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All Journal Foristek International Journal of Advances in Intelligent Informatics JOURNAL OF APPLIED INFORMATICS AND COMPUTING JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CCIT (Creative Communication and Innovative Technology) Journal EDUMATIC: Jurnal Pendidikan Informatika Innovative: Journal Of Social Science Research The Indonesian Journal of Computer Science SISFOTENIKA
Pratama, Septiano Anggun
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Public Health Other

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Business Process Analysis in the Financial System of PT. Oti Eya Abadi With Business Process Modelling and Notation (BPMN) Method Hanama, Ikhsan Wahyudin; Pratama, Septiano Anggun; Joefrie, Yuri Yudhaswana; Lapatta, Nouval Trezandy
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.v18i1.3487

Abstract

Every company certainly needs an information system for ease of work management in a company organization. As in the problems faced by the company PT. Oti Eya Abadi who needs an information system that can create and print company cash as efficiently as possible so that leaders and employees who manage the company's financial cash do not make manual formats in excel anymore and obtain cash data formats automatically from the information system. In order to achieve a sequential but still efficient system flow in the use of information systems, an analysis is made related to the business process flow of the information system with a description in the form of Business Process Modelling and Notation (BPMN). By describing BPMN, the creation of an information system can be made more directed in each access feature so that when the information system is completed it can be used with access that is easier for users to understand and more efficient in using an information system, including the financial information system of PT. Oti Eya Abadi.
RANCANG BANGUN SISTEM JARINGAN FAILOVER AUTOMATIC TELLER MACHINE (ATM) MELALUI JARINGAN PUBLIK BERBASIS PROTOCOL EOIP DAN P2TP Ardiansyah, Rizka; Pratama, Septiano Anggun; Iskandar, Iskandar; Anshori, Yusuf; Komang, Gusti
Foristek Vol. 14 No. 2 (2024): Foristek
Publisher : Foristek

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54757/fs.v14i2.584

Abstract

The network on the Automatic Teller Machine currently uses a VSAT (Very Small Aperture Terminal) network based on Geostationary Satellites. VSAT networks often experience problems such as UP-DOWN or total DOWN. Some of the problems that cause interruptions on the VSAT interconnection include the usage period of the Modem electronic device and also ODU (Outdoor Unit) devices such as RFU, LNB, and BUC, ODU devices have a transmit period and also a received period that is uncertain according to the voltage at the location. Problems with the VSAT interconnection system cause ATM services to become unusable, resulting in losses for the bank's profits. In addition, the repair process is also generally quite time-consuming. The purpose of this study is to design an inexpensive ATM backup network solution so that when there is a break/disruption in the VSAT network the service on the ATM is not interrupted and in terms of operational costs does not swell. The backup network is intended to back up the satellite-based leading network automatically so that ATM services are always available when the satellite-based network is interrupted. The result of the study is that the proposed solution can resolve service outages at ATM machines in 34 seconds. The ATM network system will experience disconnection before finally reconnecting through the backup network. The proposed solution is much cheaper than the VSAT-based failover network solution, as it is based on the public internet network.
Optimization of Urban Waste Collection Routes Using the Held-Karp Algorithm in a Web and Mobile-Based System Arsita, Tiara Juli; Lapatta, Nouval Trezandy; Joefri, Yuri Yudhaswana; Angreni, Dwi Shinta; Pratama, Septiano Anggun
Journal of Applied Informatics and Computing Vol. 9 No. 1 (2025): February 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i1.8832

