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All Journal Techno.Com: Jurnal Teknologi Informasi Journal of Information Systems Engineering and Business Intelligence Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Informasi dan Teknologi Indonesian Journal of Electrical Engineering and Computer Science Teknosains : Jurnal Sains,Teknologi dan Informatika Kontigensi: Jurnal Ilmiah Manajemen Nusantara Journal of Computers and its Applications
Ira Puspitasari
Information Systems Study Program, Faculty Of Science And Technology, Airlangga University, Mulyorejo Street, Surabaya
Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Physics Social Sciences Other

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Sistem Pendukung Keputusan Pemilihan Siswa Berprestasi di Sekolah Menengah Pertama dengan Metode VIKOR dan TOPSIS Rivanda Putra; Indah Werdiningsih; Ira Puspitasari
Journal of Information Systems Engineering and Business Intelligence Vol. 3 No. 2 (2017): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (302.173 KB) | DOI: 10.20473/jisebi.3.2.113-121

Abstract

Abstrak— Penelitian ini bertujuan merancang dan membangun sistem pendukung keputusan untuk pemilihan siswa berprestasi di SMP Taruna Jaya I Surabaya dengan metode VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) dan Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS). Sistem pendukung keputusan ini dibangun melalui 6 tahap. Tahap pertama adalah pengumpulan data dan informasi melalui wawancara dan analisis dokumen. Tahap kedua adalah pengolahan data dan informasi untuk mendapatkan rancangan sistem yang akan dibangun. Tahap ketiga adalah analisis sistem yang meliputi input data siswa, pembobotan kriteria dengan metode AHP, serta perankingan alternatif dengan metode VIKOR dan TOPSIS. Tahap keempat adalah perancangan sistem menggunakan konsep Object Oriented Design. Tahap kelima adalah implementasi sistem berbasis web. Tahap terakhir adalah evaluasi sistem dengan membandingkan tingkat akurasi antara metode VIKOR dan TOPSIS. Berdasarkan hasil uji konsistensi, terdapat 7 percobaan yang tidak konsisten dan 13 percobaan yang konsisten. Hasil yang diperoleh adalah tingkat akurasi yang tertinggi sebesar 80% dengan menggunakan TOPSIS. Berdasarkan hasil tersebut maka metode TOPSIS dapat digunakan pada kasus pemilihan siswa berprestasi di SMP Taruna Jaya I Surabaya dengan derajat kepentingan antar kriteria adalah nilai aktivitas sedikit lebih penting dari nilai rapot, nilai aktivitas lebih penting dari nilai prestasi, nilai aktivitas sangat kuat penting dari nilai sikap, nilai rapot sedikit lebih penting dari nilai prestasi, nilai rapot lebih penting dari nilai sikap, dan nilai prestasi sedikit lebih penting dari nilai sikap.Kata Kunci— AHP, Pemilihan Siswa Berprestasi, Sistem Pendukung Keputusan, TOPSIS, VIKORAbstract— This research proposes a solution to create a decision support system of student achievement selection using VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) method. The decision support system would resolve the problem of big data processing which needs more effort and more time. The development of decision support system of student achievement selection consisted of 6 phases. The first phase was collecting the data and information via interviews and document analysis. The second phase was data processing to create system design. The third phase was analyzing the system that includes the input of student data, weighing the criteria using AHP method, and rank the alternatives using VIKOR and TOPSIS method. The fourth phase was designing the system using Object Oriented Design. The fifth phase was implementing the system using a web-based. The sixth phase was the evaluation of system by comparing the level of accuracy between VIKOR and TOPSIS methods. Based on the result of consistency test, there were 7 inconsistent experiments and 13 consistent experiments. The result obtained is the highest accuracy rate of 80% by using TOPSIS. Based on these results, TOPSIS method can be used in case of selection of outstanding students in SMP Taruna Jaya I Surabaya with degree of importance among the criteria is activity value was slightly more important than report value, activity value was more important than achievement value, activity value was very important from attitude value, report value was slightly more important than achievement value, report value was more important than attitude value, and achievement value was slightly more important than attitude value.Keywords— AHP, Decision Support System, Student Achievement Selection , TOPSIS, VIKOR
The Continuance Intention of User’s Engagement in Multiplayer Video Games based on Uses and Gratifications Theory Ira Puspitasari; Elzha Odie Syahputra; Indra Kharisma Raharjana; Ferry Jie
Journal of Information Systems Engineering and Business Intelligence Vol. 4 No. 2 (2018): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (575.69 KB) | DOI: 10.20473/jisebi.4.2.131-138

