Article Per Year (5 Year)
p-Index From 2020 - 2025
6.07
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Informatika Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Kursor Jurnal Transformatika Jurnas Nasional Teknologi dan Sistem Informasi E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer JPM (Jurnal Pemberdayaan Masyarakat) Jurnal BALIRESO Dinamisia: Jurnal Pengabdian Kepada Masyarakat ILKOM Jurnal Ilmiah MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer KOMPUTIKA - Jurnal Sistem Komputer Celebes Abdimas: Jurnal Pengabdian Kepada Masyarakat Buletin Ilmiah Sarjana Teknik Elektro G-Tech : Jurnal Teknologi Terapan Journal of Information Technology and Its Utilization Indian Journal of Forensic Medicine & Toxicology International Journal of Engineering, Science and Information Technology Jurnal PkM (Pengabdian kepada Masyarakat) Caraka : Indonesia Journal of Communication Buletin Sistem Informasi dan Teknologi Islam Ilmu Komputer untuk Masyarakat Celebes Journal of Community Services KOPEMAS Jurnal Balireso: Jurnal Pengabdian pada Masyarakat
Dolly Indra
Universitas Muslim Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

Published : 51 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 51 Documents
Search

 1   2   3   4   5 
Detection System of Strawberry Ripeness Using K-Means Dolly Indra; Ramdan Satra; Huzain Azis; Abdul Rachman Manga; Harlinda L
ILKOM Jurnal Ilmiah Vol 14, No 1 (2022)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v14i1.1054.33-39

Abstract

Strawberry is one type of fruit that is favored by the people of Indonesia. The detection process to identify strawberries can be done by utilizing advances in computer technology, One of them is in the field of digital image processing. In this study, we made a strawberry ripeness detection system using the values of Red, Green and Blue as the reference values, while for identification in determining the type of classification using the K-Means algorithm that uses the Euclidean distance difference as the reference. Based on the results of testing using the K-Means algorithm on 51 strawberry images consisting of ripe, semi ripe and raw fruit yielding an accuracy rate of 82.14%, we also conducted tests other than strawberry images as many as 8 images yielded an accuracy rate of 100%.
DESIGN WEB-BASED ELECTRICAL CONTROL SYSTEM USING RASPBERRY PI Dolly Indra; Tasmil Tasmil; Herman Herman; St. Hajrah Mansyur; Erick Irawadi Alwi
Journal of Information Technology and Its Utilization Vol 2, No 1 (2019)
Publisher : Sekolah Tinggi Multi Media (STMM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jitu.2.1.2275

Abstract

The use of current website technology can be applied as a control and monitoring system, which is used to control electrical devices, so that the user can only control the PC or smartphone that has been connected to Wi-Fi or the Internet. In this case the control uses the Raspberry Pi Mini PC which has several advantages such as low power and is relatively easy when connected with a web server compared to a microcontroller. By utilizing the Raspberry Pi Mini PC as a web server, it can replace PC functions in general. The results in this study are the Electric Control System that has been made capable of controlling 4 AC voltage electronics as well as 4 relays with each relay capable of bearing a maximum load of 2200 watts using a power supply on the Raspberry Pi which has a minimum of 0.7 amperes and Control of electrical load can be done within a distance of 0 meters - 15 meters from the wireless router
Pengembangan Peningkatan Produktivitas dan Pemasaran UKM Abon Telur sebagai Oleh-Oleh Khas Malino di Desa Lonjoboko Kecamatan Parangloe Kabupaten Gowa Purnawansyah Purnawansyah; Dolly Indra; Lilis Nur Hayati; Fery Setyo Aji; Rezky Anugrah
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 14, No 1 (2023): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v14i1.5973

Abstract

Tujuan program pengabdian yang kami lakukan yaitu memberikan penyuluhan, dan simulasi tentang pemasaran produk, memberikan pelatihan bagi mitra desa Lonjoboko tentang kewirausahaan dalam memasarkan produk berbasis online dan mendesain kemasan yang menarik dan praktis. Metode dalam pelaksanaaan kegiatan ini adalah memfasilitasi dengan penyuluhan, simulasi dan pelatihan bagi para UKM dengan mewujudkan masyarakat sejahtera dan pandai dalam memasarkan produk dengan layanan sistem informasi berbasis online di desa Lonjoboko Kabupaten Gowa dalam bentuk pelatihan. Luarannya Mitra mendapatkan modul pelatihan manajemen kewirausahaan berbasis online untuk memasarkan produknya, mitra mampu mandiri dalam mengimplementasikan dan terampil dalam pemasaran produk, Software Aplikasi Web Sistem Informasi pemasaran produk.
Implementasi Sistem Penghitung Kendaraan Otomatis Berbasis Computer Vision Indra, Dolly; Herman, Herman; Budi, Firman Shantya
Komputika : Jurnal Sistem Komputer Vol 12 No 1 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i1.9082

