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Journal : Jurnal Computer Science and Information Technology (CoSciTech)

Sistem Pendukung Keputusan Menggunakan Metode Multi Attribute Utility Theory Untuk Pemilihan Layanan Digital Ira Nia Sanita; Sarjon Defit; Gunadi Widi Nurcahyo
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4742

Abstract

Dinas Komunikasi, Informatika dan Statistik (Kominfotik) Provinsi Sumatera Barat merupakan Dinas yang diberi kewenangan untuk membangun dan mengembangkan layanan digital untuk semua Perangkat Daerah di Pemerintah Provinsi Sumatera Barat. Seluruh Perangkat Daerah dapat mengajukan permintaan pembangunan layanan digital ke Dinas Kominfotik. Akan tetapi, tidak semua layanan digital yang diminta akan difasilitasi dan diakomodir oleh Dinas Kominfotik. Ada beberapa kriteria pemilihan dalam pembangunan Layanan Digital yaitu Layanan Digital yang sesuai dengan Arsitektur Sistem Pemerintahan Berbasis Elektronik (SPBE) Nasional, mendukung Program Unggulan Pemerintahan Provinsi Sumbar, Quick Win Layanan sesuai Peta Rencana SPBE, tujuan pembuatan layanan digital, serta Bahasa Pemograman yang digunakan dalam pembangunan Aplikasi. Penelitian ini menggunakan metoda Multi Attribute Utility Theory (MAUT). Metode MAUT digunakan untuk menentukan pemilihan layanan digital yang akan dibangun berdasarkan bobot dan kriteria yang sudah ditentukan. Kemudian dilakukan proses perankingan yang akan menentukan pilihan yang menjadi prioritas. Dan dari hasil pengujiannya didapatkan penerapan metode MAUT pada Sistem Pendukung Keputusan pemilihan layanan digital menghasilkan alternatif yang menjadi prioritas (rangking 1) adalah Layanan Penerimaan Peserta Didik Baru (PPDB) dengan nilai 0,933. Kata Kunci : Sistem Pendukung Keputusan, Layanan Digital, Multi Attribute Utility Theory (MAUT)
Sistem pendukung keputusan menggunakan metode analytical hierarchy process (ahp) dalam penentuan kualitas bibit cabai DWI JULISA UTARI; Gunadi Widi Nurcahyo; Yuhandri Yunus
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4743

Abstract

The system is a network of procedures made according to an integrated pattern to carry out the main activities of a company in which there is an information system which is interconnected with one another which ultimately produces information/data that is useful for the intended person according to its designation. Today's Decision Support Systems (DSS) have assisted an organization in helping make important decisions in various sectors. One of them is the agricultural sector. Chili is a horticultural crop that is widely grown by farmers and the community, one of these plants is used as an ingredient for cooking. The purpose of this research is to provide convenience in determining the quality of chili seeds to farmers and the community. The data processed in this study were 5 criteria and 6 alternatives. Data on the quality of chili seeds obtained from the TPHP Office of Sungai Penuh City. The data is processed first, calculated manually and followed by applying calculations from the Analytical Hierarchy Process method. The processing steps determine the weight of each criterion, assign a score (paired comparison), summarize all scores (total weight). During data processing, the level of accuracy is still calculated. The result of testing this method is that the calculation of chili seeds has an accuracy of 83% based on the quality level of the specified criteria. Specifically, the testing decision support system is able to identify the quality of chili seeds. The level of accuracy achieved by the analytical hierarchy process is quite accurate and can help farmers and the community.
Perbandingan algoritma c4.5 dan naive bayes dalam prediksi kelulusan mahasiswa Rovidatul; Yuhandri Yunus; Gunadi Widi Nurcahyo
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4755

Abstract

College management requires graduation predictions to determine early prevention measures for drop out cases. The length of a student's study period can be caused by various factors, so it is necessary to know which students have the potential to graduate not on time. Data mining techniques can be used to explore new knowledge so that it can produce predictions of student graduation. Some algorithms that can be used are C4.5 and Naive Bayes. The purpose of this study was to predict the graduation of students from the Faculty of Social and Political Sciences at Andalas University using the C4.5 and Naive Bayes algorithms. The attributes used are age at college, gender, grade point average 1-4. The data used are FISIP undergraduate students who graduated in 2022 as many as 378. The results show that the accuracy of the Naive Bayes algorithm is better than C4.5 with the highest accuracy of 81.58%.
The Implementation of Artificial Neural Networks to measure the correlation of teacher's workload to the number of own learning media Erizke Aulya Pasel; Yuhandri Yuhandri; Gunadi Widi Nurcahyo Nurcahyo
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4757