Abstract

One of the key success factors in video game industry, including multiplayer video game (MVG), is the user’s continuance intention. The MVG industry runs in a highly competitive market. Users can shift to another game as soon as they discover a slightly inconvenient issue. Thus, maintaining the user’s enthusiasm in playing MVG for a long time is challenging for most games. The solution to prolong the users’ engagement can be initiated by identifying all factors that facilitate the continuance use of playing MVG. This study applied uses and gratifications theory to examine seven variables (enjoyment, fantasy, escapism, social interaction, social presence, achievement, and self-presentation) and the moderating effects of age and gender on the MVG continuance intention. The data analysis and the model development were tested based on Partial Least Square method using the responses of 453 MVG users. The results revealed that enjoyment, fantasy, social interaction, achievement, and self-presentation significantly affected the continuance intention of playing MVG, with enjoyment being the strongest variable. The result also demonstrated the moderating effect of age and gender on the relation between independent variables and continuance intention. The results and findings offered additional insights into the system development to enhance the information system application.
Clustering of Drug Sampling Data to Determine Drug Distribution Patterns with K-Means Method : Study on Central Kalimantan Province, Indonesia Wahyuri Wahyuri; Umi Athiyah; Ira Puspitasari; Yunita Nita
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 2 (2019): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1970.953 KB) | DOI: 10.20473/jisebi.5.2.208-218

Abstract

Background: Drug sampling and testing in the context of post-marketing control is an important component to ensure drug safety in the supply chains. The results are used by the Indonesian National Agency for Drug and Food Control (NA-FDC) for conducting public warnings, evaluating the Good Manufacturing Practice (GMP) and Good Distribution Practice (GDP) implementation, and enforcing the law against drug violation.Objective: This study aimed to identify and analyze drug distribution patterns to provide an overview of drug sampling in the public sector. Methods: The data was collected from Balai Besar Pengawas Obat dan Makanan (BBPOM) Palangka Raya’s database. The collected data were the drug sampling data from Integrated Information Reporting Systems (IIRS) application from 2014 to 2018. Next, we employed CRISP-DM methodology to analyze the data and to identify the pattern. K-means clustering model was selected for data modeling.Results: The dataset contained five attributes, i.e., drug name, therapeutic classes, district/city, sample category, and evaluation of drug surveillance. The drug distribution pattern formed three clusters. First cluster contained 522 drug items in eight therapeutic classes and spread over ten districts, second cluster contained 1542 drug items in five therapeutic classes and spread over five districts, and third cluster contained 503 drug items in eleven therapeutic classes and spread across nine districts.Conclusion: To conclude, the applied data mining technique has improved the decision on the drug sampling planning. It also provides in-depth information on the improvement of drug post-marketing control performance in Central Kalimantan Province.Keywords: Clustering, CRISP-DM, Data Mining, Drug distribution patterns, Drug quality control, Drug sampling
Evaluation of the Electronic Structure Resulting from ab-initio Calculations on Simple Molecules Using the Molecular Orbital Theory Samuel E P P Masan; Fitri N Febriana; Andi H Zaidan; Ira Puspitasari; Febdian Rusydi
Jurnal Penelitian Pendidikan IPA Vol. 7 No. 1 (2021): January
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v7i1.545

