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All Journal Foristek International Journal of Advances in Intelligent Informatics JOURNAL OF APPLIED INFORMATICS AND COMPUTING Paedagoria : Jurnal Kajian, Penelitian dan Pengembangan Kependidikan JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CCIT (Creative Communication and Innovative Technology) Journal EDUMATIC: Jurnal Pendidikan Informatika IAIC Transactions on Sustainable Digital Innovation (ITSDI) Innovative: Journal Of Social Science Research The Indonesian Journal of Computer Science SISFOTENIKA Bomba: Jurnal Pembangunan Daerah
Septiano Anggun Pratama
Universitas Tadulako
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Public Health Social Sciences Transportation Veterinary Other

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Comparative Performance Analysis of GRPC and Rest API Under Various Traffic Conditions and Data Sizes Using a Quantitative Approach Ain, Moch. Zukhruf; Rizka Ardiansyah; Septiano Anggun Pratama; Muhammad Akbar; Nouval Trezandy Lapatta
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9276

Abstract

Web 3.0 presents challenges in efficient data exchange, especially in decentralized systems. REST API (HTTP/1.1) remains widely used due to its broad compatibility but has communication inefficiencies, while gRPC (HTTP/2) offers better performance with multiplexing and Protocol Buffers. This study compares REST API and gRPC under various traffic conditions and data sizes using Apache JMeter and Wireshark, measuring throughput, response time, latency, and data transfer efficiency. Results show that REST API has higher throughput in low-traffic scenarios (995 vs. 29.5 req/min) and faster GET response time (3 ms vs. 20 ms), while gRPC excels in large data transfers (276.34 KB/s vs. 134.1 KB/s) and stable latency (0.147 ms). However, ANOVA analysis (p > 0.05) indicates no statistically significant difference. REST API is ideal for standard web applications, while gRPC is suited for microservices and real-time systems.
CNN Algorithm for Herbal Leaf Classification Using MobileNetV2 and ResNet50V2 Pagiu, Harry T.; Kasim, Anita Ahmad; Lapatta, Nouval Trezandy; Pratama, Septiano Anggun; Laila, Rahma
CCIT (Creative Communication and Innovative Technology) Journal Vol 18 No 2 (2025): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v18i2.3776

Abstract

Indonesia is home to over 30,000 types of herbal plants, with approximately 1,200 species utilized as raw materials for alternative and traditional medicine. Leaves play a crucial role in herbal medicine preparation. However, many people struggle to identify different herbal leaves due to their similar appearances, making classification difficult. Each leaf possesses unique characteristics such as shape, size, midrib, stalk, blade, and type, which can be used for differentiation. To assist in identifying herbal leaves, a classification system based on image recognition is essential. Convolutional Neural Networks (CNN) are deep learning algorithms designed for processing two-dimensional image data. Model performance can be enhanced through transfer learning, with MobileNetV2 and ResNet50V2 being widely used architectures. These pretrained models have been trained to recognize images with high accuracy. This study focuses on classifying herbal plants based on leaf shape using CNN architectures from MobileNetV2 and ResNet50V2. The evaluation results show that the MobileNetV2 architecture, with a 90%:10% data split, achieved an accuracy of 98.51%, precision of 98.92%, recall of 98.51%, and an F1-score of 98.56%. These findings indicate that CNN with transfer learning can effectively classify herbal leaves with high accuracy.
Segmentasi Pelanggan Menggunakan Kerangka LRFMV dan Algoritma K-Means untuk Optimalisasi Strategi Pemasaran Wawagalang, A. Nolly Sandra; Syahrullah, Syahrullah; Ardiyansyah, Rizka; Angreni, Dwi Shinta; Pratama, Septiano Anggun; Nugraha, Deny Wiria
Jurnal Pendidikan Informatika (EDUMATIC) Vol 9 No 2 (2025): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v9i2.31025

