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All Journal Jurnal Sistem Informasi dan Ilmu Komputer Jurnal Kendali Teknik dan Sains
Achmad Faris Fadhlulah
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Computer Science & IT

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Sistem Temu Balik Informasi Data Penerima Bantuan PIP pada Sekolah Menengah Pertama Menggunakan Metode TF-IDF Achmad Faris Fadhlulah; Dika Arif Sihombing; Muhammad Fahri Rinanda; Rizki Riandi; Sotar Ferdinand Hutabarat
Jurnal Kendali Teknik dan Sains Vol. 4 No. 1 (2026): Januari: Jurnal Kendali Teknik dan Sains
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jkts-widyakarya.v4i1.5875

Abstract

The Indonesia Smart Program (Program Indonesia Pintar/PIP) is a government initiative aimed at ensuring equal access to education for students from underprivileged families, including those at the junior high school (SMP) level. However, at the school level, the management of PIP recipient data still faces several challenges, particularly in data searching and utilization, due to the increasing volume of data and the use of simple or manual search methods. These conditions can lead to delays in obtaining information and reduce the accuracy of decision-making. Therefore, an effective information retrieval system is needed to manage and search PIP recipient data efficiently. This study aims to design and develop an Information Retrieval System for PIP recipient data at the junior high school level using the Term Frequency–Inverse Document Frequency (TF-IDF) method. The TF-IDF method is applied to assign weights to terms in each document, enabling the system to identify and rank documents based on their relevance to user queries. The test results show that the system is able to measure document relevance accurately, where documents D3 and D4 obtain the highest similarity value of 0.099586089 and are classified as highly relevant, while other documents show lower similarity values down to zero. These results are also supported by graphical visualization, which helps users compare relevance levels more clearly. Thus, the implementation of the TF-IDF method has proven to be effective in supporting accurate, efficient, and systematic searching and management of PIP recipient data at the junior high school level.
Diagnosa penyakit Gangguan Saraf Tepi (Neuropati Perifer) menggunakan Metode Certainty Factor Achmad Faris Fadhlulah; Siswan Syahputra; Ratih Puspadini
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 4 No. 3 (2026): Agustus: Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v4i3.6665

Abstract

Peripheral neuropathy is a disorder of the peripheral nerves that can cause sensory, motor, and autonomic disturbances, as well as weakened tendon reflexes. Common early symptoms include numbness, tingling, pain, and a burning sensation, which are often more pronounced at night. Because the symptoms are nonspecific, peripheral neuropathy is often considered a minor complaint, resulting in delayed medical examination. This condition can increase the risk of complications, such as chronic wounds, balance disorders, and impaired limb function. The current problem is that the identification of peripheral neuropathy still relies heavily on the clinical experience of doctors and supporting examination results; therefore, a system is needed to assist the diagnosis process systematically and consistently. This study aims to develop an expert system for diagnosing peripheral neuropathy based on patients’ symptoms using the certainty factor method. The Certainty Factor method is used to determine the level of confidence in a diagnosis based on a combination of expert and user confidence values for the selected symptoms. The system also provides information about the disease and initial treatment recommendations to support the decision-making process. Based on the test results, the highest Certainty Factor value was obtained for Mononeuropathy, with a value of 0.9707 or 97.07%. This value indicates a high level of confidence in the diagnosis based on the symptoms entered. Therefore, the developed expert system is expected to assist in identifying peripheral neuropathy more quickly, consistently, and effectively, while supporting early detection so that appropriate treatment can be provided.
Co-Authors Dika Arif Sihombing Muhammad Fahri Rinanda Ratih Puspadini Rizki Riandi Siswan Syahputra Sotar Ferdinand Hutabarat