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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) ComEngApp : Computer Engineering and Applications Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Media Infotama Bulletin of Electrical Engineering and Informatics Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Informatika dan Teknik Elektro Terapan ICON-CSE Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Dinamisia: Jurnal Pengabdian Kepada Masyarakat International Journal of New Media Technology INTECOMS: Journal of Information Technology and Computer Science MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Linguistik Komputasional Journal of Information Systems and Informatics Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Computer Science and Information Technologies Journal of Intelligent Computing and Health Informatics (JICHI) Sriwijaya Journal of Informatics and Applications Jurnal Generic Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Abdiansah, Abdiansah
Universitas Sriwijaya
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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Palembang songket fabric motif image detection with data augmentation based on ResNet using dropout Ermatita, Ermatita; Noprisson, Handrie; Abdiansah, Abdiansah
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.6883

Abstract

A good way to spread knowledge about Palembang songket woven cloth patterns is to use information technology, especially artificial intelligence technology. This study's main goal is to develop a ResNet model with dropout regularization methods and find out how dropout regularization affects the ResNet model for detecting Palembang songket fabric motif with more data. Data was collected in places like tujuh saudara songket, Zainal songket, songket PaSH, AMS songket, and batik, Ernawati songket, Nabilah collections, Ilham songket, and Marissa songket. We used eight class of data for this research. A dataset of 7,680 data for training, 960 data for validation, and 960 data for testing is a dataset that has been prepared to be implemented in experiments. In the final results, the experimental results for DResNet demonstrated that accuracy at the training stage was 92.16%, accuracy at the validation stage was 78.60%, and accuracy at the submission stage was 80.3%. The experimental results also show that dropouts are able to increase the accuracy of the ResNet model by adding +1.10% accuracy in the training process, adding +1.80% accuracy in the validation process, and adding +0.40% accuracy in the testing process.
Ekstraksi Kata Kunci pada Bahasa Indonesia Menggunakan Metode Yake Yusliani, Novi; Plakasa, Gerald; Abdiansah, Abdiansah; Marieska, Mastura Diana; Saputra, Danny Matthew
Jurnal Linguistik Komputasional Vol 6 No 1 (2023): Vol. 6, NO. 1
Publisher : Indonesia Association of Computational Linguistics (INACL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jlk.v6i1.117

Abstract

Peneliti, Mahasiswa, dan Juga Dosen biasanya melakukan penelitian untuk menghasilkan publikasi hasil penelitiannya. Saat ini pertumbuhan publikasi ilmiah terus meningkat. ketika publikasi akan di berikan ke reviewer maka publikasi yang kirimkan harus sesuai dengan bidang yang diampu oleh reviewer tersebut. Salah satu cara untuk mengetahui inti dari sebuah publikasi ilmiah yaitu dengan melakukan ekstraksi kata kuncinya. Metode yang digunakan untuk ekstraksi kata kunci salah satunya yaitu YAKE (Yet Another Keyword Extraction). Penelitian ini menggunakan dataset 100 publikasi ilmiah dari website jtiik, jatisi, dan jepin dengan topik Ilmu Komputer. Berdasarkan penelitian yang telah dilakukan, konfigurasi pada parameter Levenshtein Distance memiliki pengaruh terhadap hasil kata kuncinya. Evaluasi dari penelitian ini menghasilkan nilai f-measure sebesar 54,1% dan nilai akurasi sebesar 97,05% dengan parameter Levenshtein Distance < 2.
KLASIFIKASI SENTIMEN EMOSI PADA DATASET GOEMOTION MENGGUNAKAN LSTM Satrio, Bagus; Dahlan, Bulan Fitri; Fathan, Fathir; Muwafa, Fadhil Zahran; Zanzabili, Muhammad Reyhan; Abdiansah, Abdiansah
Jurnal Linguistik Komputasional Vol 7 No 1 (2024): Vol. 7, NO. 1
Publisher : Indonesia Association of Computational Linguistics (INACL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jlk.v7i1.145

