Article Per Year (5 Year)
p-Index From 2021 - 2026
10.95
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Informatika Komputer JURNAL PASTI (PENELITIAN DAN APLIKASI SISTEM DAN TEKNIK INDUSTRI) Tourism & Hospitality Essentials Journal E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JTT (Jurnal Teknologi Terpadu) QALAMUNA: Jurnal Pendidikan, Sosial, dan Agama RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JIKO (Jurnal Informatika dan Komputer) Jurnal Pilar Nusa Mandiri JPM (Jurnal Pemberdayaan Masyarakat) Journal of Research and Technology Jurnal BALIRESO ILKOM Jurnal Ilmiah Jurnal RESISTOR (Rekayasa Sistem Komputer) Adimas : Jurnal Pengabdian Kepada Masyarakat KOMPUTIKA - Jurnal Sistem Komputer Buletin Ilmiah Sarjana Teknik Elektro Jurnal Teknik Industri Terintegrasi (JUTIN) Indonesian Journal of Data and Science Idealis : Indonesia Journal Information System JISO : Journal of Industrial and Systems Optimization International Journal of Engineering, Science and Information Technology Jurnal Senopati : Sustainability, Ergonomics, Optimization, and Application of Industrial Engineering Abditeknika - Jurnal Pengabdian Kepada Masyarakat Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Buletin Sistem Informasi dan Teknologi Islam Ilmu Komputer untuk Masyarakat Jurnal Algoritma Hawari: Jurnal Pendidikan Agama dan Keagamaan Islam Jurnal Pengabdian Masyarakat - Teknologi Digital Indonesia The Center For Sustainable Development Studies Journal Tatar Pasundan: Jurnal Diklat Keagamaan MANISE (Manajemen, Bisnis dan Ekonomi) The Indonesian Journal of Computer Science JURMA YUSTISI Journal of Information Technology and its Utilization Linier: Literatur Informatika dan Komputer DIMASEJATI:Jurnal Pengabdian Kepada Masyarakat
lilis nurhayati
Teknik Informatika, Fakultas Ilmu Komputer, Universitas Muslim Indonesia Makassar, Indonesia
Religion 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 Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

Published : 96 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 96 Documents
Search

 6   7   8   9   10 
Rancang Bangun Aplikasi Mobile Lost & Found Berbasis UCD untuk Meningkatkan Efisiensi Pencarian Barang di Kampus UMI Ridho Anugrah Albanjari; Lilis Nur Hayati; irawati irawati
LINIER: Literatur Informatika dan Komputer Vol 2, No 2 (2025)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/linier.v2i2.3107

Abstract

Kasus kehilangan barang di ruang lingkup kampus universitas muslim Indonesia (UMI) tidak terselesaikan secara maksimal. Hal ini disebabkan kurangnya informasi dan keterbatasan sistem pengelolaan. Untuk menindak lanjuti permasalahan tersebut, penelitian ini bertujuan untuk merancang aplikasi mobile lost found Fikom Kampus UMI berbasis User Centered Design (UCD) yang dapat meningkatkan keterlibatan dan efisiensi pengguna. Penelitian ini menggunakan pendekatan kualitatif dengan metode UCD yang mempunyai empat tahap yaitu: empati, definisi, ideasi, dan prototipe. Pada tahap empati, peneliti melakukan observasi dan wawancara kepada yang memiliki kepentingan untuk memahami kebutuhan dan permasalahan pengguna. Tahap definisi meniliti analasis data yang diperoleh untuk mengidentifikasi masalah utama dan membuat pesona pengguna. Tahap ideasi meneliti ide-ide Solusi untuk mengatasi masalah yang diidentifkasi. Pada tahap prototipe, peneliti merancang dan mengembangkan prototipe aplikasi mobile lost Found Fikom Kampus UMI. Hasil penelitian ini menunjukkan bahwa aplikasi ini yang dirancang dengan metode UCD dapat meningkatkan keterlibatan dan efisiensi pengguna dalam melakukan proses pencarian, pelaporan, dan pengembalian barang hilang dan ditemukan. Aplikasi ini diharapkan dapat membantu meningkatkan rasa aman dan nyaman bagi mahasiswa di lingkungan kampus UMI
Performance Analysis of Convolutional Neural Networks and Naive Bayes Methods for Disease Classification in Tomato Plant Leaves Nadya Salsabilah; Irawati; Lilis Nur Hayati
Indonesian Journal of Data and Science Vol. 6 No. 3 (2025): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v6i3.255

