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Journal : Journal of Computer Networks, Architecture and High Performance Computing

Implementation of the ORESTE Method in Determining the Selection of Service Ambassador Events Idaman, Akbar; Arahman, Hamjah; Muis, Abdul; Muhammad Raja Gunung, Tar; Eldo, Handry
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3225

Abstract

The selection of candidates to become Service Ambassadors is an important and complex process. Assessors need to consider many factors and the relative weight of each factor to ensure the best candidate is selected for the position. One method that can be used in candidate selection is the ORESTE method. The ORESTE method is a multi-criteria decision-making method developed by J.P. Brans and B. Mareschal in 1994. This method allows assessors to aggregate multiple criteria and consider the relative weight of each criterion to compare alternatives and produce a ranking of candidates based on the highest relative value. In the context of Service Ambassador selection, the ORESTE method can assist assessors in solving complex decision-making problems and ensuring the best candidate is selected for the position. The method allows raters to consider multiple criteria and consider the relative weight of each criterion, resulting in a ranking of candidates based on the highest relative value. Thus, the use of the ORESTE method in determining the selection of Tourism Ambassadors can simplify and speed up the candidate selection process, as well as increase accuracy and satisfaction in decision making. By using the ORESTE method, the results of the decision to select the winner of the Service Ambassador event are obtained with a preference value of 4.42
Identification of Nervosa Disease using Case-Based Reasoning Gunung, Tar Muhammad Raja; Suri, Riko Muhammad; Purnomo, Nopi; Idaman, Akbar; Muis, Abdul
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3227

Abstract

Among teenagers or adults, body shape greatly affects a person's confidence. Most people will be very confident if their body shape is ideal, where the person will be very confident speaking in public. Different things with people who have a body shape that is too thin/fat, so their confidence is less to appear in public. To get the ideal body shape they will do everything possible, one of which is dieting, taking weight loss capsules, and so on. They do not know the dangers of dieting too strictly and taking weight loss capsules carelessly which can make them contract Nervosa disease. To get the results of the expert system, the case-based reasoning method will be used. After this application is built, the result obtained is the type of nervosa disease based on the symptoms felt by the user.
Comparing Neural Networks, Support Vector Machines, and Naïve Bayes Algorhythms for Classifying Banana Types Jinan, Abwabul; Siregar, Manutur; Rolanda, Vicky; Suryani, Dede Fika; Muis, Abdul
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3381

Abstract

One of the most significant fruits for human consumption is the banana. Fruit consumption not only promotes health but also lowers the risk of heart disease, stroke, digestive issues, hypertension, some cancers, cataracts in the eyes, skin ailments, cholesterol reduction, and, perhaps most importantly, boosts immunity.The study included secondary data, which is information gathered from online resources like Kaggle. Ten categories of bananas will be identified from the 531 total varieties of bananas used as a train dataset: Ambon bananas, Stone bananas, Cavendish bananas, Kepok bananas, Mas bananas, Red bananas, plantains, Milk bananas, Horn bananas, and Varigata bananas. The development of information technology for image object recognition has become a very intriguing topic along with the rapid advancement of society, and it is undoubtedly directly tied to information data. In order to examine Naive Bayes, Support Vector Machine, and Neural Network techniques for classifying banana types, researchers will use the SqueezeNet Deep Learning model to extract features from photos. The study's findings will provide empirical evidence for the distinctions between each algorithm's accuracy, recall, and precision. Based on the collected results, the Neural Network (NN) method is the best in terms of classification, with accuracy of 72.3%, precision of 72.1%, and recall of 72.3%.
Diagnosis and Prediction of Chronic Kidney Disease Using a Stacked Generalization Approach Prabowo, Agung; Wardani, Sumita; Muis, Abdul; Gea, Radiman; Tarigan, Nathanael Atan Baskita
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3611

