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All Journal TEKNIK INFORMATIKA Jurnal Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Sistemasi: Jurnal Sistem Informasi Jurnal Teknologi dan Sistem Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal Khatulistiwa Informatika Paradigma JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Information System for Educators and Professionals : Journal of Information System JITK (Jurnal Ilmu Pengetahuan dan Komputer) Techno Nusa Mandiri : Journal of Computing and Information Technology Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Teknologi Informasi dan Terapan (J-TIT) Jurnal Informasi dan Teknologi Jurnal Restikom : Riset Teknik Informatika dan Komputer Journal of Applied Data Sciences Jurnal Responsif : Riset Sains dan Informatika International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Sosial dan Abdimas INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Journal Medical Informatics Technology SWAGATI: Journal of Community Service
Sri Hadianti
Department Of Information System, STMIK Nusa Mandiri, Jl. Raya Jatiwaringin No 2, Cipinang Melayu, Makasar, Jakarta Timur 13620|STMIK Nusa Mandiri
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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Evaluating Deep Learning Architectures for Potato Pest Identification: A Comparative Study of NasNetMobile, DenseNet, and Inception Models Hadianti, Sri; Riana, Dwiza; Sulistyowati, Daning Nur
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.545

Abstract

Manual potato pest identification that is still applied today is often time-consuming and highly dependent on farmer skills in the field. This causes delays in taking action and inaccurate reporting, especially in pest emergencies. In addition, these limitations slow down the response to pest control which ultimately risks reducing crop yields and farmer income. This study aims to develop a more accurate, fast, and consistent deep learning-based approach to identify potato pests, in order to support practical solutions that farmers can implement independently. This study contributes by comparing three deep learning architecture models, namely NasNetMobile, DenseNet, and Inception which are designed to identify pest images. The potato pest image dataset used was collected from various sources equipped with an augmentation process to increase data diversity. The model was drilled using transfer learning techniques to utilize previously learned features on a large dataset. The evaluation model was carried out comprehensively based on accuracy, precision, and inference time efficiency. The results showed that the DenseNet model achieved the highest accuracy of 97% with an inference time of 11 seconds, and this model maintained a relatively stable performance and was superior several times compared to other models. Based on these results, DenseNet was chosen as the most effective and reliable model to be developed for practical applications in the field. This study provides practical implications in the form of providing a model that can be integrated into a mobile-based application that is easy to use by farmers, including in remote areas. This allows farmers to identify pests independently without requiring in-depth technical expertise. In addition, this study is a new benchmark for the development of artificial intelligence-based pest identification systems in other crops and opens up opportunities for integration with IoT-based technologies to support sustainable agricultural practices.
Image Analysis of Skin Diseases Using DenseNet-121 Architecture Putra, Mahesa; Pioni, Pioni; Rosalina, Alya; Aditya, Diyar; Azhari, Azidan Allen Deva; Hadianti, Sri; Nurfalah, Ridan
Journal Medical Informatics Technology Volume 3 No. 2, June 2025
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v3i2.99

Abstract

Skin diseases such as dermatitis, psoriasis, and tinea often exhibit similar visual characteristics, which can lead to frequent errors in early diagnosis. Accurate diagnosis is critical, as each disease requires different treatment approaches. This study aims to develop an automated classification model for these three skin diseases using a deep learning approach based on the DenseNet-121 architecture, which consists of 121 layers designed to facilitate efficient feature reuse and gradient flow. The dataset consists of 300 labeled images, evenly distributed among the three disease classes. To enhance model generalization, preprocessing steps were applied, including data normalization and augmentation techniques such as image rotation (±20°), horizontal and vertical flipping, random zooming (range 0.8-1.2×), and brightness adjustment (±20%). The model was trained and validated using a stratified 5-fold cross-validation strategy. Experimental results demonstrated an overall classification accuracy of 94.59%, with high precision and recall scores across all classes. These results indicate the potential of using DenseNet-based deep learning models as decision support tools for early skin disease diagnosis. Further validation with larger datasets and clinical input from dermatologists is recommended to ensure reliability in real-world healthcare settings. Visual comparison through Grad-CAM heatmaps was also conducted to enhance interpretability and validate model focus on relevant skin features.
Pemanfaatan Aplikasi Pengiriman Makanan Pasca Penurunan Level Pembatasan Kegiatan Masyarakat Akibat Covid-19 Di Indonesia Kodri, Wan Ahmad Gazali; Riana, Dwiza; Hadianti, Sri
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 3: Juni 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023106859

