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IMPLEMENTASI SIMPLE ADDITIVE WEIGHTING DALAM PEMILIHAN KARYA SENI KALIGRAFI TERBAIK DI PONDOK PESANTREN DARUL AMAN GOMBARA MAKASSAR Andi Mattangkilang, Ainun; Lilis Nur Hayati; Lukman Syafie
JURNAL ILMU KOMPUTER Vol 9 No 1 (2023): Edisi April
Publisher : LPPM Universitas Al Asyariah Mandar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35329/jiik.v9i2.255

Abstract

Penentuan penilaian kaligrafi terbaik masih dilakukan secara manual (tulis tangan) karena belum adanya sistem penilaian secara berbasis website. Demikian juga belum ada penentuan metode dalam menentukan pengambilan keputusan untuk menentukan kaligrafi terbaik, dimana guru yang mengajar pada mata pelajaran khat sangat membutuhkan sebuah aplikasi atau sistem yang mendukung penilaian kaligrafi terbaik dari para santri di pondok pesantren. Aplikasi atau sistem yang akan dibuat oleh peneliti ini akan menentukan penilaian setiap kriteria-kriteria. Kriteria pada jenis khat itu ditentukan dari kaidah, warna, motif, kerapian, dan nilai estetika. Berdasarkan hal tersebut untuk menentukan kaligrafi terbaik sesuai dengan kriteria yang akan ditentukan, maka penelitian ini menggunakan metode Simple Additive Weighting (SAW). Metode SAW atau yang dikenal penjumlahan terbobot yang merupakan metode yang digunakan untuk mencari nilai bobot pada rating kinerja setiap alternatif pada setiap atribut. Dalam perhitungannya membutuhkan proses normalisasi matriks keputusan ke suatu skala yang akan dibandingkan dengan semua kriteria dari setiap alternative. Dengan adanya analisis penerapan metode SAW untuk pemilihan kaligrafi terbaik, dapat mempermudah, mempercepat serta memberikan hasil rekomendasi yang akurat untuk penilaian kaligrafi terbaik sehingga dapat membantu dalam proses pengambilan keputusan dan menentukan kaligrafi yang terbaik yang dibuat oleh santri. Dengan ini hasil pengujian black box (beta) dari cara perhitungan tersebut diperoleh skor dan pernyataan sebagai berikut: soal nomor 1 = 4,60%, soal nomor 2 = 5,00%, soal nomor 3 = 4,20 %, soal nomor 4 = 4,80%, soal nomor 5 = 4,80%, soal nomor 6 = 4,90%. Maka diperoleh nilai rata-rata 4,71% dengan nilai indeks 78,50% yang termasuk dalam baik.
BACKWARD CHAINING METHOD UNTUK DIAGNOSA PENYAKIT BINTIK MERAH PADA KULIT BAYI MENGGUNAKAN APLIKASI BERBASIS WEB Lilis Nur Hayati; Yulita Salim; Hasriwiani Habo Abbas; Rezky Anugrah; Herawati Herawati; Ihwana As'ad; Muflih Awaluddin
JURNAL INFORMATIKA DAN KOMPUTER Vol 7, No 2 (2023): SEPTEMBER 2023
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiko.v7i2.788

Abstract

Weak immunity or the baby's immune system makes it very susceptible to bacteria, germs and disease. Babies have difficulty explaining their complaints, therefore parents are expected to catch every body language from their child. In general, if a child has health problems, parents will check with a health service provider and consult with health workers who are experts in their field, but sometimes there are obstacles such as limited working hours (practice). So in this study a tool was created in the form of a website-based expert system to diagnose red spots in babies using the Backward Chaining method. The Backward Chaining method searches with the goal first followed by a description of the attributes in this case, namely the disease first and then adjusted to the existing symptoms. The system uses the waterfall method, The results of this study show that an expert system can properly diagnose red spots on the baby's skin to help parents identify and find appropriate treatment solutions. Testing this system can be understood and implemented with the value of application users obtaining an assessment of 81% agreeing according to baby's parents, nurses and dermatologists.
Prototype Of DPO Search Information System (People Search List) On CCTV Cameras Using Face Recognition Anugraha, Tri Reski; Dedy Atmajaya; Lilis Nur Hayati; Anugraha, Nurhajar
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 13 No. 2 (2023): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v13i2.65

