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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Informatika Kaputama (JIK) Jurnal Informasi dan Teknologi Vocatech : Vocational Education and Technology Journal JTIK (Jurnal Teknik Informatika Kaputama) JOURNAL OF INFORMATICS AND COMPUTER SCIENCE G-Tech : Jurnal Teknologi Terapan Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Pengabdian kepada Masyarakat Nusantara JINAV: Journal of Information and Visualization International Journal of Engineering, Science and Information Technology MALLOMO: Journal of Community Service Journal of Renewable Energy, Electrical, and Computer Engineering Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Pengabdian Masyarakat Bangsa MEUSEURAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal Informatika: Jurnal Pengembangan IT Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Yesy Afrillia
Universitas Malikussaleh
Religion Aerospace Engineering 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 Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Location Entity Recognition in Instagram Captions Using Support Vector Machine Algorithm Arifa, Cut Hilma; Adek, Rizal Tjut; Afrillia, Yesy
VOCATECH: Vocational Education and Technology Journal Vol 7, No 1 (2025): August
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v7i1.238

Abstract

AbstractThe rapid advancement of digital technology has significantly influenced productivity and facilitated access to information in daily life, particularly through the widespread use of social media. Instagram is one of the most popular platforms, where text in captions often contains location-related information that can be utilized for spatial analysis. This study aims to identify and classify location entities in Instagram captions using Support Vector Machine algorithm combine with rule-based Named Entity Recognition approach. The method involved linguistic feature extraction based on explicit spatial context, data labeling, model training, and performance evaluation using standard classification metrics: accuracy, precision, recall, and f1-score. Dataset consists of 400 captions primarily written in Indonesian, though some contain mixed-language elements such as foreign term or regional dialect. The dataset is divided into 70% training data ad 30% testing data. Experimental results show that model achieved an accuracy of 90,83%, precision of 97,01%, recall of 87,84%, and f1-score of 92,90%. Evaluation of three NER rules (exact match keyword, prepositional patterns, and descriptive structures) indicates that the combination of all rules yields the highest f1-score (89%), while the best-performing individual rule is the prepositioning pattern (74%). These results demonstrated strong performance in processing varied and unstructured Instagram captions. The combinations of SVM and NER rule-based prove effective in identifying and classifying spatial information into two classes Contains Location and No Location. This approach shows potential for implementation in text-based spatial analysis systems, such as location-based recommendation systems, geographic mapping, and location-based decision support systems. AbstrakPerkembangan teknologi digital yang pesat secara signifikan berpengaruh meningkatkan produktivitas dan kemudahan akses informasi dalam kehidupan sehari-hari, salah satunya penggunaan media sosial yang semakin meluas. Instagram merupakan salah satu platform yang banyak digunakan, dimana teks dalam caption memiliki informasi terkait lokasi yang dapat dimanfaatkan untuk analisis spasial. Penelitian ini bertujuan untuk mengidentifikasi dan mengklasifikasikan entitas lokasi dalam caption Instagram menggunakan algoritma Support Vector Machine (SVM) dengan pendekatan Named Entity Recognition (NER) rule-based. Metode yang digunakan meliputi ekstraksi fitur berbasis linguistik dengan konteks spasial eksplisit, lebelisasi data, pelatihan model, serta evaluasi kinerja model menggunakan matriks klasifikasi: akurasi, presisi, recall dan f1-score. Dataset terdiri dari 400 caption umumnya berbahasa Indonesia, namun terdapat unsur bahasa campuran seperti istilah asing atau bahasa daerah. Fokus utama penelitian diarahkan pada pengolahan dan pemahaman teks berbahasa Indonesia. Dataset dibagi menjadi 70% data training dan 30% data testing. Hasil pengujian menunjukkan bahwa model mendapatkan akurasi sebesar 90,83%, presisi 97,01%, recall 87,84% dan f1-score 92,90%. Evaluasi terhadap tiga rule NER (exact match keyword, pola preposisi, dan struktur deskriptif) menunjukkan bahwa pengenalan entitas berdasarkan gabungan seluruh rule memberikan f1-score tertinggi (89%), sementara rule individual terbaik adalah pola preposisi (74%). Nilai ini menunjukkan kinerja yang cukup baik dalam pengolahan caption Instagram yang variatif dan tidak terstruktur. Kombinasi metode SVM dan NER rule-based terbukti efektif dalam mengidentifikasi dan mengklasifikasi informasi spasial dalam dua kelas Contain Location dan No Location. Pendekatan ini berpotensi diterapkan pada sistem analisis spasial berbasis teks, seperti sistem rekomendasi lokasi, pemetaan geografis, dan pendukung keputusan berbasis lokasi.
Measuring the Level of Security Awareness of Smartphone Users Among Universitas Malikussaleh Students Using the Fuzzy Analytical Hierarchy Process Method Andreansyah, Sabda; Ula, Munirul; Afrillia, Yesy
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.861