Abstract

Penelitian ini membahas tentang pengembangan sistem klasifikasi sentimen emosi pada teks menggunakan metode deep-learning LSTM (Long Short Term Memory) dengan dataset yang digunakan yaitu dataset GoEmotion. Sistem ini bertujuan untuk mengidentifikasi emosi tersirat yang terkandung dalam suatu teks secara tepat dan efisien ke dalam 28 jenis bentuk emosi. Metode yang digunakan dalam penelitian ini adalah LSTM atau Long Short Term Memory untuk mendeteksi dan mengklasifikasikan emosi berdasarkan teks. Program dalam penelitian ini dibuat menggunakan bahasa pemrograman python dengan menggunakan beberapa library yang telah tersedia. Hasil dari eksperimen ini menunjukkan bahwa model LSTM mampu mengenali dan mengklasifikasikan emosi yang terkandung di dalam sebuah teks secara cukup baik dengan akurasi tertinggi mencapai angka 0.36 (36% akurasi). Sistem klasifikasi ini digunakan untuk dapat mengatasi masalah terkait dengan pengenalan emosi yang terkandung dalam suatu teks atau kalimat.
Aplikasi Analisis Wajah, Klasifikasi Gender dan Prediksi Usia Menggunakan Deep Learning pada Dataset Citra Wajah Manusia Marcelio, Ch Angga; Azzikra, Muhammad Adlan; Mufazzal, Dimas Putra; Illahi, Aripili Rahman; Husain, Sulaiman Al; Abdiansah, Abdiansah
Jurnal Media Infotama Vol 20 No 1 (2024): April 2024
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v20i1.5998

Abstract

Age and Gender Detection is a technology that utilizes artificial intelligence (AI) algorithms to identify and analyze the age and gender of a person through image capture as output. This technology provides automatic estimation of age and gender starting from detecting one or more objects (humans) and performing age and gender detection. The program uses pre-trained models and prototypes for face detection, age, and gender, resulting from training processes using deep learning techniques. By using these models and prototypes, the program can efficiently analyze each face found in images or videos and provide age and gender estimates with reliable accuracy. The main purpose of the Age and Gender Detection Application is to provide accurate and useful information about the age and gender of individuals based on the input images, becoming an efficient solution in image processing and artificial intelligence fields for various application contexts requiring facial data analysis.
NL2SQL For Chatbot with Semantic Parsing Using Rule-Based Methods Kurniawan, Adi; Abdiansah, Abdiansah; Utami, Alvi Syahrini
Sriwijaya Journal of Informatics and Applications Vol 5, No 1 (2024)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v5i1.66

Abstract

Structured Query Language (SQL) is a command language that allows users to access database information. Ordinary people generally donot know how to make queries with SQL to a database. The chatbot is acomputer program developed to interact with its users via text or voice. In this study, chatbots were developed to help and facilitate users intheNatural Language to Structured Query Language (NL2SQL) process tosearch for information in an Academic Information Systemdatabasewith semantic parsing using a rule-based method that accepts input inthe form of interrogative sentences or order. In the Natural Language toStructured Query Language (NL2SQL) process several problems arise, namely input problems with unique parameters for the knowledge base, and slow searching or translation processes, which make Natural Language to Structured Query Language (NL2SQL) inef icient, problems This problem will be solved using a semantic parsingapproach using a rule-based method that is proven to be ef icient insolving issues such as the Natural Language to Structured QueryLanguage (NL2SQL) process. The results showed that the semanticparsing approach using the rule-based method succeeded in obtainingan accuracy rate of 96.72% using 122 test data in the formof questionsentences or command data about the Academic Information Systemof the Department of Informatics Engineering, Sriwijaya University inIndonesian, and an average execution time of 50.68 milliseconds. seconds or 0.05 seconds.
Collaborative Filtering Recommendation System Using A Combination of Clustering and Association Rule Mining Annisa, Siti; Rini, Dian Palupi; Abdiansah, Abdiansah
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.802

Abstract

A recommendation system helps collect and analyze user data to generate personalized recommendations for users. A recommendation system for movies has been implemented, considering the vast number of available films and the difficulty users face in finding movies that match their interests. One popular recommendation method is Collaborative Filtering (CF). Although widely applied, CF still has issues. Basic CF uses overlapping user data in evaluating items to calculate user similarity. This study aims to build a collaborative filtering recommendation system using clustering techniques to group users with similar interests into the same clusters. The next step in CF application is to gather recommendation candidate items by finding users with a high level of similarity to the target user. Subsequently, user pattern analysis is carried out by applying association rule mining to predict hidden correlations based on frequently watched items and the ratings given to those movies. This study uses rating data and movie data from the Movielens website. The evaluation of the recommendation results is measured using precision, recall, and f-measure. The evaluation results show that the proposed recommendation system achieves a hit rate of 95.08%, a precision of 81.49%, a recall of 98.06%, and an f-measure of 87.66%.
PELATIHAN PENINGKATAN PENGUASAAN TEKNOLOGI INFORMASI DIGITAL GUNA MASYAKARAT MARIANA ILIR Ali Ibrahim; Ermatita, Ermatita; Abdiansah, Abdiansah; Ahmad Fali Oklilas; Al Farissi; Rizka Dhini Kurnia; Afrina, Mira; Utama, Yadi
Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Vol. 2 No. 1 (2024): Februari
Publisher : CV. Alina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jpki2.v2i1.237

