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All Journal JEJARING JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Journal of Innovation and Sustainable Empowerment Nuansa Informatika
Iwan Lesmana
Universitas Kuningan
Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Nursing

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Implementasi Algoritma Genetika pada Tata Ruang Ibukota Kecamatan (Studi Kasus : Desa Hantara) Dadan Nugraha; Iwan Lesmana; Gian Megantara
JEJARING : Jurnal Teknologi dan Manajemen Informatika Vol 6, No 2 (2021)
Publisher : Universitas Kuningan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/jejaring.v6i2.6739

Abstract

Spatial planning is an obligation that must be carried out by each Regional Government. At present, spatial planning is still conventionally planned by the spatial planning company. Regarding with the object of research that the authors examined, namely Hantara Village, Hantara Village did not yet have a plan for how the future projection and development of Hantara Village. With a touch of information technology, for now spatial planning can be done using an application by implementing a method that is Genetic Algorithm into the application .Genetic Algorithm is an optimal search algorithm which is in its implementation the genetic algorithm will look for the most optimal points which is match with the constraints that have been determined based on law 26 of 2007 concerning Spatial Planning. Then the search results of the genetic algorithm data will be visualized by using the features of the mapbox, the online map provider. In software development, the author use the Rational Unified Process (RUP) method which has four stages, namely: Inception, Elaboration, Contruction, and Transition. This application is built use the python programming language, along with html and javascript for visualizing the data. Based on the results of this research the authors can conclude that this research can make a projection of residental area in Hantara village accordance with genetic algorithm and its constraint.Keywords— Sepatial Planning, Genetic Algorithm, Data Visualization, RUP, Python
Fuzzy-Driven Adaptive NPC Behavior in a Meme-Based Platformer Game for Android Mobile: Perilaku NPC Adaptif Berbasis Fuzzy dalam Game Meme Platformer Berbasis Ponsel Android Encep Sayid Amrulloh; Rio Andriyat Krisdiawan; Iwan Lesmana; Lutfi Rohmawati
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.440

Abstract

Game-based applications are increasingly used beyond entertainment to deliver adaptive, engaging user experiences. Yet, many mobile platformer games still rely on static enemy behaviors, leading to repetitive gameplay. This study introduces Pepe the Ponderland Warrior, a 2D platformer for Android that incorporates culturally relevant meme characters and dynamic NPC behavior using fuzzy logic. Developed with the Game Development Life Cycle (GDLC), the game uses the Fuzzy Sugeno inference system to adapt NPC responses based on player distance, health, and damage received. UML modeling guided the system design, while testing included black-box, white-box, and User Acceptance Testing (UAT). The fuzzy-based system enabled real-time, context-aware NPC decisions, creating more varied and challenging gameplay. The game passed functional and logical testing, with UAT from 30 users producing a high feasibility score of 81.2%, reflecting satisfaction in design, gameplay, and difficulty balance. By integrating fuzzy logic with meme-inspired content, this study offers a novel and efficient AI approach for mobile games, highlighting potential for expansion across platforms and with more adaptive inputs.
Transformasi Karang Taruna Tangguh: Implementasi Bioflok 4.0, Olahan Lele Kreatif, dan Pupuk Organik Cair sebagai Upaya Peningkatan Ekonomi Desa Iwan Lesmana; Heri Herwanto; Jerry Dounald Rahajaan
Journal of Innovation and Sustainable Empowerment Vol. 5 No. 1 (2026)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) Universitas Kuningan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/jise.v5i1.165

