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All Journal Foristek Semantik International Journal of Advances in Intelligent Informatics Jurnal Sistem dan Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL ILMIAH MATEMATIKA DAN TERAPAN JOURNAL OF APPLIED INFORMATICS AND COMPUTING Technomedia Journal Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Indonesian Journal of Electrical Engineering and Computer Science IAIC Transactions on Sustainable Digital Innovation (ITSDI) Advance Sustainable Science, Engineering and Technology (ASSET) Jurnal Abmas Negeri (JAGRI) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Algoritma The Indonesian Journal of Computer Science Jurnal Informatika dan Kesehatan Bomba: Jurnal Pembangunan Daerah
Mohammad Yazdi Pusadan
Program Studi Teknik Informatika, Universitas Tadulako, Palu, Indonesia
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Public Health Social Sciences Transportation Veterinary Other

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Journal : the indonesian journal of computer science

 1 
Sistem Informasi Harga Bahan Pokok Dinas Perdagangan dan Perindustrian Kota Palu Nursalim, Moh. Agung; Chairunnisa Ar Lamasitudju; Miftah; Wirdayanti; Mohammad Yazdi Pusadan; Rahmah Laila
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.3937

Abstract

Pasar tradisional Indonesia sangat penting bagi perekonomian, terutama bagi pedagang kecil dan komunitas yang bergantung pada perdagangan sebagai sumber pendapatan mereka. Namun, masalah seperti pergeseran demografi, kemajuan teknologi, dan kurangnya transparansi harga telah mengganggu stabilitas pasar tradisional. Artikel ini menunjukkan betapa pentingnya sistem informasi harga bahan pokok untuk mengelola harga dan mencegah inflasi. Studi ini bertujuan untuk membangun sistem informasi yang disebut GadeMart yang akan melacak perubahan harga di dua pasar tradisional terbesar Kota Palu: Pasar Inpres Manonda dan Pasar Masomba. Diharapkan bahwa penelitian ini akan menawarkan solusi untuk meningkatkan stabilitas ekonomi dan transparansi harga di pasar tradisional.
Implementasi Face Recognition Pada Aplikasi Absensi Berbasis Android Menggunakan Algoritma Haversine Siddiq Assegaf, Djafar; Azhar, Ryfial; Pusadan, Yazdi; Anggun Pratama, Septiano; AR. Lamasitudju, Charunnisa
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4494

Abstract

Android-Based Attendance Application, Face Recognation, Haversine Algorithm, Management System. The attendance system is a method for managing employee presence, which contributes to productivity and accountability. This study aims to implement an Android-based attendance application that utilizes face recognition technology and the Haversine algorithm to enhance the accuracy and efficiency of the attendance process. Face recognition is applied to automatically verify user identity and reduce the risk of fraud in the attendance process. The system integrates the Haversine algorithm and face recognition, where the Haversine algorithm is used to calculate the distance between the employee's location and the office, ensuring that attendance can only be recorded within a predetermined radius. The results indicate that this system is effective in determining employee attendance status with high accuracy, recording employees within a radius of ≤ 30 meters as present. Additionally, the use of face recognition technology accelerates the attendance process and improves accountability. These findings open opportunities for further research in integrating technology into human resource management and are expected to enhance transparency and efficiency in managing employee attendance across various sectors.
Analisis Sentimen Terhadap Presiden Terpilih Dimedia Sosial Twitter (X) Menggunakan Algoritma Support Vector Machine Ono, Jumaita; Anshori , Yusuf; Yudhaswana Joefrie , Yuri; Yazdi Pusadan, Mohammad; Syahrullah
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4388

Abstract

The current elected presidents of Indonesia are Prabowo and Gibran, with several work programs and visions and missions that are still being discussed on various social media, especially on Twitter. Based on the problems in this research, the Support Vector Machine method was applied with the dataset used amounting to 2000 data obtained from Twitter social media using scraping techniques, and divided into five scenarios, namely positive, very positive, neutral, negative and very negative. Data were tested from 100 datasets, 500 datasets, 1000 datasets, 1500 datasets, and 2000 datasets. The accuracy results obtained from 100 data were 0.40% accuracy, 0.08% precision, and 0.20% recall. The second test used 500 data with an accuracy of 0.67%, precision of 0.33% and recall of 0.24%. The third test used 1000 data with an accuracy of 0.73%, precision of 0.52% and recall of 0.29%. The fourth test used 1500 data with an accuracy of 0.74%, precision of 0.41% and recall of 0.29%. The fifth test with the highest level of accuracy uses 2000 data, with an accuracy of 0.75%, precision of 0.47%, and recall of 0.30%
Digitalisasi Pembelajaran Budaya Sulawesi Tengah melalui Augmented Reality Menggunakan Metode Marker-Based Tracking Saleh, Muhammad Taufik; Lamasitudju, Chairunnisa Ar.; Pusadan, Yazdi; Laila, Rahmah; Pratama, Septiano Anggun
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4195

