Articles
<![CDATA[Aplikasi Web Service Perbankan untuk Pembayaran Formulir Pendaftaran Mahasiswa Baru ]]>
<![CDATA[Adi, Puspaningtyas Sanjoyo]]>
<![CDATA[ Media Teknika Vol 12, No 2 (2017) ]]>
Publisher : <![CDATA[Sanata Dharma University ]]>
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DOI: 10.24071/mt.v12i2.1087
<![CDATA[The new student registration process begins with the process of filling out the registration form where to get it, the prospective student pays to get the form. Sanata Dharma University cooperates with the bank to develop an application to pay registration form with web service technology. The advantage of this technology is electronic service and can work 24 hours. Web service technology is a service that allows communication between machines performed through a computer network with HTTP protocol web server. The web service application was developed and implemented by Sanata Dharma University and CIMB Niaga bank in October 2017. From the observation of January 2018 compared to January 2017, the January 2018 transaction increased by about 12% compared to January 2017. The proportion of web service transactions is around 30% of total transactions where 80% of them are conducted outside office hours. This data indicates that the knowledge of electronics services of prospective students and their parents is good enough.Keywords: web service, registration form, new students]]>
<![CDATA[Program Bantu Diri Terapi Kognitif Perilaku: Harapan bagi Penderita Depresi ]]>
<![CDATA[Susana, Tjipto]]>;
<![CDATA[Parmadi, Eko Hari]]>;
<![CDATA[Adi, Puspaningtyas Sanjoyo]]>
<![CDATA[ Jurnal Psikologi Vol 42, No 1 (2015) ]]>
Publisher : <![CDATA[Faculty of Psychology, Universitas Gadjah Mada ]]>
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DOI: 10.22146/jpsi.6944
<![CDATA[This article is the first-phased report of a research through a testing of cognitive behavioral therapy module. The subjects involved in this research were 27 students who were experiencing mild to moderate depression. The research design was experiment with a pretest and posttest group. Instruments used in this study were Back Depression Inventory-II (BDI-II), Automatic Thought Questionnaire (ATQ), Dysfunctional Attitude Scale (DAS). The data was analized using paired t-test. Based on qualitative analysis, the results showed that in general it was easy for the students to understand and do the module independently. This module was very helpful for them in managing thoughts and feelings and specifically in the automatic negative thoughts, dysfunctional thinking, and rules. Nevertheless, this module did not cover the core belief. The results of the t test (t (25)=9.2; p]]>
<![CDATA[Development Study of Deep Learning Facial Age Estimation ]]>
<![CDATA[Adi, Puspaningtyas Sanjoyo]]>
<![CDATA[ International Journal of Applied Sciences and Smart Technologies Volume 01, Issue 01, June 2019 ]]>
Publisher : <![CDATA[Universitas Sanata Dharma ]]>
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DOI: 10.24071/ijasst.v1i1.1899
<![CDATA[Human age estimation is one of the most challenging problem because it can be used in many applications relating to age such as age-specific movies, age-specific computer applications or website, etc. This paper will contribute to give brief information about development of age estimation researches using deep learning. We explore three recent journal papers that give significant contribution in age estimation using deep learning. From these papers, they selected classification methods and there is gradual improvement in result and also in selected loss function. The best result gives MAE (mean average error) 2.8 years and VGG-16 is the most selected CNN architecture.]]>
<![CDATA[Aplikasi Web Service Perbankan untuk Pembayaran Formulir Pendaftaran Mahasiswa Baru ]]>
<![CDATA[Puspaningtyas Sanjoyo Adi]]>
<![CDATA[ Media Teknika Vol 12, No 2 (2017) ]]>
Publisher : <![CDATA[Sanata Dharma University ]]>
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DOI: 10.24071/mt.v12i2.1087