Abstract

Mariana Ilir merupakan salah satu kelurahan yang ada di kecamatan Banyuasin I yang mempunyai potensi yang cukup besar untuk dikembangkan, namun selama ini penggunaan teknologi informasi dalam penyebaran informasi masih belum dapat dimanfaatkan secara optimal dikalangan pemerintahan khususnya di pedesaan, hal ini disebabkan karena terbatasnya sarana dan prasarana serta sumber daya manusia yang memiliki kemampuan dan keahlian dibidang ilmu komputer dan teknologi informasi. Pada kegiatan ini akan dilaksanakan sesuai dengan kesepakatan antara tim pelaksana dengan kelurahan mariana ilir. Khalayak yang akan ikut dalam kegiatan ini berjumlah 20 orang. Kegiatan PkM akan dilaksanakan secara luring. Hasil yang di harapkan dari kegiatan Pk adalah bertambahnya keterampilan apparat kelurahan dan masyarakat tentang IT. Selaian itu PkM ini memiliki luaran seperti Lapoaran PkM dan Publikasi karya ilmiah pada jurnal nasional. Kegiatan PkM Peningkatan Keterampilan Teknologi Informasi Digital Untuk Masyakarat dan Aparat Kelurahan Mariana Ilir Kecamatan Banyuasin Ilir, Kabuaten Banyuasin Sumatra Selatan terlaksana sesuai dengan rencana yang sudah disepakati oleh tim pelaksana dengan tim pelaksana dari kelurahan. Peserta sangat antusias dengan mengikuti kegiatan PkM, Harapan peserta untuk tetap diadakan kegiatan Kembali tahun selanjutnya.
AI-Driven Traffic Simulation using Unity: Implementing Finite State Machines for Adaptive NPC Behaviour Amalia, Syavira; Abidullah, M. Dzawil Fadhol; Marcellino, Fernanditho; Rabani, Diaz Dafa; Azzahra, Firna Fatima; Abdiansah, Abdiansah
Journal of Intelligent Computing & Health Informatics Vol 5, No 2 (2024): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v5i2.14595

Abstract

This research develops an AI-powered traffic simulation using the Unity Engine, leveraging finite state machines (FSM) to enable adaptive and responsive non-player characters (NPCs). The integration of FSM with advanced pathfinding algorithms, such as A*, allows NPCs to dynamically adjust their behavior based on traffic conditions, obstacles, and environmental changes. The experimental results indicate a 25% improvement in route optimization and a 30% reduction in path conflicts compared to conventional static models, demonstrating the robustness of the proposed approach. Optimized navmesh deployment further enhances navigation fluidity, ensuring efficient agent movement in high-density scenarios without compromising system performance. The findings establish the effectiveness of the FSM-driven NPC behavior in simulating realistic traffic environments, contributing both to the advancement of AI applications in game development and urban planning. By providing an interactive platform for traffic management, this simulation offers a practical tool to study congestion patterns and test intervention strategies. In addition, it improves player engagement by fostering emergent gameplay through dynamic NPC interactions. Future work could explore the integration of real-time procedural generation or multiplayer functionality to enrich simulation depth and scalability. This study provides a comprehensive framework that bridges AI-based mechanics with simulation technology, providing significant insights for researchers and practitioners in game design, artificial intelligence, and urban planning.
Generating Indonesian Poem: A Fine-Tunning Approach Using Pretrained GPT-2 Models Kusuma, Arya Mulya; Abdiansah, Abdiansah
Sriwijaya Journal of Informatics and Applications Vol 5, No 2 (2024)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v5i2.96

