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All Journal Jurnal Ilmiah Informatika Komputer UG Journal Jurnal Ilmiah KOMPUTASI Jurnal Informasi Sains dan Teknologi (ISAINTEK) Jurnal Ilmiah Teknik (JUIT) Jurnal Teknik dan Science (JTS) Jurnal Ilmiah Multidisiplin (JUKIM) Jurnal Pengabdian Masyarakat Bangsa
Nelly Sofi
Universitas Gunadarma
Agriculture, Biological Sciences & Forestry Arts Humanities 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 Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Prototype Design of InMed (Information Medicine) Application Using Goal-Directed Design (GDD) Method with Figma Tri Sulistyorini; Muhammad Achsan Isa AL Anshori; Nelly Sofi; Dwi Widiastuti
Jurnal Teknik dan Science Vol. 4 No. 2 (2025): Juni : Jurnal Teknik dan Science
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/jts.v4i2.2144

Abstract

In the world of health, a platform is needed to make it easier for a person to find information, especially related to drugs practically. To realize this, this research was carried out to produce an application called InMed (Information Medicine). This research aims to analyze, design, and evaluate matters related to telemedicine and make it easier for users to find information about medicines. The method used in this study is Goal Directed Design (GDD) which consists of several steps, namely Research, Modeling, Requirements, Framework, Refinement, Support. The results of the Likert Scale test of the InMed application prototype received a score of 92%.
Penggunaan Kecerdasan Buatan untuk Menganalisis Faktor Risiko Diabetes dengan menggunakan Random Forest Classifier Tri Sulistyorini; Nelly Sofi; Dwi Widiastuti; Viliananda Tripita Claur
Jurnal Teknik dan Science Vol. 4 No. 3 (2025): Oktober: Jurnal Teknik dan Science
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/jts.v4i3.2453

Abstract

Diabetes is a non-communicable disease that deserves attention and poses a significant public health challenge. Although not a contagious disease, preventive measures and early detection of diabetes risk are crucial. This study used machine learning-based artificial intelligence to identify diabetes risk factors. The model was created using the Random Forest Classifier (RFC) algorithm, which has 16 variables as parameters. The model was built using the Python programming language, with data collection spanning from 2015 to 2018. The research included needs analysis, data collection, data preprocessing, model training, predictive model creation, system design, implementation, and testing. The final results showed that, with an accuracy of 89%, the model could be used effectively to predict diabetes risk. Furthermore, the model identified more pre-diabetes classes than other classes.
Pemanfaatan Multimedia dalam Sistem Basis Data Penyimpanan Kegiatan Ekskul Siswa Menggunakan Microsoft Access Rahmayana, Emellika; Dwitama, Faramita; Fathullah, Fahmi; Ridwan, Anggraeni; Arimbi, Yuti Dewita; Sofi, Nelly; Marleen, Onny; Kowanda, Anacostia
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 10 (2025): Desember
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i10.3699

Abstract

Di tengah pesatnya perkembangan teknologi, sekolah harus dapat meningkatkan kemampuan siswa untuk lebih siap menghadapi kemajuan teknologi. Kebanyakan bidang saat ini sudah memanfaatkan teknologi informasi guna membantu pekerjaan agar lebih praktis dan efisien. Salah satu contoh adalah bidang multimedia. Mengoptimalkan keterampilan siswa di bidang multimedia dengan basis data untuk menambah pengetahuan siswa dalam Pemanfaatan multimedia (teks, gambar, video)  dalam Sistem Basis Data dengan aplikasi Microsoft Access, dengan studi kasus penyimpanan data ekskul. Lokasi abdimas bertempat di SMK Tirtajaya Depok, dengan bentuk kegiatan yaitu praktik langsung melalui komputer. Hasil pelatihan pada abdimas ini dikatakan berhasil karena berjalan dengan lancar. Para siswa jurusan Multimedia dari SMK Tirtajaya Depok menunjukkan antusiasme yang tinggi dalam mengikuti kegiatan serta berhasil menjawab studi kasus dan pertanyaan yang diberikan.
Rancang Bangun Deteksi Dini Kantuk Berbasis Eye Aspect Ratio dan API menggunakan Python Nelly Sofi; Tri Sulistyorini; M. Ryan Rifqi Firdaus
Jurnal Teknik dan Science Vol. 5 No. 2 (2026): Juni : Jurnal Teknik dan Science
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/jts.v5i2.2752

Abstract

Drowsiness during work can reduce productivity and increase the risk of errors, particularly in monotonous office jobs that rely heavily on screen-based activities. This study aims to design and develop a modular computer vision-based drowsiness detection system capable of detecting drowsiness conditions in real-time and providing automatic notifications to users. The system detects drowsiness conditions using the Eye Aspect Ratio (EAR) method through an internal laptop or PC camera. The implementation was carried out using the Python programming language with the OpenCV library for image processing and Dlib for facial landmark detection. Users are provided with a graphical user interface (GUI) application developed using Tkinter. The system automatically sends warning messages through the Telegram Bot API when the EAR value is detected below the threshold of 0.21 for more than 3 seconds. Notifications can be delivered automatically to both the user’s and supervisor’s Telegram accounts. The testing results indicate that the system is capable of operating in real-time with fast response times and stable notification delivery through Telegram. Warning messages are delivered concisely so as not to disrupt the user’s workflow. Based on these findings, the developed drowsiness detection system has the potential to be utilized as a supporting tool to improve alertness and prevent productivity decline among office workers.
Co-Authors Anacostia Kowanda Arimbi, Yuti Dewita Chandra, Reza Dwi Widiastuti Dwi Widiastuti, Dwi Erma Sova Faramita Dwitama Fathullah, Fahmi M. Ryan Rifqi Firdaus Maulana, Faizal Mohammad Faizul Irsyad Muhammad Achsan Isa AL Anshori Muhammad Nazaruddin Onny Marleen Rahmayana, Emellika Revida Iriana Ridwan, Anggraeni Riza Dharmawan Tri Sulistyorini Viliananda Tripita Claur