<![CDATA[The new student registration process begins with the process of filling out the registration form where to get it, the prospective student pays to get the form. Sanata Dharma University cooperates with the bank to develop an application to pay registration form with web service technology. The advantage of this technology is electronic service and can work 24 hours. Web service technology is a service that allows communication between machines performed through a computer network with HTTP protocol web server. The web service application was developed and implemented by Sanata Dharma University and CIMB Niaga bank in October 2017. From the observation of January 2018 compared to January 2017, the January 2018 transaction increased by about 12% compared to January 2017. The proportion of web service transactions is around 30% of total transactions where 80% of them are conducted outside office hours. This data indicates that the knowledge of electronics services of prospective students and their parents is good enough.Keywords: web service, registration form, new students]]>
<![CDATA[SISTEM OTENTIKASI SINGLE SIGN-ON MENGGUNAKAN ALGORITMA DIFFIE-HELLMAN DAN MENGGUNAKAN DATABASE PARALLEL DENGAN MENGGUNAKAN RMI (REMOTE METHOD INVOCATION) ]]>
<![CDATA[Ignatius Wijaya Kusuma]]>;
<![CDATA[Puspaningtyas Sanjoyo Adi]]>
<![CDATA[ Semantik Vol 2, No 1 (2012): Prosiding Semantik 2012 ]]>
Publisher : <![CDATA[Semantik ]]>
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<![CDATA[Otentikasi adalah suatu tindakan untuk mengkonfirmasikan suatu kebenaran dari sebuah entitas dan sebuah trusted thirdparty dibutuhkan ketika sebuah transaksi saling membutuhkan kepercayaan antara orang yang bertransaksi dan orangyang ditransaksi. Penelitian ini mengembangkan suatu sistem otentikasi dengan menggunakan pendekatan sistemter distribusi dengan menggunakan paralel database dan alogiritma Diffie-Hellman Ide utama dari parallel DBMS(Database Manajement System) adalah untuk membangun sebuah computer yang sangat kuat dari banyak komputer kecil, yang masing-masing memiliki rasio kinerja dan harga yang sangat baik dengan rasio biaya yang jauh lebih rendah bila dibandingkan dengan sebuah komputer mainframe. Melalui bantuan metode pemanggilan objek, teknologinya akan digunakan untuk memanggil fungsi dan prosedur secara remote/jarak jauh. Salah satu teknologinya adalah RMI(RemoteMethod Invocation). Hasil utama dari sistem ini berupa sebuah library java yang digunakan sebagai fungsi login pada sistem developer.Hasil penelitian ini menunjukkan bahwa sistem yang dikembangkan mampu mengotentikasi seorang user dalam waktu 0,125 detik. Sistem juga tetap berjalan walau ada salah sat mesin database tidak aktif.Kata Kunci : Otentikasi, trusted third-party, Diffie-Hellman key exchange, parallel DBMS(Database Manajemen System),RMI(Remote Method Invocation)]]>
<![CDATA[SISTEM REKOMENDASI NILAI MATA KULIAH MENGGUNAKAN METODE CONTENT-BASED FILTERING ]]>
<![CDATA[Puspaningtyas Sanjoyo Adi]]>
<![CDATA[ Seminar Nasional Informatika (SEMNASIF) Vol 1, No 1 (2010): Computatinal ]]>
Publisher : <![CDATA[Jurusan Teknik Informatika ]]>
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<![CDATA[Sistem rekomendasi merupakan sistem yang bertujuan memperkirakan informasi yang menarik bagi penggunanya dan juga membantu calon konsumen dalam memutuskan barang apa saja yang akan dibelinya. Pada awal semester, setiap mahasiswa mendaftar untuk menempuh suatu mata kuliah. Saat inilah, mahasiswa membutuhkan suatu rekomendasi mengenai nilai yang akan diperolehnya. Penelitian ini bertujuan membuat perkiraan nilai mata kuliah yang akan ditempuh oleh seorang mahasiswa. Metode yang digunakan adalah metode content-based filltering. Metode content-based filering diimplementasikan dengan masukan sistem adalah dokumen silabus mata kuliah. Dokumen-dokumen ini selanjutnya diproses penghapusan stop word, stemming dan pengindeksan. Proses pengindeksan mengasilkan sebuah daftar kata dan frekuensinya pada dokumen tersebut. Setelah proses pengindeksan selesai, sistem akan melakukan penghitungan bobot kata dalam semua dokumen dengan algoritma TF-IDF. Menggunakan bobot kata ini, dokumen dapat dimodelkan dalam vekor yang dikenal dengan istilah vector space model. Berdasarkan model ini, setiap mata kuliah dihitung tingkat kemiripannya satu sama lain. Nilai tingkat kemirian ini selanjutnya digunakan untuk membangkitkan rekomendasi nilai menggunakan algoritma K Nearest Neighborhood. Sistem ini telah diujicobakan pada 10 mahasiswa T. Informatika USD angkatan 2006. Sistem membangkitkan rekomendasi untuk nilai-nilai semester 3 dan semester 4. Nilai yang dibangkitkan sebanyak 176 buah dengan tingkat akurasi sebesar 53%. Tingkat akurasi ini sangat jelek karena masih belum tepatnya algoritma pembangkitan rekomendasi dalam hal ini algoritma K Nearest neighborhood. Masih diperlukan penelitian lanjutan untuk menyempurnakan sistem ini.]]>