Abstract

In this competitive digital era, customer behavior is key to maintaining loyalty and increasing profitability. This study aims to implement customer segmentation using the Length, Recency, Frequency, Monetary, Volume (LRFMV) approach and the K-Means algorithm to identify customer behavior characteristics and determine high-value segments. The combination of these five dimensions has rarely been used in previous studies, thus providing a new contribution to data-based customer behavior analysis. This study adopts an exploratory descriptive quantitative approach. The data used consists of 2,098 transactions from 452 customers, sourced from a public GitHub dataset. The data analysis process includes preprocessing, determining LRFMV values, and segmentation using K-Means Clustering. The Silhouette Coefficient is used to evaluate cluster quality and determine the optimal number of clusters. The results show that the best configuration is obtained at k=5 with a Silhouette value of 0.842. The findings show five customer segments with different characteristics and Customer Lifetime Value (CLV) values. Clusters 0 and 2 are categorized as Loyal Customers (L↑R↓F↑M↑V↑) with the highest CLV. Clusters 3 and 1 are Inactive New Customers (L↓R↑F↓M↓V↓) with low contribution. Cluster 4 consists of Inactive Customers (L↓R↓F↓M↓V↓), indicating overall inactivity. These segmentation results are used to develop more targeted strategies, such as loyalty programs or reactivation campaigns, to optimize marketing strategies based on customer value.
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.
Rancang Bangun Sistem Informasi Pariwisata Di Kabupaten Banggai Menggunakan Algoritma Haversine Pratama, Septiano Anggun; Manoppo, Maryam
SISFOTENIKA Vol. 14 No. 1 (2024): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/sisfotenika.v14i1.421

Abstract

Kabupaten Banggai merupakan suatu wilayah di Sulawesi Tengah yang memiliki tempat wisata menarik yang bisa dikunjungi oleh wisatawan lokal maupun mancanegara. Banyaknya pengunjung yang ingin berwisata di Kabupaten Banggai dapat meningkatkan pendapatan daerah serta bisa menjadi sumber penghasilan bagi masyarakat disekitar lokasi tempat wisata. Sektor pariwisata sebagai kegiatan perekonomian telah menjadi andalan dan prioritas pengembangan bagi sejumlah daerah terlebih daerah yang mempunyai potensi seperti Kabupaten Banggai. Untuk meningkatkan peran kepariwisataan, sangat terkait antara destinasi wisata yang dapat dijual dan sarana yang dapat mendukungnya dalam industri pariwisata. Usaha dalam mengembangkan daerah tujuan wisata tidak hanya berpatokan pada sarana tempat wisata yang memadai, tetapi dibutuhkan juga teknologi dan media sebagai tempat promosi. Sistem informasi ini dapat memberikan informasi tempat wisata yang akurat dan relevan dengan memanfaatkan algoritma haversine yang dimana algoritma ini sering digunakan dalam perhitungan jarak antara dua titik berdasarkan kondisi geografis sehingga dapat digunakan untuk memberikan estimasi jarak antar setiap destinasi wisata. Dengan memanfaatkan algoritma haversine, sistem ini dapat memberikan rekomendasi rute yang optimal sehingga dapat membantu pengguna dalam merencanakan perjalanan dengan lebih efisien. Metode pengembangan sistem yang digunakan yaitu metode waterfall. Model ini menggunakan pendekatan sistematis dan berurutan. Tahapan dalam model ini dimulai dari tahap perencanaan hingga tahap pengelolaan (maintenance) dan dilakukan secara bertahap. Pada pengujian algoritma haversine yang dilakukan dengan membandingkan perhitungan dengan google maps didapatkan bahwa algoritma haversine memiliki nilai jarak yang lebih rendah. Hasil yang didapatkan dari perhitungan algoritma haversine yang telah dibandingkan dengan google maps memiliki range jarak 10-20 km. Penelitian ini dibangun berbasis website sehingga penulis berharap penelitian selanjutnya bisa dikembangkan menggunakan sistem operasi lainnya seperti android dan IOS. Penelitian ini menggunakan perhitungan haversine, sehingga untuk penelitian selanjutnya bisa dikembangkan dengan menggunakan algoritma sejenis lainnya yang bisa menghitung jarak serta menentukan jalur atau rute perjalanan.
Perancangan Proses Bisnis Sistem PPDB Dengan Fokus User Experience Pada CV Mitra Global Techno (Studi Kasus TK IT AL Qolam) Pratama, Septiano Anggun; Lamasitudju, Chairunnisa Ar; Hendra, Syaiful; Putri, Fadiah Suryani
Foristek Vol. 13 No. 2 (2023): Foristek
Publisher : Foristek