Abstract

Penggunaan aplikasi pengiriman makanan meningkat sangat cepat, terlebih saat terjadinya Pandemi COVID-19, dimana pergerakan orang dibatasi, membuat setiap orang berupaya menggunakan aplikasi pengiriman makanan atau Food Delivery Application (FDA) dalam memenuhi kebutuhan pangan. Penurunan jumlah kasus COVID-19 menyebabkan pemerintah Indonesia menurunkan level Pemberlakuan Pembatasan Kegiatan Masyarakat (PPKM) sehingga masyarakat dapat beraktivitas sosial kembali. Tujuan penelitian ini adalah untuk menilai instrumen yang memengaruhi Continuance Intention FDA pasca penurunan level PPKM COVID-19 menjadi level 1 di Indonesia. Sebanyak 166 responden telah dikumpulkan. Kuesioner terdari dari 17 pertanyaan demografi dan 38 pertanyaan indikator. Skala Likert dengan lima tingkat penilaian digunakan untuk mengevaluasi pertanyaan indikator. Model yang digunakan adalah Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Data dianalisis dengan menggunakan Structural Equation Modeling (SEM) berbasis Partial Least Square (PLS), meliputi analisis faktor, analisis jalur, dan regresi. Penelitian menunjukkan Performance Expectancy, Social Influence, Habit, dan Rasa Solidaritas berdampak signifikan pada Continuance Intention FDA. Effort Expectancy, Facilitating Condition, Hedonic Motivation, Price Value, dan Risk Perception menunjukkan pengaruh yang tidak signifikan terhadap Continuance Intention. Pengembang FDA dapat menggunakan data ini untuk meningkatkan layanan mereka dan menambah pemahaman tentang FDA, loyalitas pengguna, peluang bisnis dan strategi pemasaran. Restoran dapat menggunakan kajian ini untuk melihat pergeseran pola pembelian makanan. AbstractThe use of food delivery applications is increasing very quickly, especially during the COVID-19 Pandemic, when people's movements were restricted, making everyone try to use Food Delivery Applications (FDA) to meet their meal needs. The decrease in the number of COVID-19 cases has caused the Indonesian government to lower the level of Enforcement of Restrictions on Community Activities (PPKM) so that people can return to common social activities. The purpose of this study was to assess the instruments that influence the FDA's Continuance Intention after the reduction in the level of PPKM COVID-19 to level 1 in Indonesia. A total of 166 respondents have been collected. The questionnaire consists of 17 demographic questions and 38 indicator questions. A Likert scale with five rating levels was used to evaluate the indicator questions. The model used is the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Data were analyzed using Partial Least Square (PLS) based Structural Equation Modeling (SEM), including factor analysis, path analysis, and regression. Research shows Performance Expectancy, Social Influence, Habit, and Sense of Solidarity have a significant impact on FDA Continuance Intention. Effort Expectancy, Facilitating Condition, Hedonic Motivation, Price Value, and Risk Perception show no significant effect on Continuance Intention. FDA developers can use this data to improve their services and increase their understanding of the FDA, user loyalty, and identify marketing opportunities and strategies. Restaurants can use this assessment to see shifts in food purchasing patterns. 
Desain UI/UX Aplikasi D’Laundry Dengan Metode Design Thinking Nurfalah, Ridan; Hadianti, Sri; Sari, Putri Permata; Ramadhan, Mohamad Ragil; Fatimah, Winda Astariyah
IJCIT (Indonesian Journal on Computer and Information Technology) Vol 9, No 1 (2024): IJCIT Mei 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijcit.v9i1.22000