<![CDATA[Development Study of Deep Learning Facial Age Estimation ]]>
<![CDATA[Puspaningtyas Sanjoyo Adi]]>
<![CDATA[ International Journal of Applied Sciences and Smart Technologies Volume 01, Issue 01, June 2019 ]]>
Publisher : <![CDATA[Universitas Sanata Dharma ]]>
Show Abstract
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Download Original
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Original Source
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Check in Google Scholar
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DOI: 10.24071/ijasst.v1i1.1899
<![CDATA[Human age estimation is one of the most challenging problem because it can be used in many applications relating to age such as age-specific movies, age-specific computer applications or website, etc. This paper will contribute to give brief information about development of age estimation researches using deep learning. We explore three recent journal papers that give significant contribution in age estimation using deep learning. From these papers, they selected classification methods and there is gradual improvement in result and also in selected loss function. The best result gives MAE (mean average error) 2.8 years and VGG-16 is the most selected CNN architecture.]]>
<![CDATA[Program Bantu Diri Terapi Kognitif Perilaku: Harapan bagi Penderita Depresi ]]>
<![CDATA[Tjipto Susana]]>;
<![CDATA[Eko Hari Parmadi]]>;
<![CDATA[Puspaningtyas Sanjoyo Adi]]>
<![CDATA[ Jurnal Psikologi Vol 42, No 1 (2015) ]]>
Publisher : <![CDATA[Faculty of Psychology, Universitas Gadjah Mada ]]>
Show Abstract
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Download Original
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Original Source
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Check in Google Scholar
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Full PDF (265.299 KB)
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DOI: 10.22146/jpsi.6944
<![CDATA[This article is the first-phased report of a research through a testing of cognitive behavioral therapy module. The subjects involved in this research were 27 students who were experiencing mild to moderate depression. The research design was experiment with a pretest and posttest group. Instruments used in this study were Back Depression Inventory-II (BDI-II), Automatic Thought Questionnaire (ATQ), Dysfunctional Attitude Scale (DAS). The data was analized using paired t-test. Based on qualitative analysis, the results showed that in general it was easy for the students to understand and do the module independently. This module was very helpful for them in managing thoughts and feelings and specifically in the automatic negative thoughts, dysfunctional thinking, and rules. Nevertheless, this module did not cover the core belief. The results of the t test (t (25)=9.2; p]]>
<![CDATA[Psychrometric Performance of the Air Dehumidifier Base Clothes Dryer ]]>
<![CDATA[Wibowo Kusbandono]]>;
<![CDATA[A. Prasetyadi]]>;
<![CDATA[Nico Ndaru Pratama]]>;
<![CDATA[Doddy Purwadianto]]>;
<![CDATA[Rines]]>;
<![CDATA[Y. B. Lukiyanto]]>;
<![CDATA[I. G. K. Puja]]>;
<![CDATA[Michael Seen]]>;
<![CDATA[Budi Setyahandana]]>;
<![CDATA[Puspaningtyas Sanjoyo Adi]]>
<![CDATA[ International Journal of Applied Sciences and Smart Technologies Vol. 8 No. 1 (2026): Volume 08, Issue 1, June 2026 ]]>
Publisher : <![CDATA[Faculty of Science and Technology, Universitas Sanata Dharma ]]>
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DOI: 10.24071/262r4a76
<![CDATA[Drying clothes with dehumidifier machine and additional IR light experiments were conducted to show the psychrometric performance of dehumidification drying. Experiment of dehumidification drying 7.07 kg wet clothes to 4,78 kg dry clothes and 9.9 kg wet clothes to 7.67 kg dry clothes were applied. Variation of 715 W dehumidifier and 375 W IR were conducted. Measurement of room and environment temperatures and humidity were performed. The results show that additional IR make the drying process faster. However, it reduces drying effectivity. The efficiencies of drying are 109%, 96%, 100%, and 79% for drying 4.78 kg dry clothes with dehumidifier, drying 4.78 kg dry clothes with dehumidifier + IR, drying 7.67 kg dry clothes with dehumidifier, and drying 7.67 kg dry clothes with dehumidifier + IR. The numbers also reveal need of adopting drying COP using closed loop heat pump dehumidification to be ratio of heating and cooling energy over the supplied energy plus one.]]>
