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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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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 (IJCS)
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
Pengenalan Batik Bomba Menggunakan Teknologi Augmented Reality Dengan Metode Markerless Berbasis Android Kasaedja, Tafania Natalia; Kasim, Anita Ahmad; Pusadan, Mohammad Yazdi; Syahrullah, Syahrullah; Laila, Rahmah
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.v10i2.6128

Abstract

Batik Bomba merupakan kain tradisional khas suku Kaili yang menjadi salah satu kekayaan Sulawesi Tengah. Motif dan pola batik Bomba memiliki bentuk yang unik, dengan makna filosofis yang berlandaskan kehidupan masyarakat suku Kaili yang tersirat didalamnya. Namun pemahaman tentang ragam motif batik Bomba belum dikenal luas oleh masyarakat Sulawesi Tengah khususnya Kota Palu. Hal ini disebabkan karena media informasi untuk visualisasi kain batik Bomba masih kurang, umumnya hanya berbentuk gambar 2D yang dapat ditemui di museum atau pameran seni. Dari permasalahan tersebut, penulis bertujuan untuk memberikan informasi kepada masyarakat lokal maupun masyarakat luar mengenai filosofi motif batik Bomba secara detail dan mudah dipahami dengan memanfaatkan media teknologi Augmented Reality menggunakan metode markerless yang menampilkan objek 3D batik Bomba. Dalam pengembangan aplikasi, penulis menggunakan metode agile Extreme Programming (XP) yang akan diimplementasikan kedalam aplikasi berbasis android. Diperoleh hasil analisis pengujian menggunakan metode Blackbox Testing yang dilakukan oleh develop, dan User Acceptance Testing (UAT) melalui kuesioner yang dibagikan kepada pengguna aplikasi, bahwa aplikasi yang dikembangkan berjalan sesuai dengan fungsionalitasnya dan memperoleh skor rata-rata 107,25 (Sangat Memuaskan). Dengan demikian, aplikasi AR About Bomba dapat menjadi mediator pengenalan filosofi setiap motif batik Bomba.
Pemodelan Arsitektur Enterprise Menggunakan Standar Togaf di SPBE Kabupaten Parigi Moutong: Enterprise Architecture Modeling Using Togaf Standards at SPBE Parigi Moutong Regency Pramadinda, Alda Nur; Dwiwijaya, Kadek Agus; Syahrullah, Syahrullah; Lamasitudju, Chairunnisa Ar.; Pusadan, Yazdi
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2262

Abstract

The rapid advancement of technology has raised public expectations for easy access to government services and information. In response, the Parigi Moutong District Government has implemented the Electronic-Based Government System (SPBE) with an SPBE index of 2.68, indicating that the system has been well implemented. This study employs the Enterprise Architecture (EA)methodology, based on the TOGAF ADM, with a focus on the infrastructure domain to enhance efficiency, security, and integration within SPBE. The study involves the stages of preparation, data collection, analysis, design, finalization, and validation. The identified gap is that, despite the successful implementation of SPBE, the integration of modern technologies such as AI and blockchain to strengthen security and efficiency has not yet been fully optimized. The novelty of this research lies in the integration of advanced technologies in the Enterprise Architecture blueprint for SPBE, as well as the implementation of pilot testing to evaluate the alignment of the application with real-world conditions. The research aims to develop a comprehensive blueprint offering infrastructure improvement solutions for the Parigi Moutong District Government. The results show that TOGAF ADM successfully improves system integration, bureaucratic efficiency, and public service quality. The conclusion emphasizes the importance of adjusting technology to suit local conditions and needs when applying it to other regions.  
The Image Extraction Using the HSV Method to Determine the Maturity Level of Palm Oil Fruit with the k-nearest Neighbor Algorithm Mohammad Yazdi Pusadan; Indah Safitri; Wirdayanti
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 6 (2023): December 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i6.5558

Abstract

The oil palm is one of the monocot oil-producing plants in Indonesia. Sorting errors in oil palm fruit are caused by a sorter error when distinguishing the color of ripe and immature oil palm fruit. In addition to inefficient time, the area of oil palm plantations is also a factor that causes the sorter to make mistakes in sorting. This study aims to produce a system that can classify the maturity of oil palms based on feature extraction of characteristics of the hue, saturation and value (HSV) color features. The HSV method is used to produce color characteristics from the image of the oil palm fruit. Classification of oil palm fruit maturity is classified using the K-Nearest Neighbor (KNN) algorithm with a dataset of 400 oil palm fruit image data with a data sharing ratio of 70% training data and 30% test data. 280 image data were used as training data, divided into 140 image data of ripe oil palm fruit, 140 image data of immature oil palm fruit and 120 image data of oil palm used as test data which is divided into 60 image data of ripe oil palm and 45 unripe palm oil. Based on the result of tests that have been carried out using a confusion matrix with varied k values, namely, 5 and 7, the average precision is 94.16%.
Utilization of EfficientNet-B0 to Identify Oncomelania Hupensis Lindoensis as a Schistosomiasis Host Lamadjido, Moh. Raihan Dirga Putra; Laila, Rahmah; Pusadan, Mohammad Yazdi; Yudhaswana, Yuri; Lapatta, Nouval Trezandy; Ngemba, Hajra Rasmita
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9058