Abstract

The use of learning media in the teaching and learning process is an effort to increase the effectiveness and quality of the learning process. However, the need for learning media is not compatible with the number of learning media made by the teacher himself. One of the factors that causes it is the teacher's workload which is quite a lot so that the teacher does not have enough time to make his own learning media. This study aims to measure the extent of the correlation between the teacher's workload and the amount of instructional media that the teacher himself made. Artificial Neural Network with Backpropagation method is a tool that can be used to solve complex problems, one of which is to measure the level of correlation. The ability of an Artificial Neural Network with the Backpropagation method to adapt to changes that occur in the input and output values makes the prediction accuracy quite high. The teacher's workload variables used are the number of face-to-face hours of even and odd semesters, additional assignments (deputy principal/head of laboratory), homeroom teacher, and extracurricular coaches. The target used is the number of learning media made by the teacher himself. The data used in this study were taken from the workload of teachers at SMAN 4 Payakumbuh in 2022. The architectural patterns used are 5-4-1, 5-5-1, 5-7-1, 5-10-1, and 5- 12-1. From the test results with the Matlab R2013a software, the best pattern was obtained, namely the 5-12-1 pattern with an MSE value of 0.1001, a MAPE of 2.11, and a data accuracy of 97.89%. From the results of the training and testing, it was concluded that the correlation between the teacher's workload and the amount of self-made learning media is very low or not closely related.
Prediksi Penjualan Sepeda Motor Yamaha dengan Jaringan Syaraf Tiruan dan Backpropagation (Studi Kasus: CV Sinar Mas) Santriawan, Aji; Gunadi Widi Nurcahyo; Billy Hendrik
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6709

Abstract

Perkembangan teknologi yang begitu pesat dengan kebutuhan masyarakat tentang kendaraan pribadi untuk mempermudah segala aktivitas sehari-hari. Pertumbuhan penduduk Indonesia yang meningkat juga mempengaruhi bertambahnya jumlah kendaraan bermotor yang ada di Indonesia. Sepeda Motor Yamaha merupakan salah satu brand sepeda motor yang telah lama berada di Indonesia. Oleh karena itu konsumen menggunakan sepeda motor saat ini sangatlah tinggi. Dengan peningkatan penjualan dan minat masyarakat terhadap sepeda motor untuk tahun berikutnya. Masalah yang terjadi pada CV Sinar Mas adalah tidak ada metode untuk memprediksi bagaimana kecenderungan peningkatan/penurunan jumlah unit tertentu setiap tahun. Sehinggan dengan Jaringan Syaraf Tiruan menggunakan metode Backpropagation dengan Software Matlab dapat menjadi data prediksi penjualan sepeda motor di bulan berikutnya atau yang akan datang. Penelitian ini bertujuan untuk meningkatkan akurasi penjualan sepeda motor Yamaha pada Cv Sinar Mas. Metode yang digunakan dalam penelitian ini adalah Jaringan Saraf Tiruan Backpropagation. Algoritma Backpropagation digunakan untuk memprediksi dengan akurat berdasarkan data historis penjualan sepeda motor Yamaha dari tahun 2019-2022. Dataset yang digunakan terdiri dari 48 data penjualan. Hasil penelitian ini dapat memprediksi penjualan dengan menggunakan pola terbaik yaitu 4-25-1 dengan hasil MSE 0.00010594. Oleh karena itu penelitian ini dapat menjadi acuan untuk mempredisi penjualan sepeda motor Yamaha pada CV Sinar Mas
Penerapan Metode Fuzzy Logic Dalam Sistem Pemantauan Tanaman Berbasis Internet Of Things (Iot) Dengan Arduino sabil, Muhammad; Sarjon Defit; Gunadi Widi Nurcahyo
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6710

