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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Techno.Com: Jurnal Teknologi Informasi Elkom: Jurnal Elektronika dan Komputer Bulletin of Electrical Engineering and Informatics Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Journal of Telematics and Informatics INFOKAM Sisforma: Journal of Information Systems CESS (Journal of Computer Engineering, System and Science) Proceeding SENDI_U Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Rekam Medis dan Informasi Kesehatan Media Ilmu Kesehatan Jurnal Teknik Informatika UNIKA Santo Thomas J-SAKTI (Jurnal Sains Komputer dan Informatika) Jesya (Jurnal Ekonomi dan Ekonomi Syariah) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Riset Informatika Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming SOSCIED Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Ilmiah Intech : Information Technology Journal of UMUS Tematik : Jurnal Teknologi Informasi Komunikasi Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Journal of Business and Technology J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Seminar Nasional Ilmu Terapan Jurnal Kabar Masyarakat Journal of Computing Theories and Applications Jurnal Informatika: Jurnal Pengembangan IT Journal of Future Artificial Intelligence and Technologies Proceeding of The International Conference on Mathematical Sciences, Natural Sciences, and Computing
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Journal : Jurnal Informatika: Jurnal Pengembangan IT

Perancangan Model Deteksi Potensi Siswa Putus Sekolah Menggunakan Metode Logistic Regression Dan Decision Tree Ermillian, Ade; Nugroho, Kristiawan
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 3 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i3.8007

Abstract

The phenomenon of student dropouts is one of the main challenges in education, influenced by various factors such as absenteeism, economic pressures on families, low academic performance, and lack of motivation. This issue not only affects the personal development of students but also tarnishes the reputation of educational institutions. Therefore, an innovative technology-based approach, such as data mining, is needed to detect students at risk of dropping out early. This study aims to design a model for detecting the potential of school dropout students using Logistic Regression and Decision Tree methods based on student data from SMA N 4 Tegal. The variables used in the analysis include demographic, academic, and social information such as absenteeism, average semester grades, parental income, and transportation type. The dataset is processed using one-hot encoding and label encoding techniques to convert categorical data into numeric values. The results indicate that both methods have their respective advantages. The Decision Tree model achieves high precision, especially in predicting students who continue their education, with a precision of 0.99 for the "Continue School" class. However, recall for the "Dropout" class remains low (0.60), indicating the need for improvements in detecting students at risk of dropping out. On the other hand, the Logistic Regression model shows better balance in detecting both classes, with more balanced accuracy and recall. This study concludes that both models can be used to monitor the potential of school dropouts and provide data-driven recommendations for more accurate educational decision-making.
Penerapan Metode SAW dalam Penentuan Mata Pelajaran Pilihan Siswa Kelas XI pada MAN 1 Brebes Saputro, Risky Wisnu; edi, sarwo; Perdana, Willy Yudha; Nugroho, Kristiawan; Ardhianto, Eka
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 4 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i4.9248

Abstract

The subject selection process for eleventh-grade students at Madrasah Aliyah Negeri 1 Brebes faces challenges including misalignment between student interests and academic abilities, and imbalanced teacher-to-subject ratios across Natural Sciences, Social Sciences, and Religious Studies. This study develops a decision support system using the Simple Additive Weighting (SAW) method to provide objective recommendations that consider both academic performance and student preferences. A quantitative descriptive analytical approach was applied with data from 30 tenth-grade students, incorporating four criteria: Natural Sciences scores, Social Sciences scores, Religious Studies scores, and student interests, weighted 0.25, 0.25, 0.10, and 0.40 respectively. The SAW implementation included decision matrix construction, normalization, weighted preference calculation, and recommendation determination. Results showed optimal distribution with 19 students recommended for Natural Sciences, 7 for Social Sciences, and 4 for Religious Studies, achieving 96.67% accuracy in aligning preferences while optimizing academic potential. The system preserved preferences for all students initially interested in Social Sciences and Religious Studies, while reassigning two Natural Sciences–interested students to Social Sciences based on superior performance. Top-performing students identified were Mohammad Abian for Natural Sciences (0.9802), Julia for Social Sciences (0.87243), and a student with 0.75995 for Religious Studies. The SAW method proves effective in addressing multi-criteria decision-making while ensuring transparency, objectivity, and balanced resource use in Islamic secondary education.
Usability Sentiment Analysis Menggunakan Metode SUMI, NLP Scikit-Learn pada Aplikasi New Sakpole Aminudin, Agus; Hadiono, Kristophorus; Nugroho, Kristiawan
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 2 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i2.5451

