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All Journal Foristek JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CCIT (Creative Communication and Innovative Technology) Journal EDUMATIC: Jurnal Pendidikan Informatika ScientiCO : Computer Science and Informatics Journal InPrime: Indonesian Journal Of Pure And Applied Mathematics IAIC Transactions on Sustainable Digital Innovation (ITSDI) Advance Sustainable Science, Engineering and Technology (ASSET) Innovative: Journal Of Social Science Research The Indonesian Journal of Computer Science
Dwi Shinta Angreni
Universitas Tadulako
Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Other

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ANALISIS EVOLUSI EKOSISTEM PERANGKAT LUNAK OPEN SOURCE : TINJAUAN PUSTAKA SISTEMATIS Angreni, Dwi Shinta; Prastyaningsih, Yunita
ScientiCO : Computer Science and Informatics Journal Vol 2, No 1 (2019): Scientico : April
Publisher : Fakultas Teknik, Universitas Tadulako

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Abstract

The development of an Open Source Software (OSS) can influence the development of other Open Source Systems. The relationship between OSS is often called an ecosystem, there are several aspects to the OSS ecosystem that can affect ecosystem evolution in the software. This study reports a systematic literature review on the influence of several aspects of the OSS ecosystem on the evolution of OSS. The Sistematic Literature Review method based on Kitchenham was used to analyze 1099 articles published in leading journals and conferences. The Results showed that Social aspects have a significant impact on ecosystem evolution, where communication between communities in an OSS ecosystem influences aspects of contributions and dependencies that encourage an ecosystem to develop and evolve.
IMPLEMENTASI METODE TOPSIS DALAM PENENTUAN CALON TRANSMIGRAN DI INDONESIA Ngemba, Hajra Rasmita; Angreni, Dwi Shinta; Winarta, Ardhiansyah; Hendra, Syaiful; A Djufri, Isdar
ScientiCO : Computer Science and Informatics Journal Vol 3, No 2 (2020): Scientico : November
Publisher : Fakultas Teknik, Universitas Tadulako

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Abstract

The population in Indonesia is growing, causing population density in an area. One of the impacts of population density in an area is that it causes job opportunities in that area to become smaller, so that the unemployment rate increases. To overcome this problem, the government moved or spread the population from a densely populated area to another area with a small population with the aim of improving the economy and opening up agricultural land in the region. However, problems in the field include the limited quota of transmigrant participants from the central government. So it makes it difficult to choose or make decisions to determine potential transmigration participants. This study aims to assist the government in making decisions to determine suitable transmigrant candidates using the TOPSIS(Technique for Order Preference By Similiarity To Ideal Solution) method. Application development using the prototype method with blackbox testing. Decision Support System Applications Determining prospective transmigrants can assist users (government) in determining eligible transmigrant candidates with the criteria desired by the government.
Aplikasi Antrian Pasien Pada Dokter Praktek Umum Menggunakan Metode FIFO (First In First Out) Berbasis Android Hardianti, Hardianti; Hendra, Syaiful; Kasim, Anita Ahmad; Azhar, Ryfial; Angreni, Dwi Shinta; Ngemba, Hajra Rasmita
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 1 (2023): MARET
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i1.1478

Abstract

Currently, there are so many services in Indonesia. One of the services in the health sector is the practice of general practitioners. Services that occur at the practice of general practitioners, namely dr. Zaki Mubarak and dr. Subhan Habibi, located in Palu, often has complaints because it is still ineffective where getting these services is still done manually by means of patients coming in person and taking a queue based on the order of seats then one by one they will be served. This causes patient discomfort in waiting. To make it easier for patients who want to seek treatment, a system is needed, with this; an Android-based patient queuing application for general practice doctors was made. The application of the method used in building the system is the FIFO queuing method where patients who register earlier get medical services first. Then the average waiting time is calculated where the results obtained will be used as an estimate of the waiting time for the next patient. The application development method in this research used the prototype method and application testing uses the black box testing method. The results of this research are the application of patient queues for general practice doctors based on Android which is built to be able to take queues anywhere and anytime and obtain some information including doctor’s practice schedules, queue numbers, running queues, and estimated waiting times so that patients can estimate arrival time without having to wait long. Based on system testing with black box, the results show that the functional system is running well. Based on the average waiting time calculation, from the 60 queue data tested, the result is that the distance between queue 1 and the order is around 5 minutes.
Geographic Information System Using Node Combination Based on Dijkstra's Algorithm for Determining the Shortest Tsunami Evacuation Route in Palu Bay: Rancang Bangun Sistem Informasi Geografis Menggunakan Kombinasi Node Berbasis Algoritma Dijkstra Pada Penentuan Jalur Terpendek Evakuasi Tsunami Di Teluk Palu Angreni, Dwi Shinta; Budiman, Wahyu; Anshori, Yusuf; Wirdayanti, Wirdayanti; Bintana, Rizqa Raaiqa
Foristek Vol. 14 No. 2 (2024): Foristek
Publisher : Foristek