Abstract

The development of computer technology today is very helpful for humans in completing their work in various fields. One application of computer technology i.e., in the field of computer vision which has a very important role for object recognition. In this study, we designed a computer vision-based automatic vehicle counting system. The system that we created uses the MobileNetV2 Single Shot Multibox Detector (SSD) which is placed on the Raspberry Pi 4 to carry out the process of classifying cars and motorcycles and the raspberry pi 4 also functions as a system controller. This automatic vehicle counter system has been integrated between Raspberry Pi 4 and a mobile application on a smartphone where the smartphone functions to display information such as day, date, month, year and together with the number of cars and motorcycles. We tested this automatic vehicle counting system on steam services (car and motorcycle washing) for 3 days where 10 vehicles were collected every day. The test results show that the system is capable of detecting cars and motorcyles with an average accuracy rate of 46.6%. Keywords – Vehicle Detection, SSD-MobileNet V2, Computer Vision, Raspberry Pi, Smartphone
Pengenalan Huruf BISINDO Menggunakan Chain Code Contour dan Naive Bayes Indra, Dolly; Hayati, Lilis Nur; Irja, Mulianty Cipta
Komputika : Jurnal Sistem Komputer Vol. 13 No. 1 (2024): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v13i1.10360

Abstract

Digital image processing, also known as digital image manipulation, is a method used to process or manipulate digital images. Digital image processing can address various problem domains, one of which is the recognition of Indonesian Sign Language (BISINDO) letters used by the deaf and speech-impaired individuals for communication. The aim of our research is to develop a digital image-based application that can recognize BISINDO letters from A to Z with a high level of letter similarity accuracy. The BISINDO letter dataset consists of 260 images, divided into an 80% (208 images) training data set and a 20% (52 images) testing data set. The letter recognition process begins with pre-processing, including converting RGB images to grayscale, segmentation using thresholding, morphological opening, and Sobel edge detection. The shape feature extraction is then performed using Chain Code Contour. The values obtained from this feature extraction are used in the final stage, which is the recognition of BISINDO letter images using the Naive Bayes classification method. The research involves two testing scenarios: a database scenario and an out-of-database scenario, each with three dataset divisions: 80:20, 70:30, and 60:40. The results of the database scenario testing with an 80:20 dataset division achieved 100% accuracy, while the 70:30 division achieved 92.3% accuracy, and the 60:40 division achieved 88.4% accuracy. In the out-of-database scenario, the 80:20 dataset division achieved 80.7% accuracy, the 70:30 division achieved 73.07% accuracy, and the 60:40 division achieved 75.9% accuracy. Based on the conducted testing, the best accuracy was obtained with the 80:20 dataset division, achieving 100% accuracy in the database scenario and 80.7% accuracy in the out-of-database scenario. This indicates that the Chain Code Contour shape feature extraction method and Naive Bayes classification method are capable of recognizing BISINDO letters effectively.
Penerapan Metode Random Forest dalam Klasifikasi Huruf BISINDO dengan Menggunakan Ekstraksi Fitur Warna dan Bentuk Indra, Dolly; Hayati, Lilis Nur; Daris, Mega Asfirawati; As'ad, Ihwana; Mansyur, Umar
Komputika : Jurnal Sistem Komputer Vol. 13 No. 1 (2024): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v13i1.10363

Abstract

Digital image processing is a field of study that focuses on how an image can be formed, processed, and analyzed to generate useful information for humans. In this research, the utilization of digital images is implemented to classify BISINDO (Indonesian Sign Language) letters from A to Z using the Random Forest classification method. The initial stage in the classification of BISINDO letter images involves pre-processing, which includes converting RGB images to grayscale and performing segmentation through three stages: thresholding, morphology, and edge detection using the Prewitt operator. Subsequently, features such as HSV color extraction and metric shape features, as well as eccentricity, are extracted. These extracted feature values are then utilized in the classification stage of BISINDO letter images from A to Z using the Random Forest method. In this study, three data comparison scenarios were employed for testing purposes. The first scenario involved an 80:20 data ratio, which achieved a testing accuracy of 94.2%. The second scenario with a 70:30 data ratio achieved a testing accuracy of 93.6%, while the third scenario with a 60:40 data ratio had a lower accuracy of only 77.9%. Based on the results of our testing, the system developed is capable of effectively classifying BISINDO letters from A to Z using color and shape feature extraction, along with the Random Forest classification method. The best results were obtained in the data comparison scenario of 80:20, achieving an accuracy rate of 94.2%. Keywords – BISINDO, HSV, Metric, Eccentricity, Random Forest.
Classifying BISINDO Alphabet using TensorFlow Object Detection API Hayati, Lilis Nur; Handayani, Anik Nur; Irianto, Wahyu Sakti Gunawan; Asmara, Rosa Andrie; Indra, Dolly; Fahmi, Muhammad
ILKOM Jurnal Ilmiah Vol 15, No 2 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i2.1692.358-364