Abstract

Hartree Fock (HF) and Density Functional Theory (DFT) have been commonly used to model chemical problems. This study uses the Molecular Orbital Theory (MOT) to evaluate the electronic structure of five diatomic molecules generated by HF and DFT calculations. The evaluation provides an explanation of how the orbitals of a molecule come to be and how this affects the calculation of the physical quantities of the molecule. The evaluation is obtained after comparing the orbital wave functions calculated by MOT, HF, and DFT. This study found that the nature of the Highest Occupied Molecular Orbital (HOMO) of a molecule is determined by the valence orbital properties of the constituent atoms. This HOMO property greatly influences the precision of calculating the molecular electric dipole moment. This shows the importance of understanding the orbital properties of a molecule formed from the HF and DFT calculations
Design and development of activity attendance monitoring system based on RFID Ray Adderley Jm Gining; S.S.M. Fauzi; I.M. Ayub; M.N.F. Jamaluddin; Ira Puspitasari; Okfalisa Okfalisa
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 1: January 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i1.pp500-507

Abstract

Attending activities organized by the university or institution is one of the important criteria that must be fulfilled by students for multiple purposes. Whether it is by attending classes, or any other activities, the main concern is focused on the process of recording students’ attendance. The use of a paper-based manual system to record students’ attendance is still being widely used due to the lack of an e-management system. These approaches have a lot of disadvantages due to the nature of the paper which is a fragile material - also an expensive cost to procure and produce. This paper, relying on Radio Frequency Identification (RFID), designed and developed an electronic system known as Activity Attendance Monitoring System (AAMS) that utilizes readily available resource – student card, as the student identification when attending an activity. Results from the validation, execution and continuous test suggest that AAMS can be effectively implemented to monitor and record student’s attendance. The main contribution of the study is the design and development model that capable of monitoring students’ activity attendance in university activities context. Developers and researcher in the area can adopt the proposed design and development model in formulating a similar system in managing activity attendance.
Prediksi Guru Kemungkinan Tetap Bekerja di Sekolah Al Uswah Surabaya Menggunakan Machine Learning Mochammad Edris Effendi; Imam Yuadi; Ira Puspitasari
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v5i2.361

Abstract

Penelitian ini bertujuan untuk memprediksi potensi tetap bekerjanya guru di Sekolah Al Uswah Surabaya, sehingga dapat meminimalisir tingkat turnover. Peneliti telah menggunakan algoritma klasifikasi untuk mengetahui algoritma yang paling cocok dalam memprediksi turnover guru dan diproses dengan aplikasi orange data mining. Berdasarkan tabel hasil prediksi maupun confusion matrix, menghasilkan rekomendasi bahwa algoritma yang paling bagus performanya adalah Logistic Regression. Tingkat Presicion untuk perbandingan data training dan testing 80:20 mencapai 80,8%, lebih tinggi dibanding tiga algoritma lainnya yang di bawah 80%. Melalui penelitian ini dapat memperjelas bahwa untuk studi kasus prediksi turnover karyawan, dapat menggunakan parameter Presicion. Melalui hasil penelitian dapat membantu lembaga pendidikan dalam merekrut guru yang memiliki peluang bisa bertahan lebih lama dengan memanfaatkan beberapa atribut standar dari biodatanya.
ANALISIS PENGGUNAAN METODE SEARCH ENGINE OPTIMIZATION (SEO) DALAM STRATEGI PENINGKATAN WEBOMETRICS Salsabila Devina Atmaranti; Badrus Zaman; Ira Puspitasari
NJCA (Nusantara Journal of Computers and Its Applications) Vol 5, No 1 (2020): Juni 2020
Publisher : Computer Society of Nahdlatul Ulama (CSNU) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36564/njca.v5i1.185

