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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Media Infotama JSI: Jurnal Sistem Informasi (E-Journal) Proceeding of the Electrical Engineering Computer Science and Informatics Indonesian Journal of Artificial Intelligence and Data Mining Seminar Nasional Teknologi Informasi Komunikasi dan Industri EKONOMIS : Journal of Economics and Business PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer International Journal of New Media Technology Jurnal ULTIMATICS The IJICS (International Journal of Informatics and Computer Science) JOURNAL V-TECH (VISION TECHNOLOGY) Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Bulletin of Computer Science Research Journal of Informatics Management and Information Technology Journal of Social Responsibility Projects by Higher Education Forum Bulletin of Data Science ABDINE Jurnal Pengabdian Masyarakat Journal of Computing and Informatics Research Jurnal Komunikasi, Sains dan Teknologi (JKST) Jurnal (FORSINTA) Informatika, Sistem Informasi dan Kehutanan Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS West Science Interdisciplinary Studies Journal of Informatics, Electrical and Electronics Engineering West Science Interdisciplinary Studies Jurnal Rekayasa Sistem Informasi dan Teknologi Bulletin of Informatics and Data Science Karunia: Jurnal Hasil Pengabdian Masyarakat Indonesia Jurnal Ilmu Komputer, Teknologi Dan Informasi Journal of Computer Science and Information Technology Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Akademika Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial Journal of Applied Research In Computer Science and Information Systems Proletarian : Community Service Development Journal International Journal of Innovation Research in Education, Technology and Management (IJIRETM) Journal of Decision Support System Research
Hetty Rohayani
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RANCANG BANGUN APLIKASI RENTAL MOBIL BERBASIS MOBILE DENGAN TEKNOLOGI PWA PADA AQUINA RENT JAMBI Ardian, Iqbal; Rohayani, Hetty; Helmina, Helmina
Jurnal Informatika, Sistem Informasi dan Kehutanan (FORSINTA) Vol. 3 No. 2 (2024): Jurnal Informatika, Sistem Informasi dan Kehutanan (Forsinta)
Publisher : LPPM Universitas Muhammadiyah Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53978/jfsa.v3i2.503

Abstract

Aquina Rent Jambi, sebuah perusahaan rental mobil yang masih mengandalkan sistem operasional konvensional, menghadapi berbagai tantangan dalam menjalankan bisnis sehari-hari. Sistem manual yang bergantung pada pencatatan kertas dan komunikasi melalui telepon atau kunjungan langsung ke kantor mengakibatkan proses pemesanan dan pengelolaan kendaraan menjadi lambat dan rawan kesalahan. Penelitian ini bertujuan untuk mengembangkan aplikasi rental mobil berbasis mobile dengan menggunakan teknologi Progressive Web Apps (PWA) guna meningkatkan kualitas layanan dan mempermudah proses pemesanan kendaraan kapan saja dan di mana saja. Aplikasi ini juga diharapkan dapat meningkatkan pengalaman pengguna secara keseluruhan. Pengembangan sistem mengikuti metode Waterfall, dengan dukungan basis data MySQL dan penerapan teknologi PWA, sehingga mampu mengatasi permasalahan operasional yang dihadapi oleh Aquina Rent Jambi.
TINJAUAN LITERATUR SISTEMATIS: PENERAPAN ALGORITMA KLASIFIKASI DATA MINING UNTUK PREDIKSI LOYALITAS PELANGGAN PADA PLATFORM E-COMMERCE hesti, Hesti Yulianingsih; Rohayani, Hetty
Jurnal Informatika, Sistem Informasi dan Kehutanan (FORSINTA) Vol. 4 No. 1 (2025): Jurnal Informatika, Sistem Informasi dan Kehutanan (Forsinta)
Publisher : LPPM Universitas Muhammadiyah Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53978/jfsa.v4i1.777