Abstract

Indonesian Sign Language (BISINDO) is one of the sign languages used in Indonesia. The process of classifying BISINDO can be done by utilizing advances in computer technology such as deep learning. The use of the BISINDO letter classification system with the application of the MobileNet V2 FPNLite  SSD model using the TensorFlow object detection API. The purpose of this study is to classify BISINDO letters A-Z and measure the accuracy, precision, recall, and cross-validation performance of the model. The dataset used was 4054 images with a size of  consisting of 26 letter classes, which were taken by researchers by applying several research scenarios and limitations. The steps carried out are: dividing the ratio of the simulation dataset 80:20, and applying cross-validation (k-fold = 5). In this study, a real time testing using 2 scenarios was conducted, namely testing with bright light conditions of 500 lux and dim light of 50 lux with an average processing time of 30 frames per second (fps). With a simulation data set ratio of 80:20, 5 iterations were performed, the first iteration yielded a precision result of 0.758 and a recall result of 0.790, and the second iteration yielded a precision result of 0.635 and a recall result of 0.77, then obtained an accuracy score of 0.712, the third iteration provides a recall score of 0.746, the fourth iteration obtains a precision score of 0.713 and a recall score of 0.751, the fifth iteration gives a precision score of 0.742 for a fit score case and the recall score is 0.773. So, the overall average precision score is 0.712 and the overall average recall score is 0.747, indicating that the model built performs very well.
Efektivitas Komunikasi Kepemimpinan Kepala Satuan Pendidikan dalam Skema Kerja Work from Home Indra, Dolly; Toni, Ahmad
CARAKA : Indonesia Journal of Communication Vol 3, No 1 (2022): Caraka : Indonesia Journal of Communication
Publisher : Indonesian Scientific Journal (Jurnal Ilmiah Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/caraka.v3i1.43

Abstract

Ketua program studi adalah seseorang yang dipercaya bertanggung jawab untuk melaksanakan program kerja Program Studi melalui metode kepemimpinan yang spesifik agar visi, tujuan, dan sasaran program kerja Universitas dapat berjalan sesuai dengan target yang diinginkan bersama. Dalam situasi pandemi ketua program studi dituntut memimpin secara efektif untuk dapat menyelesaikann masalah yang terjadi selama pandemi. Penelitian ini melihat efektifitas kepemimpinan ketua program studi Teknik Informatika dalam masa kerja work from home sesuai dengan teori lima ciri kepemimpinan yang efektif menurut peter duncker dengan metode kualitatif terhapad subject dan juga object topic. Hasil dari penelitian ini ketua program studi cukup efektif dengan model kepimpinan yang dilakukan. Dengan memenuhi kelima kriteria ciri kepempinan yang efektif.
Sistem Monitoring Kerja Kerukunan Mahasiswa Pinrang Universitas Muslin Indonesia (KMP-UMI) Menggunakan Push Notification Taufik, Muhammad Asrai; Indra, Dolly; Hasnawi, Mardiyyah
Buletin Sistem Informasi dan Teknologi Islam (BUSITI) Vol 2, No 4 (2021)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (648.463 KB) | DOI: 10.33096/busiti.v2i4.984

Abstract

Proses penyampaian informasi kerja kepada badan pengawas (MPO) masih dilakukan secara manual dan masih lambat, belum adanya aplikasi yang dapat memberikan informasi kerja kepada MPO secara cepat sehingga badan pengawas tidak dapat menerima informasi kerja dari pengurus secara up to date. Penelitian ini bertujuan Untuk merancang dan membangun sistem yang menggunakan push notification yang dapat membantu user untuk mengetahui informasi program kerja secara real time. Penelitian ini menghasilkan sebuah Sistem monitoring yang menggunakan layanan push notification yang memungkinkan badan pengawas (MPO) untuk mengetahui informasi program kerja secara real time. Sistem atau aplikasi ini dapat menjalankan fungsinya dengan baik dan efisien berdasarkan hasil pengujian Black Box menunjukkan formform yang terdapat pada aplikasi semua berjalan dengan semestinya dan setiap validasi yang terdapat pada aplikasi semua menunjukkan sesuai perancangan aplikasi dengan total persentase pengujian betha yang dicapai yaitu 53,2%.
Analisis Pre-processing Sentimen Terhadap Komentar Layanan Indihome Pada Twitter Novanto, Achmad; Indra, Dolly; Astuti, Wistiani
Buletin Sistem Informasi dan Teknologi Islam (BUSITI) Vol 5, No 1 (2024)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/busiti.v5i1.2066

