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Perancangan Sistem Informasi Data Kependudukan Desa Kaduaja Kecamatan Gandangbatu Sillanan Berbasis Web Ramadan, Syahril; Indra, Dolly; Azis, Huzain
Buletin Sistem Informasi dan Teknologi Islam (BUSITI) Vol 5, No 2 (2024)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/busiti.v5i2.1920

Abstract

Sistem informasi kependudukan merupakan salah satu faktor utama dalam pemerintahan dan pembangunan kependudukan yang diarahakan pada pemenuhan hak dari setiap warga negara dibidang pelayanan data kependudukan. Desa Kaduaja salah satu bagian dari Desa di Kecamatan Gandangbatu Sillanan Kabupaten Tana Toraja, pengelolaan data pada Kantor Desa Kaduaja dilakukan secara manual mengakibatkan dokumen-dokumen tersebut disusun dengan tidak teratur dan tersimpan pada arsip yang terpisah sehingga pihak pemerintah Desa Kaduaja, untuk menyelesaikan permasalahan tersebut dibangunlah sebuah sistem informasi data kependudukan. penelitian ini menghasikan sistem informasi data kependudukan Desa Kaduaja Kecamatan Gandangbatu sillanan berbasis web yang dapat mempermudah pemerintah desa mengolah data kependudukan. metode yang digunakan dalam perancangan aplikasi yaitu metode waterfall yaitu model dimana tiap tahapannya dikerjakan secara berurutan dari atas ke bawah. Pengujian yang dilakukan berdasarkan blackbox testing mendapatkan nilai penggunaan secara keseluruhan dalam tampilan interface maupun fungsionalitas aplikasi yaitu 85% dari 24 responden.
Penerapan Metode Profile Matching Pada Sistem Pendukung Keputusan Penentuan Jenjang Pendidikan Tingkat Menengah Atas Berbasis Website Hi. Talib, Juraiz; Mansyur, St. Hajrah; Indra, Dolly
Buletin Sistem Informasi dan Teknologi Islam (BUSITI) Vol 5, No 2 (2024)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/busiti.v5i2.1977

Abstract

Penerimaan siswa baru adalah suatu hal yang perlu ditentukan secara cepat dan tepat. Dalam hal penentuan calon siswa baru di perlukan beberapa pertimbangan yang cukup banyak dan rumit yaitu standarisasi nilai, persyaratan masuk serta kebijakan-kebijakan dari pemerintah dan lembaga pendidikan yang sering berubah setiap tahunnya. Selama ini pemilihan sekolah yang dilakukan oleh siswa SMP Negeri 42 Halmahera Selatan tetap di lakukan secara subjektif tanpa ada penyeleksian artinya penilaian tentang kemampuan siswa hanya dari pengamatan saja tanpa adanya parameter dan siswa yang memilih sekolah untuk melanjutkan pendidikan tingakat menengah atas tidak mendapatkan hasil yang maksimal karena tidak sesuai dengan kemampuan yang di miliki. Penelitian ini bertujuan untuk menentukan jenjang pendidikan tingkat menengah atas yang akan menjadi rekomendasi pada siswa kelas IX SMP Negeri 42 Halmahera Selatan berbasis website. Metode yang digunakan adalah Profile Matching yang merupakan metode dalam keputusan pendukung sistem (SPK) karena perhitungan yang dilakukan dengan pembobotan dan perhitungan gap. Berdasarkan hasil penelitian yang telah dilakukan pada SMP Negeri 42 Halmahera selatan dengan menerapkan metode profile matching maka dari 15 data jenjeng pendidikan tingkat menengah atas diperoleh, pertama madrasah Aliyah ulul albab dengan nilai 4,7 lalu SMA Negeri 5 kota ternate dengan Nilai 4,64 dan SMK Bina infomartika Kota Ternate dengan nilai 4,58 yang menjadi rekomendasi untuk siswa kelas IX SMP Negeri 42 Halmahera Selatan. Adapun hasil dari pengujian dari aplikasi menggunakan Blackbox Testing berdasarkan rencana pengujian maka diperoleh kesimpulan diterima.
INOVASI APLIKASI GEMA SEBAGAI PENDUKUNG PEMBELAJARAN ANAK PADA SLB AUTIS BUNDA Dolly Indra; Lutfi Budi Ilmawan; Umar Mansyur
Konferensi Nasional Pengabdian Masyarakat (KOPEMAS) #5 2024 Konferensi Nasional Pengabdian Masyarakat (KOPEMAS) #4 & International Community Service 2023
Publisher : Konferensi Nasional Pengabdian Masyarakat (KOPEMAS) #5 2024

