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All Journal Decode: Jurnal Pendidikan Teknologi Informasi Indo-MathEdu Intellectuals Journal Jurnal Pengabdian Inovasi Masyarakat Indonesia
Majalista, Riya
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Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Pemilihan Wisudawan Terbaik Menggunakan Sistem Pendukung Keputusan dengan Metode Profile Matching Ermawati, Yuli; Zulkarnain, Zulkarnain; Majalista, Riya
Indo-MathEdu Intellectuals Journal Vol. 5 No. 6 (2024): Indo-MathEdu Intellectuals Journal
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/imeij.v5i6.2225

Abstract

The selection of the best graduate is an important process in the graduation ceremony to recognize students who have demonstrated outstanding academic and non-academic achievements during their studies. However, this process often faces challenges, particularly regarding the subjectivity and complexity of assessment. Therefore, a Decision Support System (DSS) is needed to assist in determining the best graduate objectively and transparently. The criteria used include academic achievements (GPA), involvement in organizational activities, non-academic achievements, attendance, and social contributions. Each criterion is weighted according to its level of importance. With the implementation of this DSS, it is hoped that the selection of the best graduate can be conducted more effectively, efficiently, and fairly. Testing results show that this system can provide accurate results that meet stakeholder expectations.
Keripik Gedebong Pisang: Solusi Inovatif Untuk Pengolahan Limbah Organik yang Bernilai Jual Utami, Astrina; Abelia, Aura Putri; Yuliani, Selvy; Alfarouk, Fadhilatus; Devi, Puspita; Majalista, Riya
Jurnal Pengabdian Inovasi Masyarakat Indonesia Vol. 4 No. 1 (2025): Edisi Februari
Publisher : Program Studi Pendidikan Kimia FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpimi.v4i1.6280

Abstract

Gedebong pisang, meskipun sering dianggap sebagai limbah, memiliki sejumlah keunggulan yang menjadikannya bahan potensial untuk diolah menjadi produk bernilai jual. Kaya akan serat dan nutrisi, gedebong pisang bermanfaat untuk kesehatan pencernaan dan dapat membantu mengurangi risiko penyakit. Selain itu, pengolahan gedebong pisang berkontribusi pada pengurangan limbah organik dan dampak negatif terhadap lingkungan, serta menciptakan peluang ekonomi bagi masyarakat, terutama di daerah pertanian. Ketersediaannya yang melimpah sebagai hasil sampingan dari budidaya pisang menjadikannya bahan baku yang mudah diakses. Namun, statusnya sebagai limbah disebabkan oleh kurangnya pengetahuan dan kesadaran masyarakat tentang potensi pengolahannya, proses pengolahan yang rumit, serta persepsi negatif terhadap gedebong pisang. Keterbatasan pasar untuk produk olahan juga menghambat pemanfaatannya. Oleh karena itu, diperlukan upaya edukasi dan pelatihan untuk mengubah persepsi ini, sehingga gedebong pisang dapat dimanfaatkan sebagai sumber daya yang berharga dan berkontribusi pada peningkatan kesejahteraan masyarakat.
Sistem Pendukung Keputusan Pemilihan Laptop untuk Kebutuhan Kuliah Metode Simple Additive Weighting (SAW) Kurniawan, Rifqi; Majalista, Riya; Ramadhan, Agil; Mirando, Rahmad Dwiki
Indo-MathEdu Intellectuals Journal Vol. 6 No. 4 (2025): Indo-MathEdu Intellectuals Journal
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/imeij.v6i4.3561

Abstract

Laptops are essential devices that support various academic activities for university students, such as writing assignments, programming, graphic design, and attending online classes. However, the wide range of available laptops with varying specifications and prices often makes it difficult for students to choose one that fits their needs and budget. This study aims to develop a Decision Support System (DSS) using the Simple Additive Weighting (SAW) method to assist students in selecting the most suitable laptop based on several relevant criteria. This research is a quantitative descriptive study. Data was collected using questionnaires and literature studies. The test results show that the system can accurately and efficiently generate laptop recommendations that align with user preferences. The conclusion of this study indicates that the application of the SAW method in a DSS is effective in simplifying the decision-making process for selecting laptops for academic purposes.
Sistem Pendukung Keputusan untuk Penerimaan Siswa Baru di MIN 2 Oku Dengan Metode Profile Matching Husniawati, Husniawati; Majalista, Riya; Sari, Rani Puspita; Risalman, Nurmulia Risky
Indo-MathEdu Intellectuals Journal Vol. 6 No. 4 (2025): Indo-MathEdu Intellectuals Journal
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/imeij.v6i4.3581

Abstract

The acceptance of new students is one of the important processes in the world of education that determines the quality of students in an institution. At MIN 2 OKU, the selection process is still done manually, which risks causing subjectivity and inefficiency in decision-making. To address this issue, a Decision Support System (DSS) was developed using the Profile Matching method. The purpose of this research is to design and build a DSS based on the Profile Matching method in order to improve the accuracy and efficiency of new student selection at MIN 2 OKU. This method is used to assess the suitability between the candidate students' profiles and the predetermined criteria, such as academic scores, potential academic tests, interviews, and memorization. This system helps the school provide objective and systematic assessments. The test results show that this decision support system is able to provide student admission recommendations more accurately, fairly, and transparently compared to the manual process. Therefore, this system is expected to improve the quality of the selection process at MIN 2 OKU.
Keripik Gedebong Pisang: Solusi Inovatif Untuk Pengolahan Limbah Organik yang Bernilai Jual Utami, Astrina; Abelia, Aura Putri; Yuliani, Selvy; Alfarouk, Fadhilatus; Devi, Puspita; Majalista, Riya
Jurnal Pengabdian Inovasi Masyarakat Indonesia Vol. 4 No. 1 (2025): Edisi Februari
Publisher : Program Studi Pendidikan Kimia FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpimi.v4i1.6280

