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All Journal Jurnal Algoritma Jurnal sistem informasi, Teknologi informasi dan komputer Format : Jurnal Imiah Teknik Informatika Jurnal Informatika IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal Teknik Komputer AMIK BSI JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Pilar Nusa Mandiri Jurnal Mitra Manajemen JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) JURNAL ILMIAH INFORMATIKA Jurnal Teknik Informatika UNIKA Santo Thomas Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika Informatik : Jurnal Ilmu Komputer EDUMATIC: Jurnal Pendidikan Informatika JISICOM (Journal of Information System, Infomatics and Computing) INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi ScientiCO : Computer Science and Informatics Journal Jurnal Mantik Jurnal Ilmiah Sains dan Teknologi (SAINTEK) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal of Applied Multimedia and Networking JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JIKA (Jurnal Informatika) Indonesian Journal for Social Responsibility Jurnal Infortech Jurnal AbdiMas Nusa Mandiri Jurnal Dialektika Informatika (Detika) HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Computer Science (CO-SCIENCE) Technologic J-SAKTI (Jurnal Sains Komputer dan Informatika) INSANtek – Jurnal Inovasi dan Sains Teknik Elektro JUSTIN (Jurnal Sistem dan Teknologi Informasi) Madiun Spoor : Jurnal Pengabdian Masyarakat Newton : Networking And Information Technology Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Algoritme Jurnal Mahasiswa Teknik Informatika Jurnal Algoritma Paradigma Al-Ijtima: Jurnal Pengabdian Kepada Masyarakat Journal of Innovative and Creativity Al-Ijtimā: Jurnal Pengabdian Kepada Masyarakat TECHNOLOGIC Jurnal Infortech Jurnal Esensi Infokom : Jurnal Esensi Sistem Komputer dan Informasi
Jordy Lasmana Putra
Universitas Bina Sarana Informatika
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Other

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SISTEM INFORMASI ABSENSI PESERTA MAGANG BERBASIS WEB DI KANTOR PUSAT PT.PEGADAIAN (PERSERO) Savira Nur Rahmadini; Jordy Lasmana Putra; Tyas Setiyorini
Jurnal Ilmiah Sains dan Teknologi Vol. 10 No. 2 (2026): Jurnal Ilmiah Sains dan Teknologi
Publisher : Teknik Informatika Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/saintek.v10i2.4606

Abstract

The internship program at the Head Office of PT Pegadaian (Persero) still faces several issues, such as manual attendance recording for interns, lack of data integration, and difficulties in monitoring performance and generating reports efficiently. This study aims to develop a web-based application called InTrack (Intern Tracker) to assist in managing intern data, recording attendance, and generating digital reports. The system was developed using the Waterfall methodology. The application utilizes the CodeIgniter framework for the backend and MySQL as the database system. It was tested through black box testing and User Acceptance Testing (UAT) to ensure it meets user requirements. The test results indicate that the system functions well and improves efficiency and accuracy in managing intern data at PT Pegadaian. Therefore, the InTrack application can serve as an effective digital solution to support the administrative and evaluation processes of internships in a real-time and integrated manner
Classification of Adolescent Depression Risk Using Naïve Bayes Algorithm and SMOTE Method to Handle Social Media Activity Data Imbalance Widiana Salsabilah; Jordy Lasmana Putra
JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) Vol. 9 No. 2 (2026): August 2026
Publisher : University of Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jeemecs.v9i2.17345

Abstract

Advances in information technology have transformed the way adolescents communicate through social media, yet excessive use negatively impacts psychological well-being. This study aims to develop a Naïve Bayes classification model to identify adolescent depression risks and evaluate the effectiveness of the SMOTE method in addressing data imbalance challenges. This research utilizes the "Social Media Impact on Teen Mental Health" dataset from Kaggle, consisting of 1,200 rows of data, with the entire modeling process validated using 10-fold Cross Validation. The results indicate that the application of the SMOTE method was successful in optimizing detection for the minority class or at risk groups. Through the integration of SMOTE, this classification system achieved a Recall value of 96.77% and an F1-Score of 74.07%, with false negative errors reduced to just 1 case. The combination of the Naïve Bayes algorithm and SMOTE has proven to produce a classification system that is fairer, more sensitive, and relevant for early mental health detection, enabling faster and more accurate identification of depression risks in the digital era.
Clustering Social Media Addiction Levels Among Students Using the K-Means Clustering Algorithm Muhamad Sandi; Jordy Lasmana Putra; Tyas Setiyorini
Informatik : Jurnal Ilmu Komputer Vol 22 No 2 (2026): August 2026
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v22i2.12605