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Dalam pengabdian masyarakat ini kami sebagai pengabdi berkolaborasi dengan Sekolah Luar Biasa (SLB) Autis Bunda yang menghadapi tantangan terkait ketersediaan media pembelajaran berbasis digital. Selama ini, sekolah ini telah mengandalkan metode konvensional seperti ceramah, papan tulis, dan pengajaran melalui kertas dan pensil. Tujuan utama dari pengabdian ini adalah menerapkan sistem pembelajaran digital berbasis android yang inovatif di SLB Autis Bunda. Metode pelaksanaan pengabdian ini meliputi observasi, wawancara, perancangan aplikasi, sosialisasi, pelatihan, dan penerapan aplikasi bernama "GEMA" (Game dan Edukasi Mobile untuk Anak).  Selain itu, pengabdian ini juga melibatkan evaluasi terhadap 11 guru SLB Autis Bunda untuk mengukur peningkatan pengetahuan mereka tentang aplikasi mobile. Hasil evaluasi ini disusun berdasarkan uji pretest dan posttest, di mana rata-rata nilai pretest awalnya mencapai 59.55 dan mengalami peningkatan menjadi 88.64 pada posttest.
Analysis of Hybrid Learning Sentiment among Information Systems Students using The Naïve Bayes Classifier Indra, Dolly; Ramdaniah, Ramdaniah; Sukur, Widianti
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 8 No. 2 (2024)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v8i2.1144

Abstract

Hybrid learning, which combines online and face-to-face instruction, has gained significant attention. Particularly in the Faculty of Computer Science, student engagement in hybrid learning is a central concern that arises during implementation. Hybrid, or blended learning, integrates various teaching methods, such as face-to-face, computer-based, and mobile learning, and offers advantages by reducing the time required for meetings and information delivery. Sentiment analysis, a branch of text mining, aims to determine public opinion or sentiment on topics, events, or issues. This study surveyed 112 Information Systems students using an online questionnaire to assess their responses to hybrid learning, classified as positive, negative, or neutral using the Naïve Bayes classifier. The research stages included data collection, preprocessing, Naïve Bayes model training, model evaluation, and sentiment analysis. The study aimed to analyze hybrid learning’s impact on students' learning experiences and assess the accuracy of the Naïve Bayes method in classifying sentiments regarding this impact. The results indicated that the initial test had an accuracy of 60.87% without using the SMOTE up-sampling operator, while the second test achieved 80.65% accuracy with the operator.
Pelatihan Kreatifitas Digital Menggunakan Canva Bagi Anggota Karang Taruna Parangloe Indra, Dolly; Nur Hayati, Lilis; Haerdiansyah Syahnur, Muhammad; Kadri Rahmat Suat, Wahyu; Rifky Saputra Scania, Muhammad
Jurnal Pemberdayaan Masyarakat Vol 9 No 2 (2024): November
Publisher : Direktorat Penelitian dan Pengabdian kepada Masyarakat (DPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/jpm.v9i2.10601

Abstract

The community engagement partner for this project is the youth members of Karang Taruna Parangloe, who face challenges due to a lack of digital literacy, particularly in utilizing technology for self-development. This initiative will equip these youth members with graphic design skills using the Canva platform. To achieve this goal, we implemented various approaches, beginning with an initial observation to understand the partner's needs, followed by a session on the importance of digital literacy. After the awareness session, we conducted intensive training in graphic design using Canva. This training was followed by an evaluation session to assess the participants' knowledge improvement. The evaluation was carried out through pretests and posttests with 30 youth members. The training results showed that the trained members of Karang Taruna Parangloe can now independently create graphic designs using Canva. The measurements indicated a significant improvement in their knowledge, with the average pretest score of 66.303 increasing to 82.709 in the posttest, reflecting the effectiveness of this community engagement program.
Digitalization, Business Potential, and Financial Inclusion: Youth Training in Parangloe Subdistrict, Gowa Regency Indra, Dolly; Syahnur, Muh. Haerdiansyah; Lilis Nur Hayati
Celebes Journal of Community Services Vol. 3 No. 2 (2024): Juni - November
Publisher : STIE Amkop Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37531/celeb.v3i2.1679