Abstract

Chronic Kidney Disease (CKD) is. In the past, several learners have been applied for prediction of CKD but there is still enough space to develop classi?ers with higher accuracy. The study utilizes chronic kidney disease dataset from UCI Machine Learning Repository. In this paper, individual approaches, viz., linear-SVM, kernel methods including polynomial, radial basis function, and sigmoid have been used while among ensembles majority voting and stacking strategies have been applied. Stacked Ensemble is based on various types of meta-learners such as C4.5, NB, k-NN, SMO, and logit-boost. The stacking approach with meta-learner Logit-Boost (ST-LB) achieves accuracy 98,50%, sensitivity 98,50%, false positive rate 20,00%, precision 98,50%, and F-measure 98,50% demonstrating that it is the best classi?er as compared to any of the individual and ensemble approaches
Co-Authors ', Adnan A Halim A.A. Ketut Agung Cahyawan W AA Sudharmawan, AA Aat Ruchiat Nugraha Abdul Halik Abwabul Jinan Adi Wijaya Adnan Adnan Adnan Adnan Adnan Afsani, Nazhat Agung Prabowo Agus Supriyadi Ahmad Zain Sarnoto Ainur Rofieq Ajidarmo, Kusno Akbar Idaman Akmal Hidayat Al Ghifari , Abudzar Alamsyar, Al Alfarishy, Salman Alfian Zainuddin, Andi Ali, Makhrus Alimuddin Laapo Alimudin Laapo Amanah, Novi Fajar Anang Aditya Andani Achmad Andi Kurnia Bintang, Andi Kurnia Andi Weri Sompa Andra, Nabila Dwi ANDRI KURNIAWAN Angelica Anjasmara, Jodi Sabar Antonius Galih Prasetyo Aprilia Umar, Ayu Silviani Aprilia, Adinda Arfandi Arfandi, Arfandi Arifah Novia Arifin, Arifah Novia Arifuddin Lamusa Aristiawan, Aristiawan Arsal, A. Farida Arsat, Arsat Asayyidatina Ramadianty, Ashil Asgar, Muhammad Ashaeryanto, Ashaeryanto Ashary, Aldi Asvin nurulita, Asvin Aswar AULIA, FRISCHA AULIYA, NESYA AZ-ZAHRA, FAJAR RAHMA Azwar Anas Bahar, Ashari Basri, Muhammad Iqbal Cahya, Zaid Cahyono Kaelan, Cahyono Dafina Howara Dance Tangkesalu Darsan, Darsan darwis darwis, darwis Dayat Hidayat Dewanto Dewanto Dewi Kartikasari Dewi Puspita Sari Dewi Puspitasari Dian Pertiwi Dwiputri, Intan Aulia Dzulhaq, M. Iqbal Effendy Effendy Eldo, Handry Emyus, A. Zaki Erny Erny, Erny Fadlun, Fadlun Fadsyah, Dewi Fahmy, M. Fawaied Aqiel Fahruddin, Muh. Fakhri M, Faisal Farid Hidayat Figur Muhammad Fikry, Fikry Findi, Findi Fredy Susanto Fuadi, Noor Muhammad Ridha G.H, Muliana Gantima, Febrian M. Gea, Radiman Gunung, Tar Muhammad Raja Gutami, Nanda Itohasi Hadayani Hadayani Hamjah Arahman Hamjah, Muhammad Reza Hamka.L Hanisa, Hanisa Hanny Hafiar Hardiyanti Sultan Hartati Hartati Hasibuan, Dirja Hatmi, Wira Heri Susanto Hiola, Siti Fatimah Hoerniasih, Nia Holili, Moh. I Made Antara Idham Jaya Ganda, Idham Jaya Ihdiani Abubakar Ihsan, Fatih Nur Ilah Nurlaelah Ilyas, Anita Prihatini Inayah, Faidhul Indra Herlamba Siregar Iskendar Iskendar Ismoyo, Kunto Isnaeni, Firda Nur Jaib, Abd. Jamaluddin Jamaluddin Junaidi Junaidi Kadar, Darma Kamali, Ahmad Nur Kartini Kartini Kharismawati, Indah Kismanto, Adhwa Cahyani Kurnia Bintang, Andi Kustiyowati, Kustiyowati Lahandu, Sumiati A. Lantose, Lianti S. Latupeirisa, Yolenta Kartika