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54757/fs.v14i2.304

Abstract

Admission of New Students (PPDB) is one of the crucial stages or processes in the world of education, including at the Kindergarten level. A PPDB process that focuses on effective user experience is very important to maintain the reputation of educational institutions and provide a positive experience to parents of prospective students. The Al Qolam IT Kindergarten PPDB process is still carried out manually or conventionally, so it takes quite a long time for parents to process the registration form and return the registration form to the data processing process by the school operator. Considering these problems, designing the PPDB business process with a focus on user experience using BPMN (Business Process Model and Notation), it is hoped that this will create a simpler, more comfortable and intuitive registration experience for parents of prospective students and accuracy in data processing.
Perancangan Database Pada Sistem Informasi Arsip Surat (Studi Kasus Balai Pengelolaan Hasil Hutan Lestari Wilayah XII Palu) Pratama, Septiano Anggun; Ar Lamasitudju, Chairunnisa; Fahmil, Fahmil
Innovative: Journal Of Social Science Research Vol. 3 No. 5 (2023): Innovative: Journal of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini ditujukan untuk membuat sebuah sistem informasi arsip surat yang digunakan dikantor Dinas Pengelolaaan Hutan Lestari wilayah XII Palu untuk untuk bisa membuat sebuah sistem yang lebih mempermudah para pengawai yang melakukakan pengarsipan surat yang mungkin lebih manual dan juga tercecernya surat yang telah masuk dalam kantor dinas dalam bidang Data. Metode analisis data yang digunakan dalam merancang sistem yang akan dibuat adalah metode analisis data yang bersifat Kuantitatif. Metode pengembangan sistem yang dilakukan adalah metode prototyping. Metode pengumpulan data yang digunakan yaitu wawancara, observasi, dan studi literatur. Database yang digunakan dalam pembuatan sistem ini yaitu menggunakan phpMyAdmin. Jenis pengujian sistem yang akan digunakan dalam penelitian ini adalah jenis pengujian Black Box.
Pattern recognition for facial expression detection using convolution neural networks Pusadan, Mohammad Yazdi; Sasuwuk, James Rio; Pratama, Septiano Anggun; Laila, Rahma
International Journal of Advances in Intelligent Informatics Vol 11, No 4 (2025): November 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v11i1.1602

Abstract

The COVID-19 pandemic was a devastating disaster for humanity worldwide. All aspects of life were disrupted, including daily activities and education. The education sector faced significant challenges at all levels, from kindergarten to elementary, junior high, and high school, as well as in higher education, where learning had to be online. Human emotions are primarily conveyed through facial expressions resulting from facial muscle movements. Facial expressions serve as a form of nonverbal communication, reflecting a person’s thoughts and emotions. This research aims to classify emotions based on facial expressions using the Convolutional Neural Network (CNN) and detect faces using the Viola-Jones method in video recordings of online meetings. We utilize the VGG-16 architecture, which consists of 16 layers, including convolutional layers with the ReLU activation function and pooling layers, specifically max pooling. The fully connected layer also employs the ReLU activation function, while the output layer uses the Softmax. The Viola-Jones method is used for facial detection in images, achieving an accuracy of 87.6% in locating faces. Meanwhile, the CNN method is applied for facial expression recognition, with an accuracy of 59.8% in classifying emotions.
Artificial Intelligence Untuk Identifikasi Motif Tenun Tradisional Sulawesi Tengah Pusadan, Mohammad Yazdi; Laila, Rahma; Pratama, Septiano Anggun
Bomba: Jurnal Pembangunan Daerah Vol 5 No 1 (2025)
Publisher : Badan Riset dan Inovasi Daerah Sulawesi Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65123/bomba.v5i1.93

