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All Journal Sistemasi: Jurnal Sistem Informasi JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURIKOM (Jurnal Riset Komputer) Jurnal ICT : Information Communication & Technology JSAI (Journal Scientific and Applied Informatics) Indonesian Journal of Business Intelligence (IJUBI) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Yayasan Cita Cendikiawan Al Khwarizmi Jurnal J-PEMAS Mejuajua Jurnal Puan Indonesia Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Jurnal Abdimas Maduma Jurnal Bakti Dirgantara INOVTEK Polbeng - Seri Informatika Lumbung Ngabdi: Jurnal Pengabdian Masyarakat Smart Humanity: Jurnal Pengabdian Masyarakat
Tomy Nanda Putra
Institut Teknologi Mitra Gama
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Applying Artificial Intelligence to Analyze Emotions in Social Media Comments using Large Language Models Astiti, Sarah; Iswandi, Iswandi; Putra, Tomy Nanda; Darmansah, Darmansah
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.5187

Abstract

Advancements in Large Language Models (LLMs) have opened new opportunities for emotion analysis in social media comments. This study aims to explore the application of LLMs in classifying users' emotions based on their comment texts across various social media platforms. The methodology involves collecting comment data from Twitter, Facebook, and YouTube, followed by text preprocessing using Natural Language Processing (NLP) techniques. LLMs such as GPT and BERT are evaluated for their ability to detect primary emotions including happiness, sadness, anger, and fear. The results show a precision of 0.89 (89%), recall of 0.80 (80%), and an F1-score of 0.84 (84%). These findings indicate that LLMs offer higher accuracy compared to conventional sentiment analysis methods, particularly in their ability to understand linguistic context and nuances.
DIGITAL ENTREPRENEURSHIP: MENGOPTIMALKAN POTENSI MAHASISWA DI ERA INDUSTRI 4.0 Dori Gusti Alex Candra; Atika Fauziyyah; Juwita Azizah; M. Agung Vafky Ideal; Eka Sofiati; Tomy Nanda Putra; Budi Permana Putra; Nurdi Afrianto; Idir Fitriyanto
Mejuajua: Jurnal Pengabdian pada Masyarakat Vol. 5 No. 1 (2025): Agustus 2025
Publisher : Yayasan Penelitian dan Inovasi Sumatera (YPIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52622/mejuajuajabdimas.v5i1.256

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pemahaman dan kesiapan mahasiswa dalam menghadapi tantangan dunia kerja serta mengembangkan potensi kewirausahaan digital di era Industri 4.0. Secara spesifik, program ini membekali mahasiswa untuk merintis usaha di bidang jasa pemasaran digital bagi UMKM, pembuatan konten kreatif untuk media sosial, atau membangun platform e-commerce yang berfokus pada produk lokal. Program ini dirancang untuk menjembatani antara pengetahuan teoretis dan keterampilan praktis yang relevan dengan tuntutan ekonomi digital saat ini. Metode yang digunakan adalah sosialisasi dalam format pelatihan intensif selama satu hari yang diselenggarakan di Institut Teknologi Mitra Gama, dengan melibatkan dua narasumber kompeten di bidangnya. Pelaksanaan kegiatan mencakup tiga tahap utama: persiapan, implementasi, dan evaluasi. Tahap persiapan melibatkan survei kebutuhan awal untuk merancang materi yang relevan. Tahap implementasi mencakup pemaparan materi mengenai kesiapan memasuki dunia industri, penguatan soft skills, dan pemahaman mendasar tentang digital entrepreneurship. Evaluasi dilakukan melalui kuesioner pre-test dan post-test serta observasi kualitatif terhadap partisipasi peserta. Program ini berhasil mengubah pola pikir mahasiswa menjadi produsen digital, yang dibuktikan dengan 68% peserta siap memulai usaha daring dan 72% melaporkan peningkatan kepercayaan diri untuk mempresentasikan ide. Meskipun hasil ini positif, durasi program yang singkat menjadi sebuah keterbatasan. Oleh karena itu, direkomendasikan adanya bimbingan berkelanjutan atau program inkubasi untuk memastikan dampak jangka panjang yang berkelanjutan.
Sosialisasi Magang Berdampak 2024: Meningkatkan Partisipasi Mahasiswa dalam Program Penguatan Kompetensi Atika Fauziyyah; Tomy Nanda Putra; M. Agung Vafky Ideal; Dori Gusti Alex Candra; Idir Fitriyanto; Adi Prastya; Zaharani Yusno
Lumbung Ngabdi: Jurnal Pengabdian Masyarakat Vol. 2 No. 3 (2024): Desember
Publisher : Pusat Kajian dan Pengembangan Publikasi Ilmiah Institut Agama Islam Hamzanwadi Nahdlatul Wathan Lombok Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51806/ngabdi.v2i3.41

