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Jurnal Sistem Cerdas
ISSN : -     EISSN : 26228254     DOI : -
Jurnal Sistem Cerdas dengan eISSN : 2622-8254 adalah media publikasi hasil penelitian yang mendukung penelitian dan pengembangan kota, desa, sektor dan kesistemam lainnya. Jurnal ini diterbitkan oleh Asosiasi Prakarsa Indonesia Cerdas (APIC) dan terbit setiap empat bulan sekali.
Arjuna Subject : Umum - Umum
Articles 6 Documents
Search results for , issue "Vol. 5 No. 2 (2022)" : 6 Documents clear
Rancang Bangun Sistem Informasi Akademik Menggunakan Framework Codeigniter Pada universitas Muhammadiyah Purworejo Widatama Krisna; Hamid Jumasa Muhammad; Nadia Ambadar
Jurnal Sistem Cerdas Vol. 5 No. 2 (2022)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v5i2.187

Abstract

Academic Information System is a system that provides services that are academic data information designed in accordance with business processes that run to improve the performance and quality of academic services. This academic information system has many benefits for institutions in the field of education, be it in the processing of teaching data, value data, and other data related to academic learning in this case, especially universities. The problem that exists today is the absence of an academic information system at the University of Muhammadiyah that is able to store all academic data. Therefore, academic information systems that can meet the needs are very necessary. This research discusses the design of web-based systems using codeigniter 3 framework which is expected to produce an academic information system that meets the needs.
Evaluasi dan Perbaikan Desain Interaksi Edunex dengan Pendekatan User-Centered Design Alya Mizani; Fetty Fitriyanti Lubis
Jurnal Sistem Cerdas Vol. 5 No. 2 (2022)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v5i2.205

Abstract

Edunex is the Learning Management System used in Institut Teknologi Bandung to support online and hybrid learning and teaching activities. However, there are still some improvements that could be implemented in order to further meet the users’ needs. To do so, the user-centered design approach is used. The development prioritizes implementing fixes in Homepage, My Courses, Exams, and Presences because those pages have high values towards users and high feasibility to fix. Besides that, based on the questionnaire that had been shared, there are needs for new features, such as Reminder and Tutorial that need to be implemented. The outcome of this project is a high-fidelity prototype of a website for desktop screens that fulfills usability and user experience goals effective to use, efficient to use, easy to learn, and helpful. The usability and user experience goals were measured using Completion Rate for effective to use, Single Ease Question (SEQ) for easy to learn, System Usability Scale (SUS) for efficient to use, and Intrinsic Motivation Inventory (IMI) with value/usefulness subscale for helpful. After conducting the evaluation by usability testing, Completion Rate value of 100%, SEQ of 6,9 out of 7, SUS value of 90 out of 100, and IMI value/usefulness value of 6,7 per 7 are achieved. Based on those values, it could be concluded that the prototype designed has fulfilled the usability and user experience goals.
Optimasi Multi-Objektif Proses Pemesinan Milling dengan Metode Taguchi Kolaborasi Grey Relational Analysis Nadila Attin Miftah; Denny Sukma Eka Atmaja; Ayudita Oktafiani
Jurnal Sistem Cerdas Vol. 5 No. 2 (2022)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research focus on multi-objective optimization to minimize surface roughness and maximize material removal rate (MRR) on aluminum alloy 6061 T6. The experiment was designed based on the L9 orthogonal array and was carried out by milling machining process. The input parameters selected from the milling machining conditions are spindle speed, feed rate, and depth of cut. The responses obtained from these experiments are surface roughness and material removal rate. To achieve these two objectives simultaneously, the Taguchi method collaboration with of gray relational analysis can be used. The effect of cutting parameters on surface roughness and MRR can be determined using ANOVA and interaction plots. The optimal parameters to achieve minimum surface roughness and maximum MRR are the combination of a spindle speed of 600 rpm, a feed rate of 50 mm/min, and a depth of cut of 0.7 mm.
Implementasi Algoritma Naïve Bayes Menggunakan Feature Forward Selection dan SMOTE Untuk Memprediksi Ketepatan Masa Studi Mahasiswa Sarjana Dede Kurniadi; Fitri Nuraeni; Sri Mulyani Lestari
Jurnal Sistem Cerdas Vol. 5 No. 2 (2022)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v5i2.215