Abstract

Social media has become an integral part of students’ lives, yet excessive use often leads to symptoms of addiction that negatively affect mental health and academic performance. This study aims to cluster the levels of social media addiction among students and university students using the K-Means Clustering algorithm as an unsupervised learning approach. The dataset was obtained from the Kaggle platform, containing variables such as daily usage duration, access frequency, sleep disturbance, and psychological impact. The Elbow Method was employed to determine the optimal number of clusters, while Principal Component Analysis (PCA) was used for visualization. The results grouped respondents into three categories: mild addiction (46.8%), moderate addiction (22.6%), and severe addiction (30.6%). A strong correlation was observed between high access frequency and symptoms such as sleep disruption and decreased concentration. These findings highlight the importance of designing data-driven prevention strategies within educational environments and provide a foundation for further institutional interventions to maintain digital balance among youth.
EVALUASI KINERJA ALGORITMA MACHINE LEARNING DALAM KLASIFIKASI POSTUR DUDUK MENGGUNAKAN YOLOV8N-POSE: PERFORMANCE EVALUATION OF MACHINE LEARNING ALGORITHMS FOR SITTING POSTURE CLASSIFICATION BASED ON YOLOV8N-POSE KEYPOINTS Naufal Aqil Hidayat; Muhammad Rafli; Andre Saputra; Khahfiana Rosida; Muhammad Robis Alfaf; Jordy Lasmana Putra
HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Vol. 17 No. 2 (2026): Jurnal HOAQ - Teknologi Informasi
Publisher : Universitas Uyelindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52972/hoaq.vol17no2.p341-350

Abstract

Penggunaan perangkat digital yang meningkat memperpanjang durasi duduk dan berisiko menimbulkan gangguan muskuloskeletal akibat postur yang tidak ergonomis. Penelitian ini mengembangkan sistem klasifikasi postur duduk berbasis citra menggunakan YOLOv8n-Pose (Nano) untuk ekstraksi 17 titik sendi tubuh, yang kemudian diratakan (flattening) menjadi vektor 51 fitur numerik dan dinormalisasi dengan Standard Scaler. Dataset gabungan dari Roboflow dan Kaggle, yang terdiri atas 3.558 citra dengan rincian 1.044 good_form dan 2.514 bad_form, diuji pada lima algoritma yaitu Random Forest, KNN, SVM, MLP, dan Deep MLP, menggunakan skema hold-out 80:20 berbasis stratified sampling. Pada data uji, Random Forest mencatat performa generalisasi paling seimbang dengan akurasi 0,9775 dan Macro F1-Score 0,9728, sedikit mengungguli MLP Neural Network yang menunjukkan performa yang juga kuat, meskipun Random Forest sebelumnya menunjukkan indikasi overfitting pada fase pelatihan. Sistem kemudian diimplementasikan sebagai aplikasi web bernama SitSmart di Hugging Face Spaces. Penelitian ini mengindikasikan bahwa kombinasi ekstraksi koordinat pose dan model klasifikasi ensemble mampu memberikan hasil kompetitif untuk pemantauan ergonomi otomatis, meski validasi lapangan real-time masih diperlukan pada tahap lanjut.   Rising use of digital devices has extended sitting durations, thereby increasing the risk of musculoskeletal disorders from poor posture. This study develops an image-based sitting posture classification system using YOLOv8n-Pose (Nano) to extract 17 body keypoints, which are then flattened into a 51-feature numeric vector and normalized with Standard Scaler. A combined Roboflow and Kaggle dataset, consisting of 3,558 images with 1,044 good_form and 2,514 bad_form samples, was evaluated across five algorithms, namely Random Forest, KNN, SVM, MLP, and Deep MLP, using an 80:20 stratified hold-out split. On the test set, Random Forest achieved the most balanced generalization, with an accuracy of 0.9775 and a Macro F1-Score of 0.9728, narrowly ahead of MLP Neural Network, which also showed strong performance, although Random Forest had previously shown signs of overfitting during training. The best-performing model was then deployed as a web application called SitSmart on Hugging Face Spaces. These findings suggest that combining pose-based coordinate extraction with an ensemble classifier can yield competitive results for automated ergonomic monitoring, although real-world and real-time field validation remains necessary as a direction for future work.
Perbandingan Algoritma Dengan Particle Swarm Optimization Untuk Analisis Sentimen Pada Peraturan PSBB di Indonesia Raharjo, Mugi; Putra, Jordy Lasmana; Sandi, Tommi Alfian Armawan; Napiah, Musriatun
Paradigma - Jurnal Komputer dan Informatika Vol. 24 No. 1 (2022): Periode Maret 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/paradigma.v24i1.968

