Studi Kasus: Kopaja P20)

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Studi Kasus: Kopaja P20) ANALISIS POTENSI PERMINTAAN KOPAJA TERINTEGRASI TRANSJAKARTA (STUDI KASUS: KOPAJA P20) Purwhita Nuansa Budi, Alvinsyah Departemen Teknik Sipil, Universitas Indonesia, Kampus Baru UI Depok, 16426, Indonesia E-mail : [email protected] / [email protected] Abstrak Koperasi Angkutan Jakarta (KOPAJA) P20 telah diintegrasi dengan Transjakarta, disebut KOPAJA P20 Terintegrasi. Namun integrasi ini tidak menarik banyak peminat dari penumpang KOPAJA P20 Reguler, dikarenakan sistem pembayaran yang sulit dan waktu tempuh yang tidak memenuhi SPM BRT. KOPAJA merencanakan perbaikan pelayanan dengan penggunaan tiket elektronik dan percepatan waktu tempuh serta akan menambah biaya transportasi. Penelitian ini bertujuan memperkirakan potensi permintaan KOPAJA P20 Terintegrasi. Analisis dilakukan menggunakan model logit berbasiskan persamaan fungsi utilitas yang dikembangkan dengan metode wawancara stated preference ke dalam beberapa skenario selanjutnya dievaluasi dan dipilih fungsi yang terbaik. Hasil analisis menyatakan bila selisih waktu 10 menit dan selisih biaya Rp500, Rp1000 dan Rp1500 potensi permintaan penumpang yang bersedia pindah dari KOPAJA P20 Reguler ke KOPAJA P20 Terintegrasi sebesar 78% (1.769 pnp), 55% (1.247 pnp) dan 29% (658 pnp). Selisih waktu 20 menit dengan selisih biaya yang sama, potensi permintaan penumpang sebesar 90% (2.041 pnp), 74% (1.678 pnp) dan 49% (1.111 pnp). Selisih waktu 30 menit dengan selisih biaya yang sama, potensi permintaan penumpang sebesar 95% (2.155 pnp), 87% (1.973 pnp) dan 70% (1.588 pnp). Mengacu pada hasil analisis peningkatan jumlah potensi permintaan KOPAJA P20 Terintegrasi tergantung dari pelayanan yang diberikan yang meliputi selisih biaya dan selisih waktu. POTENTIAL DEMAND ANALYSIS OF KOPAJA INTEGRATED WITH TRANSJAKARTA (Case Study: KOPAJA P20) Abstract KOPAJA P20 is a medium bus service which is integrated with Transjakarta system. Yet since its integration, could not attract KOPAJA P20 Regular’s passengers significantly. This mainly due to in efficient payment system and prolong travel time. In order to increase its passenger, the management plan to improve its service by using e- ticketing system and impove travel time. On the contrary, they also plan to increase tariff. This research is aimed to estimate the potential demand of KOPAJA integrated. The demand is predicted by using binomial logit method based on the proposed utility function which is based on the data obtained from the stated preference survey. In order to establish utility function, stated preference survey is conducted and several scenario is proposed, the best function is selected. The results of analysis show that within 10 minutes travel time saving and tariff increasement Rp500, Rp1000 and Rp1500 potential demand of passengers who are willing to move from KOPAJA Regular to KOPAJA integrated is 78% (1.769passengers), 55% (1.247passengers) and 29% (658passengers). If 20 minutes travel time saving with the same tariff increasement, potential demand is 90% (2.041passenger), 74% (1.678passengers) and 49% (1.111passengers). If 30 minutes travel time saving with the same tariff increasement, potential demand is 95% (2.155passengers), 87% (1.973passengers) and 70% (1.588passengers). Based on these results, it can be declared that demand KOPAJA P20 Integrated’s potential demand is depending on the service provided, travel time saving and tariff increasement. Keywords : demand, stated preference, logit model, utility function Analisis potensi ..., Purwhita Nuansa Budi, FT UI, 2015 Pendahuluan Penggunaan Transjakarta belum bisa mengurai kemacetan di Jakarta (ITDP, 2011). Sehingga pemerintah memutuskan KOPAJA untuk diintegrasi dengan Transjakarta. Namun integrasi ini hanya sebatas fisik yaitu armada diperbolehkan memasuki jalur khusus Transjakarta sedangkan pelayanan yang diberikan masih jauh dari standar pelayanan minimal (SPM) BRT. Waktu tempuh KOPAJA Terintegrasi belum memenuhi standar SPM BRT serta sistem pembayaran yang sulit. Penumpang yang menggunakan layanan KOPAJA Terintegrasi melalui halte Transjakarta harus melakukan pembayaran dua kali, yaitu pembayaran untuk masuk ke halte dan di dalam armada KOPAJA sehingga menyebabkan penumpang KOPAJA lebih tertarik tetap menggunakan KOPAJA Reguler dibandingkan KOPAJA Terintegrasi. KOPAJA berencana meningkatkan pelayanan dengan tiket terpadu Transjakarta untuk mempermudah pembayaran dan mempercepat waktu tempuh serta meningkatkan tarif KOPAJA Terintegrasi. Penelitian ini bertujuan untuk mengetahui besar potensi permintaan penumpang KOPAJA P20 Terintegrasi berdasarkan pelayanan yang diberikan. Tinjauan Teoritis a. Stated preference Teknik SP (Stated Preference) dicirikan dengan adanya penggunaan desain eksperimen untuk membangun alternatif