Abstract

Traditional weaving from Central Sulawesi, such as the motifs of Magau, Banua Oge/Souraja, and Tadulako, reflects deep cultural and historical values. However, the complexity of the patterns and motifs often makes manual identification challenging. This research employs an Artificial Intelligence (AI) approach using Convolutional Neural Networks (CNN) to automate the identification of these motifs. The AI model is trained using a diverse dataset of woven motif images and shows significant accuracy in classifying Magau, Banua Oge/Souraja, and Tadulako motifs. This research opens up cultural preservation and innovation opportunities in woven products with modern technology. The achieved result is the evaluation of the AI model using the following metrics: accuracy, precision, recall, and the confusion matrix. The accuracy obtained for each motif reaches 90%.
PENGEMBANGAN SISTEM KEAMANAN KAMERA PENGAWAS BERBASIS INTERNET OF THINGS (IOT) DENGAN TEKNOLOGI DETEKSI OBJEK MENGGUNAKAN RASPBERRY PI DAN NOTIFIKASI TELEGRAM Pratama, Moh. Rezki; Lamasitudju, Chairunnisa; Pusadan, Mohammad Yazdi; Laila, Rahmah; Pratama, Septiano Anggun
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.6562

Abstract

Internet of Things (IoT) merupakan konsep yang memperluas manfaat konektivitas internet yang terhubung secara terus-menerus. Pada penelitian ini, IoT dimanfaatkan untuk mengendalikan kamera pengawas yang dapat dioperasikan dari jarak jauh melalui jaringan komputer. Dengan kemajuan teknologi ini, pengguna dapat memantau dan mengendalikan kamera pengawas kapan saja dan di mana saja selama lokasi tersebut memiliki koneksi internet yang memadai. Sistem ini dirancang untuk mempermudah pengawasan, terutama di gedung yang jaraknya jauh dari pengguna. Dalam penelitian ini, sistem pengawasan berbasis IoT dikembangkan dengan memanfaatkan Raspberry Pi sebagai pusat pengolahan data dan aplikasi Telegram sebagai media notifikasi real-time. Teknologi pengenalan wajah diterapkan untuk mendeteksi dan mengidentifikasi individu yang muncul di depan kamera, serta memberikan peringatan ketika wajah yang tidak dikenal terdeteksi. Integrasi ini memungkinkan sistem untuk tidak hanya memberikan pengawasan visual tetapi juga menyediakan interaksi yang lebih cerdas dan responsif melalui notifikasi langsung kepada pengguna. Hasil uji coba menunjukkan bahwa sistem ini tidak hanya meningkatkan efisiensi dan fleksibilitas pengawasan, tetapi juga menawarkan solusi keamanan yang lebih proaktif dan adaptif terhadap berbagai situasi. Dengan demikian, penelitian ini memberikan kontribusi yang signifikan terhadap pengembangan teknologi pengawasan berbasis IoT yang dapat diterapkan dalam berbagai skala dan konteks, dari rumah tangga hingga fasilitas publik.
Co-Authors Ain, Moch. Zukhruf Anita Ahmad Kasim AR. Lamasitudju, Charunnisa Ardiyansyah, Rizka Arsita, Tiara Juli Deny Wiria Nugraha Dwi Shinta Angreni Fahmil, Fahmil Faldiansyah, Faldiansyah Hanama, Ikhsan Wahyudin Iskandar Iskandar Komang, Gusti Laila, Rahma Lamasitudju, Chairunnisa Manoppo, Maryam Mohammad Yazdi Pusadan Muhammad Akbar Nanda, Rifqi Nouval Trezandy Lapatta Nurasyah Dewi Napitupulu Pagiu, Harry T. Pratama, Moh. Rezki Putri, Fadiah Suryani Rahmah Laila Reinaldy Mansa, Jeremy Rifki, Moh Rini Septiani Rinianty, Rinianty Rizka Ardiansyah Ryfial Azhar Ryka Marina Walanda Saleh, Muhammad Taufik Sasuwuk, James Rio Siddiq Assegaf, Djafar Siti Fitriana Syahrullah Syahrullah Syaiful Hendra Ulhak, Muhamad Zia Wahyu Setiawan Wawagalang, A. Nolly Sandra Wirdayanti Yuri Yudhaswana Joefrie Yusuf Anshori