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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Informasi dan Teknologi Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Majalah Ilmiah UPI YPTK Journal Of Human And Education (JAHE) Journal of Vocational Education and Information Technology (JVEIT) J-Icon : Jurnal Komputer dan Informatika JOURNAL OF COMMUNITY SERVICE AND APPLICATION SCIENCE (JCSAS) JCSE: Journal of Community Service and Empowerment Marsipature Hutanabe: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Dan Sistem Informasi Bisnis
Yofhanda Septi Eirlangga
Universitas Adzkia
Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences Other

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SISTEM PAKAR DALAM MENENTUKAN KENAIKAN PANGKAT ANGGOTA POLRI MENGGUNAKAN METODE FORWARD CHAINING Devi Gusmita; Yofhanda Septi Eirlangga; Sopi Sapriadi
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 6 No. 1 (2023): February 2023
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v6i1.1194

Abstract

Abstract: This research has been done research on the promotion of the rank of POLRI Members in this process is essentially the examination of the requirements for the proposed promotion of members of POLRI. this research is done design and manufacture of expert systems based rules (Rule Based) to help calculation requirements in the process determination of promotion in the process of appointing the promotion of members of POLRI. The inference method used is forward chaining where the tracking starts from the destination ie the type of the intended rank, then sought the rules of conditions that have tujua it for the conclusion. Tests conducted on this expert system include testing of police data that has prepared the requirements for the promotion process. The results of this study are expected to provide solutions and ease along with accurate information in the process of determining the promotion of members of POLRI Keywords: Expert system; forward chaining; promotion; rule based. Abstrak: Pada penelitian ini berisi tentang kenaikan pangkat Anggota POLRI yang proses intinya adalah pemeriksaan syarat-syarat untuk usulan kenaikan pangkat anggota POLRI. Dalam penelitian ini dilakukan perancangan dan pembuatan sistem pakar berbasiskan aturan(Rule Based) untuk membantu perhitungan syarat-syarat dalam proses penetuan kenaikan pangkat anggota POLRI. Metode inferensi yang digunakan adalah forward chaining dimana pelacakan dimulai dari tujuan yaitu jenis pangkat yang dituju, selanjutnya dicari aturan syarat-syarat yang memiliki tujuan tersebut untuk kesimpulannya. Pengujian yang dilakukan pada sistem pakar ini meliputi pengujian terhadap data polisi yang telah mempersiapkan syarat-syarat untuk proses kenaikan pangkat.Hasil dari penelitian ini diharapkan mampu memberikan solusi dan kemudahan beserta informasi yang akurat dalam proses penentuan kenaikan pangkat anggota POLRI. Kata kunci: Sistem pakar; Forward Chaining; kenaikan pangkat; Rule Based 
Analisis Sentimen Ulasan Pengguna Aplikasi Shopee Indonesia Menggunakan Algoritma Random Forest Sopi Sapriadi; Rahmatia Wulan Dari; Yofhanda Septi Eirlangga
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol. 8 No. 3 (2026): Juli 2026
Publisher :  Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v8i3.142

Abstract

Shopee is one of the most widely used e-commerce applications in Indonesia, and the reviews written by its users on the Google Play Store contain valuable information about service quality, application performance, and customer satisfaction. This study aims to classify the sentiment of Indonesian-language reviews of the Shopee application using the Random Forest algorithm. A total of 5,000 reviews were collected through web scraping, labeled based on user ratings, and processed through cleaning, case folding, slang-word normalization, tokenization, stopword removal, and stemming. Feature extraction was performed using Term Frequency-Inverse Document Frequency (TF-IDF), and the Synthetic Minority Over-sampling Technique (SMOTE) was applied to handle class imbalance in the training data. The experimental results show that the best Random Forest model, with 200 trees, achieves an accuracy of 89.34%, a precision of 89.40%, a recall of 88.30%, and an F1-score of 88.75%, outperforming Naive Bayes, Support Vector Machine, and K-Nearest Neighbor as comparison models. The analysis of feature importance shows that positive sentiment is dominated by words related to delivery speed and price, while negative sentiment is dominated by complaints about system errors, sellers, and refund processes. These findings can be used by application managers to prioritize service improvements.
Co-Authors Aldo Eko Syaputra Alima Shofia Ashim Madani, Muhammad Dari, Rahmatia Wulan Devi Gusmita Fajar Maulana Hariani Manurung, Kiki Hayati , Nova Hayati, Nova Hendra, Yomei Kiki Hariani Manurung Kiki Hariani Manurung Manurung, Kiki Hariani Maulana, Fajar Mufid, Muhammad Fauzan Muhammad Fauzan Mufid Muhammad Thoriq MUHAMMAD THORIQ Nurul Hasanah Prima, Wahyu Rahmadhani, Firda Ranti Mustika Putri Sapriadi, Sopi Silky Selfira Sopi Sapriadi Sopi Sapriadi Thoriq, Muhammad Ulya Mega Wahyuni Yomei Hendra