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All Journal JURNAL SISTEM INFORMASI BISNIS Telematika : Jurnal Informatika dan Teknologi Informasi SemanTIK : Teknik Informasi Prosiding Seminar Nasional Riset Kuantitatif Terapan 2017 Indonesian Journal of Electrical Engineering and Computer Science Jurnal Pengabdian Masyarakat Ilmu Terapan (JPMIT) Jurnal Sains dan Teknologi
Jumadil Nangi, Jumadil
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering

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PENERAPAN METODE BM25 PADA SISTEM REKOMENDASI DOSEN PEMBIMBING DAN PENGUJI TUGAS AKHIR MAHASISWA BERBASIS WEB Safril, Safril; Golok Jaya, La Ode Muhammad; Nangi, Jumadil
SemanTIK : Teknik Informasi Vol 7, No 1 (2021): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (595.164 KB) | DOI: 10.55679/semantik.v7i1.12562

Abstract

Tugas akhir merupakan salah satu mata kuliah yang harus ditempuh oleh seorang mahasiswa untuk memperoleh gelar sarjananya. Dalam menyelesaikan tugas akhir, biasanya mahasiswa telah ditentukan dosen pembimbing dan pengujinya oleh Ketua Jurusan. Dalam proses penentuan dosen pembimbing dan penguji di Jurusan Teknik Informatika Universitas Halu Oleo masih menggunakan cara konvensional dengan mengandalkan pengetahuan pribadi tentang spesifikasi keahlian dosen yang sesuai dengan topik tugas akhir mahasiswa. Penerapan metode BM25 (Best Match 25) sangat cocok digunakan untuk merekomendasikan dosen pembimbing dan penguji tugas akhir mahasiswa karena efektif dan memiliki ketepatan dalam mengurutkan dokumen berdasarkan query yang dicari. Pada hasil uji perbandingan penentuan dosen pembimbing dan penguji tanpa menggunakan sistem dan dengan menggunakan sistem diperoleh akurasi sebesar 58%.Kata kunci; BM25, Rekomendasi Dosen Pembimbing dan Penguji
WHAT DO USERS WRITE IN ONE FILE CABINET DATABASES: AN ANALYSIS BASED ON TEXT MINING Ransi, Natalis; Surimi, La; Nangi, Jumadil; Sajiah, Adha Mashur; Arman, Arman; Cahyono, Edi
SemanTIK : Teknik Informasi Vol 7, No 1 (2021): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (535.822 KB) | DOI: 10.55679/semantik.v7i1.15263

Abstract

One file cabinet adalah sistem terintegrasi yang salah satu fungsinya untuk merekam catatan kerja (logbook) dosen dan tenaga kependidikan di Universitas Halu Oleo. Dalam logbook, setiap hari kerja dosen dan tenaga kependidikan menuliskan deskripsi kerja yang telah mereka lakukan dalam sistem database. Artikel ini membahas analisis kumpulan kata-kata yang dituliskan oleh dosen dan tenaga kependidikan pada logbook mereka. Metode yang digunakan adalah penambangan teks kata-kata (text mining). Hasil analisis diperlukan oleh pimpinan (top managers) Universitas Halu Oleo dalam memperoleh gambaran global kinerja dosen dan tenaga kependidikan. Informasi ini penting untuk menentukan kebijakan dalam pengembangan sumber daya manusia.Kata kunci; Database, Logbook, One File Cabinet, Sumber Daya Manusia, Text Mining
Classification of apple maturity based on color using the K-Nearest Neighboor (KNN) method Fa, Nur; Saputra, Rizal Adi; Nangi, Jumadil
Telematika Vol 21, No 1 (2024): Edisi Februari 2024
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v21i1.11773