Abstract

Central Sulawesi has a diverse cultural heritage, but the rapid development of technology poses new challenges in maintaining the interest of the younger generation in local culture. This research developed a culture-learning application based on Augmented Reality (AR) using the Marker Based Tracking method for students at SDN Inpres 2 Tanamodindi to address these challenges. The application, "Mari Berbudaya," is designed to increase students' interest in local culture by providing an interactive and innovative learning experience through AR technology. This study employs a qualitative approach and prototyping method. Black box testing results confirm that all main functions of the application work well, while distance testing shows that markers can be optimally detected up to a distance of 1 meter. A questionnaire evaluation of the students resulted in an overall score of 89% with a classification of very feasible. Thus, from the overall evaluation, the "Mari Berbudaya" application has proven effective in increasing students' interest and understanding of Central Sulawesi's culture through AR technology.
Perbandingan Algoritma Naïve bayes Dan Support Vektor Machine Untuk Klasifikasi Status Stunting Pada Balita Muh. Faried Muchtar; Rahma Laila; Dwi Shinta; H. M. Yazdi Pusadan
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4055

Abstract

Penelitian ini bertujuan untuk membandingkan efektivitas algoritma Naïve Bayes dan Support Vector Machine (SVM) dalam klasifikasi status stunting pada balita. Stunting merupakan kondisi pertumbuhan terhambat pada balita akibat kekurangan gizi yang memiliki dampak serius terhadap kesehatan dan perkembangan anak. Dengan menggunakan data dari Puskesmas Tawaeli Kecamatan Tawaeli, penelitian ini mengimplementasikan kedua algoritma untuk mengidentifikasi balita yang mengalami stunting. Metode penelitian meliputi pengumpulan data, preprocessing, dan pengujian menggunakan metrik evaluasi yang sesuai. Hasil penelitian diharapkan dapat memberikan kontribusi dalam pengembangan metode klasifikasi stunting pada balita serta memberikan wawasan baru dalam penanganan masalah stunting pada tingkat populasi. Diharapkan penelitian ini dapat menjadi referensi bagi peneliti selanjutnya dalam pengembangan sistem informasi serupa.
Co-Authors Ahmad Imam Abdullah Aldy, Moh.Fajrin Sigit Amriana Andi Hendra Andriar Makahrun Anisa Yulandari Anita Ahmad Kasim AR. Lamasitudju, Charunnisa Buliali, Joko Lianto Dandy Pramana Hostiadi Dessy Santi Dwi Shinta Dwi Shinta Angreni Dwiwijaya, Kadek Agus Eva Hariyanti Fahmi, Moh. Fatonah, Nenden Siti Fuad Mahfud Ghifari, Ari Ginardi, Raden Venantius Hari Gunawan Feri Handono Hajra Rasmita Ngemba Handono, Gunawan Feri Indah Safitri Irene Realyta Halldy Trosi Tangkawarow JULIAN WITJAKSONO Karnita Sumbaluwu, Harlin Feby Kasaedja, Tafania Natalia Laila, Rahma Lamadjido, Moh. Raihan Dirga Putra Lamasitudju, Chairunnisa Magfirah, Magfirah Merry Miftah Miftah, Miftah Muh. Faried Muchtar Mutia Nanda, Rifqi Nouval Trezandy Lapatta Nursalim, Moh. Agung Nursiana Zasqia, Andi Nirina Ono, Jumaita Paloloang, Muhammad Fadhil Akmal B. Pramadinda, Alda Nur Pratama, Moh. Rezki Putra, Ryan Adi Rahma Laila Rahmah Laila Reonaldi, Muh. Ilham Rifki, Moh Rizka Ardiansyah Rumampuk, Viola Gracella Ryfial Azhar Sabarudin Saputra Sahrullah Sahrullah Saleh, Muhammad Taufik Sani, Ilham Abdillah Sari Handayani Pusadan Sasuwuk, James Rio Septiano Anggun Pratama Siddiq Assegaf, Djafar Sondakh, Clivent Gerhard Suriyanti Syahrullah Syahrullah Syahrullah Therry, Alvin Christian Davidson Wirdayanti Yulianti, Indira Yuri Yudhaswana Joefrie Yusuf Anshori Zakiani Sakka