Abstract

The efficiency aspect of the housing security sector is the main consideration in creating information technology in a CCTV security development, because so far CCTV has not guaranteed maximum housing security, because CCTV can only record not analyze. This makes CCTV only a recording device for the point of occurrence, so this activity is less effective considering CCTV cannot analyze the face of a person who has committed a DPO action. So on that basis, researchers are developing existing technologies with facial recognition systems using the face recognition method for housing security. This method works by detecting a person's facial features. The face recognition apps provide information to the authorities by notifying the notification on the user's smartphone (security guard). So face recognition apps have been applied to the Green Cakra Housing, to help security guards monitor the entrance and exit of guests in the housing. This system can recognize the face of DPOs by obtaining a percentage of the assessment as much as agreeing that the application is effective enough.
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.
A Comperative Study on Efficacy of CNN VGG-16, DenseNet121, ResNet50V2, And EfficientNetB0 in Toraja Carving Classification Herman; An'nisa Pratama Putri; Megat Norulazmi Megat Mohamed Noor; Herdianti Darwis; Lilis Nur Hayati; Irawati; Ihwana As’ad
Indonesian Journal of Data and Science Vol. 6 No. 1 (2025): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v6i1.220

Abstract

Introduction: Passura', or Toraja carvings, are an essential element of the cultural heritage of the Toraja people in Indonesia. These carvings feature complex motifs rooted in nature, folklore, and spiritual symbolism. This study aims to evaluate the efficacy of four Convolutional Neural Network (CNN) architectures—VGG-16, DenseNet121, ResNet50V2, and EfficientNetB0—in classifying seven traditional Toraja carving motifs. Methods: A dataset of 700 images was collected and categorized into seven motif classes. The dataset was split into 80% for training and 20% for validation. Each CNN model was trained for 25 epochs with standard pre-processing, including resizing to 224×224 and normalization. Performance evaluation was conducted based on validation accuracy and confusion matrix analysis to assess classification precision and model overfitting. Results: EfficientNetB0 achieved the highest validation accuracy of 98%, although signs of overfitting were observed. ResNet50V2 followed closely with a validation accuracy of 95.33% and demonstrated the most balanced classification results across all motif categories. VGG-16 and DenseNet121 achieved 94.67% and 81.82%, respectively. Confusion matrix analysis confirmed the robustness of ResNet50V2 in correctly identifying complex patterns. Conclusions: The findings indicate that ResNet50V2 provides a reliable balance between accuracy and generalizability for classifying Toraja carvings, making it suitable for digital preservation of cultural heritage. EfficientNetB0, while achieving higher accuracy, may require additional regularization to avoid overfitting. This study contributes to the development of AI-driven cultural documentation and suggests future research with larger and more diverse datasets to improve model robustness
An In-depth Exploration of Sentiment Analysis on Hasanuddin Airport using Machine Learning Approaches Lilis Nur Hayati; Fitrah Yusti Randana; Darwis, Herdianti
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 2 (2025): April 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i2.6253

Abstract

Machine learning-based sentiment analysis has become essential for understanding public perceptions of public services, including air transportation. Sultan Hasanuddin Airport, one of the main gateways in eastern Indonesia, faces the challenge of improving services amid changing user needs due to the COVID-19 pandemic. This study aims to compare the effectiveness of three machine learning algorithms- Support Vector Machine (SVM), Naive Bayes Multinomial, and K-Nearest Neighbor (KNN)-in analyzing the sentiment of user reviews related to airport services. The research also explores data splitting techniques, text preprocessing, data balancing using SMOTE, model validation, and method parameterization to ensure optimal results. The review data was retrieved from Google Maps (2021-2024) and underwent manual labelling. Text preprocessing includes normalization, stemming using Sastrawi, and stopword removal. The data-balancing technique uses SMOTE, while model evaluation is done with stratified k-fold cross-validation. SVM with a linear kernel showed the best performance, achieving an F1-score of 98.4%. Naive Bayes performed optimally, achieving an F1-score of 93.9%, while KNN recorded the best F1-score of 92.0%. SMOTE was shown to improve Naive Bayes' performance on unbalanced datasets, although it did not significantly impact SVM. The findings of this study provide data-driven recommendations to improve services at Sultan Hasanuddin Airport, such as the management of cleaning facilities, waiting room comfort, and passenger flow efficiency. In addition, this research opens up opportunities for developing real-time sentiment analysis systems that can be applied in other air transportation sectors.
Performance Analysis of Random Forest and Naive Bayes Methods for Classifying Tomato Leaf Disease Datasets Ananda, Rima; Lilis Nur Hayati; Irawati
Indonesian Journal of Data and Science Vol. 6 No. 2 (2025): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v6i2.252

