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Journal : Jurnal Computer Science and Information Technology (CoSciTech)

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%.
Co-Authors - Hendrick AA Sudharmawan, AA Abdul Azis Said Agung Ramadhanu Akbar Iskandar Alifcha Ghazian Alifia Restu Selvanda Allans Prima Aulia Angga Putra Juledi Arika Juwita Z Ayu Prima Siska Bobi Heri Yanto Budi Jaya Budi Permana Putra Chairul Imam Darnis, Rahmi Dendi Ferdinal Deno Yulfa Ardian Desi Laidawati Dodi Andre Putra DWI JULISA UTARI Dwika Assrani Dzaki Al Fikri Eka Naufaldi Novri Eka Sofianti Fahmi Firzada Fajri Ilhami Andrean Fhajri Arye Gemilang Gunadi Widi Nurcahyo Hasanatul Iftitah Hendro Zalmadani Henky Andema Hermanto Heru Rahmat Wibawa Putra Indah Dwi Putri Irvan Okta Mazhona Ismail Virgo Jefdy Kurniawan Johan Danu Wijaya Jufriadif Na`am, Jufriadif Julius Santony Julius Santony K Kadrahman Lc Granadi Suhaidir Lidia K Simanjuntak Lova Endriani Zen Lusi Kestina M Ilham Aldyno M Mutia Malik, Rio Andika Mardison Mesran, Mesran Mohammad Guntur Montesna Muhammad Arif Zikir Risky Muhammad Ihksan Muhammad Ikhlas Musli Yanto Nandra Sunaryo Nasma Yeni Nasution, Annio Indah Lestari Nuning Kurniasih R Rahmiyanti Rafi Septiawan Putra Ragil Ardiansyah Rahmad Dian Riski Randa Hidayatullah Rivo Stephano Roby Nurbahri Romi Hardianto Ronda Deli Sianturi Rovidatul S Salmiati S Sumijan Sahat Sonang Sitanggang Salman Alfarisi Salimu Sarjo Defit Sarjon Defit Sarjon Defit Septiana Vratiwi Setiawan, Adil Silfia Andini Sri Amalia Harahap Sri Dewi Stefani Hardiyanti Putri Subrianto Chandra Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Syahid Hakam Abdul Halim Syaljumairi, Raemon Teddy Winanda Teguh Junaidi Tessa Y M Sihite Wenni Afrodita Willy Eka Septian Yendi Putra Yosua Ade Pohan Yundari, Yundari Yuniko Fauzan Yusma Elda Zupri Henra Hartomi