Abstract

Purpose: The aim of this research is to provide support to apple fans and farmers in determining the choice of fruit that is ripe and ready to be consumed, using indicators of outer skin color as a basis for classification.Design/methodology/approach: The approach uses the K-Nearest Neighbor (KNN) method to classify the level of ripeness of apples based on skin color. KNN is used as a classification method. This approach utilizes the similarity of skin color with training data to determine the level of maturity. The evaluation results showed an accuracy of 90%, making it an effective approach for identifying the ripeness level of apples.Findings/result: From the results of the system evaluation of 206, it shows an accuracy level of 90% with a sensitivity of 80% and a specificity of 67% as measured by the Hold Out Estimation model.Originality/value/state of the art: This research uses test data/testing data originating from Kaggle and Google as well as several photos taken directly. In total, 206 images of apples were used.
Classification of apple maturity based on color using the K-Nearest Neighboor (KNN) method Fa, Nur; Saputra, Rizal Adi; Nangi, Jumadil
Telematika Vol 21 No 1 (2024): Edisi Pertama 2024
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v21i1.11773

Abstract

Purpose: The aim of this research is to provide support to apple fans and farmers in determining the choice of fruit that is ripe and ready to be consumed, using indicators of outer skin color as a basis for classification.Design/methodology/approach: The approach uses the K-Nearest Neighbor (KNN) method to classify the level of ripeness of apples based on skin color. KNN is used as a classification method. This approach utilizes the similarity of skin color with training data to determine the level of maturity. The evaluation results showed an accuracy of 90%, making it an effective approach for identifying the ripeness level of apples.Findings/result: From the results of the system evaluation of 206, it shows an accuracy level of 90% with a sensitivity of 80% and a specificity of 67% as measured by the Hold Out Estimation model.Originality/value/state of the art: This research uses test data/testing data originating from Kaggle and Google as well as several photos taken directly. In total, 206 images of apples were used.
Ensuring transcript integrity with SHA-3 and digital signature standard: a practical approach Nur Alam, Wa Ode Siti; Sajiah, Adha Mashur; Bahtiar Aksara, La Ode Muhammad; Surimi, La; Ransi, Natalis; Nangi, Jumadil
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp1957-1969

Abstract

Academic transcripts are essential documents in higher education, reflecting students’ academic performance and capabilities. However, the current management of transcript data at Halu Oleo University (UHO) lacks safeguards against unauthorized alterations, compromising their authenticity. This study proposes a method using the secure hash algorithm 3 (SHA-3) and the digital signature standard (DSS) scheme to ensure the integrity of transcript data. A Python-based web module for managing transcripts and a signing program using SHA-3 and DSS were developed and implemented. This method digitally signs transcript files, ensuring that subsequent changes invalidate the current digital signature. Efficiency tests demonstrated an average signing time of 0.242 seconds, indicating a practical and efficient solution. The study’s findings emphasize how SHA-3 and DSS effectively authenticate academic transcript files, preventing unauthorized modifications and safeguarding the integrity of critical educational records. This method presents a robust and efficient solution for educational institutions to strengthen the security and reliability of their academic record management systems.
Pemetaan Geospasial Panti Sosial di Kota Kendari Berbasis Sistem Informasi Geografis (SIG) Mashaf, Salsabila; Fadillah, Nur; Wulandari, Suci; Naisyarah, Wifna; Nangi, Jumadil
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 2 (2025): Mei - Agustus
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i2.3338

