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All Journal Elektron Jurnal Ilmiah Jurnal Momentum Indonesian Journal of Electrical Engineering and Informatics (IJEEI) SITEKIN: Jurnal Sains, Teknologi dan Industri JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INVOTEK: Jurnal Inovasi Vokasional dan Teknologi Jurnal Ilmiah Matrik JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Informasi dan Pendidikan Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Tekinkom (Teknik Informasi dan Komputer) MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat Jurnal Abdi Masyarakat Indonesia JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Abdimas: Pengabdian dan Pengembangan Masyarakat Engagement: Jurnal Pengabdian Kepada Masyarakat Jurnal Testing dan Implementasi Sistem Informasi
Yance Sonatha
Politeknik Negeri Padang
Religion Arts Humanities Automotive Engineering 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 Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Leveraging Machine Learning to Predict Future Human Development Gsim, Jamal; Zeriab Es-sadek, Mohamed; Sonatha, Yance
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.2543

Abstract

This study utilizes a rich repository of global development data to forecast the Human Development Index, harnessing the World Bank's World Development Indicators (WDI) database and the United Nations Development Program 's extensive human development metrics as primary data sources. Employing R as the driving force, this research unfolds through a meticulously structured four-phase methodology. The initial phase encompasses data pre-processing tasks, including web scraping, merging, cleansing, and transforming datasets. Subsequently, exploratory data analysis is conducted to unravel correlations and regression patterns among variables, culminating in the creation of refined data frames. The crux of this study revolves around machine learning, where two distinct random forest models are crafted: one for regression and another for classification purposes. Additionally, authentic development indicators are used to predict the Human Development Index accurately. Beyond merely deploying machine learning techniques, this research highlights the importance of adopting a multifaceted approach to assess and address global development challenges. This study not only aims to predict the Human Development Index but also lays a foundation for future research endeavors in this domain. It opens up avenues for exploring novel methodologies and datasets to make more precise and comprehensive predictions of human development indices. The findings of this research are poised to make a significant contribution to understanding the dynamics of global development and devising effective strategies for promoting human well-being worldwide.
Pemanfaatan Canva dalam Pembuatan Media Pembelajaran Interaktif bagi Para Guru SMA di Kabupaten Padang Pariaman Sonatha, Yance; Azmi, Meri; Rahmayuni, Indri; Meidelfi, Dwiny
Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat Vol 22, No 2 (2022): Suluah Bendang: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/sb.02930

Abstract

SMA 1 V Koto Timur merupakan salah satu SMA Negeri yang berada di Kecamatan V Koto Timur Kabupaten Padang Pariaman Provinsi Sumatera Barat. Selama pandemik covid 19, SMA 1 V Koto Timur melaksanakan proses pembelajaran dengan mengkombinasikan pembelajaran langsung dengan pembelajaran dalam jaringan(daring /online). Pembuatan media pembelajaran yang menarik sangat dibutuhkan untuk membuat ketertarikan siswa dalam mempelajarinya sehingga target pembelajaran dapat dicapai walaupun dilakukan secara tidak langsung. Permasalahan yang dihadapi sekarang adalah minimnya pengetahuan mengenai aplikasi-aplikasi yang dapat digunakan untuk membantu pembuatan media pembelajaran yang lebih interaktif. Pengabdian kepada Masyarakat yang diadakan berupa kegiatan pelatihan penggunaan canva untuk pembuatan media pembelajaran interaktif dan komunikatif menggunakan aplikasi Canva. Kegiatan berlangsung sukses ditandai dengan meningkatnya pemahaman mereka mengenai penggunaan aplikasi Canva dalam pembuatan media pembelajaran yang interaktif.
GDSS Prototype Model for Supplier Selection at MDM Cooperative Azmi, Meri; Sonatha, Yance; Rahmayuni, Indri; Paboreal Dunque, Kristine Mae; Putra, Dwi Sudarno
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.473

Abstract

MDM is a trade cooperative business unit that supplies healthy food options for consumers around the Andalas University campus. So far, the selection of suppliers that provide supply goods to the stores is only based on the trust between both parties, which is the principle of mutual acquaintance and kinship. The problems that may arise from a process like this are the lack of the right supplier, unavailability of goods, relatively higher product prices, late delivery, and low-quality goods. Therefore, we need a GDSS that is capable of overcoming these problems. This GDSS helps in decision-making by determining the right supplier for each of the stores owned by the MDM Cooperative. The methods used are AHP, TOPSIS, and BORDA, involving six criteria and five tested alternatives. The AHP method is used to obtain the weight of each criterion taken from the pairwise comparison matrix. The TOPSIS method is used to determine which suppliers get priority for supply goods. Combining the AHP and TOPSIS methods can reduce the weaknesses of the TOPSIS itself by giving subjective weights. The use of the BORDA method can provide maximum results in selecting this supplier. This GDSS also involves three decision-making bodies: the head of the cooperative, the deputy, and the treasurer. The results of this prototype can show the best alternative selected based on the ranking method.
A Web-based Group Decision Support System for Retail Product Sales a Case Study on Padang, Indonesia Azmi, Meri; Satria, Deni; Mulya, Farhan Rinsky; Sonatha, Yance; Putra, Dwi Sudarno
JOIV : International Journal on Informatics Visualization Vol 7, No 3 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.3.1331