Abstract

Globalisasi pendidikan tinggi saat ini diharapkan mampu meningkatkan mutu dan akses perguruan tinggi. Hal tersebut sejalan dengan salah satu kebijakan strategis Kementerian Pendidikan dan Kebudayaan (Kemendikbud) tentang kebijakan pemerataan dan perluasan akses, mutu dan daya saing lulusan. Sehingga diharapkan setiap institusi pendidikan tinggi di Indonesia bisa memposisikan dirinya dalam deretan World Class University (WCU). Webometrics menjadi salah satu lembaga pengakreditasi WCU. Upaya yang telah dilakukan oleh dua puluh perguruan tinggi di Indonesia yang menduduki peringkat teratas di webometrics untuk meningkatkan ranking sangat beragam, diantaranya dengan menggunakan metode Search Engine Optimization (SEO) seperti On-Page SEO dan Off-Page SEO. Upaya ini dilakukan untuk meningkatkan kualitas maupun kuantitas konten agar nilai pada indikator visibility webometrics perguruan tinggi meningkat. Penelitian ini bertujuan untuk menganalisis penggunaan metode SEO serta mengidentifikasi metode SEO yang efektif digunakan untuk meningkatkan visibility dalam perangkaian Webometrics pada kedua puluh peringkat pertama perguruan tinggi di Indonesia yang ada di Webometrics. Tahapan dalam penelitian ini yaitu meliputi pengumpulan data, perhitungan visibility tiap perguruan tinggi periode Juli 2019, analisis pada tiap tools SEO terhadap masing – masing perguruan tinggi, perhitungan visibility tiap perguruan tinggi periode Januari 2020, analisis hasil kondisi setelah  upaya peningkatan visibility, evaluasi dan strategi jangka panjang. Hasil penelitian menunjukkan bahwa Metode white hat SEO yaitu Off-Page SEO dan On-Page SEO merupakan metode SEO yang baik digunakan oleh perguruan tinggi untuk meningkatkan peringkat webometrics. Globalisasi pendidikan tinggi saat ini diharapkan mampu meningkatkan mutu dan akses perguruan tinggi. Hal tersebut sejalan dengan salah satu kebijakan strategis Kementerian Pendidikan dan Kebudayaan (Kemendikbud) tentang kebijakan pemerataan dan perluasan akses, mutu dan daya saing lulusan. Sehingga diharapkan setiap institusi pendidikan tinggi di Indonesia bisa memposisikan dirinya dalam deretan World Class University (WCU). Webometrics menjadi salah satu lembaga pengakreditasi WCU. Upaya yang telah dilakukan oleh dua puluh perguruan tinggi di Indonesia yang menduduki peringkat teratas di webometrics untuk meningkatkan ranking sangat beragam, diantaranya dengan menggunakan metode Search Engine Optimization (SEO) seperti On-Page SEO dan Off-Page SEO. Upaya ini dilakukan untuk meningkatkan kualitas maupun kuantitas konten agar nilai pada indikator visibility webometrics perguruan tinggi meningkat. Penelitian ini bertujuan untuk menganalisis penggunaan metode SEO serta mengidentifikasi metode SEO yang efektif digunakan untuk meningkatkan visibility dalam perangkaian webometrics pada kedua puluh peringkat pertama perguruan tinggi di Indonesia yang ada di webometrics. Tahapan dalam penelitian ini yaitu meliputi pengumpulan data, perhitungan visibility tiap perguruan tinggi periode Juli 2019, analisis pada tiap tools SEO terhadap masing – masing perguruan tinggi, perhitunganvisibility tiapperguruan tinggi periode Januari 2020, analisis hasil kondisi setelah upaya peningkatan visibility, evaluasi dan strategi jangka panjang. Hasil penelitian menunjukkan bahwa metode white hat SEO yaitu Off-Page SEO dan On-Page SEO merupakan metode SEO yang baik digunakan oleh perguruan tinggi untuk meningkatkan peringkat webometrics.
Analisis Sentimen Evaluasi Reaksi E-Learning Menggunakan Algorima Naïve Bayes, Support Vector Machine Dan Deep Learning Nurul Firdausy; Imam Yuadi; Ira Puspitasari
Techno.Com Vol 22, No 3 (2023): Agustus 2023
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/tc.v22i3.8160

