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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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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.
Analisis Seleksi Fitur untuk Optimasi Metode Klasifikasi k-NN pada Studi Kasus Penilaian Kinerja Karyawan Tangkawarow, Irene; Hostiadi, Dandy Pramana; Fatonah, Nenden Siti; Mohammad Yazdi; Hariyanti, Eva
Jurnal Sistem dan Informatika (JSI) Vol 18 No 1 (2023): Jurnal Sistem dan Informatika (JSI)
Publisher : Direktorat Penelitian,Pengabdian Masyarakat dan HKI - Institut Teknologi dan Bisnis (ITB) STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/jsi.v18i1.593

Abstract

Model Klasifikasi banyak digunakan dalam rangka menganalisis dan menemukan jenis kategori kelas data. Salah satu bentuk pemanfaatan metode klasifikasi adalah mengklasifikasikan hasil penilaian pengukuran kinerja karyawan. Metode klasifikasi yang umum dan dapat digunakan antara lain adalah metode Decision Tree, Naive Bayes, -NN dan Random Forest. Namun tidak semua metode dapat menghasilkan performa yang baik dalam penilaian kinerja Karyawan. Sehingga perlu dilakukan optimasi misalnya melalui penggunaan seleksi fitur. Beberapa penelitian telah dilakukan optimasi metode klasifikasi melalui penggunaan metode seleksi fitur dalam penilaian kinerja karyawan. Namun optimasi ini dipengaruhi oleh karakteristik data yang digunakan. Tidak semua teknik seleksi fitur sesuai untuk meningkatkan hasil klasifikasi dan jumlah penggunaan fitur dapat mempengaruhi performa model klasifikasi. Penelitian ini mengusulkan teknik analisis penggunaan jumlah fitur pada data kinerja dosen melalui metode seleksi fitur ANOVA untuk meningkatkan performa model klasifikasi metode -NN. Tujuannya adalah untuk mendapatkan jumlah fitur yang terbaik dalam peningkatan performa metode klasifikasi -NN. Hasil penelitian menunjukkan bahwa jumlah fitur terbaik dari metode ANOVA adalah sejumlah 5 fitur dengan hasil akurasi klasifikasi -NN sebesar 0.839, precision 0.8323, recall 0.839 dan F1-score 0.833. Teknik analisis ini dapat digunakan oleh sebuah perusahaan dalam mengutamakan fitur terbaik dalam menilai kualitas kinerja karyawannya.
Implementasi Data Mining untuk Prediksi Status Proses Persalinan pada Ibu Hamil Menggunakan Algoritma Naive Bayes Pusadan, Mohammad Yazdi; Ghifari, Ari; Anshori, Yusuf
Technomedia Journal Vol 8 No 1 Juni (2023): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v8i1.1980

Abstract

Childbirth is the process of taking out the fetus after 20 weeks of gestation or more to be able to live outside the uterus through the birth canal or another way, with or without assistance. Maternal Mortality Rate in Indonesia is still quite high based on the White Book of National Health System Reform in March 2022, at 305 for every 100.000 births. Causes of the high Maternal Mortality Rate is the risky of childbirth process for the mother and the baby. Clinical prediction is growing by adopting computer sience and information technology in data processing, accompanied by data mining methods for processing. The problem of pregnant mother can be anticipated by using the system for predicting the status of the childbirth process with the implementation of data mining and Naïve Bayes algorithm, with the purpose for helping to reduce Maternal Mortality Rate, especially caused by risky childbirth process. This study using 600 training data, then tested using the Confusion Matrix method on 100 testing data. Obtained Precision value was 82.4%, Recall value was 94%, F-Measure value was 88.7 and Accuracy value was 92%.
Design Thinking for Kami Peduli Website to Mobilize Community Disaster Response Nanda, Rifqi; Anggun Pratama, Septiano; Pusadan, Mohammad Yazdi; Anshori, Yusuf
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 6 No 1 (2024): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v6i1.677

Abstract

Central Sulawesi, particularly Palu City, is a disaster-prone area with communities lacking sufficient knowledge and preparation for natural disaster risks. This study aims to develop a sustainable digital platform that enhances community preparedness through a user-friendly and engaging website design. By applying the Design Thinking method, the platform integrates sustainable digital innovation to provide essential information on disaster-prone areas, volunteer opportunities, and donation channels. The platform’s design prioritizes efficient use of digital resources to minimize environmental impact, supporting long-term resilience and community mobilization. Utilizing both qualitative and quantitative approaches, data was gathered through questionnaires and interviews with PMI staff, volunteers, and the public. The Design Thinking stages: Empathize, Define, Ideate, Prototype, and Test, were employed to create a responsive and effective user experience. SEQ testing results revealed an average usability score of 4.25, highlighting the platform's ease of use. This project contributes to sustainable innovation in disaster preparedness by leveraging digital resources to empower communities in Central Sulawesi.
KLASIFKASI CURAH HUJAN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR (KNN) DI SULAWESI TENGAH Aldy, Moh.Fajrin Sigit; Angreni, Dwi Shinta; Pusadan, Mohammad Yazdi; Wirdayanti, Wirdayanti
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 4 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i4.5643