Abstract

Program pengabdian kepada masyarakat ini dilaksanakan di Desa Geresik, Kecamatan Ciawigebang, Kabupaten Kuningan dengan tujuan memberdayakan pemuda Karang Taruna melalui penerapan teknologi bioflok berbasis Internet of Things (IoT), diversifikasi produk olahan lele berupa abon, serta pemanfaatan limbah bioflok menjadi pupuk organik cair. Metode yang digunakan adalah partisipatif melalui sosialisasi, pelatihan, pendampingan, serta penerapan langsung teknologi. Pemuda dilibatkan dalam setiap tahapan, mulai dari pengelolaan kolam dengan sensor IoT untuk memantau kualitas air secara real-time, praktik pembuatan produk abon lele dengan kemasan sederhana, hingga fermentasi limbah kolam menjadi pupuk organik cair yang dapat digunakan untuk pertanian lokal. Hasil kegiatan menunjukkan peningkatan keterampilan teknis dan motivasi pemuda, produktivitas kolam lebih stabil, produk olahan mulai dipasarkan secara digital, dan limbah yang sebelumnya mencemari lingkungan kini memiliki nilai tambah. Program ini disimpulkan mampu meningkatkan kapasitas, kreativitas, dan kemandirian Karang Taruna sekaligus mendukung ekonomi dan lingkungan desa secara berkelanjutan. Ke depan, kegiatan ini direkomendasikan untuk diperluas melalui penguatan kelembagaan Karang Taruna, peningkatan mutu dan legalitas produk, serta perluasan pasar agar dampak program lebih berkelanjutan.
Pemberdayaan dan Penerapan Teknologi Pengenalan Emosi Anak Autisme Berbasis Deep Learning di SLBN Taruna Mandiri Kuningan Tito Sugiharto; Rio Priantama; Iwan Lesmana; Bagas Cahyawiguna; Lilis Apriah; Muhamad Faizal Yusuf
Abdimas Galuh Vol 8, No 1 (2026): Maret 2026
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v8i1.23418

Abstract

Anak dengan spektrum autisme seringkali memiliki hambatan dalam mengekspresikan emosi, sehingga guru di SLBN Taruna Mandiri Kuningan kesulitan memberikan respons pembelajaran yang tepat secara real time. Kondisi ini jika dibiarkan dapat menghambat efektivitas transfer materi dan perkembangan psikologis anak. Pengabdian masyarakat ini bertujuan untuk memberdayakan guru melalui peningkatan literasi digital dalam penerapan teknologi pengenalan emosi berbasis deep learning. Bahan yang digunakan mencakup perangkat lunak deteksi emosi dan modul panduan literasi digital yang dirancang secara inklusif. Metode pelaksanaan kegiatan meliputi tahap sosialisasi, pelatihan penggunaan aplikasi berbasis model MobileNetV2, implementasi langsung dalam proses belajar mengajar, serta pendampingan dan evaluasi. Hasil kegiatan menunjukkan adanya peningkatan pemahaman dan keterampilan guru dalam mengoperasikan teknologi kecerdasan buatan untuk mengenali emosi siswa (senang, sedih, marah, takut, netral, dan terkejut) secara otomatis melalui kamera dengan tingkat akurasi yang tinggi. Pembahasan menekankan bahwa integrasi teknologi ini mampu mengurangi hambatan komunikasi antara guru dan siswa serta menciptakan lingkungan belajar yang lebih adaptif dan berpusat pada kebutuhan khusus anak. Kesimpulannya, penerapan teknologi deep learning efektif membantu guru dalam memantau kondisi emosional anak autisme secara objektif. Program ini berhasil menjembatani kesenjangan antara teknologi AI dengan kebutuhan pendidikan luar biasa. Disarankan agar pihak sekolah melakukan pembaruan data secara berkala dan memperluas penggunaan aplikasi pada jenjang kelas yang berbeda untuk menjaga akurasi deteksi emosi pada berbagai karakteristik siswa.
Classification of Bougainvillea Plant Types Using Convolutional Neural Network Algorithm Fauzi Rachman; Iwan Lesmana; Nunu Nugraha
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 2 (2026): Issues January 2026
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i2.15354

Abstract

Bougainvillea is one of the most popular ornamental plants, featuring a variety of types with morphological characteristics that often appear very similar. This resemblance frequently complicates the conventional identification process, particularly for sellers and buyers at Rabiku Florist. This study aims to develop an Android application capable of automatically classifying different bougainvillea types using a Convolutional Neural Network (CNN) algorithm. The system is developed using the Rapid Application Development (RAD) methodology, leveraging the MobileNetV2 architecture and integrating it with the TensorFlow Lite framework to ensure compatibility with mobile devices. The application is designed to identify five types of bougainvillea using digital images captured via the device’s camera or selected from the user’s gallery. Based on implementation results, the system demonstrates strong classification performance and delivers accurate information to users. This application is intended to serve as a practical and user-friendly tool for both the general public and businesses in accurately identifying bougainvillea species.Keywords: Image Classification, Bougainvillea, Convolutional Neural Network, MobileNetV2, Android.
Co-Authors Bagas Cahyawiguna Dadan Nugraha Encep Sayid Amrulloh Fauzi Rachman Gian Megantara Heri Herwanto Jerry Dounald Rahajaan Lilis Apriah Lutfi Rohmawati Muhamad Faizal Yusuf Nunu Nugraha RIO ANDRIYAT KRISDIAWAN Rio Priantama Tito Sugiharto