%. The application's output meets the purpose because it is able to provide recommendations to buyers in determining which smartphone to buy and can simplify the decision-making process to become more accurate, effective, and efficient in generating information.

Increasing Trust in AI with Explainable Artificial Intelligence (XAI): A Literature Review Nasien, Dewi; Adiya, M. Hasmil; Anggara, Devi Willeam; Baharum, Zirawani; Yacob, Azliza; Rahmadhani, Ummi Sri
Journal of Applied Business and Technology Vol. 5 No. 3 (2024): Journal of Applied Business and Technology
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/jabt.v5i3.193

Artificial Intelligence (AI) is one of the most versatile technologies ever to exist so far. Its application spans as wide as the mind can imagine: science, art, medicine, business, law, education, and more. Although very advanced, AI lacks one key aspect that makes its contribution to specific fields often limited, which is transparency. As it grows in complexity, the programming of AI is becoming too complex to comprehend, thus making its process a “black box” in which humans cannot trace how the result came about. This lack of transparency makes AI not auditable, unaccountable, and untrustworthy. With the development of XAI, AI can now play a more significant role in regulated and complex domains. For example, XAI improves risk assessment in finance by making credit evaluation transparent. An essential application of XAI is in medicine, where more clarity of decision-making increases reliability and accountability in diagnosis tools. Explainable Artificial Intelligence (XAI) bridges this gap. It is an approach that makes the process of AI algorithms comprehensible for people. Explainable Artificial Intelligence (XAI) is the bridge that closes this gap. It is a method that unveils the process behind AI algorithms comprehensibly to humans. This allows institutions to be more responsible in developing AI and for stakeholders to put more trust in AI. Owing to the development of XAI, the technology can now further its contributions in legally regulated and deeply profound fields.

Penerapan Algoritma K-Means Untuk Clustering Data Obat-Obatan Pada RSUD Pekanbaru Gustientiedina, Gustientiedina; Adiya, M. Hasmil; Desnelita, Yenny
Jurnal Nasional Teknologi dan Sistem Informasi Vol 5 No 1 (2019): April 2019
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v5i1.2019.17-24

Perencanaan dari kebutuhan obat-obatan yang tepat dapat membuat pengadaan obat-obatan menjadi efektif dan efisien sehinggaobat-obatan dapat tersedia dengan cukup sesuai dengan kebutuhan serta dapat diperoleh pada saat yang diperlukan. Menganalisa pemakaian obat, perencanaan dan pengendalian obat-obatan dapat dilakukan pada data miningyaitu dengan clusterisasi.Metode yang akan di pakai untuk clustering data obat-obatan adalah algoritma K-Means yang mana merupakan metode clustering dengan non hirarki yang mempartisi data â€“ dataÂ kedalam cluster dimana data â€“ datadengan karakteristik sama akan dikelompokkan padasatu cluster dan data â€“ data dengan karakteristik yang berbeda akan dikelompokkan padacluster lainnya.Tujuan penelitian ini yaitumengelompokkan data obat-obatan pada rumah sakitsehingga dapat digunakan dalam acuan pengambilan keputusan perencanaan dan pengendaliaan persediaan obat-obatan di rumah sakit.

Automated Waste Classification Using YOLOv11 A Deep Learning Approach for Sustainable Recycling Nasien, Dewi; Adiya, M. Hasmil; Farkhan, Mochammad; Rahmadhani, Ummi Sri; Samah, Azurah A.
Journal of Applied Business and Technology Vol. 6 No. 1 (2025): Journal of Applied Business and Technology
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/jabt.v6i1.205