Abstract

Hydroponic plants in this increasingly modern era, people are increasingly aware that their vegetable needs must be met so that the body's nutritional balance can be met properly. One of the Urban Farming that is suitable in urban areas with narrow dominant land is the hydroponic system. Hydroponics comes from two Greek syllables combined, namely hydro which means water and ponos which means work, so hydroponics means working using air. One of the advantages of this agricultural system is the minimal use of land, where even small areas of land can be utilized. well. Hydroponics is agricultural cultivation without using soil, so hydroponics is an agricultural activity that is carried out using air as a medium to replace soil. Hydroponic systems are increasingly popular among farmers and agricultural service providers because they are able to produce healthier and more productive plants without using soil as a growing medium. This research aims to test the performance of an Internet of Things (IoT) based Hydroponic Monitoring System using Arduino on plants or vegetables with the method used in this research is Fuzzy logic. This method has 3 stages, namely Fuzzification, Defuzzification, Fuzzy Rule. The data set processed in this research was taken from measurements of pH and temperature on hydroponic vegetable plants in the PKK garden of Kemantan Kebalai Village. The dataset consists of 340 data. The results of this research can identify and calculate the percentage of pH and temperature measurements with an accuracy level of 90%. Therefore, this research can be a reference in measuring acid, normal and alkaline levels in hydroponic plants.
Co-Authors A Alfarisdon AA Sudharmawan, AA Abdi Rahim Damanik Afifah Cahayani Adha Afriosa Syawitri Agung Ramadhanu Ahmad Zamsuri, Ahmad Alexyusandria alexyusandria Alfarisdon, A Ali Djamhuri Andi, Muhammad Yusril Haffandi Anggraini, Siska Dwi Anita Sindar Apriade Voutama Ardia Ovidius ardialis Asyhari, Ahmad Aulia Mardhatilla Ayudia, Dina Ayunda, Afifah Trista Bayu Rianto Billy Hendrik Boy Sandy Dwi Nugraha.H Breinda, Engla Budayawan, Khairi Budiarti, Lela Bufra, Fanny Septiani Candra Putra Cyntia Lasmi Andesti Cyntia Trimulia Damanik, Abdi Rahim Daniel Theodorus Darma Yunita Darmawi Darnis, Rahmi Dedi Irawan Deri Marse Putra Dina Ayudia Dinda Permata Sukma DWI JULISA UTARI Dwi Utari Iswavigra Dyan Mardinata Putra Eka Putra, Dian Elfina Novalia Erizke Aulya Pasel Faisal Roza Fajri Karim Fanny Septiani Bufra Fauzan Azim Fauzi Erwis Febriani, Widya Febrina, Yerri Kurnia Fernando Ramadhan Fitriani, Yetti Fortia Magfira Gaja, Rizqi Nusabbih Hidayatullah Hafid Dwi Adha Handika, Yola Tri Hartati, Yuli Hasni, Salmi Hazlita, H Hendrik, Billy Honestya, Gabriela Humairoh, Putri Idir Fitriyanto Idir Ilham Effendi Indah Savitri Hidayat INTAN NUR FITRIYANI Ipri Adi Ira Nia Sanita Jefri Rahmad Mulia Johan Harlan Jufri, Fikri Ramadhan Jufriadif Na`am, Jufriadif Jufriadif Na’am Juliantho, Dwana Abdi Julius Santoni Julius Santony Julius Santony Julius Santony Julius Santony Julius Santony Karim, Fajri Khelvin Ovela Putra Kholil, Muhammad Irvan Larissa Navia Rani Leony Lidya Lidia Sutra Lova Endriani Zen Lubis, Fitri Amelia Sari Lusi Kestina Luth Fimawahib M Mutia M, Mutia M. Almepal Wanda M. Ibnu Pati Mardayatmi, Suci Mardison Mardison Marfalino, Hari Meilinda Sari Meilinda Sari Melissa Triandini Miftahul Hasanah Miftahul Hasanah, Miftahul Miftahul Mardiyah Mike Zaimy Muhammad Irvan Kholil Nabila, Tuti Nadia, Nadia Aini Hafizhah Nadya Alinda Rahmi Nasution, Amir Salim Khairul Rijal Nia Nofia Mitra Nissa, Ika Ima Nst, Ely Nurhalizah Nur Azizah Nur, Rofil M Nurdini, Siti Pati, Muhammad Ibnu Pebriyanti, Defi Petti Indrayati Sijabat Puji Chairu Sabila Putra, Akmal Darman Putra, Deri Marse Putra, Dyan Mardinata Putri Humairoh Putri, Stefani Putut Wicaksono, Putut Radillah, Teuku Rafiska, Rian Rahmad Supriadi Rahman, Zumardi Ramadhanu, Agung Riati, Itin Rika Apriani Rika Apriani, Rika Ririn Violina Ritna Wahyuni Rizka Hafsari Rizki Mubarak Roby Nurbahri Roni Salambue Rovidatul Rozakh, Muhammad Rusnedy, Hidayati Rustam, Camila S Sumijan Sabil, Muhammad Sahari Sahari Sahri, Alfi Sajida, Mayang Sandi Alam Sandrawira Anggraini Sani, Rafikasani Santriawan, Aji Sari, Fitri P. Sarjon Defit Sarjon Defit Sarjon Defit Septiana Vratiwi Sharon Sintia Sintia Siregar, Fajri Marindra Sisi Hendriani Siska Dwi Anggraini Siti Nurdini Sovia, Rini Sri Handayani Sri Layli Fajri Stefani Hardiyanti Putri Suci Mardayatmi Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan, S Suri, Melati Rahma Sutra, Lidia Syafri Arlis Tesa Vausia Sandiva Ulfa, Ulia Ulfatun Hasanah Ulia Ulfa Verdian, Ihsan Vratiwi, Septiana W Wahyudi Wahyu, Fungki Wahyudi Wahid Wahyudi Wahyudi Wendi Robiansyah Weri Sirait Widya Febriani Yeng Primawati Yerri Kurnia Febrina Yetti Fitriani Yolla Rahmadi Helmi Yoni Aswan Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri, Yuhandri Yuhandri Yunus Yuhandri, Y Yuli Hartati Yunita Cahaya Khairani Yunus, Yuhandri Yuyu, Yuhandri