Sari Laurencia Manurung, Dewi Sartika Laweangi, Fleiss Amelia Lien Damayanti Lubis, Khairuddin Lubis, Siti Sahara Lusnita, Lusnita M, Rizka. Machyono, Machyono Made Krisna Laksmayani Mahmudi Mahmudi Manutur Siregar Marhawati Mappatoba Maricar, Nadra Marliyah, Marliyah Masruroh, Nikmatul Matsura Maulana, Syahrul Max Nur Alam May Adelin Simanjuntak Meilya, Ika Rizqi Melati, Putri Mhd. Idham Khalif Mohammad Adhitya, Mohammad Mubarak, Abdul Mubarok, Rifki Muchsin Muchsin Muh. Taufik Muhadi, Darwati Muhamad Abdul Manan Muhammad Akbar MUHAMMAD ALI Muhammad Hasan Basri Muhammad Junda Muhammad Nasir Muhiddin, Rachmawati A. Muhith, Abd. Mujayati, Mujayati Mustafa Nafi, Muna Khoirun Nasarudin, Akram Nasruddin Nasruddin Nila Kesumawati Ningtyas, Alyiza Dwi Novita, Dila Nugroho, Tsani Hendro Nur Ahyani Nur Izzah Nuraini, Eni Nurdiah, Mey Nurdiana Nurdiana Nurdin, Anwas Nurfadillah Nurfadillah Nurindar, Muyadhil Nurizki, Wanda Gadis Nursalmiati, Nursalmiati Octaviani, Nilam Sari Oslan Jumadi P. S, Glorida Palebangan, Hendra Pangestu, Soleh Patellongi, Ilham Jaya Permata, Nolva Indah Pholboon, Monton Pratama, Krisna Yudha Priawasana, Endra Purnomo, Nopi Puspasari, Syifaa Putra, Kelvin Putri Ulan S, Dian Dwi Putri, Augie Leony Annisa Rachmawaty Rachmawaty, Rachmawaty Raden Mohamad Herdian Bhakti Rahmat Nuryono Ramadianty, Ashil Asayyidatina Ramli, Hartini Ratna Sari Dewi Ratni, Ratni Rina Masadah Ririn Anggraini Riskyani, Siska Kartikasari Ristiana , Evi Ristiana, Evi Rizaldi Payaman, Moh. Rivky Rofiqoh Dewi Rolanda, Vicky Royyan, Mochammad Habib RR. Ella Evrita Hestiandari Rukavina Baksh RUNTUWENE, INNEKE MAGDALENA S, Nur Hidayat Sadsyam, Sriyanty Safitri, Yuni Eka Safuri Musa Saharia Kassa Saleha Saleha Salsabila, Unik Hanifah Santika, Lora Santika, Tika Santomo, Arneta Nindi Santosa, Tomi Apra Saripuddin Muddin Sasmita Sasmita Satriawansyah, Tri Setyo Wibowo Shaliha, Shafa Nabila Sholikah, Mar'atus Sibawaihi Sibawaihi Silalahi, Amin Silanto, Wargo Siregar, Manutur Pandapotan Sirinti, Yulita Sofiyana, Rizka Arista Solissa, Everhard Markiano Sri Utami Sri Wulandari sri, Pungkasaningsih St. Fatmah Hiola Suherman, Ega Sukini, Sukini Sulaeman Sulaeman Sumiati Sumiati Suminar, Uum Sumita Wardani Sunarso Sunarso Suparman Suparman SUPRAYITNO Suri, Riko Muhammad Surya, Erdi Suryani, Dede Fika Sutarjo Sutarjo Suwidiarta, I Putu Oka Syafruddin Syafruddin Syaiful Bachri Tammasse, Jumraini Tar Muhammad Raja Gunung Tari, Dewi Sulis Tarigan, Nathanael Atan Baskita Taufiqurrohman, Heru Tiwi Dianti Tomy, John Tri Setyawan, Moh. Arief Eka Triwahyuni, Eges Tushalih, Amalia Umar, Faisyal Umar, Husaini Unpris Yastanti, Unpris Utami, Sri Dian Veronica Rumintjap wahyuni, Noni sri Walenna, Nirwana Fitriani Wantu, Hasyim Mahmud Waris Waskito, Dwitya Harits Wibawa, I Gede Laksana Wibowo, I Gede laksana Widiani, Ni Kade WILDA, WILDA Windi Windi, Windi Wisda Zulaeha Suwardi Wongkar, Risqa Ananda Putri Wulaa, Nurwapina Langga Wulandary, Andi Sri Rezky Yani Lukmayani Yantu, MR Yasin, Yade. K Yusnia, Yusnia Yusuf Nur Wijayanto, Yusuf Nur Zainal Abidin Zairusi Zairusi Zulaikha, Fatma