Abstract

Dalam era globalisasi yang terus berkembang, peran teknologi informasi menjadi krusial dalam mengubah cara manusia berinteraksi dan mengakses informasi. Perusahaan telekomunikasi, seperti PT Telkom Indonesia dengan layanannya, IndiHome, memanfaatkan kemajuan teknologi untuk menyediakan layanan digital berbasis Internet, Telepon Rumah, dan TV Interaktif/IPTV. Meskipun sudah menjangkau seluruh Indonesia, pemahaman mengenai kepuasan pengguna terhadap layanan IndiHome masih perlu diperdalam. Penelitian ini difokuskan pada analisis sentimen pengguna terhadap layanan IndiHome melalui media sosial twitter. twitter menjadi platform yang signifikan dalam mengekspresikan pandangan, kritik, dan kepuasan pengguna. Pembatasan karakter dalam setiap cuitan memunculkan gaya bahasa baru, yang memicu kreativitas pengguna. Meski demikian, menganalisis sentimen dari tweet memiliki tantangan tersendiri, terutama karena penggunaan kata-kata non-baku dan bahasa informal. Oleh karena itu, pentingnya preprocessing data dalam analisis sentimen menjadi fokus utama penelitian ini. Langkah awal dalam penelitian ini bertujuan untuk meningkatkan keberhasilan klasifikasi sentimen dengan membersihkan dan normalisasi data tweet. Hasil penelitian diharapkan dapat memberikan wawasan yang lebih akurat mengenai respons pengguna terhadap layanan IndiHome. Melalui langkah-langkah preprocessing yang dilibatkan, penelitian ini menyimpulkan bahwa data yang telah dipersiapkan menjadi lebih siap untuk tahap analisis sentimen. Dengan demikian, analisis sentimen dapat memberikan hasil yang lebih relevan dan akurat, membuka peluang untuk mengambil langkah-langkah strategis terkait dengan polarisasi sentimen yang teridentifikasi.
Co-Authors Abdul Rauf Tuasikal Agung, Riski Dewa Ahmad Toni, Ahmad Aldri Frinaldi Amir, Nur Hikmah Anik Nur Handayani Arfan Zainuddin As'ad, Ihwana Astuti, Wistiani Damanhuri, Nor Salwa Daris, Mega Asfirawati Djamereng, Asdar Erick Irawadi Alwi Erick Irawadi Alwi Erick Irawadi Alwi, Erick Irawadi Erick, Erick Irawadi Alwi Fadly Achmad Farniwati Fattah Fery Setyo Aji Firman Shantya Budi, Firman Shantya Hadyan Mardhi Fadlillah Haerdiansyah Syahnur, Muhammad Harlinda Lahuddin Hayudin Hasnanda Maila Herman Herman Hi. Talib, Juraiz Hidayat, Muh Wahyu Huzain Azis Ihwana As’ad Irawati Irawati Irja, Mulianty Cipta Jafar, Putri Jufriadif Na`am, Jufriadif Julius Santony Kadri Rahmat Suat, Wahyu Kasman Kasman Lilis Nur Hayati lilis nurhayati Lukman Syafie Lutfi Budi Ilmawan Lutfi Budi Ilmawan, Lutfi Budi Manga, Abdul Rachman Mansyur, St. Hajrah Mardiyyah Hasnawi Muh. Ridwan Rahim Muhammad Al Mubarak Muhammad Arfah Asis Muhammad Farhan Hermansyah Mukarramah, Rifqatul Mustika, Mustika Octavia Novanto, Achmad Nur Hayati, Lilis Nurhalima Nurhalima Ode, Nada Kayatri Purnawansyah Purnawansyah Rahma, Dewi Ernita Rahmat Suat, Wahyu Kadri Rahmayani, Nurul Ramadan, Syahril Ramdan Satra Ramdaniah Ramdaniah Rezky Anugrah Rifky Saputra Scania, Muhammad Rosa Andrie Asmara Salsa, Salsabila Aurelia Saputra Scania, Muhammad Rifky Satma, Satma St. Hajrah Mansyur Subhan Ardhiman Sugiarti, Sugiarti Sukur, Widianti Syahnur, Muh. Haerdiansyah Syahrul Mubarak Abdullah Tasmil Tasmil Tasrif Hasanuddin Taufik, Muhammad Asrai Umar Mansyur Umar, Fitriyani Veithzal Rivai Zainal Wahyu Sakti Gunawan Irianto Yuhandri Yuhandri, Yuhandri Yundari, Yundari Zahra, Andi Fathimatuz Zahra