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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
Septiano Anggun Pratama
Universitas Tadulako
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Public Health Other

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Geographical Information System Shortes Path Delivery Of Goods Using The Bellman-Ford And Dijkstra Algorithm (Case Study J&T Palu City) Septiani, Rini; Joefrie, Yuri Yudhaswana; Ardiansyah, Rizka; Pratama, Septiano Anggun; 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.v10i2.6289

Abstract

The demand for goods delivery services (expedition services) is currently growing very rapidly to support the many e-commerce companies that have sprung up in Indonesia. In the delivery process, there is often a delay in delivery due to the random delivery path of the delivery service courier. The development of information technology, especially computer technology, can be used to solve problems in various fields of work. This study aims to optimize the determination of Goods Delivery routes using the Bellman-Ford and Dijkstra Algorithms. The case study was conducted at JT Goods Delivery Services in Palu City, Central Sulawesi. The data used in this study is the distance data between the delivery location points of goods taken from Google Maps. This research was conducted by collecting data on the distance between the source point and the location of the delivery of goods. By using the Bellman-Ford and Dijkstra Algorithms, the Bellman-Ford Algorithm is used to handle graphs with negative weights and detect negative cycles, while the Dijkstra Algorithm is more efficient on graphs with positive weights, focusing on finding the shortest path from one point to all other points, the distance and time required for shipping goods can be minimized so that the efficiency of shipping goods can be increased
Pemanfaatan TOPSIS (Technique For Order Preference By Similarity To Ideal Solutions) untuk Rekomendasi Objek Wisata di Provinsi Sulawesi Tengah Ulhak, Muhamad Zia; Pratama, Septiano Anggun; Ardiansyah, Rizka; Angreni, Dwi Shinta
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.v13i5.4404

Abstract

Tourism is one of the key sectors in driving economic growth in Central Sulawesi. To support the enhancement of tourism, this research developed a web-based decision support system using the TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) to provide tourism destination recommendations. The system assists users in selecting tourist destinations based on several relevant criteria, such as facilities, accessibility, cost, cleanliness, and safety. By applying the TOPSIS method, the system can rank tourism destinations by comparing the distances between positive and negative ideal solutions. This implementation is expected to help tourists make more informed and accurate decisions regarding the destinations they wish to visit and contribute positively to the development of tourism in Central Sulawesi.
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.
RANCANG BANGUN SISTEM MANAJEMEN PEMBELAJARAN ASEAN CENTRE FOR ENERGY MENGGUNAKAN METODE EXTREME PROGRAMMING Faldiansyah, Faldiansyah; Laila, Rahmah; Syahrullah, Syahrullah; Lapatta, Nouval Trezandy; Pratama, Septiano Anggun
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.v10i3.6377

Abstract

ASEAN Centre for Energy (ACE) adalah lembaga antar-pemerintah yang mewakili 10 negara ASEAN dalam sektor energi. ACE berperan penting dalam merancang kebijakan kawasan energi untuk mendukung pertumbuhan ekonomi berkelanjutan dan menjaga lingkungan. Meskipun menyediakan sumber daya dan sertifikasi internasional, ACE belum memiliki sistem yang efektif untuk mengelola pembelajaran dan sertifikasi. Untuk mengatasi hal tersebut ACE berupaya mengembangkan sebuah platform Learning Management System (LMS) untuk mendukung pembelajaran dan sertifikasi dalam sektor energi di kawasan ASEAN. Penelitian ini menggunakan metode Extreme Programming (XP) yang melibatkan tahapan perencanaan, perancangan wireframe dan Entity Relationship Diagram (ERD), pengkodean dengan teknologi seperti Next.js, PostgreSQL, Django, dan Node.js, serta pengujian dengan metode Blackbox Testing dan User Acceptance Testing (UAT). Hasil penelitian menunjukkan bahwa platform LMS yang dikembangkan memenuhi ekspektasi pengguna dengan tingkat kepuasan mencapai 92,43%. Integrasi PayPal sebagai payment gateway telah memberikan kontribusi signifikan terhadap keamanan dan kemudahan transaksi keuangan, memungkinkan pembayaran lintas negara dengan efisien dan aman. Platform ini tidak hanya memfasilitasi akses ke materi pembelajaran dan kursus sertifikasi, tetapi juga mendukung interaksi antar siswa dan menyediakan informasi terbaru mengenai acara yang diselenggarakan oleh ACE. Diharapkan dengan sistem ini ACE lebih efektif dalam mendukung pengembangan kompetensi di sektor energi serta memperkuat kolaborasi regional di kawasan ASEAN.
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.
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.
Co-Authors Ain, Moch. Zukhruf Anita Ahmad Kasim Ar Lamasitudju, Chairunnisa AR. Lamasitudju, Charunnisa Ardiyansyah, Rizka Arsita, Tiara Juli Chairunnisa Ar. Lamasitudju Deny Wiria Nugraha Dwi Shinta Angreni Fahmil, Fahmil Faldiansyah, Faldiansyah Hanama, Ikhsan Wahyudin Iskandar Iskandar Komang, Gusti Laila, Rahma Manoppo, Maryam Mohammad Yazdi Pusadan Muhammad Akbar Nanda, Rifqi Nouval Trezandy Lapatta Nurasyah Dewi Napitupulu Pagiu, Harry T. Pusadan, Yazdi Putri, Fadiah Suryani Rahmah Laila Reinaldy Mansa, Jeremy Rifki, Moh Rini Septiani Rinianty, Rinianty Rizka Ardiansyah Ryfial Azhar, Ryfial 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