Abstract

The punctuality of students in completing their studies is an important aspect of the study program. Because there are still students who have not been able to complete their studies on time. The purpose of this study is to determine the factors that influence students in completing their studies by extracting student academic data to obtain a classification model that can be used to predict the accuracy of the study period. The classification method for predicting the accuracy of the student's study period uses the Naive Bayes algorithm using the Feature Forward Selection and SMOTE. The method for data processing in this study uses CRISP-DM. The results of this study are in the form of a classification model to predict the accuracy of the study period of students who obtain a fairly high accuracy value of 87.13%, a recall value of 83.82%, and a precision value of 89.76%, and an AUC value of 0.92. included in the category of Excellent Classification. The use of SMOTE has succeeded in handling Imbalanced Class on the data, and the application of Feature Forward Selection resulted in 5 factors that most influence the accuracy of the student's study period, namely the attributes of Gender, School Category, Year of Entry, Study Program and Grade Point Average for the third semester. The prediction model generated using the Naïve Bayes algorithm, Feature Forward Selection, and SMOTE is expected to help study programs to find out earlier the possibility of students completing their studies on time or not on time.
Bridging Data Sistem Informasi Rumah Sakit (SIMRS) Rumah Sakit Dan Laboratory Information System (LIS) Dhea Kalingga Lintang; Krisna Widatama; Ike Yunia Pasa
Jurnal Sistem Cerdas Vol. 5 No. 2 (2022)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v5i2.227

Abstract

Laboratory Information system (LIS) adalah sistem yang terintegerasi dengan alat yang ada di Unit Laboratorium Rumah Sakit dengan server LIS dengan mengirimkan hasil pemeriksaan. Masalah yang terjadi adalah antara server lokal dengan Sistem Informasi Manajemen Rumah Sakit (SIMRS) belum terhubung. Hal ini karena kode dari LIS belum sesuai dengan SIMRS dan mekanisme pengiriman dan penarikan data antara SIMRS dengan LIS belum terbangun. Akibatnya, petugas bekerja dengan tidak efisien karena melakukan pencatatan manual yang dapat berakibat rawat kesalahan dalam membubuhkan hasil. Kesalahan dalam pencatatan hasil berakibat fatal karena laboratorium berhubungan dengan unit-unit yang lain. Kesalahan pemeriksaan tersebut akan mengakibatkan malpraktik dan kesalahan dalam pencatatan pembayaran tagihan pemeriksaan. Metode yang digunakan dalam penelitian ini yakni mapping (memetakan) data antara data pemeriksaan yang ada di database LIS dengan database SIMRS. Hal ini disebabkan karena kode pemeriksaan di kedua database tersebut berbeda satu sama lainnya. Selain itu, metode pengiriman data yang digunakan yakni menggunakan data JSON (JavaScript Object Notation). JSON merupakan bahasa pemrograman yang memungkinkan setiap server saling bertukar data. Diharapkan dengan metode-metode tersebut, petugas Laboratorium di Rumah Sakit dapat mengefisienkan waktu dan tenaga dalam merekam hasil pemeriksaan laboratorium. Selain itu, keamanan dari data pasien yang melakukan pemeriksaan terjamin oleh sistem.
Analisis Sentimen pada Twitter menggunakan Word Embedding dengan Pendekatan Word2Vec Hastari Utama; Ahlihi Masruro
Jurnal Sistem Cerdas Vol. 5 No. 2 (2022)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v5i2.242

Abstract

In this day and age, the use of social media is familiar to some circles. The existence of social media can be analyzed for certain interests. This analysis can also be carried out for the benefit of knowing the opinions or sentiments that contain it. Therefore, a sentiment analysis is needed to get a classification of existing opinions. The use of sentiment analysis cannot be separated from the document or text representation stage. This usually takes the form of the bag of word (BOW). However, BOW has a weakness, namely it produces a lot of features so that the classification accuracy results are less than optimal. Therefore we need the Word Embedding method to represent documents in vector form. The use of this method results in fewer features so that data training time can be shorter. Apart from that, the syntax and semantics of the words that compose the tweet are also considered. So, Word Embedding produces meaningful vectors.

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