Abstract

Penelitian ini merupakan tinjauan literatur sistematis yang bertujuan untuk menganalisis secara mendalam penerapan algoritma klasifikasi dalam data mining untuk memprediksi loyalitas pelanggan pada platform e-commerce. Penelitian dilakukan menggunakan metode Systematic Literature Review (SLR) yang mengacu pada panduan PRISMA. Sebanyak 15 artikel ilmiah terpilih dari periode 2018 hingga 2025 dianalisis berdasarkan jenis algoritma, metode, serta hasil evaluasi model. Hasil studi menunjukkan bahwa algoritma seperti Naïve Bayes, C4.5, Random Forest, dan Deep Learning sering digunakan karena keunggulan masing-masing. Naïve Bayes efektif untuk data sederhana dan cepat diimplementasikan, sedangkan C4.5 unggul dalam memberikan interpretasi yang mudah dipahami. Random Forest memiliki akurasi tinggi dan cocok untuk data besar dan kompleks, sementara Deep Learning mampu mengenali pola perilaku pelanggan yang kompleks tetapi memiliki kekurangan pada transparansi hasil. Selain itu, metode clustering seperti K-Means dan DBSCAN juga penting untuk segmentasi awal sebelum klasifikasi dilakukan. Dengan demikian, penerapan algoritma klasifikasi tidak hanya meningkatkan akurasi prediksi loyalitas pelanggan, tetapi juga mendukung perumusan strategi retensi yang lebih efektif dan personal. Hasil penelitian ini diharapkan dapat menjadi dasar pengembangan penelitian lanjutan dan penerapan praktis di industri e-commerce Indonesia.
STUDI LITERATUR DATA MINING DALAM BIDANG KESEHATAN UNTUK ANALISIS DAN PREDIKSI PENYAKIT DALAM Yuniar, Fira; Rohayani, Hetty
Jurnal Informatika, Sistem Informasi dan Kehutanan (FORSINTA) Vol. 4 No. 1 (2025): Jurnal Informatika, Sistem Informasi dan Kehutanan (Forsinta)
Publisher : LPPM Universitas Muhammadiyah Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53978/jfsa.v4i1.778

Abstract

Perkembangan teknologi informasi telah mendorong pertumbuhan data yang sangat pesat di bidang kesehatan, khususnya data rekam medis pasien yang tersimpan dalam jumlah besar di berbagai fasilitas kesehatan. Data tersebut menyimpan potensi pengetahuan yang sangat berharga jika dianalisis secara tepat. Salah satu pendekatan yang efektif untuk mengekstrak pengetahuan dari data tersebut adalah data mining, yaitu serangkaian metode untuk menemukan pola tersembunyi dan informasi penting dari kumpulan data yang besar, sehingga dapat digunakan dalam pengambilan keputusan medis secara lebih akurat dan efisien. Studi literatur ini membahas penerapan berbagai algoritma data mining, seperti Naïve Bayes, Decision Tree (C4.5 dan C5.0), K-Nearest Neighbor, dan Random Forest dalam analisis dan prediksi penyakit dalam. Hasil penelitian menunjukkan bahwa algoritma Decision Tree C4.5 yang dioptimasi dengan Particle Swarm Optimization (PSO) mampu mencapai akurasi hingga 99,67% untuk prediksi hepatitis C, sedangkan Naïve Bayes efektif dalam prediksi stroke dan penyebaran COVID-19 dengan akurasi tinggi. Selain itu, Random Forest terbukti unggul dalam prediksi penyakit stroke dan diabetes dengan akurasi di atas 90%. Studi ini memberikan gambaran komprehensif tentang efektivitas berbagai metode data mining dan menjadi referensi penting bagi pengembangan aplikasi prediksi penyakit di bidang kesehatan.
HEURISTIC-BASED EXPERT SYSTEM FOR TRAINING OPTIMIZATION AND INJURY PREVENTION OF WUSHU ATHLETES Mardiana, Ananda Sri; Hetty Rohayani; Helmina, Helmina
Journal of Computer Science and Information Technology Vol. 3 No. 1 (2025): Desember
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jcsit.v3i1.2067

Abstract

This study aims to develop and evaluate a heuristic-based expert system capable of optimizing training and preventing injuries in wushu athletes through personalized and adaptive recommendations. The research method used an experimental approach with software engineering, integrating Case-Based Reasoning (CBR) and Rule-Based Expert System (RBES) into a single decision support system. Data were obtained from wushu athletes' injury histories, biomechanical data measured by wearable sensors, and interviews and questionnaires with athletes and coaches. The results showed that the system was able to classify athletes' injury risk into low, medium, and high categories consistently with expert assessments, and reduced the rate of recurrent injuries, particularly ankle sprains, by approximately 30% during the implementation period. Furthermore, the system helped improve training efficiency without compromising athlete safety. The conclusion of this study is that the integration of CBR, RBES, and heuristic approaches produces an adaptive, transparent, and effective system as a decision-making tool for training optimization and injury prevention in wushu athletes.   Keywords: Expert System, Case-Based Reasoning, Rule-Based Expert System, Injury Prevention  
Implementation of Forward Chaining Method in Laptop Damage Detection Expert System Julian Chaniago; Hetty Rohayani; Abd Halim
Journal of Applied Research In Computer Science and Information Systems Vol. 3 No. 1 (2025): Juni 2025
Publisher : PT. BERBAGI TEKNOLOGI SEMESTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61098/jarcis.v3i1.246

