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All Journal PILAR Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Pengabdian Magister Pendidikan IPA Kappa Journal Journal of Classroom Action Research Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal) International Journal of Science and Society (IJSOC) Aptekmas : Jurnal Pengabdian Kepada Masyarakat Cantilever: Jurnal Penelitian dan Kajian Bidang Teknik Sipil Journal of Community Service Buletin Ilmu Kebidanan dan Keperawatan Jurnal Keperawatan 'Aisyiyah SOCIRCLE : Journal Of Social Community Services Inovasi Gagasan Abdimas & Kuliah Kerja Nyata Journal of Computation Science And Artificial Intelligence JIQSI : Jurnal Ilmu Al Qur'an dan Studi Islam INFOKOM
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Journal : Journal of Computation Science And Artificial Intelligence

 1 
SISTEM REKOMENDASI MENU MINUMAN DENGAN METODE CONTENT – BASED FILTERING BERBASIS ANDROID PADA MUBTADA KOPI Kosim; Reza Prihandi
Journal of Computation Science and Artificial Intelligence (JCSAI) Vol. 1 No. 1 (2024): Journal of Computation Science And Artificial Intelligence (JSCAI)
Publisher : PT. Berkah Digital Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58468/wmdffh82

Abstract

Overchoice is a cognitive disorder in which people have difficulty making decisions when faced with multiple choices, having too many equivalent options is very mentally draining because each option has to consider several alternatives to choose the best option. During this technological development where everyone is faced with an infinite number of choices every day, this overchoice phenomenon often occurs in everyday life such as choosing a drink at one of the café shops, therefore the Recommendation System is needed to help in choosing the drinks you want to order and to help in choosing other options. Recommendation System (RS) is a subclass of machine learning that is generally concerned with ranking or assessing products or users. These recommendations pertain to the decision-making process, such as what items to buy, what music to hear, or what online news to read. In this study, researchers propose to build a non-personalized hospital at the Mubtada Kopi café with the best rated approach and content-based filtering techniques. The content – based filtering technique will try to take user preferences explicitly, namely asking users to choose the preferences that users want from the 6 previously created content and then calculating the match of user preferences with the 6 contents on each item using the dot matrix formula. After getting the results, the number will be changed to a rating to match the RS approach, which is best rated which is made non-personalized. This rating is an indication of the compatibility of user preferences with the items on the Mubtada Kopi menu list. The larger the rating, the more it matches the user's preferences
COMBINATIVE DISTANCE-BASED ASSESSMENT (CODAS) METHOD IN SELECTING TAHFIZ SCHOLARSHIP ACCEPTANCE AT MANBA'UL 'ULUM Islamic Boarding School Kosim; Igen Meyasha; Mohamad Alif Nurfatah
Journal of Computation Science and Artificial Intelligence (JCSAI) Vol. 1 No. 2 (2024): Journal of Computation Science And Artificial Intelligence (JSCAI)
Publisher : PT. Berkah Digital Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58468/b35qd935