Abstract

In 2023, the Environmental Agency of Palu City recorded a total waste production of 97,492 tons, of which 10.4% was plastic waste. The Palu City Government operates a fleet of garbage trucks on a predetermined collection schedule. However, garbage bins frequently overflow before their scheduled pickup, resulting in extended waste accumulation and inefficiency. This study proposes a web and mobile-based system to enhance waste management by integrating bin condition reporting and shortest route calculation for collecting full bins. The Held-Karp algorithm is utilized to address the Travelling Salesman Problem (TSP) for determining optimal collection routes. The system was developed using Golang, Flutter, ReactJS, and a MySQL database. API functionality was validated using Postman, and overall system functionality was tested using the black-box method. A case study involving 8 test points (1 starting point, 10 waste collection points, and 1 endpoint) demonstrated that the proposed system reduces travel time by up to 21.74%, costs by 22.29%, fuel consumption by 21.16%, and distance traveled by 21.16% compared to conventional methods. These results highlight the potential of the system to significantly optimize waste collection operations and support sustainable urban waste management practices.
a PREDIKSI SISWA PUTUS SEKOLAH DAN KEBERHASILAN AKADEMIK MENGGUNAKAN MACHINE LEARNING: Prediksi Siswa Putus Sekolah dan Keberhasilan Akademik Fitriana, Siti; riniyanty; laila, rahma; pratama, septiano anggun; lamasitudju, chairunnisa ar
The Indonesian Journal of Computer Science Vol. 13 No. 6 (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.v13i6.4453

Abstract

In 2020-2023. The issue of high school dropouts at SMA Negeri 2 Sigi increased, causing impacts such as declining school accreditation, a decrease in the number of students, and operational aid. This research aims to build an early prediction system for student dropouts using Machine Learning (ML). In this study, data from 200 students were used. With 16 students labeled as dropout. The results showed a model accuracy of 0.942 and an area under the curve (AUC) of 0.948. the factors most influencing student droppout are average grades, meeting targets, and father’s education leve.
PERANCANGAN ARCHITECTURE ENTERPRISE DENGAN ARTIFICIAL INTELLIGENCE DALAM PELAYANAN PENERBITAN TANDA TANGAN ELEKTRONIK DISKOMINFO KOTA PALU MENGGUNAKAN TOGAF ADM Rifki, Moh; Pratama, Septiano Anggun; Pusadan, Mohammad Yazdi; Syahrullah, Syahrullah; Lamasitudju, Chairunnisa Ar
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.v10i2.6097

Abstract

Seiring perkembangan teknologi di era industri 5.0 telah mempengaruhi berbagai aspek terutama pada pelayanan tanda tangan elektronik, dimana pada era teknologi saat ini tidak hanya menjadi atau untuk memfasilitasi kehidupan sehari-hari tetapi juga mendorong inovasi di berbagai bidang untuk memecahkan masalah global dan meningkatkan kualitas hidup secara keseluruhan. Namun penerapan teknologi informasi pada diskominfo masih menghadapi beberapa tantangan, seperti proses bisnis dan prosedur standar operasional yang tidak terstruktur dan terorganisir serta masih kurangnya efisiensi dalam penggunaan teknologi. Oleh karena itu, untuk meningkatkan kualitas pada pelayanan pada tanda tangan maka solusi yang dibutuhkan yaitu membangun perancangan arsitektur perusahaan dengan kecerdasan buatan dengan menggunakan TOGAF ADM dalam meningkatkan pelayanan organisasi dalam mendukung pengembangan kota pintar di Kota Palu. Sedangkan tahapan yang dikerjakan pada perancangan menggunakan TOGAF ADM dimulai dari Tahap Pendahuluan, visi arsitektur, arsitektur bisnis, sistem informasi, arsitektur, dan arsitektur teknologi selaras dengan standar yang diperlukan proses bisnis dan prosedur operasional standar. Hasil perancangan akan menghasilkan rencana strategi yang akan menyatukan arsitektur bisnis, data, aplikasi dan teknologi dalam hubungan untuk mendekati satu sama lain.
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.
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.
Co-Authors Anita Ahmad Kasim Ar Lamasitudju, Chairunnisa 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 Nouval Trezandy Lapatta Pagiu, Harry T. Pusadan, Yazdi Putri, Fadiah Suryani Rahmah Laila Rifki, Moh Rini Septiani Rinianty, Rinianty Rizka Ardiansyah Saleh, Muhammad Taufik Sasuwuk, James Rio Siti Fitriana Syahrullah Syahrullah Syaiful Hendra Ulhak, Muhamad Zia Wawagalang, A. Nolly Sandra Yuri Yudhaswana Joefrie Yusuf Anshori