Abstract

Expert systems are a branch of artificial intelligence designed to replicate the reasoning ability of specialists. This study applies the forward chaining method to build a web-based expert system for diagnosing laptop malfunctions. The system’s knowledge base was constructed from 20 common laptop malfunction symptoms, identified through literature review, user questionnaires, and interviews with repair technicians, and translated into inference rules. To evaluate performance, the system was tested on 50 malfunctioning laptops. Results show that the expert system achieved an accuracy rate of 85%, indicating its effectiveness in detecting various hardware and software problems. This research demonstrates that forward chaining can support non-expert users in performing early fault detection, thereby reducing repair costs and dependence on professional technicians
The Edukasi Konsep Kewirausahaan Sosial Berbasis Potensi Desa Melalui Badan Umum Milik Desa (BUMDES) Wella Sandria; Arniwita Arniwita; Siswoyo Siswoyo; Hario Tamtomo; Hetty Rohayani; Ermaini Ermaini
Journal of Social Responsibility Projects by Higher Education Forum Vol 6 No 3 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jrespro.v6i3.9757

Abstract

Village potential-based social entrepreneurship through Village-Owned Enterprises (BUMDes) represents a social business model that optimizes natural resources, cultural assets, and community capacities to address socio-economic issues while increasing Village Original Revenue (PADes). This community service activity was conducted in Muara Tembesi Subdistrict, Batanghari Regency, Jambi, Indonesia. The study aims to analyze the role of Village-Owned Enterprises (BUMDes) in village development and improving community welfare through a social entrepreneurship approach. There are 15 actively operating BUMDes distributed across 12 villages in Muara Tembesi, engaging in various types of business activities. Although these enterprises have achieved progress in managing their business units, they still face several challenges related to social entrepreneurship, including a lack of innovation in the creative economy for resource management, inadequate mapping of village potential, suboptimal utilization of village websites, and limited effectiveness in marketing and promotional channels. Based on these issues, the service team conducted field observations and provided technical assistance to BUMDes managers, carried out village potential mapping, and analyzed appropriate strategies for developing business units and creative economic activities within rural communities. The results of the mapping indicate that each village possesses distinct potentials; however, natural resource outputs are still predominantly concentrated in the agricultural and plantation sectors. Several strategies were proposed to address the challenges faced by BUMDes, including enhancing understanding of the importance of BUMDes for village development, providing training and mentoring in social entrepreneurship and small and medium enterprise management, increasing community awareness of village potential, and encouraging subdistrict and village officials to utilize BUMDes operational funds more effectively.
Optimalisasi Kompetensi Mahasiswa melalui Instalasi dan Konfigurasi Sistem Operasi Berbasis Praktik Kevin Kurniawansyah; Noneng Marthiawati; Hetty Rohayani; Hafiz Nugraha
Journal of Social Responsibility Projects by Higher Education Forum Vol 6 No 3 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jrespro.v6i3.9764

Abstract

This community service activity aims to improve students’ competencies in the installation and configuration of operating systems through a practice-based approach at Universitas Muhammadiyah Jambi, involving 25 participants. The problem faced by the participants is the low level of practical skills in independently performing operating system installation and configuration, caused by the dominance of theoretical learning and the lack of direct practical experience. Therefore, a learning approach that integrates theoretical and practical aspects in a balanced manner is required. The method used in this activity is hands-on training combined with direct mentoring through the stages of preparation, implementation, evaluation, and follow-up. During the implementation stage, participants were provided with basic materials, demonstrations, and direct practice under the guidance of the implementation team. Evaluation was carried out by comparing pre-test and post-test results as well as observing participants’ skills during the activity. The results show a significant improvement in students’ competencies, indicated by the transition from conceptual understanding to the ability to independently perform installation and configuration of operating systems. In addition, participants demonstrated improvement in basic troubleshooting skills, learning engagement, and confidence during practice. This activity produced outputs in the form of improved technical skills relevant to industry needs and the development of independent problem-solving abilities among students. Therefore, practice-based training methods are proven to be effective in improving student competencies in the field of information technology and have the potential to be further developed in advanced training programs.
Studi Literatur Review Penerapan Data Mining Untuk Prediksi Penyakit Jantung Menggunakan Naïve Bayes Anisa Rizki Septia; Hetty Rohayani
Jurnal Ilmu Komputer, Teknologi Dan Informasi Vol 4 No 1 (2026): Januari 2026
Publisher : CV. Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/jurikti.v4i1.268

