The potentiality of computational thinking (CT) in problem solving has gained much attention in academic communities. This study aimed at developing and validating an instrument, called Hi-ACT, to assess CT ability of university undergraduates. The Hi-ACT evaluates both technical and soft skills applicable to CT based problem solving. This paper reports a pilot study conducted to test and refine the initial Hi-ACT. Survey method was employed through which questionnaire comprising of 155 items was piloted among 548 university undergraduates. Structural equation modeling with partial least squares was applied to examine the Hi-ACT's reliability and validity. Composite reliability was used to assess internal consistency reliability, while convergent validity was evaluated using based on items' outer loadings and constructs' average variance extracted. As a result, 41 items were excluded, and an instrument to assess CT ability comprising 114 items and ten constructs (abstraction, algorithmic thinking, decomposition, debugging, generalization, evaluation, problem solving, teamwork, communication, and spiritual intelligence) was developed. The reliability and validity of the Hi-ACT in its pilot form have been verified.

AbstrakTaksi merupakan layanan transportasi yang umum ditemui di daerah perkotaan. Untuk menggunakan layanan taksi pengguna dapat menunggu taksi yang lewat atau memesan melalui telepon. Kendala yang terjadi dari metode ini adalah panggilan telepon tidak tersambung karena operator sedang melayani konsumen lain, posisi taksi yang berada jauh dari konsumen, atau konsumen tidak mengetahui posisinya saat ini dengan tepat. Ketika menunggu taksi di jalan, pencarian taksi dapat memakan waktu lama. Makalah ini memaparkan tentang pengembangan aplikasi pencarian taksi berbasis teknologi Android, menggunakan model proses Rational Unified Process dari pendekatan rekayasa perangkat lunak. Implementasi teknologi web service menghasilkan aplikasi pencarian taksi terdekat yang dapat mengintegrasikan aplikasi berbasis web dengan platform berbeda, dengan aplikasi mobile berbasis sistem operasi Android. Pada aplikasi mobile, pengguna dapat mencari taksi terdekat sesuai perusahaan terdaftar yang dilacak menggunakan GPS dan melihat posisi taksi pada peta dari Google Maps Application Programming Interface, melihat informasi taksi, serta memesan taksi atau membatalkan pemesanan. AbstractTaxi is a common transportation services in urban areas. In order to use taxi services customers may wait for a taxicab passing by or make a request by phone. Constraints that may arise from this method are unconnected phone call when the operator is currently serving others, far away taxicab position from the customer, customer knows not about his current position. Moreover, cab searching may take some time. This paper presents the development of Android-based taxicab searching application, using Rational Unified Process model. Implementation of web services technology resulting a taxicab search application that could integrate different platforms web-based applications, with Android-based mobile application. Using mobile application, user can search the nearest cabs tracked by GPS as well as see their positions on a map using Google Maps Application Programing Interface, view some taxicab information, request or cancel reservation.

<p style="text-align:justify">Studies have acknowledged computational thinking (CT) as an efficient approach for problem-solving particularly required in digital workplaces. This research aims to identify indicators for a holistic CT assessment instrument for undergraduate students. A three-round fuzzy Delphi study has been conducted to gain comprehensive opinions and consensus from undergraduate lecturers of computer science disciplines and experts from the information technology industry. In round 1, the experts judged a set of predefined indicators describing CT skills and attitudes identified from the literature, while rounds 2 and 3 focused on variables selection. The consensus was achieved on holistic CT, and the indicators are teamwork, communication, spiritual intelligence, generalization, problem-solving, algorithmic thinking, evaluation, abstraction, decomposition, and debugging. Results demonstrate the importance of attitudes in the process of solving a problem and suggest higher education institutions to consider holistic CT in preparing qualified future graduates. Many CT studies focused only on the skills of CT. This study outlines the assessment indicators that consider both CT skills and attitudes, particularly at the undergraduate level.</p>

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Penelitian ini bertujuan untuk mengukur dan membandingkan kinerja lima algoritma klasifikasi teks berbasis pembelajaran mesin, yaitu decision rules, decision tree, k-nearest neighbor (k-NN), naïve Bayes, dan Support Vector Machine (SVM), menggunakan dokumen teks multi-class. Perbandingan dilakukan pada efektifiatas algoritma, yaitu kemampuan untuk mengklasifikasi dokumen pada kategori yang tepat, menggunakan metode holdout atau percentage split. Ukuran efektifitas yang digunakan adalah precision, recall, F-measure, dan akurasi. Hasil eksperimen menunjukkan bahwa untuk algoritma naïve Bayes, semakin besar persentase dokumen pelatihan semakin tinggi akurasi model yang dihasilkan. Akurasi tertinggi naïve Bayes pada persentase 90/10, SVM pada 80/20, dan decision tree pada 70/30. Hasil eksperimen juga menunjukkan, algoritma naïve Bayes memiliki nilai efektifitas tertinggi di antara lima algoritma yang diuji, dan waktu membangun model klasiifikasi yang tercepat, yaitu 0.02 detik. Algoritma decision tree dapat mengklasifikasi dokumen teks dengan nilai akurasi yang lebih tinggi dibanding SVM, namun waktu membangun modelnya lebih lambat. Dalam hal waktu membangun model, k-NN adalah yang tercepat namun nilai akurasinya kurang.