Abstract

Gedebong pisang, meskipun sering dianggap sebagai limbah, memiliki sejumlah keunggulan yang menjadikannya bahan potensial untuk diolah menjadi produk bernilai jual. Kaya akan serat dan nutrisi, gedebong pisang bermanfaat untuk kesehatan pencernaan dan dapat membantu mengurangi risiko penyakit. Selain itu, pengolahan gedebong pisang berkontribusi pada pengurangan limbah organik dan dampak negatif terhadap lingkungan, serta menciptakan peluang ekonomi bagi masyarakat, terutama di daerah pertanian. Ketersediaannya yang melimpah sebagai hasil sampingan dari budidaya pisang menjadikannya bahan baku yang mudah diakses. Namun, statusnya sebagai limbah disebabkan oleh kurangnya pengetahuan dan kesadaran masyarakat tentang potensi pengolahannya, proses pengolahan yang rumit, serta persepsi negatif terhadap gedebong pisang. Keterbatasan pasar untuk produk olahan juga menghambat pemanfaatannya. Oleh karena itu, diperlukan upaya edukasi dan pelatihan untuk mengubah persepsi ini, sehingga gedebong pisang dapat dimanfaatkan sebagai sumber daya yang berharga dan berkontribusi pada peningkatan kesejahteraan masyarakat.
Pemilihan Wisudawan Terbaik Menggunakan Sistem Pendukung Keputusan dengan Metode Profile Matching Ermawati, Yuli; Zulkarnain, Zulkarnain; Majalista, Riya
Indo-MathEdu Intellectuals Journal Vol. 5 No. 6 (2024): Indo-MathEdu Intellectuals Journal
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/imeij.v5i6.2225

Abstract

The selection of the best graduate is an important process in the graduation ceremony to recognize students who have demonstrated outstanding academic and non-academic achievements during their studies. However, this process often faces challenges, particularly regarding the subjectivity and complexity of assessment. Therefore, a Decision Support System (DSS) is needed to assist in determining the best graduate objectively and transparently. The criteria used include academic achievements (GPA), involvement in organizational activities, non-academic achievements, attendance, and social contributions. Each criterion is weighted according to its level of importance. With the implementation of this DSS, it is hoped that the selection of the best graduate can be conducted more effectively, efficiently, and fairly. Testing results show that this system can provide accurate results that meet stakeholder expectations.
Penerapan Metode Case Based Reasoning dan Algoritma K-Nearest Neighbor untuk Diagnosa Penyakit dan Hama pada Tanaman Kopi Kuswanto, Joko; Dapiokta, Jum; Majalista, Riya; Sutiono, Edi
Decode: Jurnal Pendidikan Teknologi Informasi Vol. 5 No. 3: NOVEMBER 2025
Publisher : Program Studi Pendidikan Teknologi Infromasi UMK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51454/decode.v5i3.1106

Abstract

Tanaman kopi memiliki peran penting dalam perekonomian Indonesia, namun produktivitasnya sering terhambat oleh serangan penyakit dan hama. Minimnya pengetahuan petani mengenai jenis gangguan pada tanaman kopi menyebabkan proses penanganan sering terlambat atau tidak tepat, sehingga menurunkan kualitas dan kuantitas hasil panen. Penelitian ini bertujuan mengimplementasikan Sistem Pakar berbasis metode Case Based Reasoning (CBR) yang dikombinasikan dengan algoritma K-Nearest Neighbor (KNN) untuk mendiagnosis penyakit dan hama pada tanaman kopi secara lebih akurat. Sistem bekerja dengan menganalisis 39 gejala serta 8 basis aturan yang mewakili berbagai jenis penyakit dan hama. Metode CBR digunakan untuk mencari kasus lama yang memiliki kemiripan tertinggi dengan kasus baru, sementara KNN berperan dalam proses perhitungan similaritas berdasarkan bobot masing-masing gejala. Hasil pengujian menunjukkan bahwa nilai kemiripan kasus baru terhadap kasus penyakit Karat Daun sebesar 0,83, yang berada di atas ambang batas penerimaan umum pada penelitian CBR (0,70–1,00). Hal ini menunjukkan bahwa pendekatan CBR-KNN mampu memberikan diagnosis yang memadai dan relevan. Sistem pakar yang dibangun diharapkan dapat membantu petani dalam mengidentifikasi gangguan pada tanaman kopi secara lebih cepat, tepat, dan berbasis pengetahuan pakar.
Co-Authors Abelia, Aura Putri Alfarouk, Fadhilatus Dapiokta, Jum Devi, Puspita Ermawati, Yuli Husniawati, Husniawati Joko Kuswanto Kurniawan, Rifqi Mirando, Rahmad Dwiki Ramadhan, Agil Risalman, Nurmulia Risky Sari, Rani Puspita Sutiono, Edi Utami, Astrina Yuliani, Selvy Zulkarnain Zulkarnain