Abstract

Provinsi Sulawesi Tengah memiliki letak yang berdekatan dengan garis khatulistiwa, hal ini dapat mempengaruhi perubahan iklim didaerah tersebut salah satunya curah hujan. Perubahan curah hujan yang tidak menentu mengakibatkan timbulnya bencana seperti banjir yang dapat mempengaruhi gerak aktivitas masyarakat sehari-hari. Salah satu hal yang perlu dilakukan untuk mengantisipasi dengan prediksi cuaca. Pemanfaatan metode data mining dapat membantu dalam melakukan prediksi serta akurasi data dengan baik. Penelitian ini menggunakan dataset BMKG di Provinsi Sulawesi Tengah yang dikumpulkan dari 1 Januari 2019 sampai 31 Oktober 2023 serta klasifikasi dibagi menjadi 5 kelas menggunakan algoritma K-Nearest Neighbor (KNN). Tujuan penelitian ini memperoleh informasi dengan mengelompokkan data guna memprediksi curah hujan di BMKG Sulawesi Tengah. Hasil evaluasi menujukan bahwa nilai K = 23 dengan akurasi sebesar 83,0%, dan algoritma K-Nearest Neighbor (KNN) memiliki kinerja yang cukup baik dalam melakukan klasifikasi cuaca.
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 Usability Sistem Informasi Pengajuan Layanan Administrasi Dan Tugas Akhir Jurusan Teknologi Informasi Metode Heuristic Evaluation : Usability Analysis of Information System for Submission of Administrative Services and Final Assignment of Information Technology Department Heuristic Evaluation Method Mutia; Syahrullah; Kasim, Anita Ahmad; Pusadan, Mohammad Yazdi
Technomedia Journal Vol 9 No 2 Oktober (2024): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v9i2.2247

Abstract

ABSTRACT The administrative and final project service submission system is an information system that will be used at the Information Technology Department of Tadulako University in terms of carrying out the administrative process and final assignments for both lecturers, education staff, and students. SIPENDEKAR is designed for lecturers, education personnel, and students SIPENDEKAR is designed to integrate all administrative processes and final assignments. This research uses the heuristic evaluation method . The heuristic evaluation method is a method used to identify problems in the use of interface design, so that usability problems can be corrected through the redesign process. Through the application of Heuristic Evaluation, we can find obstacles and receive suggestions for improvement from experts based on usability principles that apply to websites that have 10 principles, namely Visibility of system status, Match between system and the real world, User control and freedom, Consistency and standards, Error Prevention, Recongnition rather than recall, Flexibility and efficiency of use, Aesthetic and minimalist design, Help users recognize, Dialogue, and recovers from errors, and Help and documentation. The questionnaire testing involved 37 respondents, the results of the validity and reliability test were declared valid and reliable.This research uses 6 research stages Identification of problems and literature studies, determination of evaluation methods, preparation for evaluation, and preparation for evaluation.
Pattern Recognition untuk Klasifikasi Penyakit Kanker Kulit menggunakan Artificial Intelligence (AI) Sari Handayani Pusadan; Suriyanti; Andriar Makahrun; Mohammad Yazdi; Zakiani Sakka
Jurnal Informatika dan Kesehatan Vol. 2 No. 1 (2025): IKN : Jurnal Informatika dan Kesehatan
Publisher : Universitas Ngudi Waluyo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35473/ikn.v2i1.3563

Abstract

This research aims to classify skin cancer images using an artificial intelligence method called Convolutional Neural Networks (CNN). The study focuses on classifying skin cancer into 7 categories, using data from the International Skin Imaging Collaboration (ISIC). We employed the CNN algorithm to train the model, which involved learning features, classifying images, and optimizing the model. To evaluate the model's performance, we experimented with different training data proportions (70%, 80%, and 90%), dropout rates (0.5, 0.6, 0.7, and 0.8), and batch sizes (8, 16, 32, 64). The best results were achieved with 80% of the data for training, a dropout rate of 0.4, and a batch size of 16, resulting in an accuracy of 83.22%.   ABSTRAK Penelitian ini bertujuan untuk mengimplementasikan metode kecerdasan buatan melalui algoritma Convolution Neural Network (C-NN) untuk mengklasifikasikan citra kanker kulit. Objek pada penelitian ini adalah klasifikasi kanker kulit dengan berdasarkan 7 kategori kanker kulit, sedangkan Data yang digunakan oleh peneliti adalah data  yang bersumber dari The International Skin Imaging Collaboration (ISIC). Metode yang digunakan peneliti adalah Algoritma Convolutional Neural Networks (CNN). Pada data training dilakukan pembelajaran fitur, klasifikasi, dan optimum model, dimana proses ini merupakan implementasi algoritma yang digunakan. Skenario pengujian dengan indikator skenario pengujian yaitu pembagian data training 70%, 80%, dan 90%, inisialisasi Dropout layer bernilai 0.5, 0.6, dan 0.7, dan 0,8 dan Batchsize bernilai 8, 16, 32, 64. Kesimpulan dari Penelitian ini adalah mendapatkan model terbaik dengan nilai akurasi 83.22% dari komposisi  data Taining 80%, Dropout 0.4 dan Batchsize 16.
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%
Implementation of QR Code in A Student Attendance Information Based On WhatsApp Gateway Karnita Sumbaluwu, Harlin Feby; Angreni, Dwi Shinta; Pusadan, Mohammad Yazdi; Lamasitudju, Chairunnisa; Lapatta, Nouval Trezandy
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6308

Abstract

The attendance information system at Senior High School 7 Sigi, still uses a manual attendance system, namely writing on paper sheets. The problem that often occurs is the loss of student attendance books which causes the school to have difficulty in recapitulating attendance and also reporting attendance to parents. Another problem that occurs due to manual attendance is that parents cannot directly monitor their children's attendance at school which causes some students to skip school. The recommended solution is to use an attendance information system by utilizing QR Code technology so that student attendance is more practical and also the data storage is much safer. WhatsApp Gateway is used as a monitoring medium for parents because this system will send notifications via the WhatsApp application every time the lesson starts, effectively and in real-time. This attendance system uses the Waterfall method which starts from the planning, analysis, design and implementation stages
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