Abstract

Program Magang Berdampak 2024 merupakan bagian dari kebijakan Merdeka Belajar Kampus Merdeka (MBKM) yang bertujuan untuk meningkatkan kompetensi dan kesiapan kerja mahasiswa. Kegiatan pengabdian masyarakat ini dilakukan dalam bentuk sosialisasi yang dilaksanakan oleh Institut Teknologi Mitra Gama, dengan melibatkan Wakil Rektor I, Ketua Program Studi, dan dosen pembimbing. Kegiatan berlangsung selama satu hari dan menyasar mahasiswa sebagai peserta utama. Metode yang digunakan adalah pendekatan edukatif dan praktis, di mana mahasiswa tidak hanya menerima informasi, tetapi juga langsung dibimbing untuk mendaftar di platform Simbelmawa. Hasil kegiatan menunjukkan bahwa mahasiswa tidak hanya lebih memahami manfaat program magang, tetapi juga menunjukkan antusiasme dan partisipasi aktif dalam proses pendaftaran. Sosialisasi ini terbukti efektif dalam meningkatkan kesadaran dan keterlibatan mahasiswa dalam program-program penguatan kompetensi berbasis nasional
Intelligent System for Monkeypox Disease Diagnosis Using Hybrid Certainty Factor and Fuzzy Logic Methods M. Agung Vafky Ideal; Tomy Nanda Putra
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/h13m0k54

Abstract

Monkeypox cases has the potential to spread rapidly, making early detection crucial to prevent wider transmission. Unfortunately, at the UPT Puskesmas where this study was conducted, there is no system available to assist medical personnel in performing fast and standardized diagnoses. To address this issue, this research developed a web-based intelligent system by combining the Certainty Factor (CF) and Fuzzy Logic methods. The system’s knowledge base was constructed from symptom data collected through expert interviews and literature studies. It was then tested using data from 30 patients with similar symptoms. The processing involved calculating certainty values with CF and mapping them into fuzzy membership degrees. The test results showed an accuracy of 86%, demonstrating that the combination of CF and Fuzzy Logic improves diagnostic accuracy while providing results that are easier to interpret. Therefore, the developed system can serve as a diagnostic aid for monkeypox in primary healthcare centers, particularly in situations with limited diagnostic facilities, and can also serve as a foundation for developing intelligent detection technologies for other infectious diseases.
Pelatihan dan Pembekalan Uji Sertfikasi Kompetensi Teknis BNSP Untuk Meningkatkan Kompetensi Keahlian Mahasiswa Institut Teknologi Mitra Gama Candra, Dori Gusti Alex; Yubarda, Erliza; Surya, Candra; Tambunan, Leonard; Afrianto, Nurdi; Yusno, Zaharani; Putra, Khelvin Ovela; Putra, Tomy Nanda
SMART HUMANITY : Jurnal Pengabdian Masyarakat Vol. 2 No. 1: Maret 2025
Publisher : CV. Smart Scienti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70427/sh.v2i1.184

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kompetensi keahlian mahasiswa Institut Teknologi Mitra Gama melalui pelatihan dan pembekalan uji sertifikasi kompetensi teknis yang diselenggarakan oleh Badan Nasional Sertifikasi Profesi (BNSP) oleh LSP Sumber Daya Manusia TIK. Sertifikasi kompetensi di era globalisasi menjadi salah satu syarat utama dalam meningkatkan daya saing lulusan di dunia kerja. Oleh karena itu, mahasiswa perlu dibekali dengan keterampilan teknis yang diakui secara nasional dan internasional. Metode pelaksanaan kegiatan ini meliputi tiga tahap utama: sosialisasi terkait pentingnya sertifikasi kompetensi, pelatihan teknis yang mencakup simulasi uji kompetensi, serta pendampingan dalam proses uji sertifikasi. Hasil dari kegiatan ini menunjukkan bahwa mahasiswa yang mengikuti pelatihan dan uji sertifikasi mengalami peningkatan signifikan dalam pemahaman teknis serta memiliki kepercayaan diri yang lebih tinggi untuk menghadapi tantangan di dunia kerja. Selain itu, kegiatan ini juga mendukung upaya pemerintah dalam menciptakan tenaga kerja yang kompeten dan tersertifikasi. Adapun hasil dari Uji Kompetensi Sertifikasi adalah 67 mahasiswa yang mengikutinya 62 orang mahassiswa berhasil lulus dengan predikat kompeten dan 5 orang mahasiswa belum kompten.
Sosialisasi Program Magang Berdampak: Upaya Meningkatkan Partisipasi Mahasiswa dalam Penguatan Kompetensi MBKM Fauziyyah, Atika; Tambunan, Leonard; Nanda Putra, Tomy; Gusti Alex Candara, Dori; Vafky Ideal, M.Agung; Fitriyanto, Idir; Prastya, Adi
SMART HUMANITY : Jurnal Pengabdian Masyarakat Vol. 2 No. 3: September 2025
Publisher : CV. Smart Scienti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70427/sh.v2i3.233