Abstract

Tomatoes are one of the most widely cultivated and consumed crops, but they are highly susceptible to disease attacks. The main diseases that often attack tomato plants are early blight and late blight. This study compares two machine learning-based classification methods, namely Convolutional Neural Network (CNN) and Naïve Bayes, in detecting tomato leaf diseases. The dataset used consists of 1,255 images obtained from Kaggle, which have been processed and divided into three data ratio scenarios (70:30, 80:20, and 90:10) for training and testing. The results showed that CNN is superior to Naïve Bayes, with the highest accuracy reaching 83.01%, while Naïve Bayes only achieved 34%. With better stability and accuracy, CNN has the potential to help farmers detect diseases more quickly and increase agricultural productivity
Klasifikasi Penyakit Bawang Merah Menggunakan Naïve Bayes dan Convolutional Neural Network Dian; Purnawansyah; Darwis, Herdianti; Nurhayati, Lilis
The Indonesian Journal of Computer Science Vol. 12 No. 4 (2023): 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.v12i4.3265

Abstract

Bawang merah rentan terhadap serangan penyakit yang dapat mengganggu pertumbuhan dan mengakibatkan hasil panen yang tidak maksimal bahkan gagal panen, seperti bercak ungu dan moler. Penelitian ini bertujuan untuk mengklasifikasikan penyakit bawang merah dengan mengimplementasikan meetode naïve bayes (gaussian , bernoulli, dan multinomial) dan CNN pada citra bawang merah yang diekstraksi menggunakan fourier descriptor. Metode FD – CNN memperoleh tingkat accuracy 98% dalam mengklasifikasikan penyakut bawang merah, moler dan bercak ungu, sedangkan metode CNN tanpa menggunakan ekstraksi menghasilkan nilai accuracy sebesar 97%. Adapun pada metode naïve bayes, pengklasifikasian yang memiliki accuracy paling tinggi adalah metode gaussian naïve bayes sebesar 95% sedangkan yang paling rendah yaitu metode bernoulli naïve bayes dengan tingkat accuracy sebesar 42%. Dengan demikian, dapat disimpulkan bahwa CNN, FD-CNN, dan FD-GNB efektif untuk meningkatkan performa klasifikasi pada citra daun bawang merah.
GELANG PENDETEKSI KEBERADAAN ANAK DAN MENGGUNAKAN TOMBOL DARURAT Aji, Fery Setyo; Amrin, Fery Andriawan; Wal Ikram, Muhammad Dzuljalali; Hayati, Lilis Nur
ILKOM Jurnal Ilmiah Vol 11, No 2 (2019)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i2.422.129-134

Abstract

In everyday life, humans often encounter problems in decision making, where problems that arise can be large or small, which are very influential in the results of decisions. Now humans are developing systems that can help determine the best alternative in a problem, namely the decision support system (DSS) in the decision support system there are alternatives, criteria and weights used to determine the best solution. The quality of human resources is one of the supporting factors to improve the performance productivity of an agency. So, from that competent human resources can support the level of performance, with performance appraisal, it will be known the achievements of each employee, this can be used by agencies as a consideration in determining the best employees. The purpose of this study is to create a good decision support system that can assist managers in evaluating the performance of an employee in an agency. Judging from the problem of the performance appraisal of an employee at PT. Cahaya iqra Mandiri is the object of research that produces the desired answer, the Admin section is a priority and can be implemented to determine neat administration and have important responsibilities in PT. cahaya iqra Mandiri.
Analysis of Stroke Classification Using Random Forest Method Banjar, Muhammad Firdaus; Irawati, Irawati; Umar, Fitriyani; Hayati, Lilis Nur
ILKOM Jurnal Ilmiah Vol 14, No 3 (2022)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v14i3.1252.186-193