Abstract

Heart disease is one of the leading causes of global death, often difficult to detect early due to non-specific clinical symptoms. To overcome the limitations of manual diagnosis, the application of data mining techniques utilizing the Naïve Bayes algorithm presents an efficient and accurate computational solution. This study aims to analyze and map the effectiveness of Naïve Bayes implementation in predicting heart disease through a Systematic Literature Review (SLR) approach. The contribution of this study is to provide a comprehensive taxonomic guide regarding the influence of data geometry, preprocessing techniques, and the integration of feature selection methods on optimizing the performance of probabilistic models. The results of the literature review indicate that the model accuracy level varies between 58% and 91.80%, with the majority of performance stable in the range of 79%-91% which is deterministically influenced by the quality of data dimensionality reduction. Overall, the Naïve Bayes-based data mining process has proven to have great potential as a clinical decision support system in supporting early medical preventive measures.
Studi Literatur Review: Penerapan Naive Bayes Untuk Klasifikasi Aktivitas Akademik Mahasiswa Alysa Najwa; Hetty Rohayani Hetty
JOURNAL VISION TECHNOLOGY (V-TECH) Vol. 9 No. 1 (2026): JOURNAL V-TECH (VISION TECHNOLOGY)
Publisher : LPPM Universitas Adiwangsa Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35141/btxj4p30

Abstract

Perkembangan teknologi  yang sangat pesat pada era digital saat ini berpengaruh besar terhadap berbagai bidang, termasuk dalam dunia Pendidikan perguruan tinggi. Pemanfaatan teknologi informasi pada perguruan tinggi khususnya di bidang akademik mahasiswa. Dalam pengelolaan data mahasiswa menjadi salah satu faktor untuk meningkatkan system kualitas layanan system informasi Pendidikan di kampus. Data akdemik mahasiswa meliputi nilai, kehadiran, partisipasi dalam kegiatan dan informasi pribadi tersimpan dalam system informasi kampus yang dapat dimanfaatkan untuk menganalisis prestasi akademik mahasiswa. Dengan informasi yang diperoleh pihak kampus dapat melakukan Tindakan untuk mencegah penurunan akademik mahasiswa dan merancang strategi pembelajaran yang lebih efektif serta menyenangkan bagi mahasiswa. Penelitian ini bertujuan untuk mengklasifikasi dan memprediksi peningkatan prestasi akademik mahasiswa menggunakan metode klasifikai Navie Bayes Algoritma hal ini dipilih karena kesederhanaan, efidien, dalam memproses data, serta mampu dalam mengelola hasil akademik. Hasil dari penelitian ini juga diharapkan dapat memberi dukungan dalam pengembangan system pendukung Keputusan akademik Universitas serta memberikan hal baru bagi pengelola akademik dalam merancang kebijakan dan pendekatan pembelajaran yang mendukung peningkatan prestasi akademik mahasiswa secara maksimal.
Analisis Prediksi Curah Hujan dengan Pohon Keputusan C4.5: Studi Literatur Putra Nugraha Syah; Hetty Rohayani
JOURNAL VISION TECHNOLOGY (V-TECH) Vol. 9 No. 1 (2026): JOURNAL V-TECH (VISION TECHNOLOGY)
Publisher : LPPM Universitas Adiwangsa Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35141/nzcy8v37