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54757/fs.v14i2.455

Abstract

Indonesia, an archipelagic country situated on the Equator and surrounded by the Ring of Fire, is highly susceptible to natural disasters such as tectonic earthquakes and volcanic eruptions. Palu, one of Indonesia's seismically active regions, is traversed by the Palu-Koro Fault, which has the potential to trigger strong earthquakes and tsunamis, as evidenced by the 7.4-magnitude earthquake in September 2018. To mitigate disaster risks, it is crucial to understand community vulnerability and utilize Geographic Information System (GIS) technology. This study designs a GIS-based system using the modified Dijkstra's Algorithm to determine the shortest tsunami evacuation routes in Palu. Testing results indicate that the system is effective, with a user satisfaction rate of 89.33% and satisfactory route prediction accuracy compared to Google Maps. The system can be relied upon to help communities find the nearest evacuation routes, thereby enhancing safety and preparedness in the face of potential disasters.
Optimizing User Interface of MBKM Information System & Academic Services using Design Thinking Method (Case Study: Tadulako University) Reinaldy Mansa, Jeremy; Anggun Pratama, Septiano; Wirdayanti, Wirdayanti; Angreni, Dwi Shinta
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.v6i1.676

Abstract

This study addresses the usability challenges faced by Tadulako University's MBKM & Academic Services Information System (SITAMPAN), developed in response to the Ministry of Education’s Merdeka Belajar - Kampus Merdeka (MBKM) initiative. By applying a structured Design Thinking approach, this research seeks to present a novel solution for enhancing user experience and system usability in educational information systems. Through the System Usability Scale (SUS) and User Experience Questionnaire (UEQ) evaluations, initial findings indicated a low usability score (SUS: 41.75, grade "F"), categorizing the system as a "Detractor" in the Net Promoter Score (NPS) framework. Following the implementation of user centered design improvements, the SUS score increased substantially to 86.25 ("A" grade), with NPS shifting to a "Promoter" classification, while UEQ scores showed marked improvement across all metrics. This study demonstrates the effectiveness of Design Thinking in systematically addressing and optimizing the user experience, providing valuable insights for future information system developments in educational contexts.
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.
PENGGABUNGAN METODE SYSTEM USABILITY SCALE DAN USER EXPERIENCE QUESTIONNAIRE UNTUK EVALUASI USABILITY SISTEM INFORMASI MBKM UNIVERSITAS TADULAKO DENGAN PENDEKATAN USER EXPERIENCE Sahril, Sahril; Ardiansyah, Rizka; Wirdayanti, Wirdayanti; Angreni, Dwi Shinta; Yudhaswana, Yuri
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.v9i4.5548

Abstract

Usability merupakan apsek penting dalam mengukur kualitas sebuah sistem. Tingkat Usability sangat dipengaruhi oleh pengalaman pengguna dimana hal ini dapat diukur dengan menilai seberapa cepat dan mudah pengguna mempelajari serta menyelesaikan tugas. Evaluasi usability dikategorikan menjadi pendekatan empiris dan non-empiris. Penelitian ini bertujuan mengevaluasi tingkat usability Sistem Informasi MBKM  dengan pendekatan empiris menggabungkan system usability scale (SUS) dan User Experience Questionnaire (UEQ) sehingga evaluasi yang dilakukan tidak hanya mengukur tingkat usability sebuah sistem namun juga dapat mengidentifikasi  masalah usability berdasarkan aspek pengalaman pengguna. Hasil evaluasi menggunakan SUS menunjukan skor SUS Sistem Informasi MBKM berada pada angka 63 menunjukan skor SUS untuk tingkat adjective scale  pada kategori “OK”, grade scale kategori “C-”, serta acceptability scale berada pada kategori “MARGINAL” dengan net promoter scores kategori “Passive”.  Hasil pengukuran menggunakan UEQ yang telah diadaptasi menunjukan aspek attractiveness (1.20), perspicuity (1.49), efficiency (1.06), stimulation (1.14), dan novelty (0.82) mendapatkan evaluasi positif di atas rata-rata sedangkan aspek dependability (0.88) mendapatkan evaluasi positif namun di bawah rata-rata. Penelitian selanjutnya dapat dilakukan menggunakan pendekatan dan non-empiris dengan melibatkan para ahli (evaluator) untuk menilai tingkat kegunaan serta ngidentifikasi letak masalah dari sebuah sistem
Donor Segmentation Analysis Using the RFM Model and K-Means Clustering to Optimize Fundraising Strategies ., Rezki; Lapatta, Nouval Trezandy; Ardiansyah, Rizka; ., Wirdayanti; Angreni, Dwi Shinta
Journal of Applied Informatics and Computing Vol. 8 No. 2 (2024): December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i2.8464