Abstract

Pondok pesantren merupakan lembaga pendidikan islam yang memberikan penerapan pembelajaran agama kepada santriwan dan santriwatinya dengan mengutamakan pengajaran Al-Quran dan Hadis Nabi. Sebagai pendukung para santri dalam kegiatan pembelajaran, pihak pondok pesantren berkewajiban memberikan bantuan berupa beasiswa kepada para santri yang memiliki permasalahan dalam hal keuangan. Pondok Pesantren Manba’ul ‘Ulum merupakan salah satu Pondok Pesantren yang ada di wilayah Kabupten Cirebon yang terdapat beasiswa tahfiz Al-Qur’an. Dikarenakan sistem yang digunakan oleh Pondok Pesantren Manba’ul ‘Ulum belum menggunakan sistem yang berbasis komputerisasi dalam proses menentukan pemilihan penerimaan beasiswa tahfiz, hal ini menyebabkan proses ini tidaklah berjalan secara efisien, untuk itu dibutuhkan sebuah sistem yang dapat membantu proses pemilihan penerima beasiswa tahfiz. Ada banyak metode Sistem Pendukung Keputusan namun peneliti menggunakan metode Combinative Distance-Based Assesment (CODAS) untuk diterapkan kedalam sistem. Hasil yang didapatkan berdasarkan pada nilai dari perhitungan dengan menggunakan metode CODAS, yang diurutkan dari nilai yang terbesar ke yang terkecil. ABSTRAC Islamic boarding schools are Islamic educational institutions that provide the application of religious learning to students and female students by prioritizing the teaching of the Quran and the Prophet's Hadith. As a supporter of students in learning activities, the Islamic boarding school is obliged to provide assistance in the form of scholarships to students who have financial problems. Manba'ul 'Ulum Islamic Boarding School is one of the Islamic Boarding Schools in the Cirebon Kabupten area which has a Qur'an tahfiz scholarship. Because the system used by the Manba'ul 'Ulum Islamic Boarding School has not used a computer-based system in the process of determining the selection of tahfiz scholarship recipients, this causes this process to not run efficiently, for that a system is needed that can help the process of selecting tahfiz scholarship recipients. There are many Decision Support System methods but researchers use Combinative Distance-Based Assessment (CODAS) methods to apply to the system. The results obtained are based on the value of the calculation using  the CODAS method, which is sorted from the largest value to the smallest.
ALGORITMA NAÏVE BAYES CLASSIFIER UNTUK MENGETAHUI PREDIKSI PENGGUNAAN KARTU INTERNET INDOSAT PADA PT. SAKALAGUNA SEMESTA Susi Widyastuti; Kosim; Nurul Renita Febrisya
Journal of Computation Science and Artificial Intelligence (JCSAI) Vol. 2 No. 1 (2025): Journal of Computation Science And Artificial Intelligence (JSCAI)
Publisher : PT. Berkah Digital Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58468/tcp39749

Abstract

Kartu perdana internet pada saat ini menjadi hal yang populer di berbagai kalangan masyarakat Dalam menghasilkan suatu produk yang sama atau sejenis dengan kualitas dan mutu yang baik, hal ini yang membuat perusahaan berlomba-lomba untuk mengetahui keinginan dan kebutuhan para konsumen agar menghasilkan kartu perdana internet yang banyak diminati konsumen. Prediksi penggunaan kartu internet dengan minat konsumen akan sangat penting bagi perusahaan, dimana dengan adanya prediksi penggunaan minat konsumen perusahaan dapat mengambil suatu keputusan atau strategi yang benar dan tepat bagi konsumennya. Proses memprediksi menggunakan perhitungan metode algoritma naïve bayes classifier. Hasil output dalam aplikasi ini berupa visualisasi informasi pengelompokan jenis kartu internet indosat berdasarkan data kartu internet Indosat, diharapkan mampu untuk menentukan prediksi penggunaan serta dapat menentukan produk kartu internet indosat terunggul. Abstract Internet starter cards are currently popular among various groups of people. In producing the same or similar products with good quality and quality, this is what makes companies compete to find out the desires and needs of consumers in order to produce internet starter cards that are in great demand by consumers. Predicting the use of internet cards with consumer interest will be very important for the company, where with the prediction of consumer interest usage, the company can make a decision or strategy that is right and appropriate for its consumers. The prediction process uses the naïve bayes classifier algorithm method calculation. The output results in this application are in the form of visualization of information on grouping types of Indosat internet cards based on Indosat internet card data, which is expected to be able to determine usage predictions and determine the best Indosat internet card products.
metode vlsekriterijumsko kompromisno rangiranje (vikor) untuk menentukan lokasi gudang pada sinar alam caakrabuana Gina Putri Yustina; Kosim; Fajriatus Sholehah
Journal of Computation Science and Artificial Intelligence (JCSAI) Vol. 2 No. 2 (2025): Journal of Computation Science and Artificial Intelligence (JCSAI)
Publisher : PT. Berkah Digital Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58468/jcsai.v2i2.23