Abstract

Digitalization is the process of converting physical data or media into a digital format that can be managed using information technology. In Gowa Regency, South Sulawesi, the expansion of IT infrastructure is enhancing public services and improving interactions between citizens and the government. Digitalization offers numerous benefits, such as increased efficiency in information retrieval, easier market access, and expanded market reach, which can boost the economic potential of residents, including those in Parangloe Subdistrict. This Community Service Program (PkM) aims to enhance digital skills among the youth in youth organizations in Parangloe Subdistrict. The training is designed to help the youth become economically independent and promote financial inclusion. The program includes training on creating social media accounts, setting up e-commerce accounts, using Canva, and basic computer literacy. The program will be conducted in July 2024, with prior preparations and socialization with village officials and youth organization leaders. The results indicate that the training exceeded participation targets and improved participants' understanding of digitalization. Overall, the program successfully equipped participants with valuable digital skills, contributing to broader technological and economic inclusivity.
COMPARISON OF SENTIMENT CLASSIFICATION MODELS AT SULTAN HASANUDDIN AIRPORT IN MAKASSAR Muhammad Farhan Hermansyah; Dolly Indra; Ramdaniah Ramdaniah
Jurnal Ilmiah Informatika Komputer Vol 30, No 1 (2025)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2025.v30i1.14125

Abstract

Analisis sentimen menggunakan machine learning penting untuk memahami persepsi publik terhadap layanan bandara. Renovasi Bandara Sultan Hasanuddin Makassar bertujuan meningkatkan kapasitas dan kenyamanan, namun tanggapan masyarakat terkait perubahan ini beragam. Penelitian ini membandingkan efektivitas tiga algoritma machine learning—Naive Bayes Multinomial, Support Vector Machine (SVM), dan Random Forest—dalam menganalisis sentimen ulasan pengguna terkait renovasi Bandara Sultan Hasanuddin di Makassar. Penelitian ini juga menerapkan teknik pemisahan data dan preprocessing teks menggunakan Google Colab dengan pemrograman berbasis Python, termasuk pembersihan data, stemming dengan Sastrawi, penghilangan stopword, dan ekstraksi fitur menggunakan metode TF-IDF dengan Unigram dan Bigram. Untuk mengatasi ketidakseimbangan kelas pada dataset, diterapkan teknik SMOTE. Data ulasan yang digunakan diambil dari Google Maps selama satu tahun terakhir. Hasil penelitian menunjukkan bahwa SVM dengan kernel linear memberikan performa terbaik dengan F1-score 92,3%, diikuti oleh Naive Bayes 83,7% dan Random Forest 81,9%. Unigram lebih efektif dibandingkan Bigram dalam ekstraksi fitur, dan SMOTE meningkatkan kinerja Naive Bayes pada dataset yang tidak seimbang, namun tidak berpengaruh signifikan pada SVM. Temuan ini memberikan rekomendasi untuk peningkatan layanan di Bandara Sultan Hasanuddin, seperti fasilitas kebersihan dan kenyamanan ruang tunggu.
Optimizing YOLO-Based Algorithms for Real-Time BISINDO Alphabet Detection Under Varied Lighting and Background Conditions in Computer Vision Systems Hayati, Lilis Nur; Handayani, Anik Nur; Gunawan Irianto, Wahyu Sakti; Asmara, Rosa Andrie; Indra, Dolly; Damanhuri, Nor Salwa
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.948