Abstract

Penelitian ini bertujuan untuk menganalisis dan memprediksi curah hujan menggunakan algoritma pohon keputusan C4.5. Metodologi yang digunakan dalam penelitian ini adalah pendekatan kuantitatif dengan pengumpulan data curah hujan dari stasiun meteorologi di wilayah Indonesia selama periode tertentu. Hasil analisis menunjukkan bahwa model C4.5 mampu memprediksi curah hujan dengan akurasi yang memadai. Temuan ini memberikan implikasi penting bagi perencanaan sumber daya air dan pertanian di wilayah Indonesia.
Co-Authors -, Irsyadunas Abd Halim Ade Irma Agustina Lubis Ade Pratama Adi Supriyatna Afrizal J, S.Kom Afrizal. J Agi Nanjar Agustina, Safira Ahmad Heriansyah Akbar, Zulfikri Akhsay, Tengku Alysa Najwa Amalia, Dira Amandha, Shandy Amin Amin Ananda Sri Mardiana Andrico, Ricky Anisa Rizki Septia Anisa Rizki Septia Anugrah, Septriyan Ardian, Iqbal Ardiansyah, Lulu Arif Mursidan Arini, Zaza Mutiara Armandito Armiwita, Armiwita Arniwita, Arniwita Arpan Saputra Harahap Assidiq, Ilham Azzamy, Muhammad Nabil Barkat Harefa Bella Putri Cahyani Beni Irawan Bintang, Muhammad Rizki Olihta Bister Purba Boangmanalu, Mei Mariana Dani, Rian Derist Touriano Desyanti - Desyanti Dewi Lestari Dewi Lestari Dian Aprilia Dewi Dina Fitria Murad Dwi Nopriyani Ebenezer Bangun Ediansa, Oka Eka Gustina Bancin Endah Tri Kurniasih Endah Tri Kurniasih Erick Fernando Erick Fernando Erick Fernando Erick Fernando Erick Fernando Erick Fernando B311087192 Erlin Windia Ambarsari Ermaini Ermaini Fachruddin, Fachruddin Faiza Rini Fery Purnama, Fery Fitriyani, Mia Frieyadie Frieyadie Govinda Saputra Gustinar, Gustinar Hafiz Nugraha Hafiz Nugraha Hafiz Nugraha Hario Tamtomo Helmina Helmina Helmina Helmina Helmina, Helmina Hendra Kurniawan Heri Santoso Hesti hesti, Hesti Yulianingsih Ibnu Sani Wijaya Ikke Yamalia Imam Saputra Indah Desmasari Indradewa, Rhian Irmanelly Irmanelly, Irmanelly Irvan Siahaan Jasmir Jasmir, Jasmir Jeperson Hutahaean Julian Chaniago Jumaryadi, Yuwan Kevin Kurniawansyah Khairul Imtihan Lubis, Ridha Maya Faza M. Reinaldi Mardiana, Ananda Sri Mesran, Mesran Muhamad Irsan Muhammad Alfareza Muhammad Alfareza Muhammad Choirul Umam Muhammad Fauzi Muhammad Fauzi Muhammad Ikhsan Muhammad Ikhsan Muhammad Syahrizal Nanjar, Agi Nazrul Azizi Noneng Marthiawati Novia, Tri Meli NOVITASARI Nurdiansyah Saputra Nurfazila, Aprilia Nursaka Putra Nurwijayanti Oka Ediansa Oktarino, Ade Pandapotan Siagian Pandapotan Siagian Pandapotan Siagian Partogi Simanjuntak Purba, Bister Purnama, Benni Putra Nugraha Syah R, Muhammad Rachmad Rahmi Handayani Rahmi Handayani Ramli, M Saidina Rendi Efdiansyah Rico Rico Rico Rico Rico Rico Rico Rico Rico, Rico Ridha Maya Faza Lubis Rifky Lana Rahardian Rifky Lana Rahardian Riski Ferita Wahyu Rizky Pratama Rohmat Indra Borman Safira Agustina Safira Agustina Sahrawi Sahrawi Sallaby, Achmad Fikri Salsabila Tadya Hasibuan Salsabila Tadya Hasibuan Santoso SANTOSO SANTOSO Saputri, Yolanda Sherina Intania Siagian, Jaya Sari Anggraini Siagian, Pandapotan Siswoyo Siswoyo Sitti Nur Alam Steven, Ferry Surjandy Surjandy Sussolaikah, Kelik Syam, Syahrull Hi Fi Tertia, Farhan Adhimukti Valian Yoga Pudya Ardhana Wahyu Hidayat Wella Sandria Wella Sandria Yaakub, Saleh Yuniar, Fira Yuvanda, Sesraria Zai, Iwanman Zulfikri Akbar Zulpandi, Zulpandi