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All Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Digit : Digital of Information Technology Jurnal Ilmiah Pengabdian dan Inovasi
Fachri, Muhamad
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Social Sciences

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Klasifikasi Multi Label untuk Deteksi Keseimbangan Emosi Pengguna Media Sosial Menggunakan K-Fold Cross Validation Misriati, Titik; Aryanti, Riska; Sagiyanto, Asriyani; Fachri, Muhamad; Ramadhani, Arya
Journal of Information System Research (JOSH) Vol 6 No 1 (2024): Oktober 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i1.6033

Abstract

Social media has grown in popularity, with millions of people using it to engage with and share information worldwide. Social media, in addition to serving as a communication tool, are crucial for expressing the emotions and feelings of users. The widespread use of social media has had a significant impact on people's emotions. In particular, negative emotions are frequently experienced and can have a significant impact on mental health. This study aimed to analyze multiple classification models to discover the optimal model for detecting emotional balance among social media users. The classification models utilized in this study include the K-Nearest Neighbor, Random Forest, Support Vector Machine, Decision Tree, and AdaBoost to identify the best classification model capable of detecting the emotional balance of social media users. Several classification models are applied and compared with the aim of evaluating model performance. This research project employed K-fold cross-validation to evaluate the categorization model by comparing various k values. The Random Forest algorithm achieved the greatest accuracy of 99.90% at a K-Fold cross validation value of 10 and an Area Under the Curve (AUC) value of 100%. Thus, this study successfully found a reliable model for accurately detecting emotions of social media users, which is expected to contribute to the development of mental well-being monitoring systems on social media platforms.
Penyuluhan Penggunaan ITE dan Batasan Batasanya Kepada Siswa Sekolah Menengah Atas Kusumaningsih, Rila; Luhur, Puntadewa Aji; Fachri, Muhamad; Setiawan, Mohamad Arif; Pantouw, Toar Bastian; Permana, Min Dhani; Pirgiawan, Obi
Jurnal Ilmiah Pengabdian dan Inovasi Vol. 2 No. 3 (2024): Jurnal Ilmiah Pengabdian dan Inovasi (Maret)
Publisher : Insan Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57248/jilpi.v2i3.337

Abstract

The ITE Law or Electronic Information and Transaction Law is a law that regulates electronic information and transactions. The ITE Law was first passed through Law No. 11 of 2008 before finally being revised with Law No. 19 of 2016. The stages of this counseling implementation are carried out for approximately 1 hour. In general, the implementation of activities is: Coordination and communication with the school to obtain a general description of students and identify problems that will be the basis for determining the theme of the activity. School students are one of the largest users of social media from the community, whose age range is 13-20 years. Which psychological condition at that age is still unstable in finding identity. With the ITE law, there are certain rules and restrictions on using social media, including the spread of immoral content, gambling, insults, blackmail / threats; the spread of fake news/hoaxes; personal threats of violence; unlawfully hacking someone else's electronic system; and so on. In addition, there are precautions so that we avoid ITE violations, namely being wise in social media, crosschecking the information obtained, not entering vulnerable personal data on social media, not using sentences that contain elements of sara.
PERANCANGAN E-LEARNING TERINTEGRASI CHATBOT AI MENGGUNAKAN METODE AGILE UNTUK PENGENALAN KARIR IT Hidayatun, Nunung; Putri, Dafina Nabila; Fachri, Muhamad; Murtina, Hidayanti; Susafa’ati, Susafa’ati
Jurnal Digit : Digital of Information Technology Vol 15, No 2 (2025)
Publisher : Universitas Catur Insan Cendekia (CIC) Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51920/jd.v15i2.438

Abstract

Siswa SMA sering menghadapi kesulitan dalam menentukan pilihan karir dan jurusan kuliah, terutama di bidang Teknologi Informasi (IT), akibat kurangnya bimbingan yang terstruktur dan relevan. Penelitian ini bertujuan untuk merancang sebuah model sistem informasi e-learning sebagai solusi dari permasalahan tersebut. Sistem yang diusulkan, bernama ELKARIS (E-learning Pengenalan Karir IT Terintegrasi dengan Chatbot AI), dirancang untuk memberikan platform bimbingan karir yang interaktif dan mudah diakses. Dengan menggunakan metode Agile dan kerangka kerja Scrum, diidentifikasi sebagai solusi potensial untuk menyediakan bimbingan karir yang efektif dan responsif. Sistem ELKARIS menyediakan platform e-learning berbasis web yang terstruktur, interaktif, dan terintegrasi dengan chatbot AI untuk pengenalan karir IT. Sistem ini mencakup fitur-fitur seperti materi pembelajaran karir IT, soal latihan, tes minat bakat dengan rekomendasi karir, serta chatbot AI untuk menjawab pertanyaan siswa. Hasil yang dicapai adalah platform e-learning berbasis website yang diharapkan dapat memfasilitasi siswa dengan informasi karir IT yang relevan, membantu pengambilan keputusan berbasis data, dan menyediakan simulasi interaktif serta tes untuk mengenali potensi diri di bidang IT. Kata kunci: Agile, E-learning, Chatbot, Artificial, Intelligence
Co-Authors ASRIYANI SAGIYANTO, ASRIYANI Hidayanti Murtina Kusumaningsih, Rila Luhur, Puntadewa Aji Nunung Hidayatun Pantouw, Toar Bastian Permana, Min Dhani Pirgiawan, Obi Putri, Dafina Nabila Ramadhani, Arya Riska Aryanti Setiawan, Mohamad Arif Susafa’ati, Susafa’ati Titik Misriati