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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Sistem Informasi dan Informatika (SIMIKA) Jurnal Informasi dan Teknologi Jurnal Perangkat Lunak Jurnal Computer Science and Information Technology (CoSciTech) Journal of Computer Scine and Information Technology Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Jurnal Komtekinfo Jurnal Informatika Ekonomi Bisnis RJOCS (Riau Journal of Computer Science) The Indonesian Journal of Computer Science
Sumijan
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Arts Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology

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Utilization of Convolutional Neural Network Method in Customer Identification Based on Facial Images Ade, Ade Puspita Sari; Sarjon Defit; Sumijan
Jurnal KomtekInfo Vol. 12 No. 3 (2025): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v12i3.664

Abstract

Artificial intelligence-based facial recognition technology, especially using the Convolutional Neural Network (CNN) method, is increasingly widespread in various business applications, such as customer data management. This technology allows the system to recognize and identify individuals automatically through facial images, so it is very potential to be applied in customer management. This study aims to implement CNN technology in automatically identifying old customers in a case study in JAVApace Studio. CNN method for facial recognition, optimizing the accuracy of old customer identification, designing CNN system integration in computer vision-based applications, and measuring CNN performance in real-time facial identification. The research method was carried out using a quantitative approach through data collection stages in the form of 875 customer facial images taken in JAVapace Studio, data preprocessing (cropping, resizing, and data augmentation), dataset division for training, validation, and testing. The CNN model used is the ResNet-50 architecture with fine-tuning techniques and freezing layers to improve training efficiency. Model performance evaluation uses a confusion matrix with accuracy, recall, and precision metrics. The results show that the CNN-based facial recognition system achieved 95.7% accuracy in distinguishing existing customers from the test data used. The recall rate was 94.5%, while the precision rate reached 96.2%. The discussion of the results also indicates that the fine-tuning approach is effective in optimizing model performance with an inference time suitable for real-time implementation needs. This study confirms that the implementation of CNN with ResNet-50 architecture is effectively able to recognize the faces of old customers with high levels of accuracy, recall, and precision, making it the right solution in managing customer data automatically and efficiently.
Application of Fuzzy Logic to Classify Community Welfare Levels Aditra; Sumijan; Sovia, Rini
Journal of Computer Scine and Information Technology Volume 10 Issue 3 (2024): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v10i3.104

Abstract

Information regarding family welfare does not only affect family members, but also influences the success of government, including village government. Therefore, information regarding the level of family welfare is needed to monitor the progress of development programs that have been carried out. The fuzzy logic of the Tahani model is one method that can be applied to classify things. The aim of this research is to classify the level of welfare of families as potential recipients of assistance based on population data held by the Mentawai Social Service & P3A. This research was processed using Fuzzy Tahani logic. Fuzzy Tahani is an optimization algorithm that can be used to support decisions by utilizing relational databases. Based on the research results obtained, fuzzy logic with the Tahani model can be used to process family data in accordance with indicators of family welfare levels by providing output in the form of family classification. It's just that the application of the Tahani model should be done on a single rule search function, not to process all the rules using a Tahani query to produce a family classification
IMPLEMENTASI SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN ALAT KONTRASEPSI DENGAN METODE AHP DAN TOPSIS (STUDI KASUS DI PUSKESMAS GUNUNG LABU) Refina Afindania, Pipin; Defit, Sarjon; Sumijan
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 12 No 1 (2024): TEKNOIF APRIL 2024
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2024.V12.1.1-9

Abstract

The problem that is often faced is that many mothers of couples of childbearing age do not understand how to choose a contraceptive method that is suitable for use. To address this problem among couples of reproductive age in choosing the most appropriate contraceptive method, the Analytical Hierarchy Process  (AHP)-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is proposed to be utilized. It is expected to be beneficial in aiding the selection of a suitable contraceptive method for users. The objective of this research is to implement the AHP-TOPSIS method in a decision support system for choosing contraceptive methods for couples of reproductive age at the Gunung Labu Community Health Center. The results of the analysis using the AHP-TOPSIS method indicate that the appropriate contraceptive methods for couples of reproductive age are Implan, IUD, Birth Control Injection, and Birth Control Pills. The combination of AHP-TOPSIS in contraceptive method selection yields the conclusion that the Decision Support System (DSS) built in this research is expected to facilitate midwives in recommending contraceptive methods for couples of reproductive age. AHP method is employed to calculate the weights of each contraceptive method criterion. The results of the priority weight calculations for all criteria used in this study yielded a Consistency Index (CI) of 0.07. The analysis using the AHP-TOPSIS method resulted in Implan, IUD, Birth Control Injection, and Birth Control Pills being identified as the appropriate contraceptive methods for couples of reproductive age.
Penerapan Metode Vikor Untuk Menentukan Kelayakan Penyewa Tempat Usaha Pada UIN Bukittinggi Resnawita; Yuhandri; Sumijan
Jurnal KomtekInfo Vol. 11 No. 3 (2024): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v11i3.536

