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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Algoritma Jurnal Inspiration Jurnal INSYPRO (Information System and Processing) SINTECH (Science and Information Technology) Journal Jurnal Informatika Universitas Pamulang Jurnal RESISTOR (Rekayasa Sistem Komputer) Klasikal: Journal of Education, Language Teaching and Science Indonesian Journal of Data and Science Kharisma Tech Jurnal Algoritma Journal of Technology Research in Information System and Engineering Agents: Journal of Artificial Intelligence and Data Science International Journal of Artificial Intelligence in Medical Issues
izmy alwiah musdar
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Energy Engineering Health Professions Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Public Health Other

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Journal : Journal of Technology Research in Information System and Engineering

 1 
Implementasi Metode Decision Tree Pada Sistem Penunjang Keputusan Penerimaan Karyawan Bank Izmy Alwiah Musdar; Syamsul Bahri; Baizul Zaman
JTRISTE Vol 4 No 1 (2017)
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (258.951 KB)

Abstract

One of the way that company do to get qualified employees is to select the candidates by selection process. In order to perform employee selection more efficient and to avoid the subjectivity of the decision, a Decision Support System (DSS) is required to assist the Human Resource Manager to make the decision making. This research uses Decision Tree method to determine the choice. The results show there are 2 of the 20 test data that is false in prediction. Prediction accuracy is calculated using confusion matrix and the accuracy is 0.9.
Implementasi Metode Decision Tree Dalam Menentukan Pemberian Kredit Mobil Menggunakan Visual Basic (Studi Kasus UD PUTRA MAS Makassar) Junaedy; Izmy Alwiah Musdar; Husni Angriani
JTRISTE Vol 4 No 2 (2017)
Publisher : STMIK KHARISMA Makassar

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Abstract

UD Putra Mas is developing its business by granting credit on automobile purchases. The criteria of calculation used to determine the decision on credit grant is based on the amount of salary, saving, expense, credit count, and a complete set of documents. The process itself meets a couple of obstacles, such as the piling stacks of debtors’ archives in the cabinet and the difficulty in data searching. The purpose of this research is to overcome the obstacles mentioned above. The application used to develop the system is Visual Basic 6.0 and Microsoft Access 2003 as the data management media. The system created is a Decision Support System using Decision Tree Method to obtain the model. The research is based on the result of an interview with the head of UD Putra Mas to collect significant information required by the system. The output of this system is alternative of choices. This research results in a Decision Support System for Credit Grant which helps the head of UD Putra Mas in making decisions.
APLIKASI PREDIKSI KERUSAKAN SMARTPHONE MENGGUNAKAN METODE NAIVE BAYES DAN LAPLACE SMOOTHING Randy; Hasniati; Izmy Alwiah Musdar
JTRISTE Vol 5 No 2 (2018)
Publisher : STMIK KHARISMA Makassar

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Abstract

This study aims to build and implement prediction system of smartphone damage on the android platform. This application was built using android studio 2.0 and SQLite database. The recommendation system is a software that aims to assist users by providing recommendations to users when users are faced with large amounts of information. Recommendations are expected to help users in the decision-making process, such as what items to buy, what laptops will be used, or what songs will be heard, and more. This system serves to provide prediction of damage to the smartphone built from the calculation of user input parameters in the form of questions about the symptoms experienced by users on their smartphone, then will generate predictions about the possibility of damage experienced by using methods naïve bayes and laplace smoothing, this method is used in determining an event using previously collected data. The results of this study indicate that the accuracy is not satisfactory with an accuracy rate of 20%.
PENERAPAN METODE HILL CLIMBING UNTUK MENDIAGNOSA PENYAKIT GANGGUAN SARAF BERBASIS ANDROID Nicolina Djiu; Syaiful Rahman; Izmy Alwiah Musdar
JTRISTE Vol 6 No 1 (2019): JTRISTE
Publisher : STMIK KHARISMA Makassar

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Abstract

This research intend to apply Hill Climbing method to system for diagnose nervous disorders by making an application using android programming. In this system there is symptoms of nervous diseases data which the authors get directly from the results of interviews with a neurologist in the place where author doing research. Hill Climbing method is used to look for possible diseases of nervous disorders by observing the symptoms experienced by the user. The results of the implementation of the system by applying Hill Climbing method to diagnose nervous disorders showed that this method can provide the result of temporary diagnosis in the form of early information about the possibility of disease which suffered by the user.
IMPLEMENTASI MACHINE LEARNING UNTUK MENGIDENTIFIKASI TANAMAN HIAS PADA APLIKASI TIERRA Dhio Immanuel Salintohe; Hasniati; Izmy Alwiah Musdar
JTRISTE Vol 9 No 1 (2022): JTRISTE
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (424.845 KB) | DOI: 10.55645/jtriste.v9i1.360