Abstract

The city of Kendari is home to various social institutions such as orphanages and nursing homes that require support fromthe community and attention from the government. However, limited information regarding the locations and supportingdata of these social institutions often poses challenges in the distribution of aid and the formulation of social policydecisions. This study aims to develop a web-based Geographic Information System (GIS) that visually and informativelymaps the distribution of social institutions in Kendari. The methods employed include literature review, needs analysis,system design, implementation, and testing. The system is developed using PHP for the backend, Leaflet.js for interactivemap visualization, and MySQL as the database. The data used consist of spatial data in the form of geographiccoordinates and non-spatial data such as institution names, categories, addresses, contact details, and social mediaaccounts. The testing technique applied is black box testing to evaluate key system functionalities, including map display,location search, data management by administrators, and interface reliability. The results show that the systemsuccessfully displays an interactive digital map with informative location icons and supports data operations such as add,edit, and delete through an admin interface. This system is expected to serve as an effective information tool for the public,volunteers, and authorities in accessing and managing social institution data efficiently and transparently.
Perbandingan Algoritma Winnowing dan Algoritma Rabin-Karp pada Aplikasi Pendeteksi Kesamaan Dokumen Skripsi Nangi, Jumadil; Asmara, Ida Bagus Gede Pala; Sarita, Muh. Ihsan; Jaya, Laode Muh. Golok; Mokui, Hasmina Tari; Tajidun, LM
Jurnal Sistem Informasi Bisnis Vol 14, No 2 (2024): Volume 14 Nomor 2 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss2pp131-142

Abstract

Plagiarism is often found in the academic world and is considered a serious violation because it involves the appropriation of ideas, opinions, or writings of others. A thesis is the final work of a student that must meet scientific standards and be tailored to the field of study. It is important to check the similarity of the thesis using a web-based sistem to prevent plagiarism and ensure academic integrity. This sistem will be developed as a web-based platform with the aim of comparing the Winnowing algorithm and the Rabin-Karp algorithm in checking the similarity of thesis/final project texts with existing thesis data. In principle, both methods involve searching for strings using hashing functions to compare the sought string (m) with the compared string (n) by comparing the results of the hashing function used. However, the Winnowing algorithm differs in that it does not use all hash values from each formed set of grams. The hash values formed in the previous stage will be divided into a window of size (w). In this research, the sistem testing uses data from Computer Engineering students at Halu Oleo University to facilitate checking the plagiarism level of theses using the Rabin-Karp and Winnowing algorithms. In this study, the Rabin-Karp and Winnowing algorithms have been implemented successfully in the plagiarism checking sistem for students' theses. The test results for the comparison of the Winnowing and Rabin-Karp algorithms in terms of processing time show that the Rabin-Karp algorithm takes 1.509 seconds, while the Winnowing algorithm takes 1.508 seconds. Subsequent testing using Normalized Mean Absolute Error (NMAE) reveals that the Rabin-Karp algorithm has an absolute error value of 0.1829, while the Winnowing algorithm has a value of 0.0194. Therefore, based on the NMAE test, the Winnowing algorithm performs better than the Rabin-Karp algorithm.
Co-Authors Akbar Nurdin, Akbar Aksara, L. M Fid Aksara, L. M. Fid Arman Arman ARMAN FASLIH, ARMAN Asmara, Ida Bagus Gede Pala Bahtiar Aksara, La Ode Muhammad Bambang Pramono Edi Cahyono Fa, Nur Golok Jaya, La Ode Muhammad Halim Halim, Halim Hamid, Annisa Fitri Hasmina Tari Mokui Hidayat, Adnan Ikhsan, Ainussalbi Al Ilayani, Ilayani Jaya, La Ode Muhammad Golok Jaya, Siti Nawal Jaya, St. Nawal La Aba La Surimi, La Laode Muhamad Tajidun LM Fid Aksara, LM Fid LM Tajidun, LM Mashaf, Salsabila Muh. Ihsan Sarita, Muh. Ihsan Muhammad Zakaria Umar, Muhammad Zakaria Naisyarah, Wifna Nasser, Gamal Abdel Natalis Ransi, Natalis NINGSIH, NINGSIH Nur Fadillah, Nur Prajono, Rahmat Purnama, Ika Purwanti Ningrum Rahmat Purnomo, Rahmat Rizal Adi Saputra Safril Safril Sajiah, Adha Mashur Suci Wulandari Sutardi Sutardi Syahabuddin, Syahabuddin Wa Ode Siti Nur Alam Yuwanda Purnamasari Pasrun