Abstract

Stroke is a disease in which the sufferer experiences or experiences a rupture of a blood vessel in the brain so that the brain does not get a blood supply that provides oxygen. Patients who suffer from stroke will experience cognitive disorders ranging from decreased consciousness, visuospatial disorders, non-verbal learning disorders, communication disorders, and reduced levels of patient attention. Data from the World Stroke Organization shows that there are 13.7 million new stroke cases every year, and about 5.5 million deaths occur due to stroke. This research aims to analyze the attributes of any variables that affect the classification of strike disease and to test the performance of stroke classification in the form of accuracy, precision, recall, and f-measure. The method used is a random forest using a tree, namely 50, 100, 200, and 500. The classification of stroke is divided into stroke and no stroke. The data used is 5110, divided into 70% training data and 30% testing data. The results showed that the performance of a random forest using 100 trees was better than using 50, 200, and 500 trees, with an accuracy value of 86.82%, a precision of 15.76%, a recall of 38.15%, and an f1-score 22.30% after doing SMOTE.
KOLABORASI FISH-NET DAN TECHNOLOGY UNTUK OPTIMALISASI ALAT TANGKAP IKAN Irwan, Irwan; Fikar, Sul; Surachmad, Winarto; Hayati, Lilis Nur
ILKOM Jurnal Ilmiah Vol 10, No 2 (2018)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v10i2.318.207-214

Abstract

AbstractKelurahan Untia is one of the areas occupied by the fishermen and also the majority of the population work as fishermen catch fishermen. The dominant fishing gear used by fishermen in the village of Untia is surface gill net. But the use of surface gill net capture device is considered not effective and efficient because it has constraints on the process of checking the net, the old fishing process, the net tends to disappear, and the catch is considered less. So from that problem, we encourage us to create a technological innovation called FiNe-Tech (Fish Net Technology). FiNe-Tech is designed to be able to monitor fish trapped in surface gill net captures, simplify the process of catching fish in the sea, tracking the position of the jarring, speeding up the fishing process, and increasing the net catch through a smartphone application at close range and distance from the position nets even though we are at home though.
A Hybrid Movie Recommendation System to Address Data Sparsity Using Genre-Based K-Means and Neural Collaborative Filtering Darwis, Herdianti; Syahrir, Firdaus Abrazawaiz; Hayati, Lilis Nur
ILKOM Jurnal Ilmiah Vol 17, No 2 (2025)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v17i2.2868.203-212

Abstract

Recommendation systems play a crucial role in helping users navigate the overwhelming volume of information on digital platforms. However, conventional Collaborative Filtering (CF) methods often suffer from data sparsity, leading to reduced prediction accuracy and limited recommendation diversity. To address this challenge, this study proposes a hybrid recommendation model that integrates K-Means clustering based on genre, release year, and rating statistics into the Neural Collaborative Filtering (NCF) framework. Unlike previous works that rely on a single dimension like genre or demographics for clustering, our model uniquely combines multiple content-based features. Furthermore, we explicitly integrate the cluster labels as additional embedding features within the NCF framework, enabling more nuanced and context-aware representation learning. Using the MovieLens Latest-Small dataset, our hybrid model significantly outperforms the baseline NCF across all metrics, achieving a Mean Absolute Error (MAE) of 0.6097, a Root Mean Square Error (RMSE) of 0.7946, and improvements in Precision@10 (0.6065) and Recall@10 (0.7063). These findings highlight the effectiveness of our novel, content-aware clustering approach in deep learning recommenders, resulting in more accurate, diverse, and contextually relevant movie suggestions.
Penerapan Decision Support System (DSS) menggunakan Metode TOPSIS untuk Seleksi Mahasiswa Berprestasi Irawati; Sugiarti; Lilis Nur Hayati; Herman; Siti Safira Tawetubun; Nur Asy Syams Sam Ahmad
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3200