Abstract

Perancangan desain User Unterface (UI) dan er Experience (UX) pada aplikasi D’Laundry dilakukan pada penelitian ini, yang bertujuan untuk memfasilitasi transaksi antara masyarakat dengan toko laundry pakaian terdekat. Metode yang digunakan dalam penelitian ini adalah Design Thinking, yang melibatkan serangkaian tahap dari emphatize, define, ideate, prototype, dan test. Tahap awal penelitian, emphatize, memungkinkan untuk memahami dengan mendalam tantangan yang dihadapi oleh masyarakat, seperti kesulitan dalam mengakses toko laundry dan kurangnya transparansi dalam proses transaksi, termasuk ketidakjelasan tentang kapan pakaian akan selesai dicuci. Tahap define kemudian mengidentifikasi permasalahan utama yang harus diselesaikan melalui desain UI/UX. Dari situ, melalui tahap ideate, berbagai solusi kreatif dihasilkan untuk mengatasi permasalahan-permasalahan tersebut. Desain UI/UX yang dihasilkan kemudian dikembangkan melalui prototype dan diujikan kepada 100 responden sebagai evaluasi akhir dengan pertanyaan kuisioner, yang menghasilkan 93 responden menerima dan terbantu dengan desain UI/UX yang diujikan.hasil penelitian ini dapat diterima dengan baik oleh user yang akan menggunakan aplikasi D’Laundry. Penelitian ini diharapkan memberikan kontribusi penting dalam pengembangan aplikasi D’Laundry yang lebih efektif dan memenuhi kebutuhan masyarakat.  The design of the user interface (UI) and user experience (UX) for the application named D’Laundry was carried out in this research, which aims to facilitate transactions between the public and nearby clothing laundry shops. The method used in this research is Design Thinking, which involves a series of stages from emphatize, define, ideate, prototype, and test. The initial phase of the research, emphatize, enabled researchers to understand in depth the challenges faced by the community, such as difficulties in accessing laundry shops and a lack of transparency in the transaction process, including uncertainty about when clothes will be washed. The define stage then identifies the main problems that must be resolved through UI/UX design. From there, through the ideate stage, various creative solutions are produced to overcome these problems. The resulting UI/UX design was then developed through a prototype and tested on 100 respondents as a final evaluation with questionnaire questionswhich resulted in 93 respondents accepting and being helped by the UI/UX design being tested. The results of this research can be well received by users who will use the D'Laundry application.This research is expected to make an important contribution in developing D’Laundry applications that are more effective and meet community needs.
Perancangan Website Layanan Administrasi berbasis UI/UX Di RW 013 Cipinang Melayu Jakarta Timur Nurfalah, Ridan; Mayangky, Nissa Almira; Hadianti, Sri; Kusumayudha, Mochammad Rizky
Jurnal Sosial & Abdimas Vol. 6 No. 1 (2024): Jurnal Sosial & Abdimas
Publisher : LPPM Universitas Adhirajasa Reswara Sanjaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51977/jsa.v6i1.1554