Abstract

Machine learning adalah sebuah teknologi yang dapat dimanfaatkan untuk mendeteksi suatu objek. Pada penelitian ini machine learning digunakan untuk mengidentifikasi tanaman hias pada aplikasi Tierra dan akan memanfaatkan website teachable machine yang menerapkan algoritma convolutional neural network sebagai tools dalam membuat sebuah model machine learning. Teknik pengumpulan data menggunakan metode observasi dan studi dokumen, selanjutnya dihitung persentasi akurasi hasil pengujian. Untuk proses training data pada website teachable machine akan menggunakan 30 gambar tanaman hias dan hasil yang didapat setelah melakukan pengujian menunjukkan tingkat akurasi machine learning menggunakan tools teachable machine adalah sebesar 89% yang artinya machine learning cukup baik untuk diimplementasikan dalam mengidentifikasi tanaman hias pada aplikasi Tierra.
IMPLEMENTASI DATA MINING MENGGUNAKAN ALGORITMA APRIORI PADA TOKO RUMAH SKINCARE 88 Sugianto, Michael Christian; S, Abdul Munir; Musdar, Izmy Alwiah
JTRISTE Vol 11 No 1 (2024): JTRISTE
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/jtriste.v11i1.511

Abstract

The purpose of this research is to implement the apriori algorithm on sales transaction data of cosmetic products at Rumah Skincare 88 store so that it can help develop marketing strategies and increase sales at the store. The results of this study are that the apriori algorithm was successfully implemented on the sale of cosmetic products at the RumahSkincare88 store. The support values used are 3% and 10% and the minimum confidence values are 30% and 50%. The number of association rules generated is 17 with the highest support value of 14% and the highest confidence of 53.4%. The resulting association rule with the highest support and confidence value is if consumers buy Powder/Foundation then they will also buy Lips. The recommended marketing strategies are Cross-Selling and Bundling. For Cross-Selling strategy that can be applied is if consumers buy Powder/Foundation, then when they want to pay the cashier can offer to buy Lips as well. As for Bundling, the strategy that can be applied is to sell Face Serum and Sunscreen in one package at a special price.
PERANCANGAN DESAIN UI/UX APLIKASI LOWONGAN PEKERJAAN MENGGUNAKAN METODE GOAL DIRECTED DESIGN Pangiawan, Harfandy Putra; Arianti, Arianti; Musdar, Izmy Alwiah
JTRISTE Vol 10 No 2 (2023): JTRISTE
Publisher : STMIK KHARISMA Makassar

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Abstract

This research aims to design the UI/UX for a job vacancy application using the Goal Directed Design method. Data collection was conducted with 20 respondents who had used the Hi Jobs application, and the data was processed using the System Usability Scale (SUS). Based on the first evaluation using the System Usability Scale (SUS) questionnaire, the average score was 33.5, with Acceptability Ranges receiving the label "Not Acceptable," Grade Scales falling into the "F" category, and Adjective Ratings categorized as "Poor." This indicates deficiencies in the user interface design of the Hi Jobs application, both in appearance and features, and it did not meet the standard System Usability Scale (SUS) score of 68.After making improvements to the Hi Jobs application, a final evaluation was conducted using the System Usability Scale (SUS), resulting in an average score of 77. The Acceptability Ranges received the label "Acceptable," Grade Scales were in the "C" category, and Adjective Ratings were categorized as "Good." The findings of this research indicate that the Hi Jobs application, with its UI/UX design focusing on user needs and goals, allows job seekers and employers to interact easily and efficiently. This research contributes positively to the development of job vacancy applications with a focus on satisfying user experiences.
Co-Authors Abdul Munir S. Adys, Himala Praptami Angriani, Husni Arianti Arianti Azhari SN Caroline Layadi Chandra, Rikardo Christofer Veronica Wu Derick Triady Dhio Immanuel Salintohe Erik Wijaya Erlan Darwis Fonda, Surya Fransciska Karundeng Friantika Soplanit Geraldi R Wiwono Gisella Beatrice Ticoalu Gst. Ayu Vida Mastrika Giri Ham, Ficky Hamada Zein Hamdan Arfandy Hasniati Hasniati Hasniati Hasniati, Hasniati Hendra Surasa Hong William Fondy Husni Angriani Judith Bryan Leonard Sie Junaedy Junaedy Junaedy . Kambodji, Audri Billy Layadi, Caroline Marlina marlina Melda, Melda Mohammad Fajar, Mohammad Muhammad Ariq Dzaky Nicolina Djiu Pangiawan, Harfandy Putra Poetro, Bagus Satrio Waluyo Randy Rikardo Chandra Rivaldo Winengko Ronald Kwandy S, Abdul Munir Samuel Pinontoan Sinra, A. St Muriati, St Sugianto, Michael Christian Surasa, Hendra Suwandy Sumbogo Syaiful Rahman Syamsul Bahri Syamsul Bahri Taruk, Medi Triono, Andri Maruli Imanuel Vivian Evania Liauren Willianto Willianto Yandi Aprilian Najoan