The rapid increase in waste generation due to urbanization and population growth has necessitated more efficient waste management solutions. Traditional waste sorting methods rely on manual labor, which is time-consuming, error-prone, and inefficient at large scales. This paper proposes an automated waste classification system using YOLOv11, the latest iteration of the YOLO family, which is known for its high speed and accuracy in object detection. By leveraging a custom dataset containing 10,464 labeled waste images from various categories—such as biodegradable, plastic, metal, paper, and glass—this study trains and evaluates a deep learning model capable of real-time waste identification and categorization. Experimental results demonstrate that YOLOv11 achieves high detection accuracy, with an overall classification accuracy of 94% and a mean average precision (mAP) exceeding previous methods. The model effectively differentiates between various waste types, though some misclassifications occur, particularly between visually similar materials like transparent plastic and glass. Performance metrics, including precision and recall, indicate the robustness of the proposed system in real-world applications. This research highlights the potential of YOLOv11 for integration into smart waste management systems, such as automated sorting machines and AI-powered recycling bins, to enhance efficiency and reduce environmental impact. Future work will focus on optimizing model performance by incorporating additional training data, applying advanced image augmentation techniques, and exploring hybrid approaches such as texture analysis and spectral imaging to improve classification accuracy. The implementation of this technology is expected to streamline waste recycling processes, minimize contamination in recyclable materials, and contribute to sustainable waste management practices.

Menciptakan Collaborative Learning Guru dan Peserta Didik Melalui Aplikasi Padlet Pada Sekolah Menengah Atas Pekanbaru Jollyta, Deny; Nasien, Dewi; Nora Marlim, Yulvia; Gustientiedina, Gustientiedina; Adiya, M. Hasmil; Mukhsin, Mukhsin; Rahmadian Yuliendi, Rangga; Kamal, Ahmad; Hajjah, Alyauma; Johan, Johan
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol 8, No 2 (2025): April 2025
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v8i2.3682

Collaborative Learning requires teachers and students to maintain an engaging learning environment at all times. Problems emerge when teachers, notably high school teachers in Pekanbaru, employ learning material that do not support this. Teachers' creativity is pushed to constantly update how they present materials and evaluate students' knowledge in order to foster a collaborative and pleasurable learning environment. This community service project will help Pekanbaru high school instructors create collaborative and real-time learning tools. The Community Service Team employed an observation strategy to get a sense of learning at Santa Maria High School, which served as an example school. The proposed solution is technologically based, making use of the Padlet application. The Community Service Team offers training methods on smartphones and computers to help people grasp Padlet. The community effort resulted in a polished Padlet that teachers may use to study with students at any time. It is intended that studying using the Padlet application would boost teacher innovation and student learning results at Santa Maria High School, as well as high schools around Pekanbaru.Keywords: Teacher; padlet; collaborative learning; learners;SMA. Abstrak: Pembelajaran Kolaboratif (Collaborative Learning) mengarahkan guru dan peserta didik dalam suasana belajar yang interaktif setiap saat. Permasalahan muncul pada saat media pembelajaran yang digunakan guru tidak mendukung hal tersebut, termasuk guru-guru Sekolah Menengah Atas (SMA) di Pekanbaru. Kreativitas guru ditantang untuk selalu memperbaharui cara penyampaian materi, cara mengevaluasi pemahaman peserta didik hingga penilaian, demi terciptanya suasana belajar yang kolaboratif dan menyenangkan. Kegiatan pengabdian ini bertujuan untuk membantu guru SMA di Pekanbaru dalam mempersiapkan bahan pembelajaran yang kolaboratif dan real time. Tim Pengabdian melakukan metode observasi untuk mendapatkan gambaran pembelajaran melalui SMA Santa Maria yang dijadikan sebagai sekolah sampel. Metode yang diusulkan berbasis teknologi melalui pemanfaatan aplikasi Padlet. Untuk memudahkan pemahaman Padlet, Tim Pengabdian menggunakan metode pelatihan, baik melalui komputer maupun smartphone. Hasil pengabdian adalah Padlet jadi yang dapat digunakan guru dalam pembelajaran bersama peserta didik setiap waktu. Diharapkan pembelajaran melalui aplikasi Padlet mampu meningkatkan kreativitas guru dan hasil belajar peserta didik SMA Santa Maria khususnya dan SMA di Pekanbaru umumnya.Kata kunci: guru; padlet; pembelajaran kolaboratif; peserta didik; SMA.