Abstract

Technology is developing rapidly; its benefits are manifold. The development of technology, especially smartphones, Has become a part of everyday life that cannot be distinguished anymore. The increasing number of smartphone users has also impacted the rising information security and privacy cases caused by a lack of awareness of spam, malware, and phishing. Many users upload personal information such as photos, phone numbers, and addresses without antivirus protection. This study aims to identify security and privacy challenges in smartphone use by measuring problems in the dimensions of attitude (knowledge), knowledge (attitude), and behavior (behavior). There are five focus areas: Backdoor, hardware, and AndroidOS, which is still low compared to applications and permissions. The method used the Analytical Hierarchy Process (AHP) with the Fuzzy concept to measure the level of information security awareness of Malikussaleh University students who use Android phones. The results showed that the overall level of understanding was good (80%). Although the attitude and behavior dimensions showed good awareness, the knowledge dimension was moderate. This may be why information security breaches still often occur among Android phone users. Faculty of Economics, Less Aware: 23 people Unaware: 1 person. Faculty of Social and Political Sciences, Less Aware: 24 people. Faculty of Teacher Training and Education, Less Aware: 21 people. Faculty of Law, Less Aware: 24 people. Faculty of Medicine, Less Aware: 27 people and Aware: 3 people. Faculty of Agriculture, Less Aware: 30 people. Faculty of Informatics Engineering, Less Aware: 70 people and Aware: 5 people. Total Awareness, Less Aware: 199 people, nine people, and Unaware: 1 person.
Clustering of Aquaculture Productivity Villages in East Aceh Using the K-Means Algorithm Arif, M. Arif Saputra; Dinata, Rozzi Kesuma; Afrillia, Yesy
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10102

Abstract

This study aims to classify villages based on the level of pond utilization and to develop a web-based application for categorizing aquaculture areas in East Aceh Regency. In contrast to traditional definitions based on harvest volume, this research defines productivity functionally—whether the pond area is actively managed or abandoned. The dataset consists of 146 villages and includes five primary variables: number of fish farmers, total pond area, number of pond plots, productive pond area, and abandoned pond area. Clustering was conducted using the K-Means algorithm, resulting in two main groups: productive and non-productive villages. Validation through the Silhouette Score revealed that using k = 2 yielded the highest score of 0.7576, indicating the most optimal clustering structure. The analysis showed that 92% of villages were categorized as productive, while 8% fell into the non-productive cluster. These two clusters differ significantly in terms of land utilization ratios and the number of active aquaculture workers. The findings not only offer a more refined spatial insight but also serve as a basis for the Department of Marine Affairs and Fisheries in formulating aquaculture zoning, revitalization programs, and more targeted resource allocation.
IoT-Based Adaptive Room Temperature Monitoring and Energy Optimization System Using NodeMCU ESP8266 Aswandi, Sakti; Rizal, Rizal; Afrillia, Yesy
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10052