Abstract

This research will discuss issues related to how to evaluate the usability and Sentiment Analysis aspects of the New Sakpole application system, how to determine the level of user satisfaction in using the New Sakpole mobile application and to determine sentiment analysis based on the results of analysis using the SUMI and NLP tools. The research objective is based on the formulation of existing problems to provide usability aspect values for the development of the New Sakpole mobile application and generate recommendations for improvement and determine the level of positive and negative sentiment analysis by using the New Sakpole Application as a medium for paying Motor Vehicle Tax. The test uses the Software Usability Measurement Inventory (SUMI) tool, the New Sakpole mobile application system, which is very helpful and can provide value to the community in the online vehicle tax payment process. This can be seen and obtained from a scale of helpfulness and efficiency resulting from a maximum score of 100 with an average score of 101 and 86.2. The results of the test using the SUMI tool, all average aspects get above average results, so the level of usability that occurs is that the use of New Sakpole has worked and is running well. The test uses Scikit-Learn Natural Language Processing (NLP) that the results of processing the review dataset on the New Sakpole Application from the Google Play Store with a total of 4704 reviews and a sampling of 500 reviews, that the response or reviews of the community using the New Sakpole application are negative even though for Acuracy word (words) that conveyed a review of 80.90%. From the results of the sample data test that index 0 is negative so that the words "good, very enlightening" can be concluded with Sentiment is 1 (POSITIVE)".
Co-Authors Achmad Nuruddin Safriandono Afandi , Afandi Afif, Randi Ahmad Fathoni Ajib Susanto Ajie, Ach. Ridlo Bayu Alex Chandra Iswanto Alfiqhyanto, Damas Aminudin, Agus Anjis Sapto Nugroho Anton Sujarwo Anton Sujarwo Aprico, Fikky Apriyanti, Dewi Aquinia, Ajeng Araaf, Mamet Adil Arsyad , Muhammad Rafi Haidar budi hartono Budiarto, Indri Cahaya, Agus Indra De Rosal Ignatius Moses Setiadi Dhendra Marutho Dwi Agus Diartono Dwi Budi Santoso Edy Winarno Eka Ardhianto Eko Ariyanto Eko Prasetyo Eko Prasetyo Eksawati, Rini Endang Tjahjaningsih Eri Zuliarso Ermillian, Ade Faizi, Aditya Wahyu Nur fakhri Farooq, Omar Fitrianto, Lindu Hari Murti Hermawan, Taufan Hidayat, Suluh Irawan, Sandy Islam, Hussain Md Mehedul Isworo Nugroho Kasmari . Kirana, Heni Candra Kristhoporus Hadiono Kristianto, Taufik Fredy Kristiyono, Budi Kristophorus Hadiono Lie Liana Lie Liana . Minantri Haika, Shara Muh Kholid Rizky Sapawi Muhamad Riski Atarik Mulyani , Wahyu Sri Mulyo Budi Setiawan Munna, Aliyatul Muslikh, Ahmad Rofiqul Niken Puspitasari Nurmakhlufi, Alfin Ojugo, Arnold Adimabua Omar Farooq Palupi, Dian Perdana, Willy Yudha Prabowo, Ardian Adi Prihatin, Rudi Setyo Rachman, Rahadian Kristiyanto Raden Mohamad Herdian Bhakti Radyanto, Mohammad Riza Rahadiyanto, Cahyono Raharjo, Fajar Retnowati Rokhayadi, Wakhid Ruslana, Zauyik Nana Saputra, Roni Halim Saputro, Risky Wisnu Sariyun Naja Anwar Sarwo Edi, Sarwo Setyaningtyas, Elvanita Sri Mulyani Sugeng Murdowo Suhana Suhana Sulastri Sulastri Sulistiyowati Sulistiyowati Sunardi Sunardi Suprapto, Yossy SUTANTO, FELIX Syahroni Wahyu Iriananda, Syahroni Wahyu Teguh Khristianto Veronica Lusiana Vici Tiara Anjarsari Warto - Wijayanto, Wendhie Tri Wiratno, Amat Wismarini , Th. Dwiati Wiwien Hadi Kurniawati Yayi Suryo Prabandari Yoga Ryan Fatony Yoga Ryan Fatony