Penerapan Algoritma K-Means Untuk Clustering Data Obat-Obatan Pada RSUD Pekanbaru Gustientiedina, Gustientiedina; Adiya, M. Hasmil; Desnelita, Yenny
Jurnal Nasional Teknologi dan Sistem Informasi Vol 5 No 1 (2019): April 2019
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v5i1.2019.17-24

Perencanaan dari kebutuhan obat-obatan yang tepat dapat membuat pengadaan obat-obatan menjadi efektif dan efisien sehinggaobat-obatan dapat tersedia dengan cukup sesuai dengan kebutuhan serta dapat diperoleh pada saat yang diperlukan. Menganalisa pemakaian obat, perencanaan dan pengendalian obat-obatan dapat dilakukan pada data miningyaitu dengan clusterisasi.Metode yang akan di pakai untuk clustering data obat-obatan adalah algoritma K-Means yang mana merupakan metode clustering dengan non hirarki yang mempartisi data â€“ dataÂ kedalam cluster dimana data â€“ datadengan karakteristik sama akan dikelompokkan padasatu cluster dan data â€“ data dengan karakteristik yang berbeda akan dikelompokkan padacluster lainnya.Tujuan penelitian ini yaitumengelompokkan data obat-obatan pada rumah sakitsehingga dapat digunakan dalam acuan pengambilan keputusan perencanaan dan pengendaliaan persediaan obat-obatan di rumah sakit.

Menciptakan Collaborative Learning Guru dan Peserta Didik Melalui Aplikasi Padlet Pada Sekolah Menengah Atas Pekanbaru Jollyta, Deny; Nasien, Dewi; Nora Marlim, Yulvia; Gustientiedina, Gustientiedina; Adiya, M. Hasmil; Mukhsin, Mukhsin; Rahmadian Yuliendi, Rangga; Kamal, Ahmad; Hajjah, Alyauma; Johan, Johan
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol. 8 No. 2 (2025): April 2025
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v8i2.3682

Collaborative Learning requires teachers and students to maintain an engaging learning environment at all times. Problems emerge when teachers, notably high school teachers in Pekanbaru, employ learning material that do not support this. Teachers' creativity is pushed to constantly update how they present materials and evaluate students' knowledge in order to foster a collaborative and pleasurable learning environment. This community service project will help Pekanbaru high school instructors create collaborative and real-time learning tools. The Community Service Team employed an observation strategy to get a sense of learning at Santa Maria High School, which served as an example school. The proposed solution is technologically based, making use of the Padlet application. The Community Service Team offers training methods on smartphones and computers to help people grasp Padlet. The community effort resulted in a polished Padlet that teachers may use to study with students at any time. It is intended that studying using the Padlet application would boost teacher innovation and student learning results at Santa Maria High School, as well as high schools around Pekanbaru.Keywords: Teacher; padlet; collaborative learning; learners;SMA. Abstrak: Pembelajaran Kolaboratif (Collaborative Learning) mengarahkan guru dan peserta didik dalam suasana belajar yang interaktif setiap saat. Permasalahan muncul pada saat media pembelajaran yang digunakan guru tidak mendukung hal tersebut, termasuk guru-guru Sekolah Menengah Atas (SMA) di Pekanbaru. Kreativitas guru ditantang untuk selalu memperbaharui cara penyampaian materi, cara mengevaluasi pemahaman peserta didik hingga penilaian, demi terciptanya suasana belajar yang kolaboratif dan menyenangkan. Kegiatan pengabdian ini bertujuan untuk membantu guru SMA di Pekanbaru dalam mempersiapkan bahan pembelajaran yang kolaboratif dan real time. Tim Pengabdian melakukan metode observasi untuk mendapatkan gambaran pembelajaran melalui SMA Santa Maria yang dijadikan sebagai sekolah sampel. Metode yang diusulkan berbasis teknologi melalui pemanfaatan aplikasi Padlet. Untuk memudahkan pemahaman Padlet, Tim Pengabdian menggunakan metode pelatihan, baik melalui komputer maupun smartphone. Hasil pengabdian adalah Padlet jadi yang dapat digunakan guru dalam pembelajaran bersama peserta didik setiap waktu. Diharapkan pembelajaran melalui aplikasi Padlet mampu meningkatkan kreativitas guru dan hasil belajar peserta didik SMA Santa Maria khususnya dan SMA di Pekanbaru umumnya.Kata kunci: guru; padlet; pembelajaran kolaboratif; peserta didik; SMA.