Abstract

Seiring kemajuan teknologi yang berkembangan pesat, mendorong lahirnya inovasi-inovasi baru untuk memenuhi kebutuhan dunia kerja dan sebagai alat bantu manusia. Penggunaan teknologi dalam mengelola sebuah unit usaha kampus akan membantu instansi dalam melakukan pekerjaannya. Unit usaha kampus merupakan bagian penunjang pembelajaran dan pelayanan kepada mahasiswa dan Masyarakat. Unit ini biasanya bertugas untuk mengelola pendapatan dan pengeluaran, mengembangkan strategi keuangan, mengelola layanan katering, toko buku, kantin,tempat parkir, serta menjalankan berbagai jenis usaha lainnya yang terkait dengan kebutuhan mahasiswa dan staf kampus. Pengelolan unit usaha kampus akan membutuhkan banyak pertimbangan untuk megelola unit usaha kampus seperti pengambilan keputusan untuk penyewa tempat usaha atau kantin yang sesuai dengan syarat yang terdapat dalam perguruan tinggi dalam pengambilan keputusan terdapat beberapa faktor ataupun kriteria yang diperlukan agar keputusan yang nantinya diperoleh sesuai dengan syarat yang dibutuhkan oleh unit usaha kampus. Sehingga penggunaan teknologi dibutuhkan untuk mepermudah kampus dalam menentukan keputusan yang akan diperoleh. Penelitian ini bertujuan untuk memberikan rekomendasi kelayakan penyewa tempat usaha di UIN Bukittinggi. Metode penelitian yang digunakan dalam penelitian adalah metode VIKOR (Visekriterijumsko Kompromisno Rangiranje). Data yang digunakan dalam penelitian merupakan data penyewa tempat usaha UIN Bukittinggi. Terdapat 5 kriteria penilaian dan 10 data penyewa yang digunakan dalam penelitian. Dari hasil perangkingan didapatkan hasil bahwa calon penyewa dengan ID P01 mendapatkan nilai terkecil yaitu 0 dan merupakan peringkat pertama dalam perhitungan vikor. Penelitian ini menunjukkan bahwa metode VIKOR efektif dalam memberikan rekomendasi yang berbasis data dan kriteria yang telah ditentukan, sehingga dapat digunakan sebagai alat pendukung keputusan yang handal dalam pemilihan penyewa tempat usaha di lingkungan kampus.
Skin Cancer Segmentation On Dermoscopy Images Using Fuzzy C-Means Algorithm Aldi, Febri; Sumijan
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3797

Abstract

Millions of people around the world suffer from skin cancer, a common and sometimes fatal disease. Dermoscopy has become an effective diagnostic technique for skin cancer. Precise segmentation is essential for skin cancer diagnosis. Segmentation allows more precise analysis of dermoscopic images by defining the boundaries of the lesion and separating it from surrounding healthy tissue. Dermoscopy images served as a source of research data, and Fuzzy C-Means (FCM) segmentation techniques were used. FCM is a promising method and has received a lot of attention lately. FCM is able to distinguish the various components within the lesion and effectively separate the lesion from the surrounding area. As a result, the distribution of membership degree values of each pixel in the image for each cluster represents the segmentation results obtained through FCM. The FCM technique for segmenting dermoscopic images is expected to significantly improve the precision and effectiveness of skin cancer diagnosis.
Development of an Attention-Based Convolutional Neural Network-Long Short-Term Memory Model for Real-Time Ergonomic Analysis of Sitting Posture Tendra, Gusrio Tendra; Jollyta, Deny Jollyta; Sumijan
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 25 No. 2 (2026)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v25i2.5678

Abstract

The digital era has increased the prevalence of musculoskeletal disorders caused by poor sitting posture, posing a significant global health and productivity challenge. This study introduces an attentionbased deep learning model as the analytical engine for a proposed virtual ergonomics monitor, Ergo-Guard. The primary objective is to develop a model that accurately performs real-time Movement Quality Assessment of Sitting Posture for computer users, using only a standard webcam to ensure wide accessibility. This research method is a hybrid architecture that combines a Convolutional Neural Network (CNN) and a Long Short-Term Memory (LSTM), enhanced with an attention mechanism and optimized for three-dimensional skeletal data using the BlazePose Computer Vision approach. This framework merges a One-Dimensional CNN to extract spatial features from static poses with a Bidirectional LSTM network to model temporal postural shifts. An integrated attention mechanism enables the model to dynamically focus on critical ergonomic areas, mimicking an expert’s assessment. For validation, a new OfficePosture dataset was created, containing 500 videos of five common office sitting postures. The results indicate that the proposed model achieves 94.2% classification accuracy,substantially outperforming baselines from a pure CNN (84.6%) and a standard LSTM network (89.2%). Beyond accuracy, the model offers interpretable feedback through visual attention maps. In conclusion, the proposed architecture is an effective solution for monitoring sitting posture and holds considerable promise as an affordable preventive health tool for corporate and educational settings.
Co-Authors Aal, Defrizal Adawiyah, Quratih Ade, Ade Puspita Sari Aditra Agustin, Riris Akbar, Muhamad Rafi Aktavera, Beni Aldi, Febri Auriga, Wira Billy Hendrik Budiantoro, Hendro Budiarti, Lela dedi irawan Defit , Sarjon Deti Karmanita Devi Yuliana, Devi Dewi, Dian Cyntia Dwiprihatmo, Mohammad Reza Ely Nurhalizah Nst Eriyanto, Joko Fadillah, Riszki Feriantano Sundang Pranata Feriantano Sundang Pranata Geni, Bias Yulisa Gunadi Widi Nurcahyo Gusrio Tendra Habdi, Habdi Hendrik, Billy Ilham Asy'ari Jollyta, Deny Jollyta Jufriadif Na`am, Jufriadif Julius Santony Lubis, Siti Sahara Meiditra, Irzon Mulyanda, Sandy Nurcahyo , Gunadi Widi Okmarizal, Bisma Pipin Refina Afindania Pulungan, Akhiruddin Refina Afindania, Pipin Resnawita Ridho, Ridho Afwan Ridwan, Ridwan Ruri Hartika Zain Sarjon Defit Sarjon Defit Satria Satria, Satria Sovia, Rini Supriyanto, Boby Surmayanti Syafri Arlis Syaputra, Eka B. Syofneri, Nandel Ulfa, Ulia Vidyanti, Angela Yani, Zulfitri Yanti, Salma Nofri Yuda, Fitra Yuda Yuhandri