Abstract

The industrial sector's growth has led to an increase in the number of industrial products available in the market. However, this has made it more challenging for retail merchants to choose which items to sell due to the overwhelming number of options. The seller must carefully consider various factors such as the type, quality, and probability of selling the goods to turn a profit. This research proposes a group decision support system to assist retail sellers in selecting the products to sell. The system is designed to process various information on comparing retail products against specific criteria, enabling sellers to make quick and accurate decisions. To achieve optimal results, this study combines three methods in the decision-making calculation process: Fuzzy Logic, EDAS, and Borda methods. The Fuzzy Logic method is used to assign a value to an unclear criterion, followed by the EDAS method ranking process, and ending with the combination of the decision-making results using the Borda method. The group decision support system is web-based and has been proven to provide effective solutions for retail business actors to increase sales and reduce losses. By using this system, retail sellers can make informed decisions about their products, enabling them to optimize their profits and reduce their risks. In conclusion, the increase in the number of industrial products has created challenges for retail merchants, but this research proposes a solution in the form of a group decision support system. Combining Fuzzy Logic, EDAS, and Borda methods results in an effective decision-making process that allows retail sellers to make informed decisions and achieve their business goals.
Group Decision Support System Using AHP, Topsis and Borda Methods for Loan Determination in Cooperatives Sonatha, Yance; Azmi, Meri; Rahmayuni, Indri
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.640

Abstract

Cooperatives are one of the business units which purpose is to help the economy of small and medium-sized communities. One of the cooperatives in the city of Padang, West Sumatra, Indonesia is KPN Kapur Warna. The routine business unit managed by KPN Kapur Warna is for savings and loans. So far, the savings and loan process is still done manually, including determining the eligibility of members to receive loans. Determination of the eligibility of members is carried out less objectively, by only looking at the profile of participants in general and the decision-making process is only carried out by one person, namely the chairman of the cooperative. The process that has been carried out so far has often resulted in wrong targets, namely providing loans to members who are not appropriate, resulting in bad credit or delays in paying monthly installments of participants. Therefore, we need a group decision support system that can help solve the above problems. In this study, a group decision support system was made using the AHP, TOPSIS and BORDA methods using five main criteria. The AHP method is used to determine the priority value for each criterion and the TOPSIS method is used to rank each alternative. Each decision maker performs the same process with the two methods, and then voting is carried out using the BORDA method of combining assessments for different decision makers. This study succeeded in providing a reference in determining the eligibility of which members are entitled to receive loans from cooperatives, with results that are more subjective and can help cooperatives in their work efficiently.
Pelatihan Pengenalan Flowgorithm sebagai Solusi Inovatif untuk Mendekomposisi Abstraksi Algoritma untuk Guru MGMP Informatika SMA Kota Padang Sonatha, Yance; Azmi, Meri; Rayendra, Rayendra; Rasyidah, Rasyidah; Suryani, Ade Irma
Jurnal Abdi Masyarakat Indonesia Vol 6 No 1 (2026): JAMSI - Januari 2026
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54082/jamsi.2378

Abstract

Perkembangan teknologi digital menuntut penguasaan keterampilan berpikir komputasional, di mana pemahaman algoritma menjadi fondasi kritis. Namun, pembelajaran algoritma di tingkat sekolah menengah sering terkendala oleh sifatnya yang abstrak. Observasi awal terhadap Guru MGMP Informatika Kota Padang menunjukkan 56% dari 25 responden belum pernah menggunakan alat bantu visual untuk pengajaran algoritma. Pengabdian masyarakat ini bertujuan untuk menjembatani kesenjangan tersebut melalui introduksi dan pelatihan Flowgorithm, sebuah perangkat lunak untuk memvisualisasikan algoritma dalam bentuk flowchart interaktif. Metode pelaksanaan mencakup tahap perencanaan, pendahuluan (pre-test), pelatihan (12 Agustus 2025), pendampingan intensif, dan evaluasi (post-test). Hasil kegiatan menunjukkan peningkatan kompetensi guru yang signifikan. Sebanyak 96% peserta mengalami peningkatan pemahaman konsep algoritma, 92% peserta menjadi terampil menggunakan Flowgorithm, dan 92% lainnya melaporkan peningkatan kepercayaan diri dalam mengajar. Analisis mengungkap bahwa pendekatan "learning by doing", relevansi materi dengan kurikulum, dan antarmuka Flowgorithm yang user-friendly menjadi faktor kunci keberhasilan. Disimpulkan bahwa Flowgorithm efektif sebagai media transisi dari konsep algoritma abstrak ke implementasi nyata, sehingga direkomendasikan untuk diadopsi secara lebih luas dan didukung dengan pelatihan lanjutan.
Community-Based Development of Adaptive Digital SOPs for Hydroponic Farming at BGD Hydrofarm Fazrol Rozi; Yance Sonatha; Fitri Nova; Primawati Primawati; Muhammad Ridwan Kurniawan
Engagement: Jurnal Pengabdian Kepada Masyarakat Vol. 10 No. 2 (2026): May 2026
Publisher : Asosiasi Dosen Pengembang Masyarajat (ADPEMAS) Forum Komunikasi Dosen Peneliti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29062/engagement.v10i2.2180