Convolutional Neural Network Model for Sex Determination Using Femur Bones Nasien, Dewi; Adiya, M. Hasmil; Afrianty, Iis; Farkhan, Mochammad; Butar-Butar, Rio Juan Hendri
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.1711

Forensic anthropology is the critical discipline that applies physical anthropology in forensic education. One valuable application is the identification of the biological profile. However, in the aftermath of significant disasters, the identification of human skeletons becomes challenging due to their incompleteness and difficulty determining sex. Researchers have explored alternative indicators to address this issue, including using the femur bone as a reliable sex identifier. The development of artificial intelligence has created a new field called deep learning that has excelled in various applications, including sex determination using the femur bone. In this study, we employ the Convolutional Neural Network (CNN) method to identify the sex of human skeleton shards. A CNN model was trained on 91 CT-scan results of femur bones collected from Universiti Teknologi Malaysia, comprising 50 female and 41 male patients. The data pre-processing involves cropping, and the dataset is divided into training and validation subsets with varying percentages (60:4, 70:30, and 80:20). The constructed CNN architecture exhibits exceptional accuracy, achieving 100% accuracy in both training and validation data. Moreover, the precision, recall, and F1 score attained a perfect score of 1, validating the model's precise predictions. The results of this research demonstrate excellent accuracy, confirming the reliability of the developed model for sex determination. These findings demonstrate that using deep learning for sex determination is a novel and promising approach. The high accuracy of the CNN model provides a valuable tool for sex determination in challenging scenarios. This could have important implications for forensic investigations and help identify victims of disasters and other crimes.

Software Agent Simulation Design on the Efficiency of Food Delivery Ismail, Shahrinaz; Mostafa, Salama A; Baharum, Zirawani; Erianda, Aldo; Jaber, Mustafa Musa; Jubair, Mohammed Ahmed; Adiya, M. Hasmil
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.2648

Food delivery services have gained popularity since the emergence of online food delivery. Since the recent pandemic, the demand for service has increased tremendously. Due to several factors that affect how much time additional riders spend on the road; food delivery companies have no control over the location or timing of the delivery riders. There is a need to study and understand the food delivery riders' efficiency to estimate the service system's capacity. The study can ensure that the capacity is sufficient based on the number of orders, which usually depends on the number of potential customers within a territory and the time each rider takes to deliver the orders successfully. This study is an opportunity to focus on the efficiency of the riders since there is not much work at the operational level of the food delivery structure. This study takes up the opportunity to design a software agent simulation on the efficiency of riders' operations in food service due to the lack of simulation to predict this perspective, which could be extended to efficiency prediction. The results presented in this paper are based on the system design phase using the Tropos methodology. At movement in the simulation, the graph of the efficiency is calculated. Upon crossing the threshold, it is considered that the rider agents have achieved the efficiency rate required for decision-making. The simulation's primary operations depend on frontline remotely mobile workers like food delivery riders. It can benefit relevant organizations in decision-making during strategic capacity planning.

Community Service in Winda Songket Riau: Implementation of Sustainopreneurship and Women's Empowerment: Pengabdian Kepada Masyarakat di Winda Songket Riau: Penerapan Sustainopreneurship dan Pemberdayaan Perempuan Nasien, Dewi; Adiya, M. Hasmil; Siddik, M.; Suroyo, Suroyo; Mukhsin, Mukhsin
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 8 No. 5 (2024): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v8i5.23057

Community Service Activity (PkM) at Winda Songket, Riau, focuses on efforts to preserve the cultural heritage of songket weaving as part of Riau Malay culture, as well as improving the welfare of women through the application of a sustainopreneurship model. This program integrates ecological, economic, and social concepts to increase added value in the production of traditional Riau songket cloth. In addition, this program also emphasizes the importance of women's roles in maintaining and developing the songket business, thereby improving their economic welfare. This service involves socialization, training, and mentoring for songket craftsmen, hoping to encouragethem to adopt innovations in sustainable business models

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