Abstract

Program Magang Berdampak merupakan bagian dari kebijakan MBKM yang dirancang untuk meningkatkan kompetensi dan kesiapan kerja mahasiswa. Kegiatan sosialisasi yang diselenggarakan Institut Teknologi Mitra Gama ini melibatkan pimpinan akademik dan dosen, menggunakan pendekatan edukatif sekaligus praktis agar mahasiswa tidak hanya menerima informasi, tetapi juga langsung dibimbing mendaftar melalui platform Simbelmawa. Hasilnya, mahasiswa lebih memahami manfaat program serta menunjukkan antusiasme tinggi dalam mengikuti proses pendaftaran. Kegiatan ini berhasil mendorong peningkatan partisipasi dan keterlibatan mahasiswa dalam program penguatan kompetensi tingkat nasional.
Selection-Based Optimization of Naive Bayes and Decision Trees for Intelligent Classification of Sharia Financing Eligibility Tomy Nanda Putra; Atika Fauziyyah; Dori Gusti Alex Candra; Eka Sofiati
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 2 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Oktober 2026 (In Press)
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i2.27634

Abstract

Assessing sharia financing eligibility is a critical process for Islamic microfinance institutions such as Baitul Maal wat Tamwil (BMT), as inaccurate financing decisions may increase financing risk and affect institutional sustainability. However, financing evaluations are often conducted manually and rely heavily on subjective judgment, leading to inconsistencies and potential bias in decision-making. Therefore, this study aims to evaluate the effectiveness of Correlation-Based Feature Selection (CFS) in identifying relevant financing attributes and to compare the classification performance of the Naïve Bayes and Decision Tree (J48) algorithms for sharia financing eligibility assessment. The dataset used in this study consists of 500 historical financing records obtained from BMT Indragiri, comprising 127 eligible and 373 ineligible financing applications. The research process included data preprocessing, feature selection using CFS with the BestFirst search strategy, model construction, and classification using WEKA 3.8. Model performance was evaluated using 10-fold cross-validation based on accuracy, precision, recall, F1-score, Kappa statistic, and Area Under the Curve (AUC). The feature selection results showed that all predictor attributes, namely income, number of dependents, employment status, and financing history, were retained by the CFS algorithm, indicating that each attribute contributes relevant information to financing eligibility classification. Experimental results revealed that the Naïve Bayes classifier achieved an accuracy of 92.4%, precision of 92.3%, recall of 92.4%, F1-score of 92.2%, Kappa statistic of 0.7896, and AUC of 0.971. Meanwhile, the Decision Tree (J48) classifier achieved superior performance with an accuracy of 95.6%, precision of 95.7%, recall of 95.6%, F1-score of 95.6%, Kappa statistic of 0.8851, and AUC of 0.957. In addition, the Decision Tree model generated 23 decision rules and a tree size of 42 nodes, providing transparent and interpretable knowledge to support financing eligibility assessment. The findings indicate that the Decision Tree (J48) algorithm outperformed Naïve Bayes in classifying sharia financing eligibility and offers the additional advantage of interpretable decision rules. The proposed approach can support more objective, consistent, and transparent financing decision-making processes in Islamic microfinance institutions.
SISTEM INFORMASI RIWAYAT PERJALANAN (SIRP) MASYARAKAT DIMASA PANDEMI BERBASIS WEBSITE (Studi Kasus: Kecamatan Sungai Geringging) darmansah darmansah; Tomy Tomy Nanda Putra; Willi Novrian Willi Novrian
Indonesian Journal of Business Intelligence (IJUBI) Vol 4 No 2 (2021): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v4i2.1930