Abstract

This study aims to segment donors using the Recency, Frequency, Monetary (RFM) model and the K-Means algorithm to optimize fundraising strategies. The RFM model is used to measure donor engagement through three dimensions: Recency (the last time a donation was made), Frequency (the frequency of donations), and Monetary (the amount of donations). By utilizing RFM scores, donors are then grouped using the K-means algorithm to generate more specific donor segments. This study was conducted using donation data from a non-profit organization, focusing on strategies to improve donor loyalty and donation frequency. The segmentation results identified several key segments, including Loyal Donors, New Donors, Potential Donors, and Low-Priority Donors. Each segment exhibits different donation behavior characteristics and requires a different strategic approach. The implementation of these segmentation results is expected to help the organization design more effective communication strategies and donation programs, as well as improve donor retention and lifetime value. Additionally, this study identifies the potential for enhancing the analytical model for broader applications in the future. This research contributes to non-profit organizations by offering a more efficient approach to managing donor relationships.
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.
KLASIFIKASI JENIS KAYU BERDASARKAN CITRA SERAT KAYU MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK Dwimanhendra, Muhammad Rifaldi; Syahrullah, Syahrullah; Joefrie, Yuri Yudhaswana; Angreni, Dwi Shinta; Azhar, Ryfial; Nugraha, Deny Wiria; rezandy Lapatta, Nouval; Najar, Abdul Mahatir
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.5726

Abstract

Kayu merupakan sumber daya alam yang sangat penting bagi industri mebel atau furnitur. Pemilihan jenis kayu yang tepat sangat krusial dalam industri mebel untuk menentukan kualitas hasil produksi. Pemilihan kayu secara manual memiliki risiko kesalahan yang dapat berdampak negatif pada kualitas akhir produk mebel. Oleh karena itu, diperlukan penerapan teknologi untuk meminimalkan kesalahan pemilihan jenis kayu dan meningkatkan efisiensi proses produksi. Penelitian ini bertujuan membangun model klasifikasi jenis kayu (nantu, palapi, dan uru) berbasis Convolutional Neural Network (CNN) menggunakan citra serat kayu. Dataset terdiri dari 1.584 citra yang dibagi menjadi 80% data pelatihan dan 20% data pengujian. Arsitektur model CNN terdiri dari 4 lapisan konvolusi, 4 lapisan pooling, dan 2 lapisan fully-connected. Hasil pelatihan mencapai akurasi 97,06%, sedangkan hasil pengujian dan evaluasi menggunakan matriks konfusi mencapai akurasi 95,56%. Penelitian ini membuktikan bahwa CNN dapat digunakan secara efektif untuk klasifikasi jenis kayu dengan tingkat akurasi yang tinggi, sehingga dapat membantu meningkatkan efisiensi proses produksi mebel.
Co-Authors ., Rezki A Djufri, Isdar Abdul Mahatir Najar Aldy, Moh.Fajrin Sigit Anita Ahmad Kasim Anita, Ayu Ardiyansyah, Rizka Arsita, Tiara Juli Budiman, Wahyu Chairunnisa Ar. Lamasitudju Darojah, Murtafiatun Deni Luvi Jayanto Deny Wiria Nugraha Dwimanhendra, Muhammad Rifaldi Dwiwijaya, Kadek Agus Hajra Rasmita Ngemba Harani, Makruf Hardianti Hardianti, Hardianti I Wayan Sudarsana Karnita Sumbaluwu, Harlin Feby Laila, Rahma Lamasitudju, Chairunnisa Lesnusa, Gideon Namlea Mariani Mariani Maroso, Akwan Miftah Miftah, Miftah Mohammad Yazdi Pusadan Nouval Trezandy Lapatta Parenrengi, Andi Fathur Alamsyah A. Putri, Niluh Putu Aprillia Puspitadewi Sudarsana Rahmah Laila Reinaldy Mansa, Jeremy Rinianty, Rinianty Rizka Ardiansyah Rizqa Raaiqa Bintana Ryfial Azhar, Ryfial Sahril Sahril Septiano Anggun Pratama Sondakh, Clivent Gerhard Sri Khaerawati Nur Susanti, Maulidia Syahrullah Syahrullah Syaiful Hendra Ulhak, Muhamad Zia Wawagalang, A. Nolly Sandra Widiani, Ni Nengah Winarta, Ardhiansyah Wirdayanti Yudhaswana, Yuri Yunita Prastyaningsih Yuri Yudhaswana Joefrie Yusuf Anshori Zulkifli Zulkifli