Abstract

In recent years, text generation has become an important subfield within Natural Language Processing (NLP), gaining significant attention and focus. Over the past decade, text generation technology has expanded significantly, reaching diverse application domains, especially in creative areas such as poem. Generating poetic content is a unique challenge that requires combining linguistic knowledge, creativity, and originality to craft each poem. This study focuses on developing a text generator for Indonesian language poem, using fine-tuning methodology with the pre-trained GPT-2 model from the Flax community. The study conducted a comparative analysis, benchmarking the performance of the researcher's model against a baseline model developed by Muhammad Agung Hambali. The evaluation outcomes showed the researcher's model outperformed the baseline model, exhibiting a 73.68% improvement in perplexity value. Furthermore, the study conducted a survey involving 62 respondents to determine the reception of the generated poem. The results indicated the poem produced by the research model was marginally superior to that of the baseline model. 
PENINGKATAN MOTIVASI BELAJAR SISWA SMA MELALUI PENDEKATAN PEMROGRAMAN KOMPUTER Abdiansah, Abdiansah; Utami, Alvi Syahrini; Yusliani, Novi; Miraswan, Kanda Januar; Wedhasmara, Ari
Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Vol. 1 No. 4 (2023): Agustus
Publisher : CV. Alina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jpki2.v1i4.56

Abstract

PISA adalah penilaian tingkat internasional yang diselenggarakan setiap tiga sekali untuk menguji kemampuan akademis siswa yang berusia 15 tahun. Tujuan PISA adalah untuk menguji dan membandingkan prestasi anak-anak sekolah di seluruh dunia. Nilai PISA Indonesia di tahun 2018 masih rendah untuk ketiga bidang yang dinilai, yaitu: Matematika, Sains, dan Membaca. Untuk mengatasi hal tersebut dibutuhkan metode pembelajaran yang mampu memotivasi belajar siswa, terutama di bidang STEM (Science, Technology, Engineering, Math). Salah satu metode kegiatan yang dapat meningkatkan motivasi siswa adalah dengan memberikan pengenalan konsep dan praktik pemrograman komputer untuk diterapkan di bidang matematika, fisika, dan kimia. Hasil evaluasi menunjukkan bahwa terjadi peningkatan kemampuan belajar siswa sebesar 15.00% (N-Gain) meskipun secara keseluruhan hasilnya masih belum signifikan. Meskipun demikian hasil evaluasi kegiatan pelatihan cukup memuaskan dengan nilai sebesar 84.91% (Skala Likert). Hasil tersebut membuktikan bahwa pendekatan pemrograman komputer untuk meningkatkan motivasi belajar siswa di bidang STEM cukup menjanjikan. Kata Kunci: PISA, STEM, Pemrograman Komputer
Co-Authors Abidullah, M. Dzawil Fadhol Adi Kurniawan Ahmad Fali Oklilas Ahmad Gustano Aidil Putrasyah Al Farissi Alfath, Ahmad Riyo Ali Ibrahim Alvi Syahrini Utami Amalia, Syavira Anny K. Sari Ari Firdaus Ari Wedhasmara Arrasyid, Muhammad Raihan Aruda, Syechky Al Qodrin Arya Mulya Kusuma Astero Nandito Azzahra, Firna Fatima Azzikra, Muhammad Adlan Cahyani, Nyimas Sabilina Dahlan, Bulan Fitri Deris Stiawan Dian Palupi Rini Dian Palupi Rini Dian Palupi Rini Dwiyono, Aswin Edi Winarko Elza Fitriana Saraswita Elza Fitriana Saraswita Ermatita - Erwin, Erwin Fathan, Fathir Fathoni - Febrian, Evan Frendredi Muliawan Hallatu, Nathania Calista Harisatul Aulia Hastie Audytra Hidayahni, Putri Husain, Sulaiman Al Illahi, Aripili Rahman Julian Supardi Kanda Januar Miraswan Kusuma, Arya Mulya Marcelio, Ch Angga Marcellino, Fernanditho Mastura Diana Marieska Maulana, Jimmy Megah Mulya Melati, Risma Mira Afrina Mufazzal, Dimas Putra Muhammad Afif Muhammad Alfaris Oktavian Muhammad Fachrurrozi Muhammad Ikhsan Muhammad Qurhanul Rizqie Muhammad Rizky Akbar Muwafa, Fadhil Zahran Nazuli, Muhammad Furqan Noprisson, Handrie Novi Yusliani Novran, Novran Permana, Dendi Renaldo Plakasa, Gerald Primanita, Anggina Putra, Erwin Dwika Putri Patricia Rabani, Diaz Dafa Ridho Putra Sufa Rizka Dhini Kurnia Saputra, Danny Mathew Saputra, Danny Matthew Satrio, Bagus Sihaloho, Mutiara Anastasya Siti Annisa, Siti Soraya, Atika Sri Hartati Yadi Utama Yudoyono, Vellanindhita Noorprameswari Zanzabili, Muhammad Reyhan