Abstract

The Corona virus or covid-19 began to appear in wuhan china at the end of 2019. Until now the corona virus has been a disease that has spread tremendously in countries in the world, none of which is Indonesia. To prepare accurate and reliable information in order to suppress the spread of the corona virus in Indonesia, an information system is needed. The Sungai Geringging District Government is a government in Padang Pariaman Regency which is currently collecting data on the travel history of its people during the pandemic manually or has not maximized computerization and technology. This of course makes the sub-district government in recording data, managing community data entering and leaving the government environment ineffective and inefficient. To assist the Sungai Geringging District Government in collecting data and disseminating information, it is necessary to build a website-based SIRP (Travel History Information System) information system. In designing this SIRP (Travel History Information System) the researcher used UML (Unified Modeling Language) modeling. In this study, UML was used to facilitate researchers when designing the system to be made. The method that researchers apply in this study is the prototyping method. With the construction of the Travel History Information System (SIRP) during the pandemic, it is hoped that the Sungai Geringging District Government can easily manage community data that enters and exits the government environment. In addition, the public can easily find out information on how many people are under surveillance (ODP) and people without symptoms (OTG) and other information related to the corona virus.
Peningkatan Kapasitas Dosen Pembimbing Praktik Kerja Lapangan melalui Bimbingan Teknis dan Lokakarya Partisipatif di Institut Teknologi Mitra Gama Dori Gusti Alex Candra; Atika Fauziyyah; Khelvin Ovela Putra; Zaharani Yusno; Sonya Ostha Laurency; Eka Sofiati; M. Agung Vafky Ideal; Tomy Nanda Putra; M. Hafizh Gusra
Jurnal Bakti Dirgantara Vol. 3 No. 2 (2026): Jurnal Bakti Dirgantara (In-Press)
Publisher : Universitas Dirgantara Marsekal Suryadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35968/5ebc3663

Abstract

Field Work Practice (PKL) serves to bridge the gap between the competencies taught in higher education and the actual needs of the business and industrial sectors (DU/DI). However, the effectiveness of PKL is often hindered by a focus on administrative guidance alone. This Community Service (PkM) activity aims to enhance the capacity of Field Supervisors (DPL) at the Mitra Gama Institute of Technology (ITMG) as the internal target audience. The activity was held on May 1–3, 2025, in the ITMG Auditorium for a duration of 24 instructional hours, involving 30 active faculty members at Mitra Gama Institute of Technology who were selected based on specific inclusion criteria. The implementation methods included technical guidance, focus group discussions (FGDs), and workshops. The activity was evaluated using a one-group pretest-posttest pre-experimental design through structured questionnaires, as well as an analysis of the feasibility of the Follow-Up Action Plan (RTL) documents. Data were analyzed using descriptive statistics and content analysis. The results of the program showed an increase in participants’ cognitive knowledge and managerial readiness, as evidenced by a 38% increase in the average post-test score compared to the pre-test score. In addition, the program successfully facilitated the preparation of 30 independent Action Plan (RTL) documents and produced an institutional output in the form of a draft proposal for restructuring the internship evaluation rubric with a 50:50 ratio.
Intelligent System for Monkeypox Disease Diagnosis Using Hybrid Certainty Factor and Fuzzy Logic Methods M. Agung Vafky Ideal; Tomy Nanda Putra
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/h13m0k54

Abstract

Monkeypox cases has the potential to spread rapidly, making early detection crucial to prevent wider transmission. Unfortunately, at the UPT Puskesmas where this study was conducted, there is no system available to assist medical personnel in performing fast and standardized diagnoses. To address this issue, this research developed a web-based intelligent system by combining the Certainty Factor (CF) and Fuzzy Logic methods. The system’s knowledge base was constructed from symptom data collected through expert interviews and literature studies. It was then tested using data from 30 patients with similar symptoms. The processing involved calculating certainty values with CF and mapping them into fuzzy membership degrees. The test results showed an accuracy of 86%, demonstrating that the combination of CF and Fuzzy Logic improves diagnostic accuracy while providing results that are easier to interpret. Therefore, the developed system can serve as a diagnostic aid for monkeypox in primary healthcare centers, particularly in situations with limited diagnostic facilities, and can also serve as a foundation for developing intelligent detection technologies for other infectious diseases.
Co-Authors Afrianto, Nurdi Atika Fauziyyah Budi Permana Putra Budy Satria Candra Surya Darmansah Darmansah Darmansah Darmansah Darmansah, Darmansah Dori Gusti Alex Candra Eka Sofiati Eka Sofiati Erliza Yubarda Fitra Kasma Putra Gusti Alex Candara, Dori Hafiz Mursalan Idir Fitriyanto Idir Iswandi Iswandi Juwita Azizah Khelvin Ovela Putra Leonard Tambunan M Agung Vafky Ideal M Yoka Fathoni M. Agung Vafky Ideal M. Hafizh Gusra Meiditra, Irzon Prastya, Adi Resad Setyadi Sarah Astiti S.Kom., M.MT Sofiati, Eka Sonya Ostha Laurency Willi Novrian Willi Novrian Yusno, Zaharani Zaharani Yusno Zaharani Yusno