Abstract

Dalam era digitalisasi, peran teknologi informasi menjadi krusial dalam meningkatkan efisiensi administrasi masyarakat. Penelitian ini merupakan hasil kegiatan pengabdian masyarakat yang dilakukan oleh dosen dari Universitas Nusa Mandiri di wilayah RW 013 Cipinang Melayu Jakarta Timur. Fokus utama pada penelitian ini adalah perancangan website layanan administrasi berbasis desain UI-UX yang bertujuan untuk meningkatkan efektivitas pengelolaan administrasi dan keterlibatan masyarakat dalam proses lokal. Metode penelitian yang dilakukan melibatkan partisipasi aktif dosen dan masyarakat setempat dalam proses perancangan website. Analisis data menggunakan pendekatan kualitatif untuk menggali kebutuhan masyarakat dan memastikan bahwa website yang dihasilkan sesuai dengan konteks local. Penelitian ini diharapkan memberikan pandangan yang mendalam tentang perancangan website administrasi di tingkat RW, menggabungkan konsep-konsep UI-UX terkini dan menawarkan solusi inovatif untuk meningkatkan kualitas hidup dan partisipasi masyarakat. Dengan melibatkan dosen dan masyarakat setempat, diharapkan implementasi website ini dapat memberikan dampak positif yang signifikan dalam pengelolaan administrasi lokal di RW 013 Cipinang Melayu Jakarta Timur.
WORD2VEC OPTIMALIZATION USING TRANSFER LEARNING IN INDONESIAN LANGUAGE FOR HIGHER EDUCATION Hadianti, Sri; Riana, Dwiza; Tohir, Herdian; Jarwadi, Jarwadi; Rosdiana, Tjaturningsih; Sopandi, Evi; Kristiyanti, Dinar Ajeng
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.6051

Abstract

Natural language processing (NLP) in Indonesian faces challenges due to limited linguistic resources, particularly in developing optimal word embedding models. This study optimizes the Word2Vec model for Indonesian in higher education contexts by leveraging transfer learning and lexicon expansion. Using a dataset of 4,463 higher education related tweets consisting of positive and negative sentiment categories, the proposed NewWord2Vec model combined with a Support Vector Machine (SVM) classifier achieved a 4% improvement in word detection accuracy compared to the standard Word2Vec. This enhancement demonstrates better performance in capturing linguistic nuances and sentiment orientation in Indonesian text. However, the model’s applicability remains limited to higher education terminology, and potential biases from transfer learning must be addressed. Future research should expand the dataset to diverse domains and refine the transfer learning process to better capture contextual variations in Indonesian. These findings contribute to advancing NLP applications in Indonesian, particularly for automated assessment systems, recommendation tools, and academic decision-making processes
Co-Authors Achmad Baroqah Pohan Achmad Rifai Adilah Purnamasari Aditya Gusti Aditya, Diyar Akmaludin Akmaludin, Akmaludin Aldi Jakaria Arina Selawati Azhari, Azidan Allen Deva Aziz, Faruq Chairul, Yasrizal Chandra Nugraha, Chandra Daniati Uki Eka Saputri Dinar Ajeng Kristiyanti, Dinar Ajeng Dwiza Riana Dwiza Riana Dwiza Riana Dwiza Riana Dwiza Riana Dwiza Riana Evi Sopandi, Evi Fachry Abda El Rahman Fani Nurona Cahya Fatimah, Winda Astariyah Fiqi Pranastara Frieyadie Galih Widagdo Heckel Sungkar Iftina Salya Rosa Izni Nur Karimah Jajang Jaya Purnama JARWADI, JARWADI Kodri, Wan Ahmad Gazali Kurniawantoro Kusumayudha, Mochammad Rizky Laela Kurniawati Lestari Yusuf Mayangky, Nissa Almira Mochamad Rizky Kusumayudha Mochammad Rizky Kusumayudha Muhamad Hasan Muhammad Faitullah Akbar Nanik Wuryani Nila Hardi Nugraha, Fitra Septia Nur Fiyah Nur Sulistyowati, Daning Nurfalah, Ridan Nurul Jannah Salsabila Pioni, Pioni Putra, Mahesa Rafly Pratama Ramadhan, Mohamad Ragil Resti Kartika Dewi Ridan Nurfalah Ridan Nurfalah Riski Febrianto Rizka Dahlia Rizky Ade Safitri Rosalina, Alya Rosdiana, Tjaturningsih Rousyati Rousyati Rudini, Edwin Saputra, Ridwan Siti Nurdiani siti nurlela Siti Nurlela Sofiyatul Mu’minah Sri Rahayu SRI RAHAYU Sugiyanti Sugiyanti Sulistyowati, Daning Nur Tohir, Herdian Widagdo, Galih Windu Gata WITRIANA ENDAH PANGESTI Yutri Amelia