hipotesa terhadap situasi (hypothetical situation), yang kemudian disajikan kepada responden. Selanjutnya responden ditanya mengenai pilihan apa yang mereka inginkan untuk melakukan sesuatu atau bagaimana mereka membuat rating/rangking atau pilihan tertentu didalam satu atau beberapa situasi dugaan. Dengan metode ini, kita dapat melakukan kontrol eksperimen kehidupan nyata dalam sistem transportasi (Ortuzar and Willumsen, 1994). Metode ini telah secara luas dipergunakan dalam bidang transportasi karena metode ini dapat mengukur/memperkirakan bagaimana masyarakat memilih moda perjalanan yang belum ada atau melihat bagaimana reaksi mereka bereaksi terhadap suatu peraturan baru. b. Fungsi Utilitas Fungsi utilitas merupakan besaran nilai keputusan dari alternatif pilihan yang ditawarkan. Utilitas dapat didefenisikan sebagai ukuran istimewa seseorang dalam menentukan pilihan alternatif terbaiknya atau sesuatu yang dimaksimumkan oleh setiap individu (seseorang). Dalam Analisis potensi ..., Purwhita Nuansa Budi, FT UI, 2015 memodelkan pemilihan moda, maka utilitas dari suatu pilihan bagi individu dapat dituliskan sebagai berikut: � = � !� !+ �!� ! + �!� ! + � !� ! (1) dimana: U = utilitas alternative I bagi pembuat keputusan n � !, � !, � !, �! = koefisien – koefisien dari data yang disediakan �!, �!, � !, �! = sejumlah variabel yang menerangkan atribut c. Logit Biner Model logit biner merupakan bentuk khusus dari model multinomial logit. Pada model ini alternatif yang akan dipilih adalah model yang mempunyai utilitas terbesar. Model logit merupakan model pemilihan diskrit yang paling umum digunakan pemilihan diantara dua moda I dan j. (�)=(��≥��) (2) (�)=�−(�) (3) Menurut fungsi dari distribusi logistik, persamaan probabilitas dari alternative i dan j (!"!!") (�) = ! (4) !!!(!"!!") (�) = �− (�) = ! (5) !!!(!"!!") Dengan menganggap bahwa fungsi utilitas adalah linear, maka perbedaan utilitas diekspresikan dalam bentuk perbedaan dalam sejumlah atribut n yang relevan diantara kedua moda, dirumuskan sebagai berikut. � !� ! = � ! +(�!� !-�!�!) + � ! (�!� ! − �!�!) +…+�! �!� ! − �!�! (6) Dimana: ��−�� = Selisih utilitas antara moda i dengan moda j �0 = Konstanta �1,2,�� = Koefisien masing-masing atribut yang ditentukan melalui metode least square dengan multiple linier regresion Bentuk probabilitas memilih moda tertentu, serta diberikan pada persamaan sebagai berikut: ��| !(!) | =��+(����−����)+(����−����)+⋯+(����-����) (7) !!!(!) Sehingga �� − �� = �� | !(!) | = ��|!(!) | (8) !!!(!) !(!) Analisis potensi ..., Purwhita Nuansa Budi, FT UI, 2015 d. Prosedur Kalibrasi dan Validasi Model Model dari suatu permintaan pada umumnya merupakan penyesuaian terhadap suatu daerah dimana data tersebut diambil, oleh karena itu dalam suatu perhitungan atau analisis dilakukan kalibrasi terhadap model yang dibangun. Hal ini dimaksudkan untuk mendapatkan suatu hasil keseimbangan dari perhitungan yang dilakukan (Rahardjo, 2001). Validasi berasal dari kata validity yang berarti sejauh mana ketepatan dan kecermatan suatu alat ukur dalam mengukur suatu data. Dengan demikian pada kajian ini model yang validasi adalah model yang dianggap baik yang telah diperoleh dari proses kalibrasi yaitu untuk signifikansi tujuan, ketepatan prosedur, manfaat hasil penelitian dan juga untuk memahami data, penelusuran data sesuai teori yang yang digunakan dan di analisis secara statistik (Widiarta & Wardana, 2011). Untuk mengetahui variabel bebas yang layak untuk diikutsertakan ke dalam model perlu dilakukan uji stastistik (uji hipotesis). Berikut tahap pengujian hipotesis pada analisis regresi - Uji korelasi Uji ini dilakukan untuk mengetahui apakah terdapat hubungan yang signifikan antar variabel (Santoso, 2014). Keeratan hubungan dinyatakan dengan koefisien korelasi. - Uji kelayakan model (goodness of fit test) Uji kelayakan model menggunakan uji statistik dari Hosmer and Lemeshow serta Omnibus of Model Coefficient. Uji ini bertujuan untuk mempelajari sejauh mana kesesuaian model regresi logistik yang dipakai di dalam memodelkan hubungan antara variabel bebas dan variabel tidak bebas. Hipotesis nol dari uji statistik ini adalah model yang diuji layak, sedangkan hipotesis alternatifnya adalah model yang diuji tidak. Prinsip dasar dari uji statistik ini adalah frekuensi hasil prediksi dan frekuensi observasi dari variabel tidak bebas harus mempunyai perbedaan yang relatif kecil. Model yang layak menurut uji statistik ini akan mempunyai nilai probabilitas (p-value) yang besar yaitu lebih besar dari tingkat keyakinan 5% atau a =0.05 ((Widiarta & Wardana, 2011). - Uji Wald Uji Wald digunakan untuk mengetahui pengaruh variabel bebas secara individu terhadap variabel terikatnya. Uji ini dilakukan dengan menbandingkan nilai uji Wald hitung dengan nilai Wald dari Tabel. Analisis potensi ...,
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