Abstract

The diversity of students in Indonesian universities requires an objective and transparent selection mechanism for high-achieving students, while manual selection practices remain prone to subjectivity and inconsistency in assessment. This study developed a Decision Support System (DSS) based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with a methodological innovation in the form of integrating eight multidimensional criteria that combine academic and non-academic aspects into a single structured decision-making framework. The implementation results show that the system is capable of increasing the consistency of selection decisions by up to 87% and reducing the selection process time by around 60% compared to conventional methods. These findings confirm that the TOPSIS-based DSS not only improves the objectivity of assessments but also provides significant operational efficiency, thus having the potential to become an adaptive and applicable decision support model for standardizing the selection of outstanding students in higher education.
Real-Time BISINDO Alphabet Recognition via Faster R-CNN Incorporating Skin Tone Diversity as a Classification Feature Lilis Nur Hayati; Anik Nur Handayani; Wahyu Sakti Gunawan Irianto; Rosa Andrie Asmara; Dolly Indra; Nor Salwa Damanhuri
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 3 (2026): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i3.15587

Abstract

Indonesian Sign Language (Bahasa Isyarat Indonesia/BISINDO) enables communication for deaf individuals through hand gestures, yet limited public awareness creates significant barriers between deaf and hearing communities. Existing recognition systems often fail to generalize across diverse skin tones, reducing their effectiveness in inclusive real-world deployment. The contribution of this research is a BISINDO alphabet recognition system that integrates skin color features - extracted via HSV-based skin segmentation - as an additional preprocessing layer within the Faster R-CNN framework, explicitly improving detection robustness across varied skin tones. The dataset consists of 8,000 images from ten adult actors representing light, medium-brown, and dark skin tones, augmented through flipping and brightness variation, with a 90:10 training-to-testing ratio. The model was trained over 15,000 steps with a batch size of 24, selected through empirical validation to balance convergence stability and dataset size. Experimental results show that indoor conditions outperform outdoor settings due to controlled lighting. Light-skinned and dark-skinned participants achieved the highest accuracy of 87.5% and F1-score of 85.71%, while medium-brown-skinned participants showed slightly lower performance, likely attributed to greater variability in reflectance under mixed lighting. The system achieves 24 frames per second, demonstrating potential for real-time communication support. These findings confirm that Faster R-CNN with skin color feature integration is effective for BISINDO alphabet recognition, with skin tone diversity being a critical performance factor. Future work will explore larger participant pools and dynamic gesture recognition under varied real-world lighting scenarios.
Perancangan UI/UX Pada Aplikasi Buahta Makassar Menggunakan Metode Design Thinking Berbasis Website Andi Rezaldy Jaya; Lilis Nur Hayati; Herman Herman
LINIER: Literatur Informatika dan Komputer Vol 3, No 2 (2026)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/linier.v3i2.3646