Abstract

Evaluasi reaksi atau evaluasi kepuasan merupakan bentuk evaluasi paling umum digunakan dalam pelatihan karena kemudahan dan sifatnya yang lekat dengan pelatihan. Meskipun mengandung wawasan yang dapat bernilai dalam peningkatan kualitas penyelenggaraan pelatihan, namun penelitian terkait reaksi peserta masih sangat terbatas. Penelitian ini bertujuan melakukan analisis sentiment terhadap evaluasi reaksi peserta e-learning menggunakan algoritma Naïve Bayes, Support Vector Machine dan Deep Learning. Reaksi peserta berupa komentar diklasifikasikan ke dalam kategori apresiasi, saran dan kritik. Hasil penelitian menunjukkan model Naïve Bayes memiliki kinerja yang lebih baik dibandingkan SVM dan Deep Learning dalam prediksi sentimen komentar peserta dengan tingkat akurasi, presisi dan recall masing-masing sebesar 82,54%, 68,08% dan 69,81%. Prediksi sentiment reaksi peserta menggunakan model Naïve Bayes diperoleh hasil 70% berupa apresiasi, 16% berupa saran dan 14% merupakan kritik. Penelitian ini memberikan kontribusi praktis analisis evaluasi reaksi pelatihan dan menambah literatur implementasi text mining pada domain human resource analytics. 
Opinion mining toward work from office policies on post-pandemic covid-19 by using supervised learning Tri Hadi Wicaksono; Imam Yuadi; Ira Puspitasari
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 11 No 1 (2024): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK-Sekolah Tinggi Teknologi Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v11i1.525

Abstract

Post-pandemic COVID-19, many companies have re-implemented work from office policies for their employees. However, the policy has been controversial among social media activists, especially in Twitter. The sentiment arose according to them, during the pandemic COVID-19 they believe that working from home has many advantages over working in an office. The emergence of 'work from office' sentiments is an interesting target for opinion-mining research. Opinion mining or sentiment analysis is a general research area of ​​data mining that helps to explore and analyze existing views and opinions to obtain useful information. The analysis process involves the use of machine learning with several supporting algorithms. This study used four classification algorithm models of supervised learning, including naive Bayes, support vector machines, k-nearest neighbors, and random forests. The selection of those algorithms also aims to find out which model produced a good performance for the results. The performance results of each model were evaluated by the confusion matrix and the k-nearest neighbor algorithm model with an accuracy value of 96.62% was found to give the best results and to be the most used model in the classification process. On the other hand, the algorithm model that obtains the lowest accuracy is a random forest with 72.08%.
Implementation of Sentiment Analysis in HR Management and Development Planning Using Topic Modelling on Employee Review Furqon Sandiva Utomo Putra; Ira Puspitasari
Kontigensi : Jurnal Ilmiah Manajemen Vol 11 No 2 (2023): Kontigensi: Jurnal Ilmiah Manajemen
Publisher : Program Doktor Ilmu Manajemen, Universitas Pasundan, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56457/jimk.v11i2.358

Abstract

Employee satisfaction is a crucial factor in the workplace that affects motivation, performance, and overall well-being. Dissatisfaction can lead to high turnover and organizational disruption. Enhancing satisfaction is essential for maintaining productivity and retention. However, gathering accurate data is challenging due to employee hesitancy. Career websites offer a platform for anonymous reviews; however, analyzing vast amounts of textual data can be overwhelming. Moreover, management needs to identify which aspects require priority for improvement. This study proposes a data analytics approach using sentiment analysis and topic modelling to assess employee satisfaction and identify contributing aspects. The method was applied to 9,000 publicly available reviews of Accenture on Glassdoor. The proposed method can provide insights into the positive or negative perceptions of employees towards the company and categorize them based on common topics. Opportunity mapping was then applied to highlight the areas requiring improvement. This study provides insights into employee opinions and identifies aspects that are satisfactory, lacking, or highly satisfying. This approach offers a valuable framework for organizations seeking to enhance employee satisfaction based on comprehensive data analysis.
Co-Authors Andi H Zaidan Badrus Zaman Elzha Odie Syahputra Febdian Rusydi Ferry Jie Fitri N Febriana Furqon Sandiva Utomo Putra I.M. Ayub Imam Yuadi Indra Kharisma Raharjana M.N.F. Jamaluddin Mochammad Edris Effendi Nurul Firdausy Okfalisa Okfalisa Ray Adderley JM Gining Rivanda Putra S.S.M. Fauzi Salsabila Devina Atmaranti Samuel E P P Masan Sembiring, Rinawati Tri Hadi Wicaksono Umi Athiyah Wahyuri Wahyuri Yunita Nita