Abstract

The pandemic has given rise to new rules and terms in society. Various countries have their own regulations, including Indonesia with the name PSBB for that, the author tries to conduct research related to the PSBB condition in Indonesia with the intent and purpose of knowing people's sentiments towards it, the authors carry out this modeling positively and negatively. model in a tweet on Twitter. We capture information through Twitter media which then we process the data so that it is ready to be tested on the algorithm used. In data collection and processing, we use a fast miner application. In this study, Naive Bayes,KNN,and SVM were used. We also did a model comparison with Particle Swarm Optimization. model 1 tested three algorithms using a 0.7-0.8 ratio validation and 10-fold cross-validation, In Model 2 the author used a selection feature, namely Particle swarm Optimization where PSO was used as optimization. From the second model, the accuracy is 88.00%. for SVM + PSO, 88.54%% for NB + PSO and 81.58% for K -NN + PSO. And after testing the 2 methods, it turns out that Naive Bayes + PSO has the highest level of accuracy and precision
Co-Authors Agus Subekti Akbar Fariq Mulia Alda Zevana Putri Widodo Alengka, Son Gohan Amin Nur Rais Andre Saputra Andriansah, Andriansah Atiyah Aldawiyah Bayhaqy, Achmad Chandra Kesuma Denis Chandra Prabowo Destriana, Rachmat Dirgahayu Erri Dwi Krisnandi Dwiza Riana Eni Heni Hermaliani Eni Heni Hermaliani, Eni Heni Esron Rikardo Nainggolan Esron Rikardo Nainggolan Evita Fitri Fachrurozi, Ahmad Fajar Shidiq Fariq Mulia, Akbar Fatiha, Zulfati Dinul Febri Ainun Jariyah Fikri Ismaya Findi Ayu Sariasih Firmansyah Firmansyah Firmansyah Firmansyah Fitra Septia Nugraha Fitri, Evita Frieyadie Gata, Windu Hadianto, Nur Hafifah Bella Novitasari Hafifah Bella Novitasari Hafifah Bella Novitasari Hani Harafani Hengki Rusdianto I Gusti Bagus Arya Pradnja Paramitha Imron Imron Indra Saputra Inggit Dessy Susanti Juanuari, Juanuari Khahfiana Rosida Khamdun Khamdun Khuluq, Anjahul Krisnandi, Dwi Laela Kurniawati lazuardi, sandy ibrahim Leksono, Ilham Nur Luthfi Indriyani M. Iqbal Alifudin Mahdi Abdullah Mahmud Mahmud Manzis, Ilham Marwan Marwan Miharja, Jaja Mufid Junaedi Mugi Raharjo Mugi Raharjo Mugi Raharjo Mugi Raharjo Muhamad Hasan Muhamad Sandi Muhammad Rafli Muhammad Rizqi Saputra Muhammad Robis Alfaf Musriatun Napiah Mustofa Mustofa Mustofa Mustofa Musyaffa, Abdurrozzaq Naufal Aqil Hidayat Negoro, Alexander Rio Adi Ngara, Simson Mali Nila Hardi Novitasari, Hafifah Bella Nurul Arifin Oky Kurniawan Prasetyo, Rizal Rachmat Adi Purnama Rachmawati Darma Astuti Rachmawati Darma Astuti Raharjo, Mugi Ridwan ridwan Ridwan, Ridwan Rino Indra Muhammad Rino Indra Muhammad1 Salwa Saumi Sandro Arnesto Savira Nur Rahmadini Sidik Sidik Sidik Sri Rahayu Sri Watmah Sriyadi Sriyadi Sujiliani Heristian Susafa'ati Susafa'ati Susafa’ati, Susafa’ati Suwanda Aditya Saputra Syahla, Haura Syarah Seimahuira Tika Adilah M Tommi Alfian Armawan Sandi Tyas Setiyorini Tyas Setiyorini Tyas Setyorini Ummu Radhiyah Ummu Radiyah Virda Mega Ayu Waeisul Bismi Wahyutama Fitri Hidayat Warjiyono Warjiyono Widiana Salsabilah Windu Gata Windu Gata Windu Gata Windu Gata WITRIANA ENDAH PANGESTI Yeni Angraini Zulfati Dinul Fatiha