Abstract

Website Buahta Makassar dirancang untuk mempermudah pelanggan, terutama yang tinggal jauh dari lokasi toko, dalam mengakses informasi produk secara daring. Proses perancangan menggunakan metode design thinking melalui lima tahapan: empathize, define, ideate, prototype, dan test, serta memanfaatkan tools Figma. Rancangan menampilkan fitur utama seperti daftar buah, harga, dan penambahan jumlah produk. Tahap pengujian dilakukan dengan metode usability testing menggunakan platform Maze. Hasil pengujian pada dua layar utama kategori dan review menunjukkan usability score sebesar 81, dengan rata-rata waktu interaksi 7-8 detik dan tingkat salah klik sebesar 78%. Nilai tersebut masuk dalam kategori cukup, yang berarti fitur berfungsi namun masih memerlukan peningkatan terutama dalam kejelasan navigasi. Rancangan ini menjadi pondasi awal untuk pengembangan sistem e-commerce Buahta Makassar di masa mendatang
Co-Authors A?ayunnisa, Nurul Abdi, Muhammad Alim Abdul Wahab Abdullah, Syahrul Mubarak Achmad Suyudi Amiruddin Aditya Rezky Agrienta Bellanov Agung, Riski Dewa Ahmad Zaky Aji, Fery Setyo Ali Munawir Amir, Nur Hikmah Amrin, Fery Andriawan Andi Rezaldy Jaya Andi Rizaldi Pratama Andi Syifa Salsabila Ruflin Andika Syaputra Andrian, David Anik Nur Handayani Ansari Ansari As'ad, Ihwana Asdar Djamereng Athifah Arsa Kharawan Atmajaya, Dedy Ayu Aksari Ayu Amelia Banjar, Muhammad Firdaus Bora, Leni J Damanhuri, Nor Salwa Damayanti, Florencia Agatha Daris, Mega Asfirawati Dewantoro, Albertus Daru Dewi Ernita Rahma Dewi Pancawati Novalita, Dewi Pancawati Dewi Widyawati Dian Dian Dimas, Ravael Djamereng, Asdar Dolly Indra Dwi Nur Halizah Eka Inggraha Iha Elvira Siruna Fadly Achmad Fattah, Farniwati Febriyanti, Rina Fery Setyo Aji Fikar, Sul Fikar, Sul Fitra Ramadani Fitriyani Umar Haidawati Nasir Halimahtul Wildan Haris, Najwan Firdaus Harjuna, Muhammad Harlinda Lahuddin Herdianti Herman Herman Herman Hermany, Nurul Inayah Huda, Besse Nurul Irawati - Irawati Irawati Irawati Irawati Irawati Irja, Mulianty Cipta Irwan Ardyansah Ismail, Wawan jabir, sitti rahmah Jeremy, Jason Jihan Fatihah Ismiralda Karim Abdullah Kristiani, Poppy Marselina Kurniati, Nia Lokapitasari Belluano, Poetri Lestari Lukman Syafie Lusi Mei Cahya Wulandari Luthfiya Salsabila Fakhruddin Magfirah, Magfirah Manga, Abdul Rachman Mude, Muh. Aliyazid Muh Alim Abdi Muh. Aliyazid Mude Muhammad Agus Muljanto Muhammad Alim Abdi Muhammad Arif Muhammad Bayu Rahmat Muhammad Fadhli Ardhi Indrani Muhammad Fatwa Hazjuang Muhammad Haerdiansyah Syahnur Muhammad Ikhsan Muhammad Ikhsan Supriyadi Muhammad Nazar Alfath Muhammad Rezki Muhammad Rifky Saputra Scania Muhammand Akbar Mukarramah, Rifqatul Munawir Munawir Munawir Nasir Hamzah Mush'ab Al Mubarak Nadya Salsabilah Nor Salwa Damanhuri Novianti, Nabila Nugroho, Afifah Khairunnisa Nur Asy Syams Sam Ahmad Nur Hikmah Amir Nurfadillah Said Nurlinda Nurlinda Nurul Kholifah Yulinda Nurul Rismayanti Nurwaini Situju Purba, Lasman Parulian Purnawansyah Purnawansyah Putri Bimadayanti R, M Yusuf Rafael, Ivan Rahbiah, Sitti Ramdan Satra Ratnawaty, Latifah Rayhana Bahar Resky Anugrah Rezky Anugrah Rezky Anugrah Ridho Anugrah Albanjari Rini Andari, Rini Risti Amelia Roesman Ridwan Raja Rosa Andrie Asmara Sahelangi, Milly Maria Salim, Yulita Salmat, Surya Mudti Saripah Fitriani Satma, Satma Setia Budi, Muh Arif Siti Safira Tawetubun Sitti Rahbiah Busaeri Sri Hartini Sri Widari, Nyoman Sugiarti Sugiarti Sugiarti, Sugiarti Sulfikar Sulfikar Surachmad, Winarto Surachmad, Winarto Surya Mudti Salmat Syafie, Lukman Syahrir, Firdaus Abrazawaiz Syahrul Bone Syam, Muhammad Farhan Ulhaq, Muhammad Dhiya Umar Mansyur Umar, Fitriyani Umniah Umniah Valentino, Teofilus Veithzal Rivai Zainal Wa Ode Tanti Wahyu Hidayat Ramadhan Wahyu Kadri Rahmat Suat Wahyu Sakti Gunawan Irianto Wahyudi, Yasyfa Xena Arleyda Wal Ikram, Muhammad Dzuljalali Wibowo, Nanang Roni Widyawati, Dewi Wisti Astuti Wistiani Astuti Wulan Purnama Sari Yulita Salim Yundari, Yundari