Abstract

Pemilihan lokasi gudang di PT. Sinar Alam Cakrabuana secara tradisional dilakukan secara manual, sehingga menimbulkan inefisiensi dan kesalahan perhitungan akibat banyaknya data yang diproses. Penelitian ini mengusulkan sistem pendukung keputusan menggunakan metode VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) untuk menentukan lokasi gudang yang optimal di antara beberapa alternatif. VIKOR merupakan teknik pengambilan keputusan multikriteria (MCDM) yang menyeimbangkan kriteria yang saling bertentangan dan tidak sepadan dengan menggabungkan faktor objektif dan subjektif. Kriteria yang dipertimbangkan meliputi jarak tempuh, waktu tempuh, kondisi jalan, dan keamanan, yang masing-masing diberi bobot tertentu. Hasil penelitian menunjukkan bahwa metode VIKOR efektif dalam memeringkat alternatif dan mengidentifikasi lokasi terbaik. Sistem ini mengurangi kesalahan manusia, meningkatkan akurasi keputusan, dan mempercepat proses pemilihan. Penelitian ini menunjukkan penerapan VIKOR dalam perencanaan lokasi gudang dalam konteks industri nyata. Abstract The selection of warehouse locations at PT. Sinar Alam Cakrabuana has traditionally been conducted manually, leading to inefficiencies and calculation errors due to the volume of data processed. This study proposes a decision support system using the VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method to determine the optimal warehouse location among several alternatives. VIKOR is a multi-criteria decision-making (MCDM) technique that balances conflicting and non-commensurable criteria by combining objective and subjective factors. The criteria considered include travel distance, travel time, road conditions, and security, each assigned specific weights. The results show that the VIKOR method effectively ranks alternatives and identifies the best location. The system reduces human error, improves decision accuracy, and accelerates the selection process. This research demonstrates the applicability of VIKOR in warehouse location planning within a real industrial context.
Co-Authors A. Wahab Jufri Afandi, Samsul Agusti, Adriyan Dwi Ahmad Busyairi, Ahmad Ahmad Harjono Al Jarwi, Muh. Arafatir Alrizal, Fahmi Firdaus Aris Doyan Biyanti, Alifia Cikha Devi, Via Monica Edellweisse Silvia Salsabella Ema Arum Rukmasari Fadlurrohman, Ibrahim Zauqi Faisal Akbar Fajriatus Sholehah Gina Putri Yustina Gunawan Gusgus Ghraha Ramdhanie Hafizhah, Dini Salma Haula Lodiosi Heri Sulistiyono, Heri Hesti Platini Hikmawati husnul fuadi, husnul I Wayan Gunada Ibrahim Igen mayesha Igen Meyasha Indrayani Iqlima, Sheiliana Jannatin Ardhuha JANNATIN ARDHUHA, JANNATIN Jaswadi Joni Rokhmat Kadori, Ilman Kuswantoro M.A. Muazar Habibi Maulana, Indra Maulana Mertasari, Komang Ayu Miqro’ Fajari Lathifah Mochammad Hasymi Somaida Mohamad Alif Nurfatah Muh. Makhrus Muhajirah Muhammad Arif Muhammad Erwanto MUHAMMAD TAUFIK Muhammad Zuhdi Mulia, Finda Restu Muliadi, Irman Nadra Mutiara Sari3 Ni Nyoman Sri Putu Verawati Nisrina, Nina Nurul Renita Febrisya Putri, Amanda Salma Qori Khoirun Nisa Qothrunnada, Qothrunnada Reza Prihandi Rezkiyanni, Annisa Rohkmat, Joni Saputri, Baiq Andriani Satutik Rahayu Susi Widyastuti Susilawati Sutrio Syahrial Ayub, Syahrial Teti Zubaidah Virgiyanti WAHYUDI Widia Hastuti Zainuddin