Abstract

Background: Community-based hydroponic farming at BGD Hydrofarm faces challenges including manual monitoring, static Standard Operating Procedures (SOPs), and limited digital literacy, which reduce operational efficiency and accuracy. This community service program addresses these issues through the introduction of adaptive digital technologies. Purpose of the Study: This study aims to improve hydroponic management practices and strengthen community capacity by co-developing adaptive digital SOPs that support data-driven decision-making at BGD Hydrofarm. Methods: A participatory approach was applied, including needs assessment, co-design sessions, system development, training workshops, and participatory monitoring and evaluation. The GardenKeeper system integrates IoT-based sensors (monitoring pH, TDS, temperature, humidity, and plant visual condition) with generative artificial intelligence (Google Gemini AI) to provide real-time monitoring and adaptive SOP recommendations via a mobile application. Results: The program resulted in reduced manual workload, improved monitoring efficiency, and increased partner confidence in using digital technology. Behavioral shifts from experience-based to data-driven decision-making were observed, with SOP consultations becoming a shared reference for collective action. Partners independently operated the application, and external stakeholders (Ministry of Cooperatives and SMEs, IGES) recognized the system's potential scalability. The before-after comparison showed improved digital confidence, reduced operational errors, and strengthened collaborative decision-making.
An Expert System for Early Detection of Mental Health Conditions Using Certainty Factor and DASS-42 Indri Rahmayuni; Yance Sonatha; Tsalsabila Jilhan Haura; Fazrol Rozi
Jurnal Testing dan Implementasi Sistem Informasi Vol. 4 No. 1 (2026): Jurnal Testing dan Implementasi Sistem Informasi
Publisher : Lembaga Riset dan Inovasi Almatani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/jtisi.v4i1.2214

Abstract

Mental health problems such as depression, anxiety, and stress continue to increase in many countries, while access to professional services is still limited. Many digital screening systems use fixed scoring methods and do not consider uncertainty in user responses. This study developed a web-based expert system by combining the Depression Anxiety Stress Scales (DASS-42) and the Certainty Factor (CF) method to represent uncertainty in overlapping emotional symptoms and provide more flexible screening results. The knowledge base was prepared through consultation with a licensed clinical psychologist and converted into 42 production rules based on the DASS-42 items. Each rule was assigned a confidence value according to expert judgment. The system uses forward chaining to combine active rules and calculate confidence scores for depression, anxiety, and stress at the same time. System evaluation was conducted using 50 community cases aged 18–35 years and compared with independent expert assessment. The overall accuracy reached 86% (43 of 50 cases). The accuracy for each category was 88.2% for depression, 82.3% for anxiety, and 87.5% for stress. Most classification errors occurred between anxiety and stress, which may be related to overlapping symptoms in the DASS-42 instrument. The findings indicate that the proposed system can support early mental health screening through interpretable confidence-based results. However, this study used a limited dataset and only one expert in knowledge development. The system is intended as a screening support tool and not as a replacement for clinical diagnosis.
Co-Authors Ade Irma Suryani Alde Alanda, Alde Aldo Erianda Aldo Erianda, Aldo Andres Saputra Cipto Prabowo Damayanti, Elok Deni Satria Dwi Sudarno Putra Dwiny Meidelfi Ervan Asri Fazrol Rozi, Fazrol Fitri Nova Fitri, Redhatul Gsim, Jamal Gusman, Taufik Hidra Amnur Humaira, Humaira Indra Zandi Indri Rahmayuni Indri Rahmayuni Indri Rahmayuni Iswandi Saputra Kirana, Salsabila Okta Lastri Fatika Sari Meri Azmi Meri Azmi Meri Azmi Meri Azmi Meri Azmi Muhammad Ridwan Kurniawan Mulya, Farhan Rinsky Mutia Rahmi Dewi Nurhayati - Nurhayati - Nurhayati Nurhayati Nurhayati Nurhayati Paboreal Dunque, Kristine Mae Primawati Primawati Putri, Dinda Meivianti Dwi Rasyidah Rasyidah Rasyidah, - Rayendra, Rayendra Rendhika Aditya Rika Idmayanti Rita Afyenni Rita Afyenni Rufi'i Safira Putri Nabila Sistri Indah Purnama Indah Purnama Siti Sa'adiyah Tri Lestari Tsalsabila Jilhan Haura Yogi Febrian Wibawa Yuli Purnama Sari Zeriab Es-sadek, Mohamed