Abstract

Schistosomiasis caused by the Schistosoma japonicum worm is a significant health problem in Indonesia, especially in endemic areas such as the Napu Plateau and Bada Plateau. The main problem in controlling this disease is the difficulty in rapid and accurate identification of Oncomelania hupensis lindoensis snails as intermediate hosts of the parasite. This research aims to develop an artificial intelligence-based system that can efficiently identify the snail species. The stages of this research include collecting snail image data from the Central Sulawesi Provincial Health Office, consisting of 2100 images covering seven snail species, then processed through preprocessing and augmentation stages. The model applied was EfficientNet-B0. The results showed that the EfficientNet-B0 model achieved 98.80% training accuracy and 98.33% validation accuracy. Confusion matrix testing showed good performance, with an accuracy of 98% and for the species Oncomelania hupensis lindoensis had a recall of 93%, precision of 100%, F1-score of 97%, and the resulting AUC value of 99.7%. This research successfully developed an efficient identification system, which is expected to help health surveillance personnel in accelerating the identification process of schistosomiasis intermediate hosts.
KLASIFIKASI JENIS BATIK BOMBA MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DENGAN ARSITEKTUR EFFICIENT-NET B2 (BATIK BOMBA SULAWESI TENGAH ) Witjaksono, Julian; Pusadan, Mohammad Yazdi; Anshori, Yusuf; Ardiansyah, Rizka; Azhar, Ryfial
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.6191

Abstract

Batik adalah salah satu warisan budaya Indonesia yang diakui oleh UNESCO sebagai warisan dunia. Keanekaragaman motif batik mencerminkan kekayaan budaya dan seni yang perlu dilestarikan. Salah satu motif batik yang unik adalah batik Bomba dari Kabupaten Donggala, Sulawesi Tengah. Untuk membantu mengklasifikasikan motif batik yang beragam, penelitian ini menggunakan metode Convolutional Neural Network (CNN) dengan arsitektur EfficientNet-B2. Penelitian ini melibatkan pengumpulan 21 citra batik Bomba dari berbagai sumber di Kota Palu, Sulawesi Tengah. Proses data preprocessing dilakukan melalui teknik augmentasi data, sementara model dikembangkan dengan menggunakan transfer learning dan beberapa teknik optimisasi seperti batch normalization, regulasi, dropout layer, dan fungsi aktivasi ReLU serta softmax. Model dilatih dengan optimizer Adamax dan early stopping untuk mencegah overfitting. Hasil pelatihan menunjukkan akurasi tinggi sebesar 100% pada data pelatihan dan 99.59% pada data validasi. Pengujian menggunakan confusion matrix menunjukkan akurasi total model sebesar 96%, dengan kesalahan klasifikasi minimal pada gambar "maleo". Model ini berhasil mengklasifikasikan motif batik Bomba dengan tingkat akurasi yang tinggi, menunjukkan potensi besar penggunaan teknologi kecerdasan buatan dalam pelestarian dan pengembangan warisan budaya batik.
PENERAPAN CONVOLUTION NEURAL NETWORK (CNN) UNTUK DETEKSI MEGALITIKUM DI SULAWESI TENGAH BERBASIS MOBILE Fahmi, Moh.; Laila, Rahma; Pusadan, Mohammad Yazdi; Syahrullah, Syahrullah; Azhar, Ryfial; Sani, Ilham Abdillah; Magfirah, Magfirah
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.6458

Abstract

Taman Nasional Lore Lindu di Sulawesi Tengah, Indonesia, memiliki berbagai objek megalitikum, termasuk arca, kalamba, lumpang, dan batu dulang. Kawasan ini memiliki potensi untuk secara resmi diakui sebagai Situs Warisan Dunia, namun pengguna masih menghadapi tantangan dalam mengidentifikasi dan memahami artefak megalitikum ini. Sebagai tanggapan atas masalah ini, penelitian ini telah menciptakan sistem atau aplikasi yang menggunakan algoritma CNN (Convolutional Neural Network) dengan platform Teachable Machine untuk meningkatkan kemampuan pengguna dalam mengidentifikasi objek megalitikum. Program ini akan menawarkan informasi yang lebih luas untuk setiap objek megalitikum, termasuk penggunaan yang dimaksudkan dan konteks sejarahnya. Temuan uji menunjukkan bahwa program ini memiliki kemampuan untuk mengidentifikasi objek megalitikum dengan tingkat akurasi hingga 98%. Selain itu, pengguna dapat dengan mudah mengakses informasi yang lebih komprehensif tentang artefak-artefak ini. Program ini memungkinkan pengguna untuk dengan mudah mengidentifikasi dan memahami objek megalitikum, sambil juga memberikan mereka informasi yang lebih mendalam tentang artefak-artefak tersebut.
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 (IJCS)
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.
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 (IJCS)
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.
Co-Authors Ahmad Imam Abdullah Aldy, Moh.Fajrin Sigit Amriana Andriar Makahrun Anisa Yulandari Anita Ahmad Kasim AR. Lamasitudju, Charunnisa Buliali, Joko Lianto Chairunnisa Ar. Lamasitudju 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 Pramadinda, Alda Nur Putra, Ryan Adi Rahma Laila Rahmah Laila Rifki, Moh Rizka Ardiansyah Rumampuk, Viola Gracella Ryfial Azhar, Ryfial 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 Yudhaswana Joefrie , Yuri Yudhaswana, Yuri Yulianti, Indira Yuri Yudhaswana Joefrie Yusuf Anshori Zakiani Sakka