Abstract

Tomato productivity is often disrupted by diseases affecting tomato plants, such as early blight and late blight, which can significantly reduce crop yields. Early detection of these diseases is crucial to prevent greater losses. This study compares two machine learning-based classification methods, namely Random Forest and Naïve Bayes, in identifying diseases on tomato leaves. The dataset used consists of 1,255 images obtained from Kaggle, with the data divided into two classes: early blight with 627 images and late blight with 628 images, which then underwent preprocessing and data splitting with three ratio scenarios (70:30, 80:20, and 90:10) for training and testing. This study shows that it only achieved an accuracy of 76.98%, while the Random Forest method had the highest accuracy of 92.86% in the 90:10 data ratio scenario. Thus, the Random Forest method proves to be more effective in classifying tomato leaf diseases compared to Naïve Bayes. The implementation of this model can help farmers detect diseases more quickly and accurately, thereby increasing agricultural productivity.
Implementation of a Web-Based Information System in Karang Taruna Parangloe: Implementasi Sistem Informasi Berbasis Web di Karang Taruna Parangloe Indra, Dolly; Syahnur, Muh. Haerdiansyah; Lilis Nur Hayati
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 9 No. 2 (2025): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v9i2.26465

Abstract

This study explores the implementation of a web-based information system for Karang Taruna Parangloe, a youth organization in Kelurahan Lanna, Parangloe District. The initiative was driven by the need to improve information dissemination, which previously relied on traditional methods like WhatsApp groups. While convenient, this approach had limitations in reaching a broader audience and effectively promoting organizational activities. To address these challenges, a Community Partnership Program (PKM) was carried out in four key stages: observation, socialization and training, technology implementation, and evaluation. During the observation phase, it became clear that the organization lacked an official platform for sharing updates and announcements. This was followed by socialization and training sessions, aimed at improving digital literacy among members, equipping them with the skills needed to manage and utilize a web-based system.The technology implementation phase focused on developing and launching the organization's official website, https://karangtarunaparangloe.com. Designed as a comprehensive information hub, the website includes a user guide to help administrators manage content effectively. The evaluation phase showed significant improvements in members' understanding and technical skills, with average post-test scores rising from 62 to 85. More than just a tool for sharing information, the website has helped enhance the organization's image and boost community engagement. This initiative demonstrates the power of digital transformation in empowering youth organizations and strengthening communication within communities. It also serves as an inspiring example for other organizations looking to adopt digital solutions to streamline operations and enhance their outreach efforts.
Rancang Bangun Sistem Informasi Rental Kendaraan Berbasis Website Menggunakan Metode Waterfall Nabila Putri Utami Mustan; Lilis Nur Hayati; Nia Kurnia
Inventor: Jurnal Inovasi dan Tren Pendidikan Teknologi Informasi Vol. 3 No. 3 (2025): Edisi Oktober
Publisher : STKIP Taman Siswa Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37630/inventor.v3i3.3441

Abstract

Lonjakan jumlah wisatawan domestik berdampak pada meningkatnya kebutuhan transportasi di Kota Makale. Kondisi ini turut mendorong berkembangnya layanan rental kendaraan, termasuk Rafi Motor, sebagai alternatif dalam memenuhi mobilitas wisatawan dan masyarakat lokal. Namun, sistem operasional di Rafi Motor masih dikelola secara manual sehingga menimbulkan kendala dalam pencatatan transaksi, pengelolaan kendaraan, dan pelayanan pelanggan. Penelitian ini bertujuan untuk merancang dan membangun sistem informasi rental kendaraan berbasis website menggunakan metode Waterfall agar dapat meningkatkan efisiensi operasional. Metode penelitian dilakukan melalui observasi, wawancara, dan pengumpulan data terkait kebutuhan sistem, kemudian dilanjutkan dengan tahapan pengembangan perangkat lunak mulai dari analisis, desain, pengodean, hingga pengujian. Proses implementasi menggunakan bahasa pemrograman PHP dengan basis data MySQL. Sistem yang dihasilkan menyediakan fitur registrasi, pemesanan online, pengelolaan kendaraan, galeri gambar, jenis pembayaran, dan riwayat transaksi pelanggan. Pengujian dilakukan dengan metode black-box pada tahap alpha dan beta, serta evaluasi usability menggunakan System Usability Scale (SUS). Hasil penelitian menunjukkan 80,125% artinya sistem dapat berjalan sesuai kebutuhan pengguna, terbukti dari hasil pengujian yang menyatakan semua fitur berfungsi normal serta nilai usability berada pada kategori layak digunakan. Dengan demikian, sistem ini dapat mendukung digitalisasi usaha rental kendaraan, meningkatkan kecepatan layanan, serta meminimalkan risiko kesalahan operasional.