Abstract

This research explores the optimization of YOLO-based computer vision algorithms for real-time recognition of Indonesian Sign Language (BISINDO) letters under diverse environmental conditions. Motivated by the communication barriers faced by the deaf and hearing communities due to limited sign language literacy, the study aims to enhance inclusivity through advanced visual detection technologies. By implementing the YOLOv5s model, the system is trained to detect and classify correct and incorrect BISINDO hand signs across 52 classes (26 correct and 26 incorrect letters), utilizing a dataset of 3,900 images augmented to 10,920 samples. Performance evaluation employs k-fold cross-validation (k=10) and confusion matrix analysis across varied lighting and background scenarios, both indoor and outdoor. The model achieves a high average precision of 0.9901 and recall of 0.9999, with robust results in indoor settings and slight degradation observed under certain outdoor conditions. These findings demonstrate the potential of YOLOv5 in facilitating real-time, accurate sign language recognition, contributing toward more accessible human-computer interaction systems for the deaf community.
Generative adversarial networks (GANS) for generating face images Indra, Dolly; Hidayat, Muh Wahyu; Umar, Fitriyani
Jurnal Ilmiah Kursor Vol. 13 No. 1 (2025)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v13i1.422

Abstract

The advancement of artificial intelligence technology, particularly deep learning, presents significant potential in facial image processing. Generative Adversarial Networks (GANs), a type of deep learning model, have demonstrated remarkable capabilities in generating high-quality synthetic images through a competitive training process between a generator, which creates new data, and a discriminator, which evaluates its authenticity. However, the use of public facial datasets such as CelebA and FFHQ faces limitations in representing global demographic diversity and raises privacy concerns. This study aims to generate realistic synthetic facial datasets using the StyleGAN2-ADA architecture, a specialized variant of GAN, with two training approaches: training from scratch on two types of datasets (private and public), each containing 480 images. The public dataset used is FFHQ (Flickr-Faces-HQ), known for its broader facial variation and high-quality images. Evaluation is conducted using the Frechet Inception Distance (FID), a metric that assesses image quality by comparing the feature distributions of real and generated images. Results indicate that training from scratch with the public dataset (FFHQ) using a batch size of 16 and a learning rate of 0.0025 achieves an FID score of 85.67 and performance of 86.46% at Tick 100, whereas the private dataset, under the same conditions, results in an FID score of 98.59 with a performance of 18.54%.. The training from scratch approach with the public dataset proves more effective in generating high-quality synthetic facial images compared to the private dataset. In conclusion, this approach supports the optimal generation of realistic synthetic facial data.
Improving Indonesian Sign Alphabet Recognition for Assistive Learning Robots Using Gamma-Corrected MobileNetV2 Hayati, Lilis Nur; Handayani, Anik Nur; Irianto, Wahyu Sakti Gunawan; Asmara, Rosa Andrie; Indra, Dolly; Damanhuri, Nor Salwa
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i3.13300

Abstract

Sign language recognition plays a critical role in promoting inclusive education, particularly for deaf children in Indonesia. However, many existing systems struggle with real-time performance and sensitivity to lighting variations, limiting their applicability in real-world settings. This study addresses these issues by optimizing a BISINDO (Bahasa Isyarat Indonesia) alphabet recognition system using the SSD MobileNetV2 architecture, enhanced with gamma correction as a luminance normalization technique. The research contribution is the integration of gamma correction preprocessing with SSD MobileNetV2, tailored for BISINDO and implemented on a low-cost assistive robot platform. This approach aims to improve robustness under diverse lighting conditions while maintaining real-time capability without the use of specialized sensors or wearables. The proposed method involves data collection, image augmentation, gamma correction (γ = 1.2, 1.5, and 2.0), and training using the SSD MobileNetV2 FPNLite 320x320 model. The dataset consists of 1,820 original images expanded to 5,096 via augmentation, with 26 BISINDO alphabet classes. The system was evaluated under indoor and outdoor conditions. Experimental results showed significant improvements with gamma correction. Indoor accuracy increased from 94.47% to 97.33%, precision from 91.30% to 95.23%, and recall from 97.87% to 99.57%. Outdoor accuracy improved from 93.80% to 97.30%, with precision rising from 90.33% to 94.73%, and recall reaching 100%. In conclusion, the proposed system offers a reliable, real-time solution for BISINDO recognition in low-resource educational environments. Future work includes the recognition of two-handed gestures and integration with natural language processing for enhanced contextual understanding.
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