Abstract

This study presents the development of an IoT-based room temperature monitoring and AC control system at the Faculty of Engineering, Universitas Malikussaleh, using NodeMCU ESP8266, DHT11 sensor, PIR sensor, and IR LED for real-time automation via a Firebase web interface. The system automatically adjusts AC operation based on room temperature and occupancy, with daily logic resets to accommodate dynamic conditions. Testing conducted over one week demonstrated effective temperature stabilization within 25–26°C with ±2°C fluctuations and significant energy savings by deactivating the AC when the temperature drops below 25°C or the room is unoccupied. The PIR sensor supports a detection range of up to 7 meters, allowing scalability for different room sizes. User evaluation involving five respondents reported satisfaction scores of 4.2 for comfort and energy efficiency, though aspects such as the web interface (3.6) and system information display (2.6) require improvement. Overall, the system effectively enhances energy efficiency, ensures room comfort, and provides flexible control for users, supporting the smart classroom concept. Future development is directed toward the use of more accurate sensors like DHT22 or DS18B20, improved network stability, and integration with virtual assistants for voice-controlled operation.
Optimalisasi Pelayanan Kesehatan Sebagai Inovasi Pelayanan Publik Melalui Pendampingan Pemanfaatan Website Di Puskesmas Dewantara Afrillia, Yesy; Faridhatul Ulva, Ananda; Fidyati, Fidyati; Wardana, Ade Bagus; Zuhra, Elviza
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 4 No. 4 (2023): Jurnal Pengabdian kepada Masyarakat Nusantara (JPkMN)
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Puskesmas Dewantara terletak pada wilayah Kampus Utama Universitas Malikussaleh. Yang kita ketahui saat ini mahasiswa di kampus Universitas Malikussaleh sebagai cerminan Indonesia mini yang diisi oleh mahaiswa dari sabang hingga marauke. Hal ini menjadi landasan bahwa perlu adanya optimalisasi pelayanan kesehatan sebagai inovasi pelayanan publik dengan pemanfaatan website sebagai media penyampaian suatu informasi yang terpercaya kepada masyarakat secara umum. Tujuan dari kegiatan ini ialah mendorong pemanfaatan inovasi teknologi informasi dalam program pembangunan desa untuk mendukung terwujudnya smart village pada lingkup pelayanan publik dari optimalisasi pelayanan kesehatan. Metode yang digunakan dalam penyelesaian masalah ini ialah dengan observasi, koordinasi serta teknik pengumpulan data. Analisis data menggunakan teknik analisis data interaktif. Hasil inovasi yang diberikan oleh tim pengabdian kepada masyarakat Universitas Malikussaleh yaitu berupa Website kepada mitra yaitu UPTD Puskesmas Dewantara sangat diterima karena ini menjadi suatu kebutuhan yang tepat bagi inovasi yang belum mereka miliki baik bagi peningkatan mutu akreditasi instansi.
Klasifikasi Kesehatan Mental Remaja Tingkat SMA di Kota Lhokseumawe Menggunakan Algoritma Random Forest Afrillia, Yesy; Fhonna, Rizky Putra; Rahma, Mutiara
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 6 No. 3 (2025): Edisi Juli - September
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v6i3.6377

Abstract

Kesehatan mental menjadi isu penting dalam perkembangan seorang remaja yang berdampak pada prestasi akademik, hubungan sosial, kualitas hidup, dan kesejahteraan secara keseluruhan. Dengan data dari 229 remaja di Kota Lhokseumawe, penelitian ini mengembangkan model klasifikasi kesehatan mental remaja berbasis Random Forest. Data dikategorikan ke dalam empat kelas gangguan mental (Tidak Ada Indikasi, Level 1-3) berdasarkan indikator HSCL-25 dan motivasi belajar. Metode penelitian mencakup studi literatur, pengumpulan data, preprocessing data, training model, serta evaluasi kinerja menggunakan metrik akurasi evaluasi. Hasil menunjukkan bahwa model mencapai akurasi sebesar 86,96%, dengan F1-score masing-masing sebesar 0,94 Tidak Ada Indikasi), 0,81 (level 1), 0,75 (level 2), dan 0,00 (level 3). Analisis feature importance mengidentifikasi bahwa kesepian, perasaan tidak berharga, dan kehilangan harapan merupakan fitur utama paling berpengaruh dalam klasifikasi. Meskipun model mampu mengklasifikasikan sebagian besar data dengan baik, masih terdapat kesalahan klasifikasi pada beberapa tingkat gangguan mental. Model, yang dibangun menggunakan API Flask dan Laravel dalam sistem berbasis web, memungkinkan remaja mengisi kuesioner dan memperoleh hasil klasifikasi secara otomatis. Dengan demikian, model Random Forest dapat digunakan sebagai alat bantu klasifikasi yang efektif dalam mendeteksi potensi gangguan mental remaja. Hasil penelitian ini dapat menjadi dasar bagi institusi pendidikan dalam merancang strategi intervensi yang lebih tepat sasaran
PKM Strategi Pemanfaatan Teknologi Informasi untuk Menghadapi Cyberbullying di Kalangan Siswa Retno, Sujacka; Maida, Eka; Fhonna, Rizky Putra; Afrillia, Yesy; Fachrurrazi, Sayed; Yusuf, Edi
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 9 (2025): November
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i9.3469

Abstract

Perkembangan teknologi informasi membawa dampak positif terhadap kemajuan pendidikan, namun di sisi lain juga menimbulkan fenomena negatif seperti cyberbullying yang semakin marak di kalangan siswa. Cyberbullying sebagai bentuk kekerasan psikologis berbasis digital dapat mengganggu kesehatan mental, motivasi belajar, hingga prestasi akademik peserta didik. Pengabdian ini bertujuan untuk menganalisis strategi pemanfaatan teknologi informasi dalam mengidentifikasi, mencegah, dan menanggulangi cyberbullying di lingkungan sekolah melalui integrasi pendekatan teknologi dan edukatif. Metode pengabdian yang digunakan adalah studi literatur dengan mengkaji hasil pengabdian terdahulu, jurnal terakreditasi, serta laporan lembaga pendidikan nasional maupun internasional. Hasil kajian menunjukkan bahwa pemanfaatan artificial intelligence (AI) untuk deteksi ujaran kebencian, penggunaan learning management system (LMS) yang dilengkapi fitur pelaporan anonim, serta penerapan sistem pengawasan berbasis machine learning dapat membantu mengurangi insiden cyberbullying. Namun, efektivitas teknologi tersebut sangat bergantung pada kesadaran etika digital dan kemampuan literasi siber siswa. Oleh karena itu, kolaborasi antara sekolah, guru, dan orang tua dalam memberikan edukasi literasi digital menjadi aspek krusial. Sinergi antara inovasi teknologi dan program pendidikan karakter mampu membangun lingkungan digital yang aman, inklusif, dan mendukung kesejahteraan psikologis siswa.
Co-Authors Abadi, Sabani Abdul Hadi Adek, Rizal Tjut Ananda Faridhatul Ulva Andreansyah, Sabda Annas, Muhammad Aqmal, Jamalul Arif, Abdul Halim Arif, M. Arif Saputra Arifa, Cut Hilma Asmi, Nurul Annisa Asrianda Asrianda Asrifan, Andi Aswandi, Sakti Ayu Indah Lestari Berutu, Indah Fachlira Bustami Bustami Dahlan Abdullah Dasril Dasril David Sarana Deassy Siska Dewi, Tursina Dinanti, Intan Putri EDI YUSUF, EDI eva darnila, eva darnila Fadlisyah Fadlisyah Fadlisyah Fajar, Kasihan Muhammad Fakhruddin Ahmad Nasution Fatika, Dian Fidyati, Fidyati Fikria, Putri Fuadi, Wahyu Hafidh Rafif, Teuku Muhammad Harahap, Ilham Taruna Herman Fithra Hidayat, Amam Taufiq Ilsa Hidayat Jamalul Aqmal Julianansa, Ririn Kautsar, Al Khairuni Khairuni Lidya Rosnita Maida, Eka Muhammad Fikry Muhammad Muhammad Muhammad Yusuf Mukhlis Mukhlis Mukti Qamal Munirul Ula Muzaffar Rigayatsyah Muzaffar Rigayatsyah NELI SUSANTI, NELI Nurdin Nurdin Nurqamarina Rahma, Mutiara Rahmawati, Rahmawati Rini Meiyanti Risawandi, Risawandi Riza, Saiful Rizal Rizal Rizal S.Si., M.IT, Rizal Rizky Putra Fhonna Rozzi Kesuma Dinata Safriand, Safriand Sayed Fachrurrazi Selian, Riko Ardiansyah Siregar, Winda Ramadhani Sofyan Sofyan Suci Ramadani Sujacka Retno Teuku M. Arief Afwan Uliana, Lisa Ulva Ilyatin Veri Ilhadi Wahyu Fuadi Wardana, Ade Bagus Widari, Liz Ayu